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[ "<title>Introduction</title>", "<p id=\"Par9\">Health insurance continues to become one of the most important health financing programs and has been used as a complementary or substitute source of healthcare financing in the developing world [##UREF##0##1##]. Community-based health insurance (CBHI) schemes are often voluntary and applied by pooling funds from community members to protect themselves against the significant cost of pursuing medical care and treatment for medical conditions [##UREF##1##2##, ##UREF##2##3##]. Inability to afford out-of-pocket (OOP) expenditures has been one of the foremost obstacles to getting healthcare, especially for poor individuals and the vulnerable population at large [##UREF##3##4##]. Thus, CBHI has been implemented as a health financing tool and part of health transformation programs and policies in most low- and middle-income countries aimed at providing operational and proficient healthcare for citizens, most particularly for the poor and vulnerable [##UREF##0##1##, ##UREF##4##5##].</p>", "<p id=\"Par10\">Though health insurance has been initiated in many countries, the majority of the population in developing countries suffers from financial devastation, and about 100 million are forced into poverty due to high OOP payments for healthcare services globally [##REF##18438519##6##–##UREF##6##8##]. However, health insurance schemes in many low- and middle-income (LMIC) countries are still in their early stages of implementation, especially in most African countries, with the goal of universal coverage of the population in the health sector [##REF##21609505##9##–##REF##34847939##12##]. OOP payment to get health care is regressive as it limits admission to healthcare services for poor individuals, and it has contributed to the impoverishment of families due to having to pay for unexpected healthcare services at the time of illness [##UREF##8##13##].</p>", "<p id=\"Par11\">There are many factors contributing to the enrollment and satisfaction of households with CBHI programs. Studies report that residency status, educational status, occupational status, household size, time taken to reach a health facility, and provided service qualities contribute to the enrollment of individuals or households in the healthcare services of CBHI [##UREF##9##14##–##REF##32484840##16##]. On the other hand, the satisfaction of enrolled clients with the CBHI service was determined by the availability of medications and laboratory services, the qualification of healthcare service providers, and the waiting time to access health services [##REF##34847939##12##, ##UREF##10##17##].</p>", "<p id=\"Par12\">CBHI in Ethiopia is currently voluntary; individuals have the choice to enroll or not, and OOP has been a major means of financing health expenditures for several decades since the introduction of modern healthcare services [##REF##28629358##18##, ##REF##29702804##19##]. Nevertheless, recently, the Ethiopian government has developed a mutual health insurance strategy and a new policy for the CBHI schemes targeting employees from the rural and informal sectors through the Federal Ministry of Health (FMOH) of Ethiopia [##UREF##11##20##]. It has brought some improvements to the population’s health and the financing structure of healthcare [##UREF##12##21##]. The Ethiopian Health Insurance Service (EHIS) has been working to improve risk pooling among different groups of the population, such as between rich and poor, healthy and sick [##REF##24920538##22##, ##UREF##13##23##]. CBHI packages in Ethiopia include all necessary family health services and curative care for disease conditions, which are part of the primary health packages, excluding dental and optical care and out-of-country referrals [##REF##24920538##22##]. A high percentage of families registered in CBHI might be an indicator of the program's overall appeal and a gauge of how long it has been in place. More households will be able to ensure access to care when needed and avoid the financial burden of expensive treatments as more people join health insurance. However, in practice, CBHI frequently falls short of its potential, mainly due to low levels of involvement [##UREF##14##24##]. The commitment of authorities to support the program, and the attitude and awareness of the community towards the importance of health insurance services determine the enrollment and inclusion of individuals in the scheme [##REF##34723992##25##–##REF##12899905##28##]. Financial constraints and informal sector and economy dominance are also posing a problem of enrollment in the CBHI scheme because it is challenging to reach them through traditional enrollment channels. Subsidising premiums, information campaigns, and leveraging the informal sector are among the solutions.</p>", "<p id=\"Par13\">Although EHIS’s initiatives have been practiced throughout the country and studies have been conducted regarding enrollment [##REF##32484840##16##, ##REF##24920538##22##] and clients’ satisfaction [##REF##34847939##12##, ##UREF##10##17##, ##UREF##16##29##], the existing evidence focuses on either enrollment or clients' satisfaction in enrolled households. In addition, because of differences in community engagement with the CBHI scheme and variations in administrative and healthcare service provider facilities across different areas of the country, investigating the current study area is crucial to providing tailored insights because little is known about the extent of utilization of health insurance by households and the level of client satisfaction among CBHI scheme users in the study area. Furthermore, the clients’ level of utilization of and satisfaction with the CBHI scheme could be assessed in terms of individuals' perceptions of, expectations, and experiences with service delivery [##UREF##17##30##–##REF##24501659##32##]. Consequently, the current study assessed the enrollment of households in CBHI, the level of clients’ satisfaction, and associated factors in Gondar Zuria, District, Northwest Ethiopia. The findings from the study may help to understand the extent of community involvement in CBHI and the level of satisfaction among individuals enrolled in the scheme. Besides, the findings serve as a baseline for further research and as input for improving the program outcomes by concerned authorities and stakeholders.</p>" ]
[ "<title>Methods and materials</title>", "<title>Study design and setting</title>", "<p id=\"Par14\">A community-based cross-sectional survey was conducted between April and June 2022 in Gondar Zuria District, Northwest Ethiopia. Gondar Zuria District is one of the twelve districts that constitute the Central Gondar Zone in Amhara National Regional State. The district has 44 <italic>kebeles (</italic>smallest administrative units) and shares a boundary with Lake Tana in the West, East Dembia in the North, Libo-Kemkem in the South and in the east with West Belesa. According to City and state facts report, the district has a population size of 231,866 in 2015 [##UREF##18##33##]. The district has been involved in CBHI service provision since 2018/19. According to the Gondar Zuria CBHI office, among the 43,965 eligible households in the study area, about 30,697 (69.8%) (25,231 payable and 5,466 indigent) households are enrolled in the CBHI scheme as of May 2022.</p>", "<title>Study population inclusion and exclusion criteria</title>", "<p id=\"Par15\">The study participants included all household leads or household members responsible for providing information related to the household in Gondar Zuria District who had a verified household serial number and/or had an identification card that testified to their membership in the district. The data were collected from residents who were present around their homes during the data collection period and were willing to participate in the study. Individuals who were under 18 years old without parents or caretakers of the household were excluded from the survey.</p>", "<title>Sample size and sampling producers</title>", "<p id=\"Par16\">The sample size was determined using the single population proportion formula with the assumption that the proportion of participants’ usage of CBHI and/or the level of satisfaction of 50% since no such study has been conducted so far in the area with a 95% confidence level. After considering 10% of the non-response rate, the final sample size was 422. Proportional allocation of the total sample size for each <italic>kebele</italic> in the study was demonstrated on the basis of their respective population size. Then, study participants from each <italic>kebele</italic> were recruited using systematic random sampling and coded according to their <italic>kebele's</italic> household record number (a number that can be found on the list of households in each <italic>kebele</italic>). A simple random sampling technique was also used to select the first participant to get the starting point. Thus, depending on the sampling interval, participants were selected until the required sample size was obtained.</p>", "<title>Operational definitions</title>", "<title>Enrollment</title>", "<p id=\"Par17\">Refers to the engagement of the community in CBHI. Here, participants are classified as “enrolled” or “not-enrolled” in the CBHI scheme [##REF##32484840##16##].</p>", "<title>Household</title>", "<p id=\"Par18\">Refers to a person or a group of people related by blood, marriage, or adoption legally, who live together and share a common pot. Household size refers to the number of members of a household.</p>", "<title>Level of clients’ satisfaction</title>", "<p id=\"Par19\">Satisfaction refers to happiness with the way services in the CBHI scheme are arranged. “Level of client satisfaction” refers to the extent of satisfaction participants had in relation to the package of CBHI services. This was measured on a scale (ranging from 1 to 5) consisting of satisfaction measuring items. The tool has validated and has been used in the Ethiopian population. Each satisfaction-measuring item has five scales from “very dissatisfied” to “very satisfied,” with corresponding scores from 1 to 5, respectively. Then, the average score of responses from every item (minimum 1 and maximum 5) was transformed to provide a total satisfaction score ranging from 20 to 100% for each item used as a percentage mean score. “Dissatisfied” individuals were those who scored less than 75% on the satisfaction-measuring scale items, while those who had 75% and above scores on the scale were labelled as “satisfied” [##UREF##16##29##].</p>", "<title>Kebele</title>", "<p id=\"Par20\">Refers to a small governmental administrative unit in Ethiopia.</p>", "<title>Data collection instruments, producers and quality management</title>", "<p id=\"Par21\">Data were collected via home-to-home interviews using structured questionnaires. The questionnaire was developed based on previous reports [##REF##21609505##9##, ##REF##34847939##12##, ##UREF##11##20##, ##UREF##16##29##, ##UREF##19##34##] and adapted in light of the local context and the research problem. The questionnaire was initially prepared in the English language and translated into Amharic, the local language, to make the data collection process smooth. It was pretested on 5% of the sample before the actual data collection in another adjacent district. Based on the pretesting exercise, the instrument was checked for completeness and consistency. In order to avoid repetition, the participants’ household record numbers were entered into Microsoft Excel 2016. On the field, the actual data collection was conducted by four trained individuals (training was given about the objectives of the study, the data collection producers, and ethical issues). A supervisor was recruited to oversee the data collection procedures and the data quality.</p>", "<p id=\"Par22\">The level of clients’ satisfaction was measured using a scale consisting of seven items. The internal consistency of items was examined, and the reliability test resulted in a Cronbach’s alpha (α) of 0.88. Given the number of items, the value for Cronbach’s alpha (α) indicates the reliability of the instrument used.</p>", "<title>Data processing and analysis</title>", "<p id=\"Par23\">After the data were collected, it was checked for completeness, consistency, and cleanliness, and then coded and entered into Epi Info version 8 and exported to the Statistical Package for Social Sciences (SPSS) version 26 for analysis. Statistical analysis on determinants of enrollment in the CBHI scheme and clients’ satisfaction with the services provided was performed independently. The normal distributions of the data were examined using a Q-Q plot and histogram. Continuous variables were presented using mean and standard deviation, and frequency and percentages were used to present the distribution of the categorical variables. Independent-samples t-test and one-way ANOVA tests were used to compare group mean scores on “level of client satisfaction” pertaining to services rendered in the CBHI scheme. Logistic regression analysis was also used to identify the association of variables with enrollment in the CBHI scheme and client satisfaction. A <italic>p</italic>-value &lt; 0.05 was considered statistically significant.</p>" ]
[ "<title>Results</title>", "<title>Socio-demographics characteristics of the study participants</title>", "<p id=\"Par24\">Out of 422 approached study subjects, 410 participated in the study, resulting in a response rate of 97.2%. The majority of the study participants were males (76.1%) and rural residents (62%), with a mean (±SD) age of 46.4 (±12) years. Most of the study participants (266, 64.9%) used health insurance to cover their healthcare services (Table ##TAB##0##1##).\n</p>", "<title>Enrollment of CBHI scheme and associated factors</title>", "<p id=\"Par25\">Out of 410 study participants, around two-thirds (64.9%, 266) were enrolled in the CBHI scheme. Around two-thirds (64.9%) of the participants were enrolled in the CBHI scheme. Logistic regression analysis was performed to identify predictors of CBHI enrollment. Eventually, the multivariate logistic regression model showed that place of residence, family size, and average time taken from home to healthcare facility were significantly associated with enrollment in the CBHI scheme. After adjusting and other variables taken as constant, rural residents were found to be more likely to not be enrolled in the CBHI scheme compared to urban residents (AOR = 1.38, 95% CI: 1.02–5.32; <italic>p</italic> = 0.038). Similarly, participants who travelled for a longer time from home to healthcare facilities were found to be more likely to not get enrolled in the CBHI scheme (AOR = 1.01, 95% CI: 1.00–1.02; <italic>p</italic> = 0.001). In contrast, participants with a larger family size were found to be more likely to be enrolled in the CBHI scheme (AOR = 0.77, 95% CI: 0.67–0.88; <italic>p</italic> &lt; 0.001) (Table ##TAB##1##2##).\n</p>", "<title>Others clients’ satisfaction with the community-based health insurance scheme</title>", "<p id=\"Par26\">Overall, two-thirds (66.5%) of the enrolled households disclosed that they were dissatisfied with the CBHI scheme, with an overall mean satisfaction score of 3.2 (SD ±0.8) on a scale of 5 points. A significantly higher proportion of the study participants reported that they were not satisfied and/or very satisfied regarding the overall quality of healthcare service (68%) and the availability of medications and diagnostic laboratory tests (88.7%), with a significantly lower mean satisfaction score of 2.9 (SD±1.1) and 2.6 (SD±0.8), respectively. However, more than half of the participants were satisfied and/or very satisfied regarding the respectful care of healthcare providers, the cleanness of the healthcare facilities, and referee services. The mean (±SD) satisfaction scores were (3.5±1.2), (3.6±1.0), and (3.6 ±0.9), respectively, out of five points (Table ##TAB##2##3## and Fig. ##FIG##0##1##).\n</p>", "<title>Satisfaction differences among different groups of the participants</title>", "<p id=\"Par27\">The independent samples t-test showed that there was a significant satisfaction difference between different household sizes (t = 1.7; <italic>p</italic> = 0.044). Participants who had less than or equal to five household members had a significantly better satisfaction score (Mn = 3.5) than those with more than five household members (Mn = 3.1).</p>", "<p id=\"Par28\">A one-way ANOVA test also indicated that there were significant differences in the mean satisfaction scores of participants with different educational status (F = 3.5; <italic>p</italic> = 0.008) and occupations (F = 5.9; <italic>p</italic> = 0.001) (Table ##TAB##3##4##). The Tukey post hoc test also revealed that college and university-graduated participants had significantly higher satisfaction mean scores (Mn = 3.9) than those who were unable to read and write (Mn = 3.2); <italic>p</italic> = 0.048; and who could read and write only (Mn = 3.0); <italic>p</italic> = 0.012. Regarding the occupation of study participants, merchants had significantly higher satisfaction mean scores (Mn = 3.4) than farmers (Mn = 3.1); <italic>p</italic> = 0.045. Similarly, daily laborers had significantly higher satisfaction mean scores (Mn = 3.7) than farmers (Mn = 3.1); <italic>p</italic> = 0.001.\n</p>", "<title>Associated factors of clients’ satisfaction in community-based health insurance schemes</title>", "<p id=\"Par29\">Crude logistic regression analysis showed that there are important factors linked to the level of client satisfaction. Educational status, marital status, household size, occupational status, and waiting time to get healthcare services at the facilities were significantly associated with clients’ satisfaction level in the crude logistic regression. However, the multivariable logistic regression model showed that only household size and waiting time at health facilities to get healthcare access were significantly associated with clients’ satisfaction with the CBHI scheme services.</p>", "<p id=\"Par30\">After adjusting and controlling other variables, participants who had ≤ 5 household members were found to be more likely to have satisfaction with the CBHI scheme services compared with those having less than five members (AOR = 1.31, 95% CI: 1.01–2.24; <italic>p</italic> = 0.043). Similarly, participants who waited less than 50 minutes to get healthcare access at the health facility were more likely to be satisfied compared with participants who were waiting longer than 50 minutes (AOR = 3.14, 95% CI: 1.01–9.97; <italic>p</italic> = 0.047) (Table ##TAB##4##5##).\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par31\">This community-based survey aimed to assess the enrollment of households in the CBHI scheme and the level of client satisfaction with the services provided by the program. Consequently, this study showed that most participants were enrolled in the CBHI scheme, and two-thirds (66.5%) of the enrolled participants were dissatisfied with the services of the program. Residency status, time taken to health facilities, and household size were factors associated with the enrollment of the CHBI scheme, while household size and waiting time to get healthcare services were variables significantly associated with enrolled clients’ level of satisfaction with the CBHI scheme.</p>", "<p id=\"Par32\">The current study has shown that around two-thirds of the participants were enrolled in the CBHI scheme. This figure indicates a better enrollment rate than the report by EHIS, which indicated a national rate of 58% [##UREF##11##20##]. This implies the existence of factors that motivate residents in the study area to enroll in the program. However, it could still be encouraged to engage the communities in the program. It has an important implication for healthcare financing by protecting citizens from catastrophic health expenditures. Consistent with previous studies [##UREF##9##14##, ##REF##34411148##15##], the current findings revealed that residence, household size, and time taken from home to healthcare facility were predictor variables for CBHI scheme enrollment among households. Consequently, rural residents and participants who travelled a longer distance from home to healthcare facilities were found to have lower enrollment in the CBHI scheme compared with urban residents and participants who travelled a shorter distance, respectively. This might be because of lower awareness, poor knowledge regarding the programs and services, and a lack of information about how they engage with the health insurance systems. Rural residents and those who live at a longer distance from health facilities may not have better knowledge and access to information about health insurance systems and services. This intern decreases their enrollment in the insurance scheme. Therefore, rural communities living a longer distance from home to health facilities may need attention. The service providers must design policies or evaluate their implementation to better accommodate rural communities. This study also demonstrated that participants with a larger family size were more inclined to join in the CBHI scheme. This could be the case because people with larger families might not be able to afford the OOP expenses associated with receiving healthcare. As a result, individuals are free to select health insurance plans, enlist in the program, and go via the CBHI for only the best pre-paid coverage.</p>", "<p id=\"Par33\">This study revealed that, despite the fact that most of the community had enrolled in the CBHI, a lower proportion (33.5%) of the clients were satisfied with the services of the program. This finding is much lower than the previous studies [##REF##21609505##9##, ##REF##34847939##12##, ##UREF##20##35##, ##UREF##21##36##]. The finding implies that the CBHI scheme office may not go through the way it is designed to because of different reasons. This can compromise the service of the program and lead to clients’ dissatisfaction. For instance, in this study, a significantly higher proportion of participants were not satisfied with the overall quality of services, and more than 80% of the participants were dissatisfied with the availability of medications and laboratory tests. This may contribute to the overall dissatisfaction of the clients. The clients also reported that they were forced to leave refereed health facilities without receiving healthcare access because of the inability of the district to recover the costs from the previous one and two years; this in turn affects the clients’ satisfaction with the overall services. However, more than half of the participants reported that they were satisfied and/or very satisfied with the respectful care of healthcare providers, the cleanliness of the healthcare facilities, and the referee services when the program recovered the costs for healthcare facilities. The finding may suggest that the health insurance system should adhere to the interests of clients in its implementation.</p>", "<p id=\"Par34\">In this study, satisfaction levels among different participants were significantly different. Thus, the findings showed that there was a significant satisfaction difference between different household size members, different waiting times to get healthcare services, different educational statuses, and different occupational types. Consequently, participants with larger household sizes were found to have significantly lower satisfaction scores compared to those with lower household family members. This might be partially justified because clients with larger family sizes could pay a higher pre-paid cost of coverage proportionally to their household size, which in turn affects their perceptions and satisfaction with the services of the program. The association of household size and clients’ satisfaction in this study also showed that participants who had smaller household sizes were found to be more likely to have higher satisfaction with the CBHI scheme services compared to those with larger household families. This might be because households with large families might be reluctant to pay for their pre-paid cost coverage based on their family size. This can contribute to a lower perceived service quality. Thus, the compromised healthcare service may make them dissatisfied, in contrast to their expectations.</p>", "<p id=\"Par35\">This study also revealed that participants who waited a shorter time to get healthcare access at the health facility had a high satisfaction score. An impact of waiting time on the satisfaction level also uncovered that patients who were waiting a shorter time were found to be more likely to be satisfied compared with participants who were awaiting a longer time to get healthcare services from health facilities. This finding agrees with a previous study conducted by Haile et al [##REF##34847939##12##]. The finding indicates that healthcare providers should be encouraged to provide healthcare for the clients as early as possible on their referral or admission to the health facility.</p>", "<p id=\"Par36\">There is also a significant satisfaction mean score difference among different participants regarding their educational status and occupational types. The finding revealed that college and university-graduated participants had significantly higher satisfaction mean scores compared to participants who were unable to read and write and who could read and write. This could be because those participants with higher educational levels may have better awareness and knowledge regarding how the services of the program can be implemented, making them more likely to adhere to the services that can result in high satisfaction scores compared to participants with lower educational status. Additionally, in terms of occupational characteristics of study participants, merchants had significantly higher satisfaction mean scores than farmers on CBHI scheme services. This might be related to their level of awareness, knowledge, and information regarding the service in general, which can affect their level of involvement and their level of satisfaction with the service. However, this study did not show a statistically significant association between the educational status and occupation of participants and their level of satisfaction.</p>", "<p id=\"Par37\">Generally, the study highlighted the level of household engagement with the CBHI scheme and clients’ satisfaction in Northwest Ethiopia. The findings showed that the services provided by the program should be encouraged. The ultimate goal for which every health system should strive is to achieve and maintain client satisfaction and increase the provision of service to customers. Therefore, the commitment of the district authorities to support the scheme through the implementation of cost recovery would have a great value in improving clients’ satisfaction. Additionally, healthcare facilities could implement the CBHI services based on the aim, which is to maintain the healthcare financial balance of individuals and the community at large.</p>", "<title>Strength and limitation of the study</title>", "<p id=\"Par38\">This study presents a comprehensive finding of enrollment and satisfaction of enrolled households with the CBHI scheme and associated factors in the study area. This is the first study to assess both enrollment and satisfaction of clients. However, this study has some limitations. Firstly, this study captures data at a single point in time, making it impossible to determine the cause-and-effect relationship between variables. Secondly, participants may not accurately recall their past experiences, particularly regarding sensitive topics like healthcare utilization, quality of services, and other financial information. This can lead to biassed results. Furthermore, the survey relies on participants to accurately report their own experiences and opinions. This can be problematic due to social desirability bias, where participants may under-report healthcare services because they need further improvements. Lastly, findings from a single woreda may not be generalizable to other communities with different contexts and characteristics. Therefore, the authors welcome future research using triangulation, combining cross-sectional surveys with qualitative methods, and prospective longitudinal studies to track participants over time and assess changes in enrolment, satisfaction, and other factors.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par39\">This study concluded that a significant proportion of households in the district were enrolled in the CBHI scheme, but most of these participants were dissatisfied with the program's services. Significantly, a higher proportion of participants were not satisfied with the overall quality of services and/or the availability of medications and laboratory tests. Household family size and waiting time to get healthcare access were predictors clients’ satisfaction with the CBHI scheme services. Therefore, the CBHI services need to be monitored and audited based on its objectives, in particular the overall quality of service and availability of medications, and laboratory tests should need special attentions. </p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Although the Ethiopian government has implemented a community-based health insurance (CBHI) program, community enrollment and clients’ satisfaction have not been well investigated in Gondar Zuria district, Northwest Ethiopia. This study assessed CBHI scheme enrollment, clients’ satisfaction, and associated factors among households in the district.</p>", "<title>Methods</title>", "<p id=\"Par2\">A community-based cross-sectional survey assessed CBHI scheme enrollment and clients’ satisfaction among households in Gondar Zuria district, Northwest Ethiopia, from May to June 2022. A systematic random sampling method was used to select the study participants from eligible households. A home-to-home interview using a structured questionnaire was conducted. Data were analysed using the statistical packages for social sciences version 26. Logistic regression was used to identify variables associated with enrollment and clients’ satisfaction. A <italic>p</italic>-value &lt; 0.05 was considered statistically significant.</p>", "<title>Results</title>", "<p id=\"Par3\">Out of 410 participants, around two-thirds (64.9%) of the participants were enrolled in the CBHI scheme. Residency status (AOR = 1.38, 95% CI: 1.02–5.32; <italic>p</italic> = 0.038), time taken to reach a health facility (AOR = 1.01, 95% CI: 1.00–1.02; <italic>p</italic> = 0.001), and household size (AOR = 0.77, 95% CI: 0.67–0.88; <italic>p</italic> &lt; 0.001) were significantly associated with CBHI scheme enrollment. Two-thirds (66.5%) of enrolled households were dissatisfied with the overall services provided; in particular, higher proportions were dissatisfied with the availability of medication and laboratory tests (88.7%). Household size (AOR = 1.31, 95% CI: 1.01–2.24; <italic>p</italic> = 0.043) and waiting time to get healthcare services (AOR = 3.14, 95% CI: 1.01–9.97; <italic>p</italic> = 0.047) were predictors of clients’ satisfaction with the CBHI scheme services.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Although a promisingly high proportion of households were enrolled in the CBHI scheme, most of them were dissatisfied with the service. Improving waiting times to get health services, improving the availability of medications and laboratory tests, and other factors should be encouraged.</p>", "<title>Keywords</title>" ]
[]
[ "<p>The authors would like to thank data collectors and study participants. We also extend our gratitude to Gondar Zuria district community-based health insurance officers for helping us giving secondary data.</p>", "<title>Authors’ contributions</title>", "<p>AKS contributed to the conception, data curation, formal analysis, investigation, methodology, supervision, validation and writing of the original draft manuscript.  AHG contributed to the data curation, formal analysis, methodology, supervision, and validation.  MWT contributed to the data curation, formal analysis, methodology, project administration, resources and validation. All authors reviewed the manuscript. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agreed to be accountable for all aspects of the work.</p>", "<title>Funding</title>", "<p>We did not receive funding for this study.</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated and/or analyzed during the current study are not publicly available to protect from unnecessary abuse of full data of the participants, but are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par40\">The study was ethically approved by the ethical review committee of the University of Gondar with a reference number of SoCI300/2014. Participants were informed with both written and verbal consent forms after the objectives of the study were briefed. Participants involved in the study were in condition to providing informed consent willing with all proper understanding of the study purposes. All methods were carried out in accordance with relevant guidelines and regulations.</p>", "<title>Consent for publication</title>", "<p id=\"Par41\">Not applicable because confidentiality was kept and participants were sufficiently anonymized.</p>", "<title>Competing interests</title>", "<p id=\"Par42\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Satisfaction level of participants for each satisfaction measuring item</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Socio-demographic characteristics of the study participants at Gondar Zuria District, 2022 (<italic>N</italic>= 410)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"2\"><bold>Socio-demographic variables</bold></th><th align=\"left\"><bold>Frequency (%)</bold></th><th align=\"left\"><bold>Mean (±SD)</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Sex</td><td align=\"left\">Male</td><td align=\"left\">312 (76.1)</td><td align=\"left\"/></tr><tr><td align=\"left\">Female</td><td align=\"left\">98(23.9)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"2\">Age (in years)</td><td align=\"left\">-</td><td align=\"left\">46.4 (12)</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of Residence</td><td align=\"left\">Rural</td><td align=\"left\">254(62)</td><td align=\"left\"/></tr><tr><td align=\"left\">Urban</td><td align=\"left\">156(38)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"5\">Educational status</td><td align=\"left\">Unable to read or write</td><td align=\"left\">179(43.7)</td><td align=\"left\"/></tr><tr><td align=\"left\">Read and write only</td><td align=\"left\">65 (15.9)</td><td align=\"left\"/></tr><tr><td align=\"left\">Primary school</td><td align=\"left\">119 (29)</td><td align=\"left\"/></tr><tr><td align=\"left\">Secondary school</td><td align=\"left\">26(6.3)</td><td align=\"left\"/></tr><tr><td align=\"left\">College and university</td><td align=\"left\">21(5.1)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"2\">Religious affiliation</td><td align=\"left\">Orthodox Christian</td><td align=\"left\">373 (91)</td><td align=\"left\"/></tr><tr><td align=\"left\">Muslim</td><td align=\"left\">37(9)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"4\">Marital status</td><td align=\"left\">Single</td><td align=\"left\">44(10.7)</td><td align=\"left\"/></tr><tr><td align=\"left\">Married</td><td align=\"left\">310(75.6)</td><td align=\"left\"/></tr><tr><td align=\"left\">Divorced</td><td align=\"left\">34(8.3)</td><td align=\"left\"/></tr><tr><td align=\"left\">Widowed</td><td align=\"left\">22(5.4)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"2\">Household size</td><td align=\"left\">-</td><td align=\"left\">5.4 (2.1)</td></tr><tr><td align=\"left\" rowspan=\"4\">Occupation</td><td align=\"left\">Farmer</td><td align=\"left\">259(63.2)</td><td align=\"left\"/></tr><tr><td align=\"left\">Merchant</td><td align=\"left\">64(15.6)</td><td align=\"left\"/></tr><tr><td align=\"left\">Daily labor</td><td align=\"left\">36(8.8)</td><td align=\"left\"/></tr><tr><td align=\"left\">Others</td><td align=\"left\">51(12.4)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"2\">Coverage of healthcare cost</td><td align=\"left\">Out of pocket</td><td align=\"left\">130 (31.7)</td><td align=\"left\"/></tr><tr><td align=\"left\">Health insurance</td><td align=\"left\">266 (64.9)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"2\">Average time taken from home to healthcare facility (in minutes)</td><td align=\"left\"/><td align=\"left\">46.4 (38.1)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Association of independent variables with enrollment in CBHI</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"2\"><bold>Variables</bold></th><th align=\"left\" colspan=\"2\"><bold>Enrollment in CBHI scheme</bold></th><th align=\"left\" colspan=\"2\"><bold>95% CI</bold></th><th align=\"left\" rowspan=\"2\"><bold><italic>P</italic></bold><bold>-value</bold></th></tr><tr><th align=\"left\"><bold>Not enrolled</bold></th><th align=\"left\"><bold>Enrolled</bold></th><th align=\"left\"><bold>COR</bold></th><th align=\"left\"><bold>AOR</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Sex</td><td align=\"left\">Male</td><td align=\"left\">114</td><td align=\"left\">198</td><td align=\"left\">1.31(0.80–2.13)</td><td align=\"left\">1.34(0.612–2.90)</td><td align=\"left\" rowspan=\"2\">0.463</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">30</td><td align=\"left\">68</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" colspan=\"2\">Age (in years) (mean ±SD)</td><td align=\"left\">43.8 (12.4)</td><td align=\"left\">47.8 (11.6)</td><td align=\"left\">0.92(0.85–0.99)</td><td align=\"left\">0.99(0.97–1.01)</td><td align=\"left\">0.270</td></tr><tr><td align=\"left\" rowspan=\"2\"> Place of Residence</td><td align=\"left\">Rural</td><td align=\"left\">90</td><td align=\"left\">164</td><td align=\"left\">1.04(0.62–1.58)</td><td align=\"left\">1.38(1.02–5.32)</td><td align=\"left\" rowspan=\"2\">0.038*</td></tr><tr><td align=\"left\">Urban</td><td align=\"left\">54</td><td align=\"left\">102</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"5\"> Educational status</td><td align=\"left\">Unable to read or write</td><td align=\"left\">70</td><td align=\"left\">109</td><td align=\"left\">0.48(0.19–1.20)</td><td align=\"left\">0.64(0.22–1.86)</td><td align=\"left\" rowspan=\"5\">0.053</td></tr><tr><td align=\"left\">Read and write only</td><td align=\"left\">16</td><td align=\"left\">49</td><td align=\"left\">0.25(0.09–0.69)</td><td align=\"left\">0.31(0.10–1.00)</td></tr><tr><td align=\"left\">Primary school</td><td align=\"left\">33</td><td align=\"left\">86</td><td align=\"left\">0.29(0.11–0.75)</td><td align=\"left\">0.36(0.12–1.02)</td></tr><tr><td align=\"left\">Secondary school</td><td align=\"left\">13</td><td align=\"left\">13</td><td align=\"left\">0.75(0.24–2.37)</td><td align=\"left\">0.61(0.18–2.08)</td></tr><tr><td align=\"left\">College and university</td><td align=\"left\">12</td><td align=\"left\">9</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\"> Religious affiliation</td><td align=\"left\">Orthodox Christian</td><td align=\"left\">130</td><td align=\"left\">243</td><td align=\"left\">0.88(0.44–1.77)</td><td align=\"left\">0.66(0.29–1.47)</td><td align=\"left\" rowspan=\"2\">0.304</td></tr><tr><td align=\"left\">Muslim</td><td align=\"left\">14</td><td align=\"left\">23</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"4\"> Marital status</td><td align=\"left\">Single</td><td align=\"left\">14</td><td align=\"left\">30</td><td align=\"left\">2.10(0.60–7.37)</td><td align=\"left\">1.51(0.39–5.95)</td><td align=\"left\" rowspan=\"4\">0.429</td></tr><tr><td align=\"left\">Married</td><td align=\"left\">113</td><td align=\"left\">197</td><td align=\"left\">2.58(0.85–7.82)</td><td align=\"left\">02.57(0.65–10.11)</td></tr><tr><td align=\"left\">Divorced</td><td align=\"left\">13</td><td align=\"left\">21</td><td align=\"left\">2.79(0.77–10.07)</td><td align=\"left\">2.25(0.57–8.92)</td></tr><tr><td align=\"left\">Widowed</td><td align=\"left\">4</td><td align=\"left\">18</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" colspan=\"2\">Household size (mean ±SD)</td><td align=\"left\">4.8 (1.9)</td><td align=\"left\">5.7 (2.1)</td><td align=\"left\">0.80(0.72–0.89)</td><td align=\"left\">0.77(0.67–0.88)</td><td align=\"left\">&lt;0.001*</td></tr><tr><td align=\"left\" rowspan=\"4\"> Occupation</td><td align=\"left\">Farmer</td><td align=\"left\">90</td><td align=\"left\">169</td><td align=\"left\">0.90(0.48–1.67)</td><td align=\"left\">0.89(0.20–3.94)</td><td align=\"left\" rowspan=\"4\">0.271</td></tr><tr><td align=\"left\">Merchant</td><td align=\"left\">19</td><td align=\"left\">45</td><td align=\"left\">0.71(0.33–1.55)</td><td align=\"left\">0.77(0.31–1.88)</td></tr><tr><td align=\"left\">Daily labor</td><td align=\"left\">16</td><td align=\"left\">20</td><td align=\"left\">1.35(0.57–3.21)</td><td align=\"left\">1.96(0.71–5.41)</td></tr><tr><td align=\"left\">Others</td><td align=\"left\">19</td><td align=\"left\">32</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" colspan=\"2\">Average time taken from home to healthcare facility (minute) (mean ±SD)</td><td align=\"left\">55.6 (37.7)</td><td align=\"left\">41.4 (37.5)</td><td align=\"left\">1.34(1.07-2.71)</td><td align=\"left\">1.01(1.00–1.02)</td><td align=\"left\">0.001*</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Level of client satisfaction on CBHI scheme service measuring items and overall satisfaction of clients (<italic>N</italic> = 266)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"><bold>Items</bold></th><th align=\"left\" colspan=\"5\"><bold>Satisfaction level (%)</bold></th></tr><tr><th align=\"left\"><bold>Very dissatisfied</bold></th><th align=\"left\"><bold>Dissatisfied</bold></th><th align=\"left\"><bold>Neutral</bold></th><th align=\"left\"><bold>Satisfied</bold></th><th align=\"left\"><bold>Very satisfied</bold></th></tr></thead><tbody><tr><td align=\"left\">Overall quality of healthcare service</td><td align=\"left\">44 (16.5)</td><td align=\"left\">44 (16.5)</td><td align=\"left\">93 (35)</td><td align=\"left\">74(27.8)</td><td align=\"left\">11 (4.2)</td></tr><tr><td align=\"left\">Respectful care of CBHI SCHEME officers</td><td align=\"left\">18 (6.8)</td><td align=\"left\">68 (25.6)</td><td align=\"left\">77 (28.9)</td><td align=\"left\">81 (30.5)</td><td align=\"left\">22 (8.3)</td></tr><tr><td align=\"left\">Respectful care of healthcare providers</td><td align=\"left\">9 (3.4)</td><td align=\"left\">59 (22.2)</td><td align=\"left\">58 (21.8)</td><td align=\"left\">68 (25.6)</td><td align=\"left\">72 (27.1)</td></tr><tr><td align=\"left\">Getting services in a short waiting time</td><td align=\"left\">6 (2.3)</td><td align=\"left\">71 (26.7)</td><td align=\"left\">70 (26.3)</td><td align=\"left\">75 (28.2)</td><td align=\"left\">44 (16.5)</td></tr><tr><td align=\"left\">Medications and laboratory availability</td><td align=\"left\">26 (9.8)</td><td align=\"left\">87 (32.7)</td><td align=\"left\">123 (46.2)</td><td align=\"left\">28 (10.5)</td><td align=\"left\">2 (0.8)</td></tr><tr><td align=\"left\">Cleanness of the healthcare facility</td><td align=\"left\">1 (0.4)</td><td align=\"left\">49 (18.4)</td><td align=\"left\">72 (27.1)</td><td align=\"left\">86 (32.3)</td><td align=\"left\">58 (21.8)</td></tr><tr><td align=\"left\">Referee services for better management</td><td align=\"left\">1 (0.4)</td><td align=\"left\">30 (11.3)</td><td align=\"left\">86 (32.3)</td><td align=\"left\">96 (36.1)</td><td align=\"left\">53 (19.9)</td></tr><tr><td align=\"left\" rowspan=\"3\"><bold>Overall satisfaction level</bold></td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"3\"><bold>Frequency (%)</bold></td></tr><tr><td align=\"left\" colspan=\"2\">Dissatisfied</td><td align=\"left\" colspan=\"3\">177 (66.5)</td></tr><tr><td align=\"left\" colspan=\"2\">Satisfied</td><td align=\"left\" colspan=\"3\">89 (33.5)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Mean satisfaction score differences among the respondents regarding CBHI scheme services are illustrated with the Independent-samples T-test and One-Way ANOVA analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"><bold>Variables</bold></th><th align=\"left\" rowspan=\"2\"><bold>Category</bold></th><th align=\"left\" colspan=\"3\"><bold>Satisfaction score of the CBHI scheme services</bold></th></tr><tr><th align=\"left\"><bold>Mean (±SD)</bold></th><th align=\"left\"><bold>T/F</bold></th><th align=\"left\"><bold><italic>P</italic></bold><bold>-value</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Sex</td><td align=\"left\">Male</td><td align=\"left\">3.2(0.8)</td><td align=\"left\" rowspan=\"2\">0.4<sup>a</sup></td><td align=\"left\" rowspan=\"2\">0.669</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">3.2(0.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">Age (in years)</td><td align=\"left\">&lt; 50</td><td align=\"left\">3.2 (0.8)</td><td align=\"left\" rowspan=\"2\">-0.7<sup>a</sup></td><td align=\"left\" rowspan=\"2\">0.459</td></tr><tr><td align=\"left\">≥ 50</td><td align=\"left\">3.3 (0.8)</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of Residence</td><td align=\"left\">Rural</td><td align=\"left\">3.2(0.8)</td><td align=\"left\" rowspan=\"2\">-1.1*</td><td align=\"left\" rowspan=\"2\">0.264</td></tr><tr><td align=\"left\">Urban</td><td align=\"left\">3.3(0.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">Religious affiliation</td><td align=\"left\">Orthodox Christian</td><td align=\"left\">3.2 (0.8)</td><td align=\"left\" rowspan=\"2\">-1.1<sup>a</sup></td><td align=\"left\" rowspan=\"2\">0.280</td></tr><tr><td align=\"left\">Muslim</td><td align=\"left\">3.4(0.8)</td></tr><tr><td align=\"left\" rowspan=\"4\">Marital status</td><td align=\"left\">Single</td><td align=\"left\">3.5(0.8)</td><td align=\"left\" rowspan=\"4\">1.8<sup>b</sup></td><td align=\"left\" rowspan=\"4\">0.144</td></tr><tr><td align=\"left\">Married</td><td align=\"left\">3.2 (0.8)</td></tr><tr><td align=\"left\">Divorced</td><td align=\"left\">3.2 (0.8)</td></tr><tr><td align=\"left\">Widowed</td><td align=\"left\">3.4 (0.7)</td></tr><tr><td align=\"left\" rowspan=\"2\">Household size</td><td align=\"left\">≤ 5</td><td align=\"left\">3.5 (0.8)</td><td align=\"left\" rowspan=\"2\">1.7<sup>a</sup></td><td align=\"left\" rowspan=\"2\"><bold>0.044</bold></td></tr><tr><td align=\"left\">&gt; 5</td><td align=\"left\">3.1 (0.8)</td></tr><tr><td align=\"left\" rowspan=\"5\">Educational status</td><td align=\"left\">Unable to read or write</td><td align=\"left\">3.2(0.8)</td><td align=\"left\" rowspan=\"5\">3.5<sup>b</sup></td><td align=\"left\" rowspan=\"5\"><bold>0.008</bold></td></tr><tr><td align=\"left\">Read and write only</td><td align=\"left\">3.0 (0.9)</td></tr><tr><td align=\"left\">Primary education</td><td align=\"left\">3.4 (0.8)</td></tr><tr><td align=\"left\">Secondary education</td><td align=\"left\">3.2(0.8)</td></tr><tr><td align=\"left\">College and university</td><td align=\"left\">3.9(0.7)</td></tr><tr><td align=\"left\" rowspan=\"4\">Occupation</td><td align=\"left\">Farmer</td><td align=\"left\">3.1 (0.8)</td><td align=\"left\" rowspan=\"4\">5.9<sup>b</sup></td><td align=\"left\" rowspan=\"4\"><bold>0.001</bold></td></tr><tr><td align=\"left\">Merchant</td><td align=\"left\">3.4 (0.8)</td></tr><tr><td align=\"left\">Daily labor</td><td align=\"left\">3.7 (0.7)</td></tr><tr><td align=\"left\">Others</td><td align=\"left\">3.2 (0.7)</td></tr><tr><td align=\"left\" rowspan=\"2\">Average-waiting time to get healthcare services (minute)</td><td align=\"left\">≤ 50</td><td align=\"left\">3.3 (0.9)</td><td align=\"left\" rowspan=\"2\">1.41<sup>a</sup></td><td align=\"left\" rowspan=\"2\">0.159</td></tr><tr><td align=\"left\">&gt; 50</td><td align=\"left\">3.2 (0.8)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Association of independent variables with clients’ satisfaction on CBHI scheme healthcare services</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"2\"><bold>Variables</bold></th><th align=\"left\" colspan=\"2\"><bold>Clients’ satisfaction</bold></th><th align=\"left\" colspan=\"2\"><bold>95% CI</bold></th><th align=\"left\" rowspan=\"2\"><bold><italic>P</italic></bold><bold>-value</bold></th></tr><tr><th align=\"left\"><bold>Satisfied</bold></th><th align=\"left\"><bold>Dissatisfied</bold></th><th align=\"left\"><bold>COR</bold></th><th align=\"left\"><bold>AOR</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Sex</td><td align=\"left\">Male</td><td align=\"left\">64</td><td align=\"left\">131</td><td align=\"left\">0.93(0.51-1.69)</td><td align=\"left\">1.41(0.6-3.32)</td><td align=\"left\" rowspan=\"2\">0.43</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">22</td><td align=\"left\">42</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Age (in years)</td><td align=\"left\">&lt; 50</td><td align=\"left\">42</td><td align=\"left\">95</td><td align=\"left\">0.77(0.463-1.285)</td><td align=\"left\">0.75(0.42-1.32)</td><td align=\"left\" rowspan=\"2\">0.315</td></tr><tr><td align=\"left\">≥ 50</td><td align=\"left\">47</td><td align=\"left\">82</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of Residence</td><td align=\"left\">Rural</td><td align=\"left\">48</td><td align=\"left\">115</td><td align=\"left\">0.63(0.38-1.06)</td><td align=\"left\">2.49(0.70-8.88)</td><td align=\"left\" rowspan=\"2\">0.16</td></tr><tr><td align=\"left\">Urban</td><td align=\"left\">41</td><td align=\"left\">62</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"5\">Educational status</td><td align=\"left\">Unable to read or write</td><td align=\"left\">33</td><td align=\"left\">79</td><td align=\"left\">0.33(0.08-1.32)</td><td align=\"left\">0.35(0.07-1.87)</td><td align=\"left\" rowspan=\"5\">0.553</td></tr><tr><td align=\"left\">Read and write only</td><td align=\"left\">13</td><td align=\"left\">33</td><td align=\"left\">0.32(0.07-1.36)</td><td align=\"left\">0.38(0.06-2.24)</td></tr><tr><td align=\"left\">Primary school</td><td align=\"left\">34</td><td align=\"left\">52</td><td align=\"left\">0.52(0.13-2.09)</td><td align=\"left\">0.57(0.12-2.99)</td></tr><tr><td align=\"left\">Secondary school</td><td align=\"left\">4</td><td align=\"left\">9</td><td align=\"left\">0.36(0.06-2.08)</td><td align=\"left\">0.49(0.07-3.60)</td></tr><tr><td align=\"left\">College and university</td><td align=\"left\">5</td><td align=\"left\">4</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Religious affiliation</td><td align=\"left\">Orthodox Christian</td><td align=\"left\">79</td><td align=\"left\">164</td><td align=\"left\">0.63(0.26-1.49)</td><td align=\"left\">0.70(0.25-1.94)</td><td align=\"left\" rowspan=\"2\">0.487</td></tr><tr><td align=\"left\">Muslim</td><td align=\"left\">10</td><td align=\"left\">13</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"4\">Marital status</td><td align=\"left\">Single</td><td align=\"left\">20</td><td align=\"left\">20</td><td align=\"left\">1.13(0.36-3.51)</td><td align=\"left\">0.81(0.22-3.04)</td><td align=\"left\" rowspan=\"4\">0.064</td></tr><tr><td align=\"left\">Married</td><td align=\"left\">52</td><td align=\"left\">129</td><td align=\"left\">0.45(0.17-1.24)</td><td align=\"left\">0.38(0.10-1.06)</td></tr><tr><td align=\"left\">Divorced</td><td align=\"left\">9</td><td align=\"left\">19</td><td align=\"left\">0.53(0.15-1.84)</td><td align=\"left\">0.40(0.10-1.54)</td></tr><tr><td align=\"left\">Widowed</td><td align=\"left\">8</td><td align=\"left\">9</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Household size</td><td align=\"left\">≤ 5</td><td align=\"left\">90</td><td align=\"left\">44</td><td align=\"left\">1.06(0.64-1.76)</td><td align=\"left\">1.31(1.01 -2.24)</td><td align=\"left\" rowspan=\"2\">0.043*</td></tr><tr><td align=\"left\">&gt; 5</td><td align=\"left\">87</td><td align=\"left\">45</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"4\">Occupation</td><td align=\"left\">Farmer</td><td align=\"left\">35</td><td align=\"left\">102</td><td align=\"left\">0.87(0.41-1.84)</td><td align=\"left\">0.99(0.40-2.46)</td><td align=\"left\" rowspan=\"4\">0.117</td></tr><tr><td align=\"left\">Merchant</td><td align=\"left\">24</td><td align=\"left\">30</td><td align=\"left\">2.03(0.88-4.69)</td><td align=\"left\">2.07(0.76-5.44)</td></tr><tr><td align=\"left\">Daily labor</td><td align=\"left\">17</td><td align=\"left\">12</td><td align=\"left\">3.60(1.35-9.57)</td><td align=\"left\">2.71(0.83-8.86)</td></tr><tr><td align=\"left\">Others</td><td align=\"left\">13</td><td align=\"left\">33</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Waiting time to get healthcare services (minute)</td><td align=\"left\">≤ 50</td><td align=\"left\">48</td><td align=\"left\">68</td><td align=\"left\">1.88(1.121-3.141)</td><td align=\"left\">3.14(1.01-9.79)</td><td align=\"left\" rowspan=\"2\">0.047*</td></tr><tr><td align=\"left\">&gt; 50</td><td align=\"left\">41</td><td align=\"left\">109</td><td align=\"left\">1</td><td align=\"left\">1</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><sup><bold>*</bold></sup>Indicates <italic>p</italic> &lt; 0.05, other includes, students; homemakers</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>T<bold>-</bold>Independent-samples T-test</p><p><sup>b</sup>F-one-way ANOVA test; age, household size and waiting time to get healthcare services was transformed into categorical variables from their average values</p><p>Bold values denote significant differences (<italic>p</italic> &lt;0.05)</p></table-wrap-foot>", "<table-wrap-foot><p><italic>CI</italic> Confidence interval, <italic>COR</italic> Crude odds ratio, <italic>AOR</italic>, Adjusted odds ratio; age, household size and waiting time to get healthcare service were transformed into categorized variables from their average values; * indicates <italic>p</italic> &lt; 0.05</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["1."], "mixed-citation": ["McIntyre, D., Golbal Forum for Health Research; Helping Correct the 10/90 GAP. Health care financing in low and middle-income countries. Accessed on 25 Jun 2022. Available: "], "ext-link": ["https://www.files.ethz.ch/isn/48554/2007-06%20Health%20care%20financing.pdf"]}, {"label": ["2."], "surname": ["Kebede", "Gebreslassie", "Yitayal"], "given-names": ["A", "M", "M"], "article-title": ["Willingness to pay for community based health insurance among households in the rural community of Fogera District, North West Ethiopia"], "source": ["Int J Economics Finance Manag Sci"], "year": ["2014"], "volume": ["2"], "issue": ["4"], "fpage": ["263"], "lpage": ["269"]}, {"label": ["3."], "mixed-citation": ["Uzochukwu BS, Onwujekwe OE, Eze S, Ezuma N, Obikeze E, Onoka C. Community Based Health Insurance Scheme in Anambra State, Nigeria: an analysis of policy development, implementation and equity effects. London: Consortium for Research on Equitable Health Systems, London School of Hygiene and Tropical Medicine; 2009. p. 1\u201335. Available: "], "ext-link": ["http://www.crehs.lshtm.ac.uk/downloads/publications/Community_based_health_insurance_Nigeria.pdf"]}, {"label": ["4."], "mixed-citation": ["Judy, W.M. and P. Sathirakorn, Access to health care: the role of a community based health insurance in Kenya. PAMJ. 2012. 12(35)."]}, {"label": ["5."], "surname": ["Parmar", "Souares", "de Allegri", "Savadogo", "Sauerborn"], "given-names": ["D", "A", "M", "G", "R"], "article-title": ["Adverse selection in a community-based health insurance scheme in rural Africa: implications for introducing targeted subsidies"], "source": ["BMC Health Serv Res"], "year": ["2012"], "volume": ["28"], "issue": ["12"], "fpage": ["181"], "pub-id": ["10.1186/1472-6963-12-181"]}, {"label": ["7."], "collab": ["World Health"], "surname": ["O. 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Improving the quality and use of birth, death and cause-of-death information: guidance for a standards-based review of country practices. Geneva: WHO; 2010. (Accessed 25 Jun 2022). Available at: "], "ext-link": ["https://www.who.int/healthinfo/tool_cod_2010.pdf"]}, {"label": ["14."], "mixed-citation": ["Moyehodie YA, Fenta SM, Mulugeta SS, Agegn SB, Yismaw E, Biresaw HB, Muluneh MW, Masresha BM, Dagnaw FT. Factors associated with community based health insurance healthcare service utilization of households in South Gondar zone, Amhara, Ethiopia. A community-based cross-sectional study.\u00a0Health Serv Insights. 2022;15:11786329221096065."]}, {"label": ["17."], "mixed-citation": ["Biruktawit A. Client\u2019s Satisfaction with a Community Based Health Insurance Scheme and Associated Factors in Addis Ababa. June, 2021. Source: "], "ext-link": ["http://etd.aau.edu.et/handle/123456789/29434/"]}, {"label": ["20."], "mixed-citation": ["Ethiopian Health Insurance Agency. Evaluation of Community-Based Health Insurance Pilot Schemes in Ethiopia: Final Report. Addis Ababa, Ethiopia.\u00a02015. Available: "], "ext-link": ["https://www.hfgproject.org/evaluation-cbhi-pilots-ethiopia-final-report/"]}, {"label": ["21."], "mixed-citation": ["Barnett I, Tefera B. Poor Households\u2019 Experiences and Perception of User Fees for Healthcare: a mixed-method study from Ethiopia. Young Lives; 2010. Available: "], "ext-link": ["https://www.younglives-ethiopia.org/sites/default/files/syndicated/YL-WP59-Barnett-HealthcareFinancingInEthiopia_0.pdf"]}, {"label": ["23."], "surname": ["Wang"], "given-names": ["H"], "source": ["and G"], "year": ["2014"], "publisher-loc": ["Ramana"], "publisher-name": ["Universal Health Coverage for Inclusive and Sustainable Development"]}, {"label": ["24."], "mixed-citation": ["De Allegri M, Kouyat\u00e9 B, Becher H, Gbangou A, Pokhrel S, Sanon M, et al. Understanding enrolment in community health insurance in sub-Saharan Africa: a population-based case-control study in rural Burkina Faso. Bulletin of the World Health Organization. 2006;84:852\u20138. 10.2471/blt.06.031336."]}, {"label": ["27."], "surname": ["Harris", "Keane"], "given-names": ["KM", "MP"], "article-title": ["A model of health plan choice: Inferring preferences and perceptions from a combination of revealed preference and attitudinal data"], "source": ["J Econometrics"], "year": ["1998"], "volume": ["89"], "issue": ["1\u20132"], "fpage": ["131"], "lpage": ["157"], "pub-id": ["10.1016/S0304-4076(98)00058-X"]}, {"label": ["29."], "surname": ["Sagaro", "Yalew", "Koyira"], "given-names": ["GG", "AW", "MM"], "article-title": ["Patients\u2019 satisfaction and associated factors among outpatient Department at Wolaita Sodo University Teaching Hospital, Southern Ethiopia: a cross sectional study"], "source": ["Sci J Clin Med"], "year": ["2015"], "volume": ["4"], "issue": ["5"], "fpage": ["109"], "lpage": ["116"], "pub-id": ["10.11648/j.sjcm.20150405.16"]}, {"label": ["30."], "mixed-citation": ["Nyandekwe, M., M. Nzayirambaho, and J. Baptiste Kakoma, Universal health coverage in Rwanda: dream or reality. Pan Afr Med J. 2014; 17:232."]}, {"label": ["33."], "mixed-citation": ["City and state facts logo, 2015. Gonder Zuria, ET. (Accessed on 25 June 2022). Available: "], "ext-link": ["https://www.city-facts.com/gonder-zuria-et"]}, {"label": ["34."], "mixed-citation": ["Sharma D, Basnet P, Kafle R. Awareness, Enrollment and Utilization of Health Insurance among Adults of Pokhara.\u00a0JCMS-Nepal. 2021;17(2):109\u201316. 10.3126/jcmsn.v17i2.29389."]}, {"label": ["35."], "surname": ["Osungbade", "Obembe", "Oludoyi"], "given-names": ["KO", "TA", "A"], "article-title": ["Users\u2019 satisfaction with services provided under National Health Insurance Scheme in south western Nigeria"], "source": ["Int J Trop Dis Health"], "year": ["2014"], "volume": ["4"], "issue": ["5"], "fpage": ["595"], "lpage": ["607"], "pub-id": ["10.9734/IJTDH/2014/7280"]}, {"label": ["36."], "mixed-citation": ["Mangeni R. Client Satisfaction With Health Care Services of a Community Health Insurance Scheme (Doctoral dissertation, International Health Sciences University.); 2014. Available: "], "ext-link": ["http://ir.ciu.ac.ug:8080/handle/123456789/545"]}]
{ "acronym": [ "CBHI", "EHIS", "FMOH", "OOP" ], "definition": [ "Community-based health insurance", "Ethiopian health insurance service", "Federal Ministry of health", "Out-Of-pocket" ] }
36
CC BY
no
2024-01-14 23:43:44
BMC Health Serv Res. 2024 Jan 13; 24:70
oa_package/b7/0b/PMC10787395.tar.gz
PMC10787396
37306161
[ "<title>Introduction</title>", "<p>Developmental dysplasia of the hip (DDH) is a term that encompasses a spectrum of abnormal hip morphology involving the acetabulum and the proximal femur.<sup>##REF##26738905##1##,##REF##27752989##2##</sup> Current notions describe a resultant instability of the hip joint with subsequent chondral degeneration and secondary osteoarthritis.<sup>\n##REF##31977605##3##\n</sup> It is thought that DDH is a risk factor of early-onset osteoarthritis.<sup>##REF##31977605##3##,##REF##21543681##4##–##REF##21543683##8##</sup> Amongst patients with mild degenerative change in their hip, those with DDH have almost 3 times the risk of progressing to end-stage osteoarthritis or total hip arthroplasty (THA), compared with normal morphology.<sup>\n##REF##27071391##9##\n</sup> In those with Tönnis grade 1 degenerative change, 1 in 3 patients received a THA within 10 years, compared to 1 in 5 shown in those with normal or femoroacetabular impingement (FAI) morphology.<sup>\n##REF##27071391##9##\n</sup> This implies that those with DDH are at increased risk of rapid degenerative change of their hip joint, once they develop early degenerative change.<sup>\n##REF##27071391##9##\n</sup></p>", "<p>The international hip-related pain research network has identified acetabular dysplasia as one of the most common hip conditions in active adults presenting with hip pain.<sup>\n##REF##31959678##10##\n</sup> The true prevalence of DDH is difficult to ascertain as the condition can often be asymptomatic and there are inconsistencies regarding the diagnosis in the literature.<sup>##REF##31977605##3##,##REF##21543683##8##,##REF##20439662##11##</sup> Prevalence ranges from 1.7% to 20% in the general population.<sup>##REF##15479751##7##,##REF##20439662##11##–##UREF##1##14##</sup> The traditional measure of DDH is the lateral centre-edge angle (LCEA) of Wiberg radiographically assessed from a weight-bearing anterioposterior (AP) pelvic view. A value &lt;20° is defined as dysplasia, between 20° and 25° has been defined as borderline dysplasia, and 25–39° is defined as normal.<sup>\n##UREF##2##15##\n</sup> It is unclear whether radiological severity affects outcomes. As the complex multi-directional nature of DDH has become better understood, the importance of utilising a combination of radiological and clinical findings has been recognised, though not agreed upon.<sup>##REF##31977605##3##,##REF##32566146##16##,##REF##32030604##17##</sup></p>", "<p>Limited evidence suggests people suffering from DDH may experience pain, physical impairments, sporting limitations, and reduced quality of life (QOL).<sup>##REF##23594221##18##–##REF##30334645##20##</sup> Surgical management options include arthroscopy, osteotomy, and THA.<sup>\n##REF##31977605##3##\n</sup> Hip arthroscopy is considered controversial and is often cautioned in patients with DDH due to conflicting outcomes,<sup>\n##REF##31977605##3##\n</sup> with 1 in 4 failures of hip arthroscopy occurring in patients with DDH as a primary or secondary diagnosis.<sup>\n##REF##23637056##21##\n</sup> Despite this, hip arthroscopy is commonly used in patients with DDH, and so requires evaluation. The most common surgical treatment used to address symptomatic DDH is periacetabular osteotomy (PAO).<sup>##REF##19381741##22##,##UREF##3##23##</sup> The procedure aims to preserve the native hip joint and delay the need for THA by medialising the hip joint centre, redistributing the high contact stresses from the acetabular rim to the entire articular surface, and transforming the dysplastic hip’s shear stresses across the articular cartilage into compressive stresses that are more favourable for cartilage longevity.<sup>##REF##33163202##24##–##REF##20953924##27##</sup> Successful PAO surgery should not only improve structural abnormalities but also aim to improve pain, physical impairments, sporting limitations, and QOL. Several hip-specific patient-reported outcome measures (PROMs) exist to provide information on hip-related pain, function and QOL. However, there is limited systematic synthesis of PROMs, inhibiting our ability to confidently understand what these patients are experiencing. This affects our clinical approach and management, and our ability to truly appreciate the burden of this condition.</p>", "<p>This systematic review aimed to, in adults with DDH: (1) evaluate differences in pain, function and QOL in those undergoing PAO and healthy controls; (2) evaluate pre- to postoperative changes in pain, function and QOL following PAO; (3) evaluate differences in pain, function and QOL in those with mild versus severe dysplasia, undergoing PAO; and (4) evaluate differences in pain, function and QOL in those having primary PAO versus those with previous hip arthroscopy.</p>" ]
[ "<title>Methods</title>", "<p>Study selection, eligibility criteria, data extraction, and statistical analysis were performed according to the Cochrane Collaboration guidelines.<sup>\n##UREF##4##28##\n</sup> The systematic review was reported according to the preferred reporting guidelines for systematic reviews and meta-analysis (PRISMA) guidelines,<sup>\n##UREF##5##29##\n</sup> and was registered on the Prospero international prospective register of systematic reviews (ID: CRD42020144748).</p>", "<title>Search strategy</title>", "<p>A comprehensive, reproducible search strategy was performed on the following databases MEDLINE CINAHL, EMBASE, Sports Discuss, and PsychINFO from inception until 05 January 2021.</p>", "<p>The search strategy was conducted by 2 reviewers (MO, AS) and using the following concepts:</p>", "<p>(1) Humans with DDH aged ⩾15 years</p>", "<p>(2) Periacetabular osteotomy</p>", "<p>(3) Hip-specific patient-reported outcome measure</p>", "<p>Synonyms were searched within concepts using ‘OR’ operator and searched between concepts using ‘AND’ operator.</p>", "<p>For search strategy used see <ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 1</ext-link>.</p>", "<p>All potential references were imported into Endnote X8 (Thomson Reuters, Carlsbad, CA, USA) and duplicates removed. All included studies were then uploaded into Covidence software (Veritas Health Innovation Ltd, Australia) for screening. Title, abstract and full text screening was conducted by 3 independent reviewers (MO (A–Z), CS (A–M), LR (N–Z). Any disagreements were resolved by a 4th independent reviewer (JK).</p>", "<title>Eligibility criteria</title>", "<p>Studies were eligible for inclusion if they used a hip-specific patient-reported outcome measure (PROM) and were written in English. All quantitative observational study designs were considered eligible including randomised control trials, non-randomised controlled trials, case series, prospective or retrospective study designs.</p>", "<title>Participants/population</title>", "<p>People aged 15 years and older with DDH undergoing PAO (based on the mean or median age of the study sample). Studies were ineligible if the PAO was undertaken in people with Cerebral Palsy, Down Syndrome or Charcot-Marie Tooth Disease populations.</p>", "<title>Intervention(s), exposure(s)</title>", "<p>Studies utilising PAO surgery as primary intervention for DDH. The terms ‘Bernese Osteotomy’ and ‘Ganz Osteotomy’ were considered interchangeable with ‘Periacetabular Osteotomy’. Studies were ineligible if the PAO was reported to be a ‘rotational’ or ‘curved’ procedure as these procedures differ in surgical technique.</p>", "<title>Comparator(s)/control</title>", "<p>Studies using sham treatment, no treatment or other treatment (e.g. THA or hip arthroscopy surgery) as the comparator/control treatment were included. We also included studies where no comparison group was present if they used 2 time-points (e.g. case series). In this instance, the pre-intervention time-point was considered the ‘comparison’.</p>", "<title>Outcomes</title>", "<p>Primary outcomes of interest were hip-specific PROMs. These included: Hip disability and Osteoarthritis Outcome Score (HOOS), Western Ontario and McMaster universities osteoarthritis Index (WOMAC), the International Hip Outcome Tool (iHOT), the Copenhagen Hip and Groin Outcome Score (HAGOS), NonArthritic Hip Score (NAHS), and the Oxford Hip Score (OHS).</p>", "<p>The HOOS is a PROM used for patients with reduced hip function with or without hip osteoarthritis, consisting of 5 subscales (pain, symptoms, activities of daily living, sport/recreation and QOL) with a 0–100 score for each, with 100 being the best possible result.<sup>\n##REF##31069098##30##\n</sup> In patients undergoing PAO the minimal clinically important difference (MCID) is 10.3 for pain, 10.2 for symptoms, 10.8 for activities of daily living, 12.6 for sport and recreation, and 11.2 for QOL.<sup>\n##UREF##6##31##\n</sup> The HOOS has also shown adequate internal consistency and external validity.<sup>\n##UREF##6##31##\n</sup></p>", "<p>The WOMAC is a valid PROM for those with hip pain, consisting of 3 subscales (Pain, Stiffness, Function).<sup>\n##REF##2786253##32##\n</sup> Each subscale is summated to a maximum score of 20, 8, and 68, respectively. A lower score indicates a lower level of pain or symptoms. Typically, it has been used in older patients with degenerative joint disease but has also shown to be sensitive in a younger population following PAO.<sup>\n##REF##22159857##33##\n</sup> The minimal detectable change (MDC) has been reported as 5.51 for pain, 9.10 for function and 1.96 for stiffness,<sup>\n##UREF##6##31##\n</sup> and the MCID has been reported as 10.8 for pain, 12.9 for stiffness, 10.8 for function, in patients with DDH undergoing PAO.<sup>\n##REF##22159857##33##\n</sup></p>", "<p>The iHOT-33 is a PROM developed for younger active patients presenting with a variety of hip pathologies. Each score is out of 100, with 100 being the best score. It comprises of 33 questions relating to symptoms and functional limitations, sports and recreation activities, job-related concerns, and social, emotional and lifestyle concerns. The final score is then divided by 33. It has shown excellent validity and reliability with a minimal important change (MIC) of 6 and MDC ranging from 3.3 to 4.9 in those with hip pain.<sup>##REF##27011811##34##,##REF##29289588##35##</sup></p>", "<p>The HAGOS employs 6 subscales (symptoms, pain, function in daily living, function in sport and recreation, participation in physical activities, and QOL). Each subscale is scored from 0 to 100, with 100 being the best possible score. The HAGOS has also been used in patients following PAO and has been recently recommended one of the most appropriate PROMs to use in young and middle-aged active adults with hip-related pain.<sup>##REF##30712500##36##,##REF##32066573##37##</sup></p>", "<p>The NAHS was also developed for young active patients with higher demands and expectations.<sup>\n##UREF##7##38##\n</sup> It consists of 20 items distributed in 4 domains of pain, mechanical symptoms, functional symptoms, and activity level. The NAHS has satisfactory reliability and fair validity.<sup>\n##REF##27011811##34##\n</sup></p>", "<p>The OHS is a 12-question outcome measure assessing the patient’s hip pain and function.<sup>\n##REF##8666621##39##\n</sup> It generates a total score ranging from 0 to 48, where 48 indicates best possible result. The MIC for individual patients has been reported as 8, though this was in a population undergoing THA.<sup>\n##REF##25441700##40##\n</sup></p>", "<p>Certain hip-specific PROMs were not eligible for inclusion in this systematic review due to their reported limitations in this population. The modified Harris Hip Score (mHHS) has been shown to have a lack of content validity and the presence of a ceiling effect.<sup>##REF##27011811##34##,##REF##23835268##41##</sup> Similarly, the Hip Outcome Score (HOS) has also shown a ceiling effect and limited responsiveness following hip surgery.<sup>\n##REF##23835268##41##\n</sup> Therefore, studies that used the mHHS or the HOS as the primary PROM were not included. Studies using the Merle d’aubigne score, University of California Los Angeles activity-level rating score (UCLA), and visual analogue scale (VAS) were also excluded as these PROMs are not hip-specific. Studies using generic health-related QOL questionnaires were also not included as the purpose of this systematic review was to evaluate hip-specific outcome measures.</p>", "<p>Studies were excluded if: (1) no full text was available; (2) the study was an animal study; or (3) the study was written in a language other than English.</p>", "<title>Quality evaluation</title>", "<p>A modified version of the Downs and Black checklist was used to assess the quality of included studies. This modified version scores 18 potential criteria and has been used in other systematic reviews on hip pain.<sup>\n##REF##27301577##42##\n</sup> Studies were considered high quality with a score of &gt;60%.<sup>\n##REF##27301577##42##\n</sup> Included studies were rated by 2 independent reviewers (MO, LR). Any disagreements between reviewers were discussed in a consensus meeting and an independent arbitrator (JK) was employed when consensus could not be met. Agreement between rates was determined using Cohen’s Kappa (K).</p>", "<p>The Grades of Recommendation, Assessment, Development and Evaluation (GRADE) was applied to assess the quality of evidence for each meta-analysis.<sup>##REF##15205295##43##,##REF##18456631##44##</sup> The overall GRADE certainty ratings include ‘very low’, ‘low’, ‘moderate’ and ‘high’. Observational data is initially graded at ‘low’ and can be increased or decreased for various reasons.<sup>\n##REF##29051107##45##\n</sup> Certainty can be rated up for (1) large magnitude of effect, (2) dose response gradient, (3) all residual confounding would decrease magnitude of effect. Certainty can be rated down for (1) risk of bias (if mean modified epidemiology appraisal instrument scored &lt;60%), (2) imprecision (if upper or lower confidence interval [CI]) spanned a standardised mean difference [SMD] or standardised paired difference [SPD] of 0.5 in either direction), (3) inconsistency (if I<sup>2</sup> was ⩾25%), (4) indirectness (if clinically heterogeneous) and (5) publication bias (for example, small studies that are industry-sponsored).</p>", "<title>Data extraction, synthesis and analyses</title>", "<p>Data were extracted by 2 independent reviewers (MO, LR) into customised excel worksheets. The following data was extracted: author, year, country of origin, number of participants, demographic characteristics of participants (age, gender, body mass index [BMI], type of PAO), PROM scores, length of follow-up, and a summary of the findings was collated. Any discrepancies in data extraction were resolved by an independent reviewer (JK). A hierarchy of the different PROMs was decided on between authors to prioritise data extraction where more than one had been used, as recommended in the Cochrane guidelines.<sup>\n##UREF##4##28##\n</sup> The order of the hierarchy was based on the established level of validity and reliability of the PROM for young people with hip pain, and applicability to people with DDH undergoing PAO. In order of selection, the hierarchy was HOOS, WOMAC, IHOT, HAGOS, NAHS, OHS. Where data was insufficient, authors were contacted and asked to provide missing data.</p>", "<p>Studies were grouped according to design including: (1) between-group studies or (2) paired-data studies assessing change between pre- and post-PAO. If studies used a similar subscale, such as pain or QOL, at similar time-points then we performed meta-analysis using the random effects model. For between-group results this was done using Review Manager (RevMan) (Version 5.4.1 The Cochrane Collaboration, 2020), with a SMD and 95% CI for continuous data. The SMD is a summary statistic used to combine results from different studies that have measured similar outcomes but with different scales.<sup>\n##UREF##4##28##\n</sup> For analysis of paired-data studies, a standardised paired difference (SPD) was calculated using R statistical software (version 4.0.4, Metafor package version 3.0-2). The SPD and 95% CI were calculated from the sample size, mean and SD of the difference between time-points. SMDs and SPDs of 0.2, 0.5 and 0.8 were interpreted as small, moderate and large effect sizes, respectively.<sup>\n##UREF##8##46##\n</sup> Subgroup analyses were performed for specific time-points. Statistical heterogeneity across the pooled data was assessed using an I<sup>2</sup> statistic, with 25% considered low, 50% moderate and 75% as high levels of heterogeneity.<sup>\n##REF##12958120##47##\n</sup></p>", "<p>Where mean and SDs were not presented, we approximated mean scores from the median scores and SD from the range scores.<sup>\n##REF##25524443##48##\n</sup> Studies that only included total scores for outcomes that require subgroup scores, were not included in meta-analysis. Where patients had undergone 2 PAO surgeries, data was taken only for the first PAO. Participants were also excluded if it was easily identifiable that they had significant concomitant pathologies (e.g. Down syndrome, Charcot Marie Tooth Disease, septic arthritis). If postoperative data were not provided but change scores were, then the postoperative mean was calculated as the difference between the preoperative score and the change score. The preoperative standard deviation [SD] score was used as the postoperative SD score if this was unable to be imputed, as per the Cochrane guidelines.<sup>##REF##22159857##33##,##REF##28053253##49##,##REF##30393556##50##</sup></p>", "<p>Where individual studies were not sufficiently homogenous to be included in a meta-analysis, a best evidence synthesis was used to provide an overall rating for the body of evidence.<sup>\n##REF##19680101##51##\n</sup> Grading of the best evidence synthesis was completed using previously published criteria.<sup>##REF##27301577##42##,##REF##30389399##52##</sup> They were graded as strong (⩾2 studies with low risk of bias and ⩾75% agreement), moderate (⩾2 studies including at least 1 low risk of bias and ⩾75% agreement), limited (⩾1 moderate/high risk of bias studies, with ⩾75% agreement, or 1 low risk of bias study), conflicting (inconsistent findings &lt;75% agreement), or no evidence.</p>" ]
[ "<title>Results</title>", "<title>Search strategy</title>", "<p>The search yielded 5017 titles and abstracts for screening. 124 full-text studies were screened, and 62 studies were excluded. 62 studies fulfilled the inclusion criteria and were included in this systematic review. An overview of the study identification process is provided in ##FIG##0##Figure 1##.</p>", "<title>Methodological quality</title>", "<p><ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 2</ext-link> contains the results of risk of bias assessment using the modified Downs &amp; Black checklist. Initial agreement between quality assessors was moderate (K = 0.546).<sup>\n##REF##843570##53##\n</sup> The methodological quality scores ranged from 39% to 94%,<sup>##REF##24970582##54##,##REF##25822456##55##</sup> with an overall mean (SD) rating of 71% (11.6%). Of the included studies, 61 (98%) clearly described their aims or hypothesis and 60 (97%) outlined their main outcomes in the introduction or methods section. 17 studies (27%) stated if the main outcome measures used were valid and reliable, and only 8 studies (13%) provided characteristics of patients lost to follow-up.</p>", "<title>Participants</title>", "<p>The 62 studies included 8222 participants, with 6852 of these participants undergoing PAO. A proportion of these participants represent data-points that were published on multiple occasions. Sample sizes of the PAO groups ranged from 16 patients to 599 patients.<sup>##REF##30733041##56##,##REF##32106751##57##</sup> The mean (SD) ages for patients in the included studies ranged from 17 years to 45 years.<sup>##REF##33163209##58##,##REF##18534506##59##</sup> 26 studies were single cohort studies which assessed PROM preoperatively and postoperatively, <sup>##UREF##5##29##,##REF##31069098##30##,##REF##2786253##32##,##REF##29289588##35##,##REF##25524443##48##,##REF##33163209##58##,##REF##25287520##60##–##REF##20848246##80##</sup> 3 studies compared those having PAO as a first-time surgery with those who have had previous arthroscopy,<sup>##UREF##10##81##–##REF##28617619##83##</sup> and 3 studies compared those having PAO with healthy controls.<sup>##REF##25191933##19##,##UREF##11##84##,##UREF##12##85##</sup></p>", "<title>Outcome measures</title>", "<p>17 studies used the HOOS, 33 studies used the WOMAC, 5 studies used the iHOT, 4 studies used the HAGOS, 3 studies used the NAHS, and no studies used the OHS. Study details are contained in ##TAB##0##Table 1##. When a study used more than 1 of these questionnaires, only data from the highest-ranking PROM in our hierarchy was used.</p>", "<title>PAO versus healthy controls</title>", "<p>2 studies compared outcomes pre-operatively and postoperatively, between PAO patients and healthy controls, 1 high-quality prospective cohort study, and 1 high quality cross-sectional study.<sup>##REF##25191933##19##,##UREF##11##84##</sup> An additional high-quality cross-sectional study also compared the pain subscale only, between patients with DDH and healthy controls, preoperatively.<sup>\n##UREF##12##85##\n</sup> Meta-analysis of the preoperative time-point showed significantly worse pain (SMD [95% CI]: −4.05; −4.78 to −3.32) (##FIG##1##Figure 2##), activities of daily living (−2.81; −3.89 to −1.74) (##FIG##2##Figure 3##), QOL (−4.10; −4.43 to −3.77) (##FIG##3##Figure 4##), symptoms (−3.84; −4.36 to −3.29) (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 3</ext-link>), and sport &amp; recreation (−3.47; −3.79 to −3.16) (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 4</ext-link>), for those undergoing PAO versus controls. Despite the large magnitude of effect found, the GRADE level of certainty of these pre-operative difference between PAO patients and healthy controls is low. This is due to inconsistency in data and risk of bias.<sup>\n##REF##29051107##45##\n</sup></p>", "<p>Data were unable to be pooled for the postoperative time points as the studies used different follow-up time periods. Jacobsen et al.<sup>\n##REF##25191933##19##\n</sup> reported follow-up data at 6 months and 12 months postoperatively, and Maeckelbergh et al.<sup>\n##UREF##11##84##\n</sup> reported 32 months postoperative data. Across all subgroups the PAO group had significantly worse outcomes than the healthy controls, at every time point. The magnitude of difference between healthy controls and those undergoing PAO has significantly reduced with time following PAO (<italic toggle=\"yes\">p</italic> &lt; 0.001).</p>", "<title>Change from pre-op to post-PAO</title>", "<p>9 studies measured change in pain in their respective cohorts following PAO (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 5</ext-link>). Meta-analysis of 3 studies reported an improvement at the 1-year time-point (SPD 1.35; 95% CI, 1.02–1.67; I<sup>2</sup> = 80%). This included a prospective observational study,<sup>\n##UREF##6##31##\n</sup> a high-quality retrospective case series study,<sup>\n##UREF##12##85##\n</sup> and a high-quality prospective case series study.<sup>\n##REF##30712500##36##\n</sup></p>", "<p>A similar result was found at the 2-year timepoint (1.35; 1.16–1.54; I<sup>2</sup> = 64%) with meta-analysis of 4 studies. A prospective observational study,<sup>\n##UREF##6##31##\n</sup> and 3 respective cohort studies,<sup>\n##REF##22159857##33##\n</sup> 2 of which were high-quality.<sup>##REF##31069098##30##,##REF##30272611##72##</sup> Other included studies also reported improvement in pain at different timepoints, but meta-analysis was not possible at these timepoints as only single studies assessed the timepoint as shown in <ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 5</ext-link>.</p>", "<p>Changes in activities of daily living (ADL) following PAO was measured in 5 studies (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 6</ext-link>). Meta-analysis of a prospective observational cohort study and a high-quality prospective case series showed improvement at the 1-year time-point (1.22; 1.09–1.35; I<sup>2</sup> = 0%).<sup>##UREF##6##31##,##REF##30712500##36##</sup> This was also shown at the 2-year time-point (1.06; 0.90–1.22; I<sup>2</sup> = 53%) with meta-analysis of 3 studies, 2 high-quality retrospective cohort studies and a prospective observational study. A single study also showed improvement at the 1.5 year timepoint (1.63; 1.23–2.02).</p>", "<p>Improvements following surgery were also observed for QOL at 1-year (1.36; 1.22–1.5; I<sup>2</sup> = 0%) and 2-year (1.3; 1.1–1.5; I<sup>2</sup> = 65%) time-points (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 7</ext-link>), sport and recreation at 1-year (1.29; 1.01–1.57; I<sup>2</sup> = 68%) and 2-year (1.24; 0.92–1.57; I<sup>2</sup> = 87%) time-points (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 8</ext-link>), and symptoms at 1-year (1.16; 1.01–1.32; I<sup>2</sup> = 16%) and 2-year (1.02; 0.79–1.25; I<sup>2</sup> = 77%) time-points (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 9</ext-link>).</p>", "<p>The improvements found across all subgroups from pre- to post- PAO surgery provide low level certainty that pain, ADL, QOL, sport and recreation, and symptoms improve following surgery. Despite the large magnitude of effect found, risk of bias of studies and inconsistency in data means the GRADE certainty rating remains at low.<sup>\n##REF##29051107##45##\n</sup></p>", "<title>Primary PAO versus PAO following arthroscopy</title>", "<p>3 high-quality studies compared outcomes between those having a PAO as their first hip surgery, and those having a PAO following a previous arthroscopy.<sup>##UREF##10##81##–##REF##28617619##83##</sup> We were able to perform meta-analyses of 2 studies.<sup>##UREF##10##81##,##REF##30647927##82##</sup> The observational methodology of the studies means these results provide low level certainty that there was no significant difference preoperatively between both groups in pain (SMD 0.15; 95% CI, −0.38 to 0.68) (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 10</ext-link>), stiffness (−0.29; −1.10 to 0.52) (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 11</ext-link>) and function (−0.03; 0.90 to 0.84) (<ext-link xlink:href=\"https://journals.sagepub.com/doi/suppl/10.1177/11207000231179610\" ext-link-type=\"uri\">Supplemental Appendix 12</ext-link>).</p>", "<p>1 study provided limited evidence showing despite similar baseline values (0.17; −0.31 to 0.65), those with previous arthroscopy had significantly worse outcomes at 6 months (1.08; 0.43 to 1.74) and 1 year (0.83; 0.22 to 1.44) post PAO compared to those who had not had previous arthroscopy, as measured by the iHOT-33.<sup>\n##REF##28617619##83##\n</sup></p>", "<title>Mild versus severe dysplasia</title>", "<p>2 high-quality studies dichotomised their groups by their lateral centre-edge angle (LCEA) measurement.<sup>##REF##31069097##99##,##REF##27791238##101##</sup> We were unable to pool the data from these studies because of differences in outcome measures used, and differences in the LCEA used to define both groups. Ricciardi et al.<sup>\n##REF##28617619##83##\n</sup> compared those with a LCEA of 18–25° to those with LCEA of ⩽17° using the iHOT-33 at preoperative (−0.06; −0.57 to 0.45), 6-month (0.10 (−0.47 to 0.66) and 1-year time-points 0.05 (−0.64 to 0.73).<sup>\n##REF##27791238##101##\n</sup> Møse et al.<sup>\n##REF##31069097##99##\n</sup> compared those with a LCEA of 20–25° to those with a LCEA of &lt;20° using the WOMAC Pain subscale preoperatively (0.20; −0.23 to 0.63) and at 2 years postoperative (0.00; −0.43 to 0.48).</p>", "<p>This limited evidence shows no significant difference between groups with DDH pre-operatively or following surgery when dichotomised using LCEA.</p>" ]
[ "<title>Discussion</title>", "<p>Our systematic review aimed to evaluate pain, function, and QOL in adults with DDH undergoing PAO, as assessed by PROMs. We found low level evidence that those with DDH undergoing PAO had significantly worse PROMs (pain, symptoms, activities of daily living, sport &amp; recreation, and quality of life) preoperatively compared with healthy participants. Patients do improve following PAO surgery, and these improvements appear to be maintained for the 7 years of data we have available. Despite these improvements, post-operatively patients do not return to the same level of pain, function, and QOL as healthy participants for the 3-year period following surgery.</p>", "<p>We dichotomised results for patients with DDH based on their LCEA, into mild versus severe dysplasia. There is growing recognition that the diagnosis of DDH is more complex than just examining the LCEA, and probably involves multiple variables in the pattern of dysplastic morphology.<sup>\n##REF##31977605##3##\n</sup> The Ottawa classification system, as an example, identifies a proportion of dysplastic patients who have no lateral acetabular deficiency.<sup>\n##REF##32566146##16##\n</sup> There is also a greater recognition that variations in hip morphology are common in those who do not have symptoms,<sup>##REF##33356776##108##,##REF##33387651##109##</sup> implying that while morphology is a factor potentially influencing the severity of a patient’s symptoms, it may not be the primary driver of pain.</p>", "<p>Surgical complications are known to affect pain and activity in these patients but was not evaluated in this systematic review.<sup>##REF##15180229##26##,##REF##20953924##27##</sup> Though the PAO is considered a safe procedure with low levels of complications,<sup>##REF##30418279##106##,##REF##25471911##110##</sup> a recent study reported bony non-union as the most common major surgical complication at 12%, with 26% of these patients being symptomatic requiring open reduction and internal fixation.<sup>\n##REF##25471911##110##\n</sup></p>", "<p>There are a number of orthobiologic products utilised in other surgeries that have been shown to enhance bone grafts and provide higher rates of fusion in spinal orthopaedic surgery.<sup>\n##REF##26825787##111##\n</sup> However, it is unknown whether these are effective in PAO surgery or improve outcomes such as pain or QOL. There has also been no synthesis of the evidence in relation to PAO surgery. Understanding complications that potentially affect long-term pain and activity and possible solutions for such complications warrants further investigation.</p>", "<p>We only investigated differences in patient-reported outcomes, between patients with DDH undergoing PAO and healthy participants in this systematic review. However, similar deficits have been shown in this cohort in individual studies investigating physical impairments.<sup>##UREF##0##5##,##UREF##2##15##,##REF##15180229##26##,##UREF##6##31##,##REF##2786253##32##,##REF##27011811##34##,##REF##25287520##60##</sup> A synthesis of the evidence relating to physical impairments would provide greater understanding of how these patients present physically. Understanding physical impairments may also help inform pre- and postoperative rehabilitation by allowing clinicians to target these impairments in rehabilitation programs. These young adults may wish, and should be encouraged, to return to sport and physical activity.<sup>\n##REF##31959678##10##\n</sup> While this was not investigated in our review, future studies should explore this important domain.</p>", "<p>This review contains several limitations that should be acknowledged. Firstly, there were no randomised controlled trials, and a large proportion of retrospective studies, which have implications for introducing selection, performance and detection bias. Included studies demonstrated considerable variability in the risk of bias, outcomes reported, and post-operative assessment timepoints, which limited opportunities for meta-analysis. Included studies had poor transparency in describing characteristics of patients lost to follow-up, and a lack of validity and reliability for main outcome measures. The above factors rendered it impossible to obtain findings with ‘high’ level evidence and certainty ratings.<sup>\n##REF##15205295##43##\n</sup> Longitudinal studies are critical to investigate potential causality and better understand the relationships between pain, function and QOL in patients with DDH undergoing PAO.</p>", "<p>Adults with DDH undergoing PAO have more pain and worse function and QOL scores compared to healthy participants. Patients do improve following PAO surgery, and maintain this improvement, but they do not to the same level as their healthy participants. Our findings are important to patients and clinicians when considering PAO surgery, to appropriately manage expectations of recovery, thus enhancing the shared decision-making process, weighing up benefits of surgery against risks.</p>" ]
[]
[ "<title>Background:</title>", "<p>Hip dysplasia is a common condition in active adults with hip pain that can lead to joint degeneration. Periacetabular osteotomy (PAO) is a common surgical treatment for hip dysplasia. The effect of this surgery on pain, function and quality of life (QOL) has not been systematically analysed.</p>", "<title>Purpose:</title>", "<p>In adults with hip dysplasia: (1) evaluate differences in pain, function and QOL in those undergoing PAO and healthy controls; (2) evaluate pre- to post-PAO changes in pain, function and QOL; (3) evaluate differences in pain, function and QOL in those with mild versus severe dysplasia, undergoing PAO; and (4) evaluate differences in pain, function and QOL in those having primary PAO versus those with previous hip arthroscopy.</p>", "<title>Methods:</title>", "<p>A comprehensive, reproducible search strategy was performed on 5 different databases. We included studies that assessed pain, function and QOL in adults undergoing PAO for hip dysplasia, using hip-specific patient reported outcomes measures.</p>", "<title>Results:</title>", "<p>From 5017 titles and abstracts screened, 62 studies were included. Meta-analysis showed PAO patients had worse outcomes pre- and post-PAO compared to healthy participants. Specifically, pain (standardised mean difference [SMD] 95% confidence interval [CI]): −4.05; −4.78 to −3.32), function (−2.81; −3.89 to −1.74), and QOL (−4.10; −4.43 to −3.77) were significantly poorer preoperatively.</p>", "<p>Meta-analysis found patients experienced improvements following PAO. Pain improved from pre-surgery to 1-year (standardised paired difference [SPD] 1.35; 95% CI, 1.02–1.67) and 2 years postoperatively (1.35; 1.16–1.54). For function, the activities of daily living scores at 1 year (1.22; 1.09–1.35) and 2 years (1.06; 0.9–1.22) and QOL at 1 year (1.36; 1.22–1.5) and 2 years (1.3; 1.1–1.5) all improved. No difference was found between patients undergoing PAO with mild versus severe dysplasia.</p>", "<title>Conclusions:</title>", "<p>Before undergoing PAO surgery, adults with hip dysplasia have worse levels of pain, function and QOL compared to healthy participants. These levels improve following PAO, but do not reach the same level as their healthy participants.</p>", "<title>Registration:</title>", "<p>PROSPERO (CRD42020144748)</p>" ]
[ "<title>Supplemental Material</title>" ]
[ "<p>The authors would like to acknowledge the following people for providing additional information from their included study to assist our data analysis: Robert Cates, D.O.; Line Borreskov Dahl; Lea Franken; Jitendra Balakumar; and Julie Jacobsen.</p>" ]
[ "<fig position=\"float\" id=\"fig1-11207000231179610\"><label>Figure 1.</label><caption><p>Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flow diagram.</p></caption></fig>", "<fig position=\"float\" id=\"fig2-11207000231179610\"><label>Figure 2.</label><caption><p>Forest plot comparing <bold>Pain</bold> subscale scores in those undergoing PAO and healthy controls.</p><p>Interpretation of findings:</p><p>- 3.1.1 (pre-op) SMD = −4.05: large effect size (&gt;0.8) showing worse Pain scores in PAO patients versus healthy controls preoperatively.</p><p>- 3.1.2 (6 months) SMD = −2.19: large effect size (&gt;0.8) showing worse Pain scores in PAO patients versus healthy controls at 6 months postoperatively.</p><p>- 3.1.3 (12 months) SMD = −1.56: large effect size (&gt;0.8) showing worse Pain scores in PAO patients versus healthy controls at 12 months postoperatively.</p><p>- 3.1.4 (32 months) SMD = −0.83: large effect size (&gt;0.8) showing worse Pain scores in PAO patients versus healthy controls at 32 months postoperatively.</p><p>CI, confidence interval; IV, Random, random effects model; Std, standardised; SD, standard deviation; SMD, standardised mean difference; PAO, periacetabular osteotomy.</p></caption></fig>", "<fig position=\"float\" id=\"fig3-11207000231179610\"><label>Figure 3.</label><caption><p>Forest plot comparing <bold>Activities of Daily Living (ADL)</bold> subscale scores in those undergoing PAO and healthy controls.</p><p>Interpretation of findings:</p><p>• 3.3.1 (pre-op) SMD = −2.81: large effect size (&gt;0.8) showing worse ADL scores in PAO patients versus healthy controls preoperatively.</p><p>• 3.3.2 (6 months) SMD = −1.44: large effect size (&gt;0.8) showing worse ADL scores in PAO patients versus healthy controls at 6 months postoperatively.</p><p>• 3.3.3 (12 months) SMD = −1.12: large effect size (&gt;0.8) showing worse ADL scores in PAO patients versus healthy controls at 12 months postoperatively.</p><p>• 3.3.4 (32 months) SMD = −0.5: moderate effect size (0.5) showing worse ADL scores in PAO patients versus healthy controls at 32 months postoperatively.</p><p>CI, confidence interval; IV, Random, random effects model; Std, standardised; SD, standard deviation; SMD, standardised mean difference; PAO, periacetabular osteotomy.</p></caption></fig>", "<fig position=\"float\" id=\"fig4-11207000231179610\"><label>Figure 4.</label><caption><p>Forest plot comparing <bold>Quality of Life</bold> subscale scores in those undergoing PAO and healthy controls.</p><p>Interpretation of findings:</p><p>• 3.6.1 (pre-op) SMD = −4.1: large effect size (&gt;0.8) showing worse QOL scores in PAO patients versus healthy controls preoperatively.</p><p>• 3.6.2 (6 months) SMD = −2.48: large effect size (&gt;0.8) showing worse QOL scores in PAO patients versus healthy controls at 6 months postoperatively.</p><p>• 3.6.3 (12 months) SMD = −1.81: large effect size (&gt;0.8) showing worse QOL scores in PAO patients versus healthy controls at 12 months postoperatively.</p><p>• 3.6.4 (32 months) SMD = −1.42: large effect size (&gt;0.8) showing worse QOL scores in PAO patients versus healthy controls at 32 months postoperatively.</p><p>CI, confidence interval; IV, Random, random effects model; Std, standardised; SD, standard deviation; SMD, standardised mean difference; QOL, quality of life; PAO, periacetabular osteotomy.</p></caption></fig>" ]
[ "<table-wrap position=\"float\" id=\"table1-11207000231179610\"><label>Table 1.</label><caption><p>Summary of included studies.</p></caption><alternatives><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/><col align=\"char\" char=\".\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">Author (year)<break/>Study type</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Sample size/comparison<break/>Sex (Female %)/comparison<break/>Age mean (years)/comparison<break/>BMI mean (kg/m<sup>2</sup>)/comparison</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Quality Appraisal (using modified Downs &amp; Black)</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Population/Inclusion criteria</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Exclusion criteria</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">PROM data extracted</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Comparison Group</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">Timepoints</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">SMD Between Group<break/>Positive value = PAO group or first comparison favoured</th><th align=\"left\" rowspan=\"1\" colspan=\"1\">SPD Paired Data<break/>Positive value = Improvement from baseline to follow-up.</th></tr></thead><tbody><tr><td rowspan=\"3\" colspan=\"1\">Beaulé et al.<sup>\n##REF##25287520##60##\n</sup> (2015) Retrospective case series</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 67<break/>69%<break/>32y(R14–54)<break/>26kg/m<sup>2</sup></td><td rowspan=\"3\" colspan=\"1\">12/16</td><td rowspan=\"3\" colspan=\"1\">PAO patients. Surgical criteria: acetabular dysplasia with a CEA &lt;25°, hip pain for ⩾1 year, and failure of non-surgical management (medications and physiotherapy).</td><td rowspan=\"3\" colspan=\"1\">Surgical exclusion for PAO:<break/>(1) Tönnis grade 2<break/>(2) lack of congruity<break/>(3) age &gt;50 years.</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"3\" colspan=\"1\">Pre-op, 1 year post-op</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">0.99(0.70–1.29)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\">0.86(0.58–1.14)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\">0.76(0.48–1.03)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"3\" colspan=\"1\">Belzile et al.<sup>\n##REF##29632687##86##\n</sup> (2016) Retrospective cohort Study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 144/<italic toggle=\"yes\">n =</italic> 144<break/>82%/82%<break/>27y(R15 – 46)/27y(R14 – 46)<break/>24kg/m<sup>2</sup>/24kg/m<sup>2</sup></td><td rowspan=\"3\" colspan=\"1\">11/18</td><td rowspan=\"3\" colspan=\"1\">Patients undergoing PAO for DDH. Comparison group: patients treated for FAI</td><td rowspan=\"3\" colspan=\"1\">LCPD, neuromuscular disorders, bilateral procedures, joint space narrowing of &gt;2 mm, unavailable for 2-year follow-up and concomitant femoral corrective osteotomy</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">FAI (open and arthroscopic surgery)</td><td rowspan=\"3\" colspan=\"1\">Pre-op, 1 year post-op, 2 years post-op</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold> 0.21(-0.02–0.44)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/><bold>1-year:</bold> 0.84(0.6–1.08)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/><bold>2-years:</bold> 0.09(-0.14–0.32)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"3\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold> 0.30(0.07–0.53)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/><bold>1-year:</bold> 0.54(0.3–0.77)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/><bold>2-years:</bold> 0.09(-0.14–0.32)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold> 0.26(0.03–0.5)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/><bold>1-year:</bold> 0.4(0.17–0.64)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/><bold>2-years:</bold> -0.01(-0.24–0.22<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Biederman et al.<sup>\n##REF##17579861##87##\n</sup> (2008) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 50<break/>72%<break/>27y(R12 – 44)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">12/18</td><td rowspan=\"1\" colspan=\"1\">PAO with ⩾2 years follow-up</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Mean 7.4 years post-op</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Bogunovic et al.<sup>\n##REF##24914031##61##\n</sup> (2014)<break/>Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 36<break/>58%<break/>25y(R15 – 45)<break/>24 kg/m<sup>2</sup> (3.5)</td><td rowspan=\"1\" colspan=\"1\">10/16</td><td rowspan=\"1\" colspan=\"1\">PAO with preoperative UCLA score of ⩾7 and minimum of 18 months follow-up</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 33 months post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not-estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"5\" colspan=\"1\">Boje et al.<sup>\n##REF##31069098##30##\n</sup> (2019) Retrospective cohort study</td><td rowspan=\"5\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 321<break/>88%<break/>31y(R14-49)<break/>23 kg/m<sup>2</sup>(R16 – 34)</td><td rowspan=\"5\" colspan=\"1\">10/16</td><td rowspan=\"5\" colspan=\"1\">Patients undergoing PAO for DDH, who completed pre-operative questionnaire.<break/>Surgical indications: CEA &lt;25°, persistent hip pain, reduced walking distance, hip congruence, Tönnis OA Grade 0–1, hip flexion &gt;110° and internal hip rotation &gt;15°</td><td rowspan=\"5\" colspan=\"1\">Incomplete PROMs, underwent PAO due–other diagnoses DDH, underwent reverse PAO or femoral osteotomy, in patients operated bilaterally, the second operated hip was excluded</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"5\" colspan=\"1\">Pre-op and 2 years post-op</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.29(1.15–1.44)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\">0.95(0.82–1.08)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\">1.11(0.98–1.23)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\">1.32(0.88–1.75)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\">1.31(1.04–1.57)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Brusalis et al.<sup>\n##REF##32516278##62##\n</sup> (2020) Retrospective study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 25<break/>100%<break/>27y(7)<break/>NR</td><td rowspan=\"1\" colspan=\"1\"> 12/18</td><td rowspan=\"1\" colspan=\"1\">PAO patients who had ⩾1 prior hip arthroscopy on ipsilateral hip, a preoperative LCEA of ⩽24°, a Tonnis angle of &lt;10°, and ⩾6 months of follow-up clinical outcomes data<break/>Surgical indications: PAO performed if failed hip arthroscopy (persistent or recurrent pain within 5 years of arthroscopy</td><td rowspan=\"1\" colspan=\"1\">Incomplete radiographic data</td><td rowspan=\"1\" colspan=\"1\">iHOT-33</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 22 months</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">0.88(0.42–1.34)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Cates et al.<sup>\n##REF##31069099##63##\n</sup> (2019) Prospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 23<break/>83%<break/>25y(7)<break/>25kg/m<sup>2</sup> (6)</td><td rowspan=\"1\" colspan=\"1\">10/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO for DDH and retroversion</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 1 year and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Clohisy et al.<sup>\n##REF##28060231##64##\n</sup> (2017) Prospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 391<break/>79%<break/>25y(10)<break/>25kg/m<sup>2</sup></td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO for DDH</td><td rowspan=\"1\" colspan=\"1\">PAO for another diagnosis and revision PAO</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 2.6 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Dahl et al.<sup>\n##REF##24817397##88##\n</sup> (2014)<break/>Cross-sectional study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 116<break/>NR<break/>NR<break/>NR</td><td rowspan=\"1\" colspan=\"1\">13/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">7 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"3\" colspan=\"1\">Davidson et al.<sup>\n##REF##22159857##33##\n</sup> (2011) Retrospective cohort study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 83<break/>17%<break/>27y(R17-42)<break/>NR</td><td rowspan=\"3\" colspan=\"1\">8/16</td><td rowspan=\"3\" colspan=\"1\">PAO patients with completed WOMAC and SF-36 questionnaires</td><td rowspan=\"3\" colspan=\"1\">Non-completed questionnaires</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"3\" colspan=\"1\">Pre-op and 2 years post-op</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.34(1.04–1.64)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Domb et al.<sup>\n##REF##26233270##65##\n</sup> (2015) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 17<break/>82%<break/>24y(7)<break/>24kg/m<sup>2</sup>(5)</td><td rowspan=\"1\" colspan=\"1\">9/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing hip arthroscopy and PAO</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">NAHS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Duncan et al.<sup>\n##REF##25637398##89##\n</sup> (2015) Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 180<break/>77%<break/>26y<break/>24 kg/m<sup>2</sup></td><td rowspan=\"1\" colspan=\"1\">11/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO for symptomatic acetabular deformity</td><td rowspan=\"1\" colspan=\"1\">Perthes-like deformities, acetabular retroversion, no available digital radiographs, ipsilateral osteotomy</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Males vs. females</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Edelstein et al.<sup>\n##REF##33300755##66##\n</sup> (2021) Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 67<break/>93%<break/>29y(10)<break/>24 kg/m<sup>2</sup>(4)</td><td rowspan=\"1\" colspan=\"1\"> 11/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing concurrent arthroscopy and PAO Surgical criteria: Hip pain affecting daily function, persistent following 3 months of nonsurgical treatments, LCEA &lt;20° on radiographs without degenerative changes.</td><td rowspan=\"1\" colspan=\"1\">Diagnoses other than DDH. Associated neuromuscular disease, LCPD, SCFE, post-traumatic deformity, and isolated acetabular retroversion</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 6.5 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.42(1.08–1.76)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Garbuz et al.<sup>\n##REF##18534506##59##\n</sup> (2008)<break/>Cross-sectional cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 28/34<break/>90%/88%<break/>45y/47y<break/>NR</td><td rowspan=\"1\" colspan=\"1\">9/18</td><td rowspan=\"1\" colspan=\"1\">DDH with minimal or no osteoarthritis (Tönnis grade 0 or 1), age &gt;40 years, and 2-year follow-up data</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">THA</td><td rowspan=\"1\" colspan=\"1\">4 years post-op</td><td rowspan=\"1\" colspan=\"1\">Not estimable but results favoured THA group<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"3\" colspan=\"1\">Goronzy et al.<sup>\n##REF##27590644##90##\n</sup> (2017) Retrospective cohort study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 32/42<break/>100%/75%<break/>27y(11)/29y(10)<break/>23(4) kg/m<sup>2</sup>/24 kg/m<sup>2</sup>(4)</td><td rowspan=\"3\" colspan=\"1\">12/18</td><td rowspan=\"3\" colspan=\"1\">Patients undergoing PAO for DDH. Surgical criteria: decreased LCEA with hip pain lasting ⩾6 months not responding adequately to conservative therapy</td><td rowspan=\"3\" colspan=\"1\">Surgical PAO contraindications: advanced radiographic OA (Kellgren-Lawrence Grade 3 &amp; 4), joint space incongruency on radiographs, or patient age &gt;50 years</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">Isolated PAO<break/>/<break/>PAO+CAM</td><td rowspan=\"3\" colspan=\"1\">Pre-op and 31–102 months post-op</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.05(-0.51–0.41)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>6 years:<break/>0.0(-0.46–0.46)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"3\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.15(-0.31–0.61)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>6 years:<break/>0.0(-0.46–0.46)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.16(-0.3–0.62)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>6 years:<break/>0.07(-0.39–0.53) <sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Goronzy et al.<sup>\n##REF##33357245##67##\n</sup> (2020)<break/>Case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 86<break/>82%<break/>27y(10)<break/>24 kg/m<sup>2</sup>(4)</td><td rowspan=\"1\" colspan=\"1\"> 12/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing isolated PAO for DDH Surgical criteria: decreased LCEA with hip pain lasting ⩾6 months not responding adequately–conservative therapy</td><td rowspan=\"1\" colspan=\"1\">Surgical PAO contraindications: advanced radiographic OA (Kellgren-Lawrence Grade 3 &amp; 4), joint space incongruency on radiographs, or patient age &gt;50 years. Minors.</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 62 months post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Grammatopoulos et al.<sup>\n##UREF##13##91##\n</sup> (2018) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 244<break/>84%<break/>26y(10)<break/>24 kg/m<sup>2</sup>(4)</td><td rowspan=\"1\" colspan=\"1\">11/18</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO surgery</td><td rowspan=\"1\" colspan=\"1\">LCPD, SCFE, neuromuscular conditions, skeletal dysplasia, and no 2-year+ follow-up data</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 4 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Grammatopoulos et al.<sup>\n##REF##26066064##92##\n</sup> (2016) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 57<break/>86%<break/>25y(7)<break/>24 kg/m<sup>2</sup>(3)</td><td rowspan=\"1\" colspan=\"1\">13/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO for symptomatic DDH, developmentally mature hip without evidence of major joint incongruence or subluxation.</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Mean 8 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"3\" colspan=\"1\">Hartig-Andreasen et al.<sup>\n##REF##27011862##93##\n</sup> (2015)<break/>Prospective cohort study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 90<break/>88%<break/>34y(R15-59)<break/>NR</td><td rowspan=\"3\" colspan=\"1\">14/18</td><td rowspan=\"3\" colspan=\"1\">Patients following PAO. Surgical indications: persistent hip pain, a CEA of &lt;25°, pelvic bone maturity, IR&gt;15°, hip flexion &lt;110° and Tönnis grade of 0 or 1.</td><td rowspan=\"3\" colspan=\"1\">Multiple complaints from several joints, failure–show up at 2-year follow-up.</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">Hip Arthroscopy after PAO</td><td rowspan=\"3\" colspan=\"1\">Pre-op and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\">0.77(0.3–1.24)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"3\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\">0.6(0.13–1.06)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\">0.65(0.19–1.12)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Hartig-Andreasen et al.<sup>\n##REF##22576934##94##\n</sup> (2012) Cross-sectional study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 316<break/>72%<break/>33.9y(R13– 61)<break/>24 kg/m<sup>2</sup>(R15–37)</td><td rowspan=\"1\" colspan=\"1\">13/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO.<break/>Surgical indications: persistent hip pain, CEA of &lt;25°, pelvic bone maturity, absence of hip subluxation, IR of &gt;15°, and hip flexion &gt;110°.</td><td rowspan=\"1\" colspan=\"1\">Incomplete follow-up data or death. PAO contraindications: OA, reduced ROM, lack of hip congruence.</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Post-op (R4–12 years)</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Heyworth et al.<sup>\n##REF##26969123##95##\n</sup> (2016) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 46<break/>88%<break/>26y(R13–41)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">11/16</td><td rowspan=\"1\" colspan=\"1\">Aged 10–45 years at the time of surgery, minimum UCLA-AS score of 8/10, self-reported sport participation, and completed a hip questionnaire before surgery and ⩾1-year post-op.<break/>Surgical indications: hip pain secondary–DDH with LCEA of &lt;20°</td><td rowspan=\"1\" colspan=\"1\">Underlying neuromuscular disease, incomplete questionnaires, or not an athlete.</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 3 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Hingsammer et al.<sup>\n##REF##25834078##68##\n</sup> (2015) Prospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 37<break/>92%<break/>26y(9)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">10/16</td><td rowspan=\"1\" colspan=\"1\">Symptomatic DDH with a LCEA of &lt;20°</td><td rowspan=\"1\" colspan=\"1\">Hip flexion of &lt;90°, Tönnis grade of &gt;1, neuromuscular and chromosomal disorders, and an incongruous hip joint on radiographs</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 1 year and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Hsieh et al.<sup>\n##REF##19567851##96##\n</sup> (2009) Retrospective case-control study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 31/31<break/>84%/84%<break/>32y(R29–52)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">11/18</td><td rowspan=\"1\" colspan=\"1\">Patients who had undergone both PAO and THA on the contralateral side. Surgical indication: progressive hip pain.</td><td rowspan=\"1\" colspan=\"1\">THA performed at a different institution, lost–follow-up before two years after operation, previous hip surgery</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">THA</td><td rowspan=\"1\" colspan=\"1\">Post-op (mean 7, R3–10 years)</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"2\" colspan=\"1\">Jacobsen et al.<sup>\n##REF##25191933##19##\n</sup> (2014) Prospective cohort study</td><td rowspan=\"2\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 32/32<break/>81%/81%<break/>34y(R18–53)/33y(R18–54)<break/>22 kg/m<sup>2</sup>/22 kg/m<sup>2</sup></td><td rowspan=\"2\" colspan=\"1\">14/18</td><td rowspan=\"2\" colspan=\"1\">Diagnosis of DDH, planned pelvis operation, Tönnis OA grade 0–1, aged between 18–69 years</td><td rowspan=\"2\" colspan=\"1\">LCPD or epiphysiolysis, previous operations due–a herniated disc, joint preservation, or alloplastic surgery at the hip, knee or ankle region, or neurological or rheumatological disease</td><td rowspan=\"1\" colspan=\"1\">HAGOS Pain</td><td rowspan=\"1\" colspan=\"1\">Healthy Controls</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 6 months post-op</td><td rowspan=\"2\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-3.31(-4.08–-2.54)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>6 months:</bold>\n<break/>-2.19(-2.83–-1.54)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>1 year:</bold>\n<break/>-1.56(-2.14–-0.98)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"2\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS Symptoms</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-3.42(-4.21–-2.64)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>6 months:<break/>-2.03(-2.66–-1.4)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>-1.71(-2.30–-1.12)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HAGOS ADL</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-2.23(-2.86–-1.6)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>6 months:<break/>-1.44(-2.01–-0.87)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>-1.12(-1.67–-0.58)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HAGOS Sport</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-3.37(-4.15–-2.6)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>6 months:<break/>-2.30(-2.96–-1.64)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>-1.76(-2.36–-1.16)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HAGOS Participation</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-2.88(-3.59–-2.17)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>6 months:<break/>-2.04(-2.67–-1.4)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>1-year:<break/>-1.48(-2.05–-0.91)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HAGOS QOL</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-3.83(-4.67–-2.99)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>6 months:<break/>-2.48(-3.17–-1.80)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>-1.81(-2.41–-1.21)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"5\" colspan=\"1\">Jacobsen et al.<sup>\n##REF##30712500##36##\n</sup> (2019) Prospective case series</td><td rowspan=\"5\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 82<break/>87%<break/>30y(9)<break/>23kg/m<sup>2</sup>(3)</td><td rowspan=\"5\" colspan=\"1\">13/16</td><td rowspan=\"5\" colspan=\"1\">Surgical indications: LCEA of &lt;25°, groin pain &gt;3 months, and scheduled for PAO, &lt;45 years, with BMI &lt;30, &gt;110° of hip flexion, and with Tönnis grade &lt;2</td><td rowspan=\"5\" colspan=\"1\">Patients with comorbidities and previous surgical interventions affecting their hip function</td><td rowspan=\"1\" colspan=\"1\">HAGOS Pain</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"5\" colspan=\"1\">Pre-op and 1 year post-op</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.52(1.20–1.83)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS Symptoms</td><td rowspan=\"1\" colspan=\"1\">1.04(0.77–1.31)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS ADL</td><td rowspan=\"1\" colspan=\"1\">1.27(0.98–1.56)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS Sport</td><td rowspan=\"1\" colspan=\"1\">1.29(1.01–1.57)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS QOL</td><td rowspan=\"1\" colspan=\"1\">1.28(0.99–1.57)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"3\" colspan=\"1\">Kain et al.<sup>\n##UREF##10##81##\n</sup> (2011) Retrospective cohort study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 34/17<break/>100%/100%<break/>31y(10)/31y(10)<break/>NR</td><td rowspan=\"3\" colspan=\"1\">11/16</td><td rowspan=\"3\" colspan=\"1\">PAO only with MRI evidence of labral pathology prior–surgery<break/>/<break/>Initial arthroscopy for labral tear but eventual PAO</td><td rowspan=\"3\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">Initial arthroscopy for labral tear but eventual PAO</td><td rowspan=\"3\" colspan=\"1\">Pre-op and post-op (unspecified)</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.22(-0.91–0.48)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>Post-op:<break/>-0.40(-1.10–0.30)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"3\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.77(-1.49–-0.05)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>Post-op:<break/>-0.37(-1.07–0.33)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.52(-1.24–0.17)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>Post-op:<break/>-0.51(-1.22–0.19)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Karam et al.<sup>\n##REF##22096426##69##\n</sup> (2011) Prospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 33<break/>82%<break/>29y(R16–50)<break/>27kg/m<sup>2</sup>(R19–38)</td><td rowspan=\"1\" colspan=\"1\">10/16</td><td rowspan=\"1\" colspan=\"1\">PAO for symptomatic DDH</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 1 year post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Khan et al.<sup>\n##REF##28053253##49##\n</sup> (2017) Prospective longitudinal cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 151<break/>90%<break/>32y(R15–56)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO.<break/>Surgical indications: symptomatic DDH that had failed non-surgical treatment with a CEA &lt;25°, AI &gt;10° and a congruent hip joint</td><td rowspan=\"1\" colspan=\"1\">Surgery for acetabular retroversion.</td><td rowspan=\"1\" colspan=\"1\">NAHS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 3 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Kralj et al.<sup>\n##REF##16470438##70##\n</sup> (2005)<break/>Cross-sectional study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 26<break/>85%<break/>30y(R18–50)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">9/16</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO for DDH</td><td rowspan=\"1\" colspan=\"1\">Missing radiographs</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 12 years (R7–15)</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Larsen et al.<sup>\n##REF##32106751##57##\n</sup> (2020) Retrospective study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 599<break/>85%<break/>32y(R13–59)<break/>NR</td><td rowspan=\"1\" colspan=\"1\"> 14/16</td><td rowspan=\"1\" colspan=\"1\">PAO surgical indications: symptomatic DDH with persistent hip pain and reduced function, LCEA &lt; 25°, pelvic bone maturity, absence of hip subluxation, IR &gt;15°, and hip flexion &gt;110°, Tönnis OA grade 0, BMI ⩽ 25 and age ⩽ 45 years.</td><td rowspan=\"1\" colspan=\"1\">Reverse PAO, femoral osteotomy, persons without a Danish civil registration number, LCPD, and congenital hip dislocation. Surgical contraindications: OA, reduced ROM indicating joint degeneration, lack of hip congruence, BMI &gt; 30 kg/m<sup>2</sup></td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 6 months, 2 years, 5 years and 10 years</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"5\" colspan=\"1\">Li et al.<sup>\n##REF##31910042##71##\n</sup> (2020) Retrospective study</td><td rowspan=\"5\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 220<break/>84%<break/>28y(8)<break/>25kg/m<sup>2</sup>(4)</td><td rowspan=\"5\" colspan=\"1\"> 10/16</td><td rowspan=\"5\" colspan=\"1\">Patients undergoing PAO symptomatic DDH who did not respond–nonoperative treatment</td><td rowspan=\"5\" colspan=\"1\">Patients &lt;18 years, history of ipsilateral hip surgery</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"5\" colspan=\"1\">Pre-op and mean 1.5 years (R1–2.9) post-op</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.74(1.33–2.16)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\">1.28(0.93–1.64)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\">1.63(1.23–2.02)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\">1.85(1.41–2.28)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\">1.51(1.13–1.89)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Maeckelbergh et al.<sup>\n##UREF##11##84##\n</sup> (2018) Cross-sectional study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 42/963<break/>76%/66%<break/>27y(R14–50)/NR<break/>NR/24kg/m<sup>2</sup>(R11–38)</td><td rowspan=\"1\" colspan=\"1\">13/18</td><td rowspan=\"1\" colspan=\"1\">PAO for symptomatic DDH</td><td rowspan=\"1\" colspan=\"1\">Major intra- or postoperative complications. Incomplete or absent PROMs</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"1\" colspan=\"1\">Healthy Controls</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 2.6 years (R1–5)</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-4.23(-4.59–-3.87)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>32 months:<break/>-0.83(-1.14–-0.52)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-4.01(-4.37–-3.66)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>32 months:<break/>-1.0(-1.31–-0.68)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-3.33(-3.67–-2.99)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>32 months:<break/>-0.5(-0.81–-0.19)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-3.49(-3.84–-3.15)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>32 months:<break/>-0.94(-1.25–-0.63)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-4.15(-4.50–-3.79)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>32 months:<break/>-1.42(-1.73–-1.10)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\">Maldonado et al.<sup>\n##REF##30733041##56##\n</sup> (2019) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 16<break/>81%<break/>24y(7)<break/>24 kg/m<sup>2</sup> (6)</td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">Concomitant hip arthroscopy and PAO Surgical indications: LCEA &lt;18°, no evidence of severe chondral damage evidence on dGEMRIC MRA</td><td rowspan=\"1\" colspan=\"1\">Reverse’ PAO for acetabular retroversion. Surgical Contraindications: Advanced OA, Tönnis grade &gt;1, active infection, skeletally immature (age &lt;12 yr), MRI findings of significant chondral damage and subchondral cysts, ‘older age groups’</td><td rowspan=\"1\" colspan=\"1\">iHOT</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Minimum 5 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Matheney et al.<sup>\n##REF##19723987##97##\n</sup> (2009) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 109<break/>70%<break/>27y(9)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">14/16</td><td rowspan=\"1\" colspan=\"1\">PAO for DDH</td><td rowspan=\"1\" colspan=\"1\">Non-DDH. &lt;5 years outcome data</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">9 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"5\" colspan=\"1\">McClincy et al.<sup>\n##REF##30272611##72##\n</sup> (2019)<break/>Retrospective cohort study</td><td rowspan=\"5\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 49<break/>94%<break/>27y(8)<break/>24 kg/m<sup>2</sup>(5)</td><td rowspan=\"5\" colspan=\"1\">12/16</td><td rowspan=\"5\" colspan=\"1\">Patients undergoing PAO with pain and a LCEA of 18–25°</td><td rowspan=\"5\" colspan=\"1\">Surgical contraindications: Bilateral procedures, Dysplasia caused by surgical excision of a proximal femoral tumor, Tönnis grade 2 OA without remaining cartilage–correct into the weight-bearing zone.</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"5\" colspan=\"1\">Pre-op and 2 years post-op</td><td rowspan=\"5\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\"><bold>2 years:</bold>\n<break/>1.01(0.67–1.45)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\"><bold>2 years:</bold>\n<break/>0.8(0.44–1.16)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\"><bold>2 years:</bold>\n<break/>0.78(0.42–1.14)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\"><bold>2 years:</bold>\n<break/>1.03(0.64–1.42)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\"><bold>2 years:</bold>\n<break/>1.3(0.85–1.7) <sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Mechlenburg et al.<sup>\n##REF##30462599##73##\n</sup> (2018) Prospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 41<break/>83%<break/>29y(9)<break/>23 kg/m<sup>2</sup>(5)</td><td rowspan=\"1\" colspan=\"1\">13/16</td><td rowspan=\"1\" colspan=\"1\">LCEA ⩽24°, Tönnis OA grade 0 or 1, spherical femoral heads, painful hip, ⩾110° hip flexion and living &lt;70 km away from the hospital</td><td rowspan=\"1\" colspan=\"1\">LCPD, previous PAO or other hip surgery on the affected leg, age &lt;18 years</td><td rowspan=\"1\" colspan=\"1\">HAGOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 4 months and 12 months post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Mechlenburg et al.<sup>\n##REF##25822456##55##\n</sup> (2015) Prospective cohort study</td><td rowspan=\"1\" colspan=\"1\">26<break/>NR<break/>NR<break/>NR</td><td rowspan=\"1\" colspan=\"1\">15/16</td><td rowspan=\"1\" colspan=\"1\">Scheduled for PAO for DDH</td><td rowspan=\"1\" colspan=\"1\">Metal implants, neurologic illnesses, LCPD, previous corrective paediatric hip surgery</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 10 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Millis et al.<sup>\n##REF##19421831##98##\n</sup> (2009) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 70<break/>NR<break/>44y(R40–51)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">9/16</td><td rowspan=\"1\" colspan=\"1\">Symptomatic DDH, &gt;40 years of age at time of surgery</td><td rowspan=\"1\" colspan=\"1\">Acetabular dysplasia secondary–Down’s syndrome, inflammatory arthritis, LCPD, neuromuscular diagnoses, or isolated acetabular retroversion</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 5 years post-op (R2–14)</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Møse et al.<sup>\n##REF##31069097##99##\n</sup> (2019) Prospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 99<break/>92%<break/>34y(R14–59)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">Patients following PAO.<break/>Surgical indications: persisting hip pain, LCEA &lt;25°, pelvic bone maturity, IR &gt;15°, hip flexion &lt;110<sup>o</sup> and Tönnis OA grade 0 or 1</td><td rowspan=\"1\" colspan=\"1\">Multiple complaints from several joints, failure–show up at 2-year follow-up</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"1\" colspan=\"1\">Dysplasia (LCEA &lt;20 <sup>o</sup>) vs Borderline Dysplasia (LCEA 20 <sup>o</sup> -24 <sup>o</sup>)</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.2(-0.23–0.63)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>2 years:<break/>0.0(-0.43–0.48)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"6\" colspan=\"1\">Mortensen et al.<sup>\n##REF##30132502##100##\n</sup> (2018) Feasibility study</td><td rowspan=\"6\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 16<break/>75%<break/>28y(R22–40)<break/>24.3kg/m<sup>2</sup></td><td rowspan=\"6\" colspan=\"1\"> 12/16</td><td rowspan=\"6\" colspan=\"1\">Patients with DDH on waiting list for PAO and living within 50 km of Aarhus University Hospital, able–transport themself–the study location, and age ⩾18 years</td><td rowspan=\"6\" colspan=\"1\">Tönnis OA score &gt; 1; retroverted acetabulum, LCPD and epiphyseolysis; previous surgery for a herniated disc and spondyloses; lower limb joint preserving or arthroplasty of the hip, knee; neurological or rheumatological diseases affecting hip function; tenotomy of the iliopsoas tendon or z-plastic of the iliotibial band; BMI⩾ 40 kg/m<sup>2</sup></td><td rowspan=\"1\" colspan=\"1\">HAGOS Pain</td><td rowspan=\"6\" colspan=\"1\"> NA</td><td rowspan=\"6\" colspan=\"1\">Pre- and post strengthening programme</td><td rowspan=\"6\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">9.5(0.9–18.1)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS Symptoms</td><td rowspan=\"1\" colspan=\"1\">12.1(2.9–21.2)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS ADL</td><td rowspan=\"1\" colspan=\"1\">Reported no significant change<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS Sport</td><td rowspan=\"1\" colspan=\"1\">12.5(4.0–21.0)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS Participation</td><td rowspan=\"1\" colspan=\"1\">Reported no significant change<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HAGOS QOL</td><td rowspan=\"1\" colspan=\"1\">7.5(1.7–13.3)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"3\" colspan=\"1\">Novais et al.<sup>\n##REF##29876131##75##\n</sup> (2018) Retrospective case-control study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 104<break/>94%<break/>25y(8)<break/>24 kg/m<sup>2</sup>(4)<break/>/<break/><italic toggle=\"yes\">n =</italic> 52<break/>94%<break/>25y(7)<break/>24 kg/m<sup>2</sup>(5)</td><td rowspan=\"3\" colspan=\"1\">13/16</td><td rowspan=\"3\" colspan=\"1\">Patients undergoing PAO.<break/>Surgical criteria: DDH; no previous hip surgery; no concurrent femoral osteotomy procedure<break/>/<break/>PAO residual or persistent pain after an ipsilateral hip arthroscopy and the diagnosis of DDH based on LCEA &lt;25° or acetabular roof inclination of Tönnis &gt;10°</td><td rowspan=\"3\" colspan=\"1\">Diagnosis different than DDH; previous open surgeries.</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">PAO following arthroscopy</td><td rowspan=\"3\" colspan=\"1\">Pre-op and &gt;1 year post-op</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.35(0.01–0.68)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>0.56(0.22–0.9)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"3\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.77(-1.49–-0.05)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>0.38(0.05–0.72)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.36(0.03–0.70)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/>1 year:<break/>0.44(0.10–0.77)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Novais et al.<sup>\n##REF##23212768##74##\n</sup> (2013) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 51<break/>92%<break/>27y(11)<break/>24 kg/m<sup>2</sup>(4)</td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">Symptomatic DDH with complete data; hip pain for at least 3 months; LCEA &lt;16°, ACEA &lt;20°, or both; and Tönnis Grade 0–2</td><td rowspan=\"1\" colspan=\"1\">Tönnis Grade &gt;3; other significant hip condition; neuromuscular disease; incomplete data or medical records</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 1 year post-op and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Novais et al.<sup>\n##REF##30647927##82##\n</sup> (2018) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 33<break/>100%<break/>20y(6)<break/>23 kg/m<sup>2</sup>(3)</td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">Only female patients, &gt;1-year follow-up post-op, participation in dance</td><td rowspan=\"1\" colspan=\"1\">Surgical contraindications: Tönnis OA grade 2</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and median 2.7 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but trend towards improvement at follow-up</td></tr><tr><td rowspan=\"3\" colspan=\"1\">Okoroafor et al.<sup>\n##REF##31689124##76##\n</sup> (2019)<break/>Retrospective case series</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 58<break/>72%<break/>25y(R14–47)<break/>24 kg/m<sup>2</sup>(R19–32)</td><td rowspan=\"3\" colspan=\"1\"> 13/16</td><td rowspan=\"3\" colspan=\"1\">PAO for symptomatic DDH, not improving after 3 months of activity modification, physical therapy, NSAIDS and intra-articular CSI; radiographic evidence of femoral head uncovering; LCEA &lt;25° were indicated for surgery UCLA score of 7 preoperatively; ⩾5 years of follow-up data</td><td rowspan=\"3\" colspan=\"1\">Other significant hip condition; UCLA score &lt;7; history of trauma; neuromuscular or connective tissue disorder’ previous surgery; Tönnis grade 2 or 3; LCPD; SCFE</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"3\" colspan=\"1\">Pre-op and 7 years post-op</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.13(0.79–1.47)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\">0.64(0.35–0.93)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\">0.84(0.54–1.15)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Petrie et al.<sup>\n##UREF##9##77##\n</sup> (2020)<break/>Retrospective case study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 359<break/>77%<break/>25y(R10–54)<break/>25 kg/m<sup>2</sup>(R17–47)</td><td rowspan=\"1\" colspan=\"1\"> 11/16</td><td rowspan=\"1\" colspan=\"1\">Primary diagnosis of symptomatic acetabular dysplasia with minimum 2-year follow-up</td><td rowspan=\"1\" colspan=\"1\">Other significant hip conditions; neuromuscular disorders, and a history of prior ipsilateral pelvic osteotomy</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 45 months post-op (R20–91)</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ramírez-Núñez et al.<sup>\n##REF##32197953##78##\n</sup> (2020) Retrospective study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 118<break/>78%<break/>32y(10)<break/>NR</td><td rowspan=\"1\" colspan=\"1\"> 12/16</td><td rowspan=\"1\" colspan=\"1\">Patients with persistent mechanical hip pain, DDH, congruent joint surfaces, joint space greater than 3 mm, hip flexion greater than110<sup>0</sup> and IR &lt; 15<sup>0</sup></td><td rowspan=\"1\" colspan=\"1\">Missing radiological or functional information</td><td rowspan=\"1\" colspan=\"1\">NAHS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 7.7 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">2.86(2.44–3.26)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ricciardi et al.<sup>\n##REF##28617619##83##\n</sup> (2017) Retrospective case-control study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 27/<italic toggle=\"yes\">n =</italic> 50<break/>100%/88%<break/>25y(R15–43)/23y(R12–41) 22(R18–36) kg/m<sup>2</sup> / 23 kg/m<sup>2</sup> (R17–30)</td><td rowspan=\"1\" colspan=\"1\">15/18</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing PAO.<break/>&gt;6/12 postoperative from final hip surgery.<break/>Surgical indications: DDH (LCEA &lt;25), pain that has failed ⩾6 weeks of conservative management including physical therapy and NSAIDs, joint congruency, and Tönnis grade 0-1</td><td rowspan=\"1\" colspan=\"1\">Patients undergoing bilateral PAO with unilateral borderline dysplasia</td><td rowspan=\"1\" colspan=\"1\">iHOT-33</td><td rowspan=\"1\" colspan=\"1\">Mild DDH / Severe DDH</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 6 months and 1 year post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured follow-up<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ricciardi et al.<sup>\n##REF##27791238##101##\n</sup> (2017) Retrospective case-control study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 22<break/>91%<break/>27y(R18–41)<break/>22 kg/m<sup>2</sup>(3)</td><td rowspan=\"1\" colspan=\"1\">16/18</td><td rowspan=\"1\" colspan=\"1\">PAO for symptomatic DDH, &gt;6 months from last hip surgery, with pre-op hip-specific functional outcome, minimum 1-year clinical follow-up from their first PAO</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">iHOT-33</td><td rowspan=\"1\" colspan=\"1\">PAO following previous arthroscopy</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 6 months and 1 year post-op</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.17(-0.31–0.65)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>6 months:<break/>1.08(0.43–1.74)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>1 year:<break/>0.83(0.22–1.44)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ricciardi et al.<sup>\n##REF##27416990##102##\n</sup> (2016) Retrospective case-control study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 52/<italic toggle=\"yes\">n =</italic> 21<break/>89%/100%<break/>23y(R12–43)/27y(R12–41)<break/>23 kg/m<sup>2</sup>(3)/ 22 kg/m<sup>2</sup>(3)</td><td rowspan=\"1\" colspan=\"1\">14/18</td><td rowspan=\"1\" colspan=\"1\">symptomatic DDH undergoing PAO, &gt;6 months post-op from last hip surgery, with pre- and post-op outcome scores</td><td rowspan=\"1\" colspan=\"1\">Combined hip arthroscopy with labral debridement alone, and patients with a scope/PAO on 1 hip with a contralateral PAO alone</td><td rowspan=\"1\" colspan=\"1\">iHOT-33</td><td rowspan=\"1\" colspan=\"1\">PAO / Scope + PAO</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 6 months and 1 year post-op</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.46(-0.05–0.97)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>6-months: 0.10(-0.51–0.71)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>1 year:<break/>-0.41(-1.09–0.27)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ross et al.<sup>\n##REF##24970582##54##\n</sup> (2014) Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 30<break/>77%/87%<break/>24y/27y<break/>25 kg/m<sup>2</sup>/24 kg/m<sup>2</sup>(R18–35)</td><td rowspan=\"1\" colspan=\"1\">7/18</td><td rowspan=\"1\" colspan=\"1\">Symptoms that were refractory–non-operative treatment, a physical examination and radiographic findings consistent with acetabular dysplasia and a complete data set</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">PAO/PAO post-scope</td><td rowspan=\"1\" colspan=\"1\">Pre-op</td><td rowspan=\"1\" colspan=\"1\">Not estimable but favoured PAO group<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Scott et al.<sup>\n##UREF##12##85##\n</sup> (2020) Cross-sectional cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 24/21<break/>100%/91%<break/>24y(9)/25y(6)<break/>24 kg/m<sup>2</sup>(4)/24 kg/m<sup>2</sup>(3)</td><td rowspan=\"1\" colspan=\"1\"> 13/18</td><td rowspan=\"1\" colspan=\"1\">Aged 15–39 years with DDH (LCEA &lt;25°) scheduled for treatment with PAO</td><td rowspan=\"1\" colspan=\"1\">PAO exclusively for acetabular retroversion, neuromuscular condition, history of Perthes disease, Tönnis grade &gt;1, or previous open hip surgery were excluded</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"1\" colspan=\"1\">Healthy Participants</td><td rowspan=\"1\" colspan=\"1\">Pre-op</td><td rowspan=\"1\" colspan=\"1\">-4.84(-6.09–-3.6)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Swarup et al.<sup>\n##REF##33163209##58##\n</sup> (2018) Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 33<break/>97%<break/>17y(2)<break/>21.2 kg/m<sup>2</sup>(4)</td><td rowspan=\"1\" colspan=\"1\"> 10/16</td><td rowspan=\"1\" colspan=\"1\">Primary PAO or PAO following hip arthroscopy with a minimum of 1 year follow-up.<break/>Surgical indications: aged ⩽21, a LCEA ⩾18 and ⩽25.<break/>Patients undergoing bilateral PAO were included in this study if their outcomes were at least 12 months from the second sided surgery.</td><td rowspan=\"1\" colspan=\"1\">Patients that had missing baseline or 1-year follow-up data, patients that underwent anteverting PAO</td><td rowspan=\"1\" colspan=\"1\">iHOT-33</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 1-year post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">3.32(2.45–4.19)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Selberg et al.<sup>\n##REF##32452931##103##\n</sup> (2020) Retrospective study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 314<break/>85%<break/>24y(9)<break/>NR</td><td rowspan=\"1\" colspan=\"1\"> 12/18</td><td rowspan=\"1\" colspan=\"1\">Patients with symptoms &gt; 3 months preoperatively and DDH with a LCEA &lt;25°, minimum of 12 months postoperatively</td><td rowspan=\"1\" colspan=\"1\">Reverse PAO or PAO due–skeletal chondrodysplasia</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">Non-union following PAO</td><td rowspan=\"1\" colspan=\"1\">Pre-op and 12+ months post-op</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"5\" colspan=\"1\">Thanacharoenpanich et al.<sup>\n##REF##29423247##104##\n</sup> (2018) Retrospective case-control study</td><td rowspan=\"5\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 47/<italic toggle=\"yes\">n =</italic> 60<break/>87%/92%<break/>25y(10)/31y(9)<break/>25 kg/m<sup>2</sup>(4)/25 kg/m<sup>2</sup>(4)</td><td rowspan=\"5\" colspan=\"1\">14/18</td><td rowspan=\"5\" colspan=\"1\">Skeletally mature DDH patients (LCEA&lt;20° and/or ACEA &lt;20°) with a full thickness labral tear on preoperative MRA, ⩾1 year of follow-up after surgery.<break/>Surgical indications: ⩾3 months of hip and/or groin pain aggravated by activity, despite non-operative management</td><td rowspan=\"5\" colspan=\"1\">Any syndromic form of DDH and those who had incomplete data</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"5\" colspan=\"1\">PAO / PAO+A (Arthrotomy or Arthroscopy)</td><td rowspan=\"5\" colspan=\"1\">Pre-op and mean 2.1 years post-op (R1–3)</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.45(0.06–0.84)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>2 years:<break/>0.13(-0.25–0.51)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"5\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.68(0.29–1.07)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>2 years:<break/>0.18(-0.21–0.56)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.42(0.03–0.8)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>2 years:<break/>0.22(-0.17–0.6)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.61(0.22–1.0)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>2 years:<break/>0.3(-0.08–0.69)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>0.60(0.21–0.99)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>2-years:<break/>0.37(-0.01–0.76)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Troelsen et al.<sup>\n##REF##19723994##105##\n</sup> (2009) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 96<break/>78%<break/>30y<break/>24 kg/m<sup>2</sup>(R15–37)</td><td rowspan=\"1\" colspan=\"1\">11/16</td><td rowspan=\"1\" colspan=\"1\">Surgical indications: symptomatic acetabular dysplasia defined by persistent pain, a CEA of &lt;25°, a congruent hip joint, hip flexion of &gt;110°, and IR of &gt;15°</td><td rowspan=\"1\" colspan=\"1\">Unavailable for follow-up</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Mean 6.8 years (R5–9)</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"2\" colspan=\"1\">Wasko et al.<sup>\n##UREF##6##31##\n</sup> (2019) Prospective observational cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 294<break/>84%<break/>21y<break/>23 kg/m<sup>2</sup></td><td rowspan=\"2\" colspan=\"1\">8/16</td><td rowspan=\"2\" colspan=\"1\">Aged 18–40 years and undergone PAO for acetabular dysplasia and returned for 1 year follow-up</td><td rowspan=\"2\" colspan=\"1\">PAO for diagnoses other than DDH or if they presented with other lower-limb injuries at any time point</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op, 1 year and 2 years post-op</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\"><bold>1-year:</bold> 1.5(1.33–1.67)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>2-years:</bold>\n<break/>1.57(1.4–1.74)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>1-year:</bold> 1.21(1.06–1.36)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>2-years:</bold>\n<break/>1.22(1.07–1.37)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>1-year:</bold> 1.38(1.22–1.54)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>2-years:</bold>\n<break/>1.18(1.03–1.32)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>1-year:</bold> 1.41(1.25–1.57)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>2-years:</bold>\n<break/>1.54(1.37–1.71)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\"><bold>1-year:</bold> 1.38(1.22–1.54)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup>\n<break/><bold>2-years:</bold>\n<break/>1.45(1.28–1.61)<sup>\n<xref rid=\"table-fn2-11207000231179610\" ref-type=\"table-fn\">a</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Wells et al.<sup>\n##REF##29406343##79##\n</sup> (2018) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 154<break/>86%<break/>26yR10–60)<break/>24 kg/m<sup>2</sup>(R17–34)</td><td rowspan=\"1\" colspan=\"1\">13/16</td><td rowspan=\"1\" colspan=\"1\">PAO for symptomatic DDH</td><td rowspan=\"1\" colspan=\"1\">Neuromuscular or connective-tissue disorder, prior trauma, additional diagnoses other than DDH</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"1\" colspan=\"1\">Preserved vs symptomatic hips</td><td rowspan=\"1\" colspan=\"1\">Pre-op and ⩾6 months post-op</td><td rowspan=\"1\" colspan=\"1\">3.06(2.49–3.62)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Wells et al.<sup>\n##REF##30418279##106##\n</sup> (2019) Retrospective case series</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 129<break/>86%<break/>26y<break/>24 kg/m<sup>2</sup>(R17–34)</td><td rowspan=\"1\" colspan=\"1\">12/16</td><td rowspan=\"1\" colspan=\"1\">PAO for symptomatic DDH.<break/>Surgical criteria: symptomatic DDH, radiographic evidence of femoral head uncovering, and a LCEA of &lt;25°</td><td rowspan=\"1\" colspan=\"1\">Neuromuscular or connective-tissue disorder, prior trauma, additional diagnoses other than DDH</td><td rowspan=\"1\" colspan=\"1\">WOMAC</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Mean 10 years post-op (R1.7–20.5)</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Wells et al.<sup>\n##REF##27752989##2##\n</sup> (2017) Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 64/<italic toggle=\"yes\">n =</italic> 31<break/>83%/93%<break/>25y(9)/27y(8)<break/>26 kg/m<sup>2</sup>(5)/28 kg/m<sup>2</sup>(7)</td><td rowspan=\"1\" colspan=\"1\">13/16</td><td rowspan=\"1\" colspan=\"1\">PAO patients.<break/>Surgical criteria: Patients with hip pain and radiographic evidence of femoral head uncovering and a LCEA &lt;20° as well as closed triradiate cartilage</td><td rowspan=\"1\" colspan=\"1\">Hip trauma, neuromuscular or connective tissue disorder.<break/>Surgical contraindications: OA without remaining cartilage–correct into the weightbearing zone or prior hip trauma.</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">PAO Asymptomatic/ PAO Symptomatic</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 18 years (R14–22) post-op</td><td rowspan=\"1\" colspan=\"1\">Not estimable<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"1\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"5\" colspan=\"1\">Wyles et al.<sup>\n##REF##30393556##50##\n</sup> (2018) Retrospective cohort study</td><td rowspan=\"5\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 71<break/>87%<break/>27y(7)<break/>25 kg/m<sup>2</sup>(5)</td><td rowspan=\"5\" colspan=\"1\">10/18</td><td rowspan=\"5\" colspan=\"1\">Surgical criteria: closed triradiate cartilage and symptomatic DDH</td><td rowspan=\"5\" colspan=\"1\">Isolated acetabular retroversion, neurogenic dysplasia, LCPD or SCFE</td><td rowspan=\"1\" colspan=\"1\">HOOS Pain</td><td rowspan=\"5\" colspan=\"1\">PAO Arthrotomy / PAO Arthroscopy</td><td rowspan=\"5\" colspan=\"1\">Pre-op and post-op (unspecific)</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.02(-0.49–0.45)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>Follow-up:<break/>-0.57(-1.05–-0.09)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td><td rowspan=\"5\" colspan=\"1\">NA</td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Symptoms</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.11(-0.57–0.36)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>Follow-up:<break/>-0.53(-1.01–-0.05)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS ADL</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.02(-0.49–0.45)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>Follow-up:<break/>-0.37(-0.84–0.10)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS Sport</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.17 (-0.64–0.30)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>Follow-up:<break/>-0.39(-0.86–0.08)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">HOOS QOL</td><td rowspan=\"1\" colspan=\"1\"><bold>Pre-op:</bold>\n<break/>-0.03(-0.49–0.44)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup>\n<break/>Follow-up:<break/>-0.69(-1.18–<break/>-0.21)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"3\" colspan=\"1\">Ziebarth et al.<sup>\n##REF##20848246##80##\n</sup> (2011) Retrospective cohort study</td><td rowspan=\"3\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 38<break/>0%<break/>24y(10)<break/>NR</td><td rowspan=\"3\" colspan=\"1\">14/16</td><td rowspan=\"3\" colspan=\"1\">PAO for DDH.<break/>Surgical indications: pain, femoral head uncovering on the AP radiograph with LCEA &lt;20°</td><td rowspan=\"3\" colspan=\"1\">Surgical contraindications: OA, open triradiate cartilage, prior surgery</td><td rowspan=\"1\" colspan=\"1\">WOMAC Pain</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"3\" colspan=\"1\">Pre-op and mean 3 years post-op (R1–7.6)</td><td rowspan=\"3\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">1.36(0.86–1.87)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Stiffness</td><td rowspan=\"1\" colspan=\"1\">0.53(0.14–0.92)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">WOMAC Function</td><td rowspan=\"1\" colspan=\"1\">0.04(-0.32–0.41)<sup>\n<xref rid=\"table-fn3-11207000231179610\" ref-type=\"table-fn\">b</xref>\n</sup></td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ziran et al.<sup>\n##UREF##14##107##\n</sup> (2019) Retrospective cohort study</td><td rowspan=\"1\" colspan=\"1\"><italic toggle=\"yes\">n =</italic> 258<break/>83%<break/>32y(10)<break/>NR</td><td rowspan=\"1\" colspan=\"1\">12/18</td><td rowspan=\"1\" colspan=\"1\">Surgical indications: &gt;6 months of pain in the involved hip, adequate range of motion, Tönnis grade 1-2 or less with some exceptions, LCEA &lt;20°, and closure of the triradiate cartilage</td><td rowspan=\"1\" colspan=\"1\">NR</td><td rowspan=\"1\" colspan=\"1\">HOOS</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Pre-op and mean 11.2 years (R0.25–28 years)</td><td rowspan=\"1\" colspan=\"1\">NA</td><td rowspan=\"1\" colspan=\"1\">Not estimableb</td></tr></tbody></table></alternatives></table-wrap>" ]
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[ "<supplementary-material id=\"suppl1-11207000231179610\" position=\"float\" content-type=\"local-data\"><caption><title>sj-pdf-1-hpi-10.1177_11207000231179610 – Supplemental material for Pain, function and quality of life are impaired in adults undergoing periacetabular osteotomy (PAO) for hip dysplasia: a systematic review and meta-analysis</title></caption><p>Supplemental material, sj-pdf-1-hpi-10.1177_11207000231179610 for Pain, function and quality of life are impaired in adults undergoing periacetabular osteotomy (PAO) for hip dysplasia: a systematic review and meta-analysis by Michael JM O’Brien, Adam I Semciw, Inger Mechlenburg, Lisa CU Tønning, Chris JW Stewart and Joanne L Kemp in HIP International</p></supplementary-material>" ]
[ "<table-wrap-foot><fn id=\"table-fn1-11207000231179610\"><p>ACEA, anterior centre-edge angle; ADL, activities of daily living; AP, anteroposterior; CEA, centre-edge angle; CSI, corticosteroid injections; DDH, developmental dysplasia of the hip; FAI, femoroacetabular impingement; HAGOS, Copenhagen Hip and Groin Outcome Score; HOOS, Hip disability and Osteoarthritis Outcome Score; iHOT, International Hip Outcome Tool; IR, internal rotation; LCEA, lateral centre-edge angle; LCPE, Legg-Calvé-Perthes disease; MRI, magnetic resonance imaging; MRA, magnetic resonance arthrography; NA, not applicable; NAHS, Non-arthritic Hip Score; NR, not reported; NSAIDs, nonsteroidal anti-inflammatory drugs; PROM, patient-reported outcome measure; QOL, quality of life; ROM, range of motion; SCFE, slipped capital femoral epiphysis; UCLA, University of California Los Angeles; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.</p></fn><fn id=\"table-fn2-11207000231179610\"><label>a</label><p>Result also included in meta-analyses.</p></fn><fn id=\"table-fn3-11207000231179610\"><label>b</label><p>Result not included in meta-analyses for one of the following reasons: single study for a particular outcome or timepoint, same cohort as another study, incomplete data provided.</p></fn></table-wrap-foot>", "<fn-group><fn fn-type=\"COI-statement\"><p>The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</p></fn><fn fn-type=\"financial-disclosure\"><p><bold>Funding:</bold> The author(s) received no financial support for the research, authorship and/or publication of this article.</p></fn><fn fn-type=\"other\"><p><bold>ORCID iDs:</bold> Michael JM O’Brien \n<ext-link xlink:href=\"https://orcid.org/0000-0002-7438-0160\" ext-link-type=\"uri\">https://orcid.org/0000-0002-7438-0160</ext-link></p><p>Inger Mechlenburg \n<ext-link xlink:href=\"https://orcid.org/0000-0001-5432-8691\" ext-link-type=\"uri\">https://orcid.org/0000-0001-5432-8691</ext-link></p><p>Joanne L Kemp \n<ext-link xlink:href=\"https://orcid.org/0000-0002-9234-1923\" ext-link-type=\"uri\">https://orcid.org/0000-0002-9234-1923</ext-link></p></fn><fn fn-type=\"supplementary-material\"><p><bold>Supplemental material:</bold> Supplemental material for this article is available online.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"sj-pdf-1-hpi-10.1177_11207000231179610.pdf\"><caption><p>Click here for additional data file.</p></caption></media>" ]
[{"label": ["5"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Cooperman"], "given-names": ["D"], "article-title": ["What is the evidence to support acetabular dysplasia as a cause of osteoarthritis?"], "source": ["J Pediatr Orthop"], "year": ["2013"], "volume": ["33"], "issue": ["Suppl. 1"]}, {"label": ["14"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Ortiz-Neira", "Paolucci", "Donnon"], "given-names": ["CL", "EO", "T"], "article-title": ["A meta-analysis of common risk factors associated with the diagnosis of developmental dysplasia of the hip in newborns"], "source": ["Eur J Radiol"], "year": ["2012"], "volume": ["81"]}, {"label": ["15"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Clohisy", "Carlisle", "Beaul\u00e9"], "given-names": ["JC", "JC", "PE"], "etal": ["et al"], "article-title": ["A systematic approach to the plain radiographic evaluation of the young adult hip"], "source": ["J Bone Joint Surg Am"], "year": ["2008"], "volume": ["90"], "issue": ["Suppl. 4"], "fpage": ["47"], "lpage": ["66"]}, {"label": ["23"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Ganz", "Klaue", "Vinh"], "given-names": ["R", "K", "TS"], "etal": ["et al"], "article-title": ["A new periacetabular osteotomy for the treatment of hip dysplasia. Technique and preliminary results"], "source": ["Clin Orthop Relat Res"], "year": ["1988"], "volume": ["232"], "fpage": ["26"], "lpage": ["36"]}, {"label": ["28"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Cumpston", "Li", "Page"], "given-names": ["M", "T", "MJ"], "etal": ["et al"], "article-title": ["Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions"], "source": ["Cochrane Database Syst Rev"], "year": ["2019"], "volume": ["10"]}, {"label": ["29"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Page", "Moher", "Bossuyt"], "given-names": ["MJ", "D", "PM"], "etal": ["et al"], "article-title": ["PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews"], "source": ["BMJ"], "year": ["2021"], "volume": ["372"]}, {"label": ["31"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Wasko", "Yanik", "Pascual-Garrido"], "given-names": ["MK", "EL", "C"], "etal": ["et al"], "article-title": ["Psychometric properties of patient-reported outcome measures for periacetabular osteotomy"], "source": ["J Bone Joint Surg Am"], "year": ["2019"], "volume": ["101"]}, {"label": ["38"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Christensen", "Althausen", "Mittleman"], "given-names": ["CP", "PL", "MA"], "etal": ["et al"], "article-title": ["The nonarthritic hip score: reliable and validated"], "source": ["Clin Orthop Relat Res"], "year": ["2003"], "volume": ["406"], "fpage": ["75"], "lpage": ["83"]}, {"label": ["46"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Cohen"], "given-names": ["J"], "source": ["Statistical power analysis for the behavioural sciences"], "edition": ["2nd ed."], "publisher-loc": ["New York, NY"], "publisher-name": ["Erlbaum Associates"], "year": ["1988"]}, {"label": ["77"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Petrie", "Novais", "An"], "given-names": ["JR", "EN", "TW"], "etal": ["et al"], "article-title": ["What is the impact of periacetabular osteotomy surgery on patient function and activity levels?"], "source": ["J Arthroplasty"], "year": ["2020"], "volume": ["35"], "issue": ["Suppl."]}, {"label": ["81"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Kain", "Novais", "Vallim"], "given-names": ["MS", "EN", "C"], "etal": ["et al"], "article-title": ["Periacetabular osteotomy after failed hip arthroscopy for labral tears in patients with acetabular dysplasia"], "source": ["J Bone Joint Surg Am"], "year": ["2011"], "volume": ["93"], "issue": ["Suppl. 2"], "fpage": ["57"], "lpage": ["61"]}, {"label": ["84"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Maeckelbergh", "Peeters", "Moskal"], "given-names": ["L", "T", "J"], "etal": ["et al"], "article-title": ["Normative functional outcomes as a new outcome assessment tool following hip procedures"], "source": ["Orthopedics"], "year": ["2018"], "volume": ["41"]}, {"label": ["85"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Scott", "Willey", "Mercado"], "given-names": ["EJ", "MC", "A"], "etal": ["et al"], "article-title": ["Assessment of disability related to hip dysplasia using objective measures of physical performance"], "source": ["Orthop J Sports Med"], "year": ["2020"], "volume": ["8"]}, {"label": ["91"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Grammatopoulos", "Beaul\u00e9", "Pascual-Garrdio"], "given-names": ["G", "PE", "C"], "etal": ["et al"], "article-title": ["Does severity of acetabular dysplasia influence clinical outcomes after periacetabular osteotomy? A case-control study"], "source": ["J Arthroplasty"], "year": ["2018"], "volume": ["33"], "issue": ["Suppl."]}, {"label": ["107"], "mixed-citation": ["\n"], "person-group": ["\n"], "surname": ["Ziran", "Awad", "Matta"], "given-names": ["NM", "T", "JM"], "article-title": ["The periacetabular osteotomy technique"], "source": ["Tech Orthop"], "year": ["2016"], "volume": ["31"], "fpage": ["251"], "lpage": ["260"]}]
{ "acronym": [], "definition": [] }
111
CC BY
no
2024-01-14 23:43:45
Hip Int. 2024 Jan 12; 34(1):96-114
oa_package/1e/08/PMC10787396.tar.gz
PMC10787397
0
[ "<title>Background</title>", "<p id=\"Par9\">Studies on children and adolescents’ psychological well-being (PWB) have generally found a negative association with increased screen time [##REF##30406005##1##–##UREF##0##10##]. Overall screen use from video and online games, television, internet, smartphones, and online education increased, especially during the coronavirus disease of 2019 (COVID-19) pandemic year of 2020 [##REF##33879822##11##, ##REF##33885969##12##]. Previous studies have investigated the effect of the pandemic on screen time and its associations with mental health among children [##REF##34596669##13##, ##REF##34724543##14##]. However, these studies evaluated associations only during the pandemic, and among a subset of children previously reporting severe family and economic impact of COVID-19 [##REF##34596669##13##] or “COVID-related worry,” [##REF##34724543##14##] within specific age ranges. Thus, a study including all school-age children (6–17 years old) widely across the United States (US) representing all demographics and economic status, and analyzing the relationship between screen time and PWB over time, before and during the pandemic, is important.</p>", "<p id=\"Par10\">Since the pandemic generally increased screen time among school-age children due to online courses, we aimed to investigate recreational screen time (<italic>i.e.</italic> outside of school-related instructive screen use) more specifically, as we postulated that voluntary excessive screen overuse may be especially alarming during the time when school was mostly conducted online. Use of smartphones and other electronic devices has been shown to have both positive and negative effects [##REF##30406005##1##, ##REF##27997851##15##]. There is no definitive cut-off to determine hours of excessive screen use, and the specific type or content could have different impact. However, the American Academy of Pediatrics (AAP)’s current guideline for children aged 2–5 years old is to limit non-educational screen time to 1 h per day, and for children aged 6 years and older, to ensure that screen time does not interfere with sleep, physical activity, and other healthy behaviors [##REF##27256486##16##, ##UREF##1##17##].</p>", "<p id=\"Par11\">The American Psychiatric Association (APA) classifies internet gaming addiction as an impulse disorder [##UREF##2##18##], and as of 2018, the World Health Organization (WHO) included gaming disorder within the International Classification of Diseases, 11th revision (ICD-11) [##UREF##3##19##]. On the other hand, screen addiction from smartphones and other electronic devices has not yet been classified as a clinical disorder, even though the harms of screen overuse specifically related to these devices are well documented [##UREF##4##20##, ##UREF##5##21##]. Assessments of behavioral addiction include functional impairment or distress and persistence of the behavior over time [##REF##28198052##22##]. Various addiction screening tools specifically for smartphone or internet addiction have been proposed and used in research studies [##REF##31679605##4##, ##UREF##4##20##], and previous studies have reported associations between increased screen time and indicators of addiction [##REF##36405875##9##, ##REF##29435355##23##–##REF##28777828##25##]. Thus, further studies addressing the negative impact of screen time and overuse on PWB is important.</p>", "<p id=\"Par12\">The objective of this study is to explore the impact of the pandemic on recreational screen time and overuse, and its association with various measures of children’s PWB, using the National Survey of Children’s Health (NSCH), a large sample of children widely across the US. This survey includes various measures most relevant to this age group that could be used to assess PWB, highlighting the advantage of our study design aimed at understanding children’s conditions. We explored whether the trends and association between screen overuse and PWB have evolved during the year before versus during the pandemic, as well as the impact of the pandemic as an effect measure modifier to strengthen the association.</p>" ]
[ "<title>Methods</title>", "<title>Study subjects</title>", "<p id=\"Par13\">Since 2016, the Census Bureau has been administrating the National Survey of Children’s Health (NSCH) by mail and web-based surveys (instead of the earlier telephone method) in 50 states and the District of Columbia. Questionnaires are sentto one randomly chosen child aged 0–17 years, or their caregiver, per household. The publicly available dataset includes 50,212 observations for 2016, 21,599 for 2017, 30,530 for 2018, 29,433 for 2019, 42,777 for 2020, and 50,892 for 2021 [##UREF##6##26##]. Since our objective is to investigate school-age children, we included those aged 6–17 years widely. For years 2016 and 2017, the NSCH collected data on computer and TV hours separately, and total screen time can be assessed by adding those hours together. From 2018, the NSCH combined the survey question on computer and TV hours to collect screen time as one measure. We found that screen time range for 2016 and 2017 to be 0– ≥ 8 h, and 2018–2021 to be 0–4 h, providing the evidence that the data is not comparable. Therefore, we included only data from 2018, 2019, 2020, and 2021 to maintain consistency in the methods to collect data on screen time. We excluded respondents with reported autism, blindness, cerebral palsy, deafness, Down syndrome, developmental delay, epilepsy, or intellectual disabilities, as PWB measures and screen time behavior may require different assessments. Furthermore, we excluded missing data on screentime or PWB symptoms. In summary, we analyzed a total of 88,823 observations (18,746 respondents for 2018, 18,212 for 2019, 26,253 for 2020, and 25,612 for 2021) (Fig. ##FIG##0##1##).</p>", "<title>Variables and measures used</title>", "<title>Description of NSCH data</title>", "<p id=\"Par14\">Details on the NSCH study variable names according to the code book, questions used to collect data, and descriptions of recoded variables used in our study for subsequent analyses are provided in Additional file ##SUPPL##0##1##: Table S1. The 4 year weight for 2018–2021 was obtained from the NSCH’s Guide to Multi-Year Analysis, and adjusted weight was used for the analyses.</p>", "<title>Subject demographics</title>", "<p id=\"Par15\">We obtained data on age, race, ethnicity, sex, and poverty ratio. In accordance with the NSCH’s Guide to Analysis with Multiply Imputed Data, we computed the poverty ratio by averaging across the six imputed poverty ratio values, for subsequent analyses.</p>", "<title>Recreational screen time measure</title>", "<p id=\"Par16\">We used the NSCH variable, <italic>SCREENTIME</italic> for reported recreational screen use hours (TV, computer, cellphone, or other electronic devices to watch programs, play games or use social media) on most weekdays. The reported value ranges from 0.5 to 4, where 0.5 represents average screen time of &lt; 1 h, and 4 indicates ≥ 4 h. As previously reported [##REF##30406005##1##], low screen usage (&lt; 1 h) was found to negatively impact PWB, while between 1 and ≥ 4 h, increasing time was associated with worse PWB (Fig. ##FIG##1##2##). Thus, for the regression analyses, we only included 71,302 observations with at least one hour of screen usage every weekday.</p>", "<title>Screen overuse assessment</title>", "<p id=\"Par17\">We considered reported recreational screen time during a weekday of ≥ 4 h to be an indicator of screen overuse (variable <italic>Overuse</italic>, yes or no). After accounting for time for school (8 h), sleep (8 h), and commuting, eating and personal time (3–4 h) during a typical school day, there are approximately 4–5 h remaining for the day. We postulated that especially during the pandemic when school was conducted online, ≥ 4 h of recreational screen time indicates that a child is using a screen constantly throughout the day, and there is a reasonable concern of screen overuse. As described above, the maximum survey answer is ≥ 4 h, which is around a similar range to previous studies, including a previous study showing ≥ 3 h per day on social media as a risk factor for mental health among adolescents [##UREF##0##10##], or a study on screen addiction among children which used ≥ 4 h per weekday as the maximum survey answer [##REF##36405875##9##], or a study on smartphone addiction among university students, which considered ≥ 5 h per weekday as excess use [##REF##28777828##27##].</p>", "<title>PWBIS development</title>", "<p id=\"Par18\">In a previous study, PWB was described as a broad concept reflective of various factors, including, “emotional stability, positive interpersonal relationships, self-control, and indicators of flourishing as well as diagnoses of mood disorders such as anxiety or depression.” [##REF##30406005##1##] Accordingly, we considered the following NSCH study variables as PWB factors relevant to school-aged children: ability to remain calm and in control when challenged (K7Q85_R), argues too much (K7Q70_R), difficulty making or keeping friends (MAKEFRIEND), works to finish tasks they have started (K7Q84_R), shows interest and curiosity (K6Q71_R), is difficult to care for (K8Q31), has ever been diagnosed by healthcare professionals with depression (K2Q32A) or anxiety (K2Q33A). The original study variables were recoded as dichotomous variables for developing PWB issue scores (PWBIS) for downstream analyses (Additional file ##SUPPL##0##1##: Table S1). A child experiencing low PWB is expected to have one or more of the above related psychological symptoms. We constructed two scores to indicate PWB issues (Additional file ##SUPPL##0##1##: Table S2) as described below:</p>", "<p id=\"Par19\"><bold><italic>PWBIS1</italic></bold> is a composite score ranging from 0 to 6, where the higher the value is, the lower the PWB, and calculated by adding six of the PWB symptom dichotomous variables relating to depression and anxiety (<italic>Not Calm</italic>, <italic>Argues Too Much</italic>, <italic>Difficult to Make Friends</italic>, <italic>Does Not Finish Tasks</italic>, <italic>Not Curious</italic>, and <italic>Difficult to Care</italic>).</p>", "<p id=\"Par20\"><bold><italic>PWBIS2</italic></bold> is a dichotomous score with a value of 1 if any of the eight distinct symptom variables are 1 (<italic>Not Calm</italic>, <italic>Argues Too Much</italic>, <italic>Difficult to Make Friends</italic>, <italic>Does Not Finish Tasks</italic>, <italic>Not Curious</italic>, <italic>Difficult to Care</italic>, <italic>Depression</italic>, or <italic>Anxiety</italic>), or otherwise is 0.</p>", "<title>Multivariable regression models</title>", "<p id=\"Par21\">Various multivariable Generalized Least Square (GLS) models for PWBIS1 (Model1 and Model2), or logistic regression models for PWBIS2 (Model3 and Model4), were constructed (Additional file ##SUPPL##0##1##: Table S3). For each of the four models, either screen time in hours (<italic>Screen Time</italic>) or screen overuse, defined as recreational screen time ≥ 4 h a day (<italic>Overuse</italic>) was included in the model as the main effect to be assessed. Compared to Model1 and Model3, Model2 and Model4 include two additional variables: a dummy variable to represent the pandemic years 2020 and 2021 (<italic>Pandemic years 2020 and 2021</italic>), and an interaction term between the pandemic years dummy variable and screen time or overuse (<italic>Screen Time or Overuse</italic> × <italic>Pandemic years</italic>), to understand how the pandemic years may be an effect modification for the association between recreational screen time and PWBIS. As conventionally conducted in a multi-level model, the centralized and standardized screen time was used to compute the interaction term. Age was categorized as elementary school-age (6–10 years old), middle school-age (11–13 years old), and high school-age (14–17 years old) as the reference group. Categorical variables for sex (female as reference), race (White as reference), and ethnicity (not otherwise Hispanic or Latino as reference) were used.</p>", "<p id=\"Par22\"><bold><italic>Software</italic></bold> SAS version 9.4 (SAS Institute Inc, NC).</p>" ]
[ "<title>Results</title>", "<title>Recreational screen time and overuse significantly increased during the pandemic year compared to previous years</title>", "<p id=\"Par23\">Our study included a total of 88,823 school age children (6–17 years old) in the NSCH survey over four years (18,746 in 2018, 18,212 in 2019, 26,253 in 2020, and 25,612 in 2021) (Fig. ##FIG##0##1##). The overall demographics show that a large number of elementary (6–7 years old), middle (11–13 years old), and high (14–17 years old) school-age children across the US are represented (Table ##TAB##0##1##). On average, they spent increasing hours of screen recreationally (<italic>i.e.</italic> outside of school work) over the years, with 2.38 h in 2018, 2.41 h in 2019, 2.70 h in 2020, and 2.59 h in 2021 (p &lt; 0.01 compared to each previous year) (Table ##TAB##1##2##). The proportion of those with screen overuse (hours reported) or overuse (≥ 4 h of recreational screen time a day), also significantly increased over time, with 22.72% in 2018, 24.39% in 2019, 32.80% in 2020, and 29.41% in 2021 (p &lt; 0.01 compared to each previous year), and especially during 2020, the first pandemic year showing a notable 8.41% surge from the previous year (Table ##TAB##1##2##). The 2020 results also showed a decrease in the proportion reporting ≤ 2 h compared to 2018 and 2019, and an increase in reporting of ≥ 3 h (23.15% in 2018 and 23.79% in 2019, versus 33.86% in 2020), showing an overall changing trend in recreational screen time (p &lt; 0.0001) (Table ##TAB##2##3##). In addition, the combined amounts from the pre-pandemic years of 2018 and 2019 (23.15% and 23.79%, respectively) are much smaller than the pandemic years of 2020 and 2021 (33.86% and 29.02%).</p>", "<title>PWB declined significantly during the pandemic</title>", "<p id=\"Par24\">We devised two scores (PWBIS1 and PWBIS2) as indicators of overall mental health, using the NCHS survey variables, allowing an assessment most relevant to children. The composite PWBIS1 considers six NCHS survey questions related to the inability to stay calm, arguing behavior, difficulty in making and maintaining friendship, inability to finish tasks, lack of curiosity, and difficulty for parents to care for. The dichotomous PWBIS2 considers whether any of those six conditions, or additionally, depression or anxiety were reported (Additional file ##SUPPL##0##1##: Table S2). While PWBIS1 was comparable between 2018 and 2019 (0.843 and 0.839, respectively, p = 0.0641), it increased significantly in the pandemic year, 2020 (1.031, p &lt; 0.0001 compared to 2019) and 2021 (1.029, p = 0.0018) (Table ##TAB##2##3##). Similarly, while PWBIS2 score was comparable between 2018 and 2019 (45.3% and 45.8%, respectively, p = 0.284), it increased significantly in 2020 (51.7%, p &lt; 0.0001), and 2021 (51.3%, p = 0.385 compared between 2020 and 2021) (Table ##TAB##2##3##). These observations demonstrate that the pandemic years indeed had an impact on children’s PWB.</p>", "<title>Screen time and PWB are associated with various demographic factors</title>", "<p id=\"Par25\">In order to further explore potential factors associated with screen time and PWB, we evaluated the distributions of screen time and PWB across sex, race, ethnicity, and poverty ratio. In all age groups (<italic>i.e.</italic> elementary school, middle school, and high school), higher proportions of females were found in the lower &lt; 1 h, 1 h, 2 h screen time categories, while, higher proportions of males were found in the higher 3 h and ≥ 4 h screen time categories (p &lt; 0.0001) (Table ##TAB##3##4##). For PWBIS1 and PWBIS2 where higher scores indicate worse psychological well-being issue, among all age groups, higher scores were found for males compared with females, while for high school, higher scores were found for females than males.</p>", "<p id=\"Par26\">The proportions of the various race categories across screen time were variable among elementary school (5.05% Hawaiian or other Pacific Islander as the lowest and 11.19% White as the highest for the &lt; 1 h category; and 8.65% some other race alone as the lowest and 21.62% Hawaiian or Other Pacific Islander as the highest for the ≥ 4 h category); middle school (1.19% Native American or Alaska Native as the lowest and 10.47% Hawaiian or other Pacific Islander as the highest for the &lt; 1 h category; and 16.25% Hawaiian or other Pacific Islander as the lowest and 35.22% Native American or Alaska Native as the highest for the ≥ 4 h category); and high school (2.14% Native American or Alaska Native as the lowest and 6.57% some other race alone as the highest for the &lt; 1 h category, and 30.09% some other race alone as the lowest and 45.36% Black or African American as the highest for the ≥ 4 h category). A relatively higher proportion of Hispanic or Latino related children were found among the ≥ 4 h screen time category across age groups (18.42% Hispanic or Latino related versus 15.02% otherwise, among elementary school children; 30.33% Hispanic or Latino related versus 27.88% otherwise, among elementary school children; 42.55% Hispanic or Latino related versus 39.94% otherwise, among elementary school children). With regards to PWB measures, for elementary school, Native American or Alaska Native categories were found to have the highest PWBIS1 and PWBIS2 (1.14 and 56.53%). Some Other Race Alone was found as having the lowest PWBIS1 (0.74) and Hawaiian or other Pacific Islander as the lowest PWBIS2 (37.90%). For middle school, Native American or Alaska Native was found to have the highest PWBIS1 (1.12) and Hawaiian or other Pacific Islander as the highest PWBIS2 (52.09%), while Asian was found having the lowest PWBIS1 (0.77) and some other race alone as the lowest PWBIS2 (39.71%). For high school, Native American or Alaska Native was found with both the highest PWBIS1 and PWBIS2 (1.2 and 57.65%). Some Other Race Alone was found as having the lowest PWBIS1 (0.76) and Asian aas the lowest PWBIS2 (46.03%).</p>", "<p id=\"Par27\">As there are various definitions for poverty level, in this study, we evaluated the median poverty ratio of the overall study as the cut off and compared the screen time above and below the median poverty ratio. For all age groups (<italic>i.e.</italic> elementary school, middle school, and high school), higher proportions were found in the below median poverty ratio groups for ≥ 4 h screen time categories (p &lt; 0.0001), while the results for the lower &lt; 1 h, 1 h, 2 h and 3 h screen time categories were variable. For all age groups, below median poverty ratio was found to have higher PWBIS1 and PWBIS2, compared to above median, as expected.</p>", "<title>Recreational screen time and overuse are associated with declining PWB, and the pandemic years significantly strengthened the association</title>", "<p id=\"Par28\">As previously suggested [##REF##30406005##1##], low screen usage (&lt; 1 h) resulted in reduced PWB, while increasing time was associated with worse PWB when evaluating screen usage between 1 and ≥ 4 h, (Fig. ##FIG##1##2##). Therefore, we performed regression analyses, with only 71,302 observations with at least one hour of screen usage every weekday. We constructed various multivariable GLS models to evaluate the magnitude of the association between recreational screen time (in hours) or overuse (≥ 4 h a day) and PWBI1, adjusting for age, race, ethnicity, and poverty ratio, first without considering the 2020 and 2021 pandemic years (Model1), and separately, including the pandemic years as a covariate in the model or as an interaction term (Model2) to assess its impact as an effect measure modifier (Table ##TAB##4##5##). Both screen time and overuse were positively associated with PWBI1, and the models including the 2020 and 2021 pandemic years as a covariate also showed significant association or effect modification (p &lt; 0.001 in all models).</p>", "<p id=\"Par29\">Using a similar approach, we also constructed multivariable logistic regression models for the PWBI2 outcome, adjusting for age group, sex, race, ethnicity, and poverty ratio. Each hour increase in screen time was associated with 1.498 times increased odds (p &lt; 0.001), and screen overuse, was associated with 2.0 times (p &lt; 0.001) the odds of PWBIS2 outcome, without considering the pandemic years (Model3) (Table ##TAB##5##6##). Including the pandemic years and their interaction term, screen hours was associated with an OR of 1.489, and screen overuse with an OR of 1.978, for the PWBIS2 outcome (Model4). In these models, the pandemic years were associated with an OR of 1.094 for the model with screen time, or 1.102 for the model with overuse. The interaction terms also showed a positive significant association (p &lt; 0.001), suggesting the impact of the pandemic on strengthening the effect of screen time and overuse on PWB issues.</p>", "<p id=\"Par30\">Collectively, these various results show that higher screen time and overuse are significantly related to various measures of PWBIS over 2018–2021, and that the pandemic years of 2020 and 2021 contributed to children’s low PWB. Furthermore, the interaction terms between screen time or overuse and the years 2020 and 2021 highlight the impact of the pandemic on strengthening the effect of screen time or overuse on PWB issues.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par31\">The NCHS dataset used in this study included a large sample of school-age children across the entire US, providing results that are more widely applicable compared to previous studies. Previous studies explored the impact of the pandemic years on the overall (<italic>i.e.</italic> instructional and recreational combined) screen use [##REF##33879822##11##, ##REF##33885969##12##] or their associations with mental health only among a subset of children from a narrower age range who previously reported severe COVID-related family and economic hardship [##REF##34596669##13##] or worry [##REF##34724543##14##]. Therefore, our objective was to perform a more comprehensive study comparing the years before versus during the pandemic, to evaluate the effect, specifically of recreational screen overuse, among all school-age children (6–17 years old) and all demographics and economic status generally across the US, rather than specific groups of children. These differences underscore the wide applicability, importance, and novelty of our findings.</p>", "<p id=\"Par32\">Among our study’s large population, we quantified the significant surge in recreational screen time and overuse and decline in PWB during the 2020 and 2021 pandemic years, compared to prior years of 2018 and 2019. We developed various PWBIS that are relevant to children, and assessed their association with recreational screen time and overuse in various regression models, as well as constructed additional models to demonstrate the impact of the pandemic on PWB independently of screen time or overuse, and also found evidence that it strengthens the association between screen use and PWB. We also identified differences in both screen time and PWB scores comparing various demographic variables of sex, race, ethnicity, and socioeconomic status to investigate subgroup differences. Additional investigations of possible long-term impact and studies in other nations could also be informative.</p>", "<p id=\"Par33\">Innovations and decreasing costs have made online education, entertainment, and virtual social connections increasingly more accessible and equitable [##UREF##7##28##], and during the pandemic, access to education and social connections through screens was vital to children’s mental health [##UREF##8##29##]. A previous study conducted several years before the pandemic suggested that while excessive internet use is well-established to be associated with depression, too little usage hours could also be associated with depression [##REF##27940794##30##]. Our study using data of two years leading up to, and during the pandemic, also found that screen use of less than one hour resulted in worse PWB compared to one hour, while increasing hours beyond one hour showed worsened PWB. Despite the benefits from reasonable use, excessive screen use is a major concern especially among children, as reduced recreational activities that involve observations and explorations of the environment can negatively impact cognitive development [##REF##35666518##31##].Excessive screen time is also associated with adverse physiological effects, including obesity [##REF##27256486##32##, ##REF##34334279##33##], sleep disruption, [##REF##29499467##2##, ##REF##34334279##33##–##REF##27294324##36##] and cardiovascular, vision and skeletal problems [##REF##29499467##2##], biochemical imbalances [##REF##29499467##2##], depression and inattention problems, depression, anxiety, and poor self-esteem [##REF##32041697##7##, ##REF##36405875##9##, ##UREF##0##10##, ##REF##28257638##35##–##REF##29511725##38##]; and on cognitive functioning, including language development [##REF##36291513##39##], executive and academic performance [##REF##36405875##9##, ##REF##34334279##33##], attention span [##REF##35430923##40##], and hindered social interactions from a sedentary lifestyle [##REF##31727052##41##]. Taken together, these results suggest that optimal screen time exposure that allows sufficient remote social interactions and entertainment, while limiting excess use is key, and further studies to identify the optimal length of time that is advantageous for PWB is informative.</p>", "<p id=\"Par34\">This study has several limitations pertaining to the use of the NSCH dataset used and analysis methods. The 2020 data collection occurred between June 2020 and January 2021 [##UREF##9##42##], during which most children were undergoing only online instruction; however, it is not possible to determine the exact timing when each study participant responded to the survey questions, and variability in the phase of the pandemic is expected. Moreover, the survey answer choices on recreational screen hours are designed such that ≥ 4 h is the maximum recorded response, and anything above is classified as the same response. Additionally, self-reported average hours on a weekday was the response recorded, although in reality, usage hours are expected to be variable between days. Furthermore, some of the survey questions gathered the parents’ responses, rather than the children’s. Another limitation is in the lack of an established definition for problem use versus addiction [##REF##28198052##22##, ##REF##22624087##43##], and in our study, we considered reported use of ≥ 4 h of recreational (<italic>i.e.</italic> not school-related) screen time during school days as excessive use, as it suggests that after accounting for school, sleep, commute and feeding time, a child is spending the rest of the day on a screen. From the current dataset’s survey questions [##UREF##10##44##], it is not possible to ascertain whether these children have psychological dependency on screen devices and other indicators of addiction, and future studies with survey questions or clinical evaluations directly assessing screen addiction, with follow-up to evaluate persistence of the behavior would be beneficial. Finally, compared to surveys administered before the pandemic when children were physically in school, self-reported recreational screen time may be more likely to be overestimated during the pandemic when online instruction was used.</p>", "<p id=\"Par35\">Despite the limitations above, our study finding strong associations between screen time or overuse and PWB, and the significant impact of the pandemic on strengthening these associations, using a large survey dataset collected widely across the US is important. Future studies to evaluate whether these associations persist post-pandemic, and investigations in other regions are also informative. Prevention of screen overuse by incorporating other activities, such as sports, music, arts, and social hours [##REF##33238925##45##] off screens is expected to improve children’s PWB. Practical implications from our study may include recommending parents to discourage excessive screen time that dominate adolescents’ after school schedules. Previous studies reporting that parental mediation can be protective of [##UREF##11##46##], and on the other hand, negative parenting is associated with [##REF##36405875##9##] dependency and decreased PWB supports this notion. For educators, while it is necessary to integrate technology into learning and assignments, it may also be important to include other modes of learning tools to help adolescents have periodic screen-free time. Finally, for policymakers, while it is important to promote technology and make it available to all children, it is equally important to encourage additional research on screen overuse to better understand its impact on PWB, and elucidate additional protective factors.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Previous studies on screen use and children’s mental health during the Coronavirus Disease 2019 (COVID-19) pandemic focused only on the timeframe during the pandemic, on children between narrow age ranges, only among a subset of children who have previously reported COVID-related severe family economic hardship or worries, or did not distinguish between instructive versus recreational device usage. Thus, in this study, we analyzed trends, specifically related to recreational screen use, and associations with psychological well-being (PWB) in the years before versus during the COVID-19 pandemic, among a wide range of school-aged children, widely across the nation.</p>", "<title>Methods</title>", "<p id=\"Par2\">Using the National Survey of Children’s Health (NSCH) years 2018–21, we analyzed a large random sample of school-aged children (6–17 years old) across the US (n = 88,823). We developed PWB issue scores (PWBIS) using self-reported measures relevant to this age group, and constructed regression models to assess the magnitude of the contribution of the pandemic on recreational screen use and PWB.</p>", "<title>Results</title>", "<p id=\"Par3\">The prevalence of recreational screen overuse and PWBIS increased significantly during the pandemic, compared to prior years. We also detected a notable effect of the pandemic on increased PWBIS, as well as its interaction term finding that it strengthened the association between screen time and PWBIS (p &lt; 0.01 across all regression models).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Accordingly, our results demonstrate the importance of the pandemic itself as an independent adverse factor and effect measure modifier for screen overuse and PWB more generally among all school-age children widely across the US. Our study used the most current data available, and future studies to evaluate whether these effects are persistent in the years after the pandemic are important.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13034-023-00688-7.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Author contributions</title>", "<p>HTW conceptualized the study, performed the analysis, prepared the figures and tables, and wrote and edited the main manuscript text. JL performed the analysis, prepared the figures and tables, and wrote and edited the main manuscript text. AT supervised, wrote and edited the main manuscript text. All authors reviewed the manuscript.</p>", "<title>Funding</title>", "<p>The authors received no financial support for the research, authorship, and/or publication of this article.</p>", "<title>Availability of data and materials</title>", "<p>Datasets were downloaded from the National Survey of Children’s Health (NSCH) website, <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.census.gov/programs-surveys/nsch/data/datasets.html\">https://www.census.gov/programs-surveys/nsch/data/datasets.html</ext-link>.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par36\">This study used deidentified publicly available survey data and did not involve human participants; and therefore, Institutional Review Board (IRB) approval was not necessary.</p>", "<title>Competing interests</title>", "<p id=\"Par37\">The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flowchart of study inclusion/exclusion criteria</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Assessment of recreational screen time by psychological average well-being issue scores for <bold>A</bold> PWBIS1 and <bold>B</bold> PWBIS2</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Summary of the study population demographics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">N = 88,823</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\">Age group</td></tr><tr><td align=\"left\"> Elementary school (age 6–10 years)</td><td align=\"left\">31,840(35.84%)</td></tr><tr><td align=\"left\"> Middle school (age 11–13 years)</td><td align=\"left\">21,608 (24.32%)</td></tr><tr><td align=\"left\"> High school (age 14–17 years)</td><td align=\"left\">35,375 (39.82%)</td></tr><tr><td align=\"left\" colspan=\"2\">Sex</td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">45,012 (50.67%)</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">43,811 (49.32%)</td></tr><tr><td align=\"left\" colspan=\"2\">Race</td></tr><tr><td align=\"left\"> White</td><td align=\"left\">68,899 (77.56%)</td></tr><tr><td align=\"left\"> Black or African American</td><td align=\"left\">6227 (7.01%)</td></tr><tr><td align=\"left\"> American Indian or Alaska Native</td><td align=\"left\">851 (0.96%)</td></tr><tr><td align=\"left\"> Asian</td><td align=\"left\">5002 (5.63%)</td></tr><tr><td align=\"left\"> Native Hawaiian or Other Pacific Islander</td><td align=\"left\">540 (0.60%)</td></tr><tr><td align=\"left\"> Some other race alone</td><td align=\"left\">486 (0.54%)</td></tr><tr><td align=\"left\"> Two or more races</td><td align=\"left\">6818 (7.67%)</td></tr><tr><td align=\"left\" colspan=\"2\">Ethnicity</td></tr><tr><td align=\"left\"> Hispanic or Latino</td><td align=\"left\">10,884 (12.25%)</td></tr><tr><td align=\"left\"> Otherwise</td><td align=\"left\">77,939 (87.75%)</td></tr><tr><td align=\"left\">Poverty ratio</td><td align=\"left\">292.38 ± 116.82</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Summary of recreational screen time hours and proportion of screen overuse (≥ 4 h)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"4\">Screen time average (hours)</th><th align=\"left\" colspan=\"4\">Percentage of screen overuse (≥ 4 h of screen time)</th></tr><tr><th align=\"left\">2018</th><th align=\"left\">2019</th><th align=\"left\">2020</th><th align=\"left\">2021</th><th align=\"left\">2018</th><th align=\"left\">2019</th><th align=\"left\">2020</th><th align=\"left\">2021</th></tr></thead><tbody><tr><td align=\"left\">All ages (N = 63,211)</td><td align=\"left\">2.38</td><td align=\"left\">2.41</td><td align=\"left\">2.70</td><td align=\"left\">2.59</td><td align=\"left\">18,746 (22.72%)</td><td align=\"left\">18,212 (24.39%)</td><td align=\"left\">26,253 (32.80%)</td><td align=\"left\">25,612 (29.41%)</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\">–</td><td align=\"left\">0.0045</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">–</td><td align=\"left\">0.0002</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\">Elementary school (age 6–10 years) (n = 21,857)</td><td align=\"left\">1.98</td><td align=\"left\">2.02</td><td align=\"left\">2.37</td><td align=\"left\">2.21</td><td align=\"left\">6478 (11.78%)</td><td align=\"left\">6249 (13.55%)</td><td align=\"left\">9130 (20.78%)</td><td align=\"left\">9983 (17.15%)</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\">–</td><td align=\"left\">0.0635</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">–</td><td align=\"left\">0.0026</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\">Middle school (age 11–13 years) (n = 15,634)</td><td align=\"left\">2.46</td><td align=\"left\">2.47</td><td align=\"left\">2.79</td><td align=\"left\">2.67</td><td align=\"left\">4561 (24.36%)</td><td align=\"left\">4564 (24.30%)</td><td align=\"left\">6509 (34.59%)</td><td align=\"left\">5974 (30.48%)</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\">–</td><td align=\"left\">0.9190</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">–</td><td align=\"left\">0.9455</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"><p>High school (age 14–17 years)</p><p>(n = 25,720)</p></td><td align=\"left\">2.80</td><td align=\"left\">2.86</td><td align=\"left\">3.03</td><td align=\"left\">3.01</td><td align=\"left\">7707 (34.88%)</td><td align=\"left\">7399 (38.00%)</td><td align=\"left\">10,614 (45.83%)</td><td align=\"left\">9655 (43.57%)</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\">–</td><td align=\"left\">0.0002</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">0.0540</td><td align=\"left\">–</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">0.0012</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Changes in hours of recreational screen time and PWBIS before and during the COVID-19 pandemic</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Total (N = 63,211)</th><th align=\"left\">2018 (N = 18,746)</th><th align=\"left\">2019 (N = 18,212)</th><th align=\"left\">2020 (N = 26,253)</th><th align=\"left\">2021 (N = 25,612)</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"6\">Screen time</td></tr><tr><td align=\"left\"> &lt; 1 h</td><td align=\"left\">5349 (6.02%)</td><td align=\"left\">1315 (7.01%)</td><td align=\"left\">1372 (7.53%)</td><td align=\"left\">1222 (4.65%)</td><td align=\"left\">1440 (5.62%)</td></tr><tr><td align=\"left\"> 1 h</td><td align=\"left\">12,172 (13.70%)</td><td align=\"left\">3144 (16.77%)</td><td align=\"left\">2828 (15.53%)</td><td align=\"left\">2803 (10.68%)</td><td align=\"left\">3397 (13.26%)</td></tr><tr><td align=\"left\"> 2 h</td><td align=\"left\">26,239 (29.54%)</td><td align=\"left\">5903 (31.49%)</td><td align=\"left\">5726 (31.44%)</td><td align=\"left\">7234 (27.55%)</td><td align=\"left\">7376 (28.80%)</td></tr><tr><td align=\"left\"> 3 h</td><td align=\"left\">20,070 (22.60%)</td><td align=\"left\">4045 (21.58%)</td><td align=\"left\">3954 (21.71%)</td><td align=\"left\">6105 (23.25%)</td><td align=\"left\">5966 (23.29%)</td></tr><tr><td align=\"left\"> 4 or more hours</td><td align=\"left\">24,993 (28.14%)</td><td align=\"left\">4339 (23.15%)</td><td align=\"left\">4332 (23.79%)</td><td align=\"left\">8889 (33.86%)</td><td align=\"left\">7433 (29.02%)</td></tr><tr><td align=\"left\"> <italic>P</italic> value compared to each previous year</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> PWBIS1 (mean)</td><td align=\"left\">0.936</td><td align=\"left\">0.843</td><td align=\"left\">0.839</td><td align=\"left\">1.031</td><td align=\"left\">1.029</td></tr><tr><td align=\"left\"><italic> P</italic> value compared to each previous year</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">0.0641</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">0.0018</td></tr><tr><td align=\"left\"> PWBIS2 (%)</td><td align=\"left\">48.6%</td><td align=\"left\">45.3%</td><td align=\"left\">45.8%</td><td align=\"left\">51.7%</td><td align=\"left\">51.3%</td></tr><tr><td align=\"left\"><italic> P</italic> value compared to each previous year</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">0.284</td><td align=\"left\"> &lt; 0.0001</td><td align=\"left\">0.385</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Assessment of hours of recreational screen time and PWBIS by various demographic and socioeconomic variables</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"6\">Screen time</th><th align=\"left\" colspan=\"4\">PWB measures</th></tr><tr><th align=\"left\"> &lt; 1 h</th><th align=\"left\">1 h</th><th align=\"left\">2 h</th><th align=\"left\">3 h</th><th align=\"left\">4 or more</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">PWBIS1</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">PWBIS2</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"11\">Elementary school age (6–10 years)</td></tr><tr><td align=\"left\"> Female</td><td char=\".\" align=\"char\">10.79%</td><td char=\".\" align=\"char\">22.46%</td><td char=\".\" align=\"char\">34.38%</td><td char=\".\" align=\"char\">17.77%</td><td char=\".\" align=\"char\">14.60%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.81</td><td char=\".\" align=\"char\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">44.47%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Male</td><td char=\".\" align=\"char\">9.71%</td><td char=\".\" align=\"char\">19.35%</td><td char=\".\" align=\"char\">33.39%</td><td char=\".\" align=\"char\">20.52%</td><td char=\".\" align=\"char\">17.03%</td><td char=\".\" align=\"char\">0.95</td><td char=\".\" align=\"char\">47.90%</td></tr><tr><td align=\"left\"> Black or African American</td><td char=\".\" align=\"char\">7.84%</td><td char=\".\" align=\"char\">14.65%</td><td char=\".\" align=\"char\">32.02%</td><td char=\".\" align=\"char\">24.09%</td><td char=\".\" align=\"char\">21.39%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.81</td><td char=\".\" align=\"char\">0.0003</td><td char=\".\" align=\"char\">42.28%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Native American or Alaska Native</td><td char=\".\" align=\"char\">5.88%</td><td char=\".\" align=\"char\">8.45%</td><td char=\".\" align=\"char\">45.54%</td><td char=\".\" align=\"char\">24.01%</td><td char=\".\" align=\"char\">16.12%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.14</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">56.53%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Asian</td><td char=\".\" align=\"char\">10.81%</td><td char=\".\" align=\"char\">22.16%</td><td char=\".\" align=\"char\">28.54%</td><td char=\".\" align=\"char\">20.76%</td><td char=\".\" align=\"char\">17.73%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.85</td><td char=\".\" align=\"char\">0.3460</td><td char=\".\" align=\"char\">40.30%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Hawaiian or other Pacific Islander</td><td char=\".\" align=\"char\">5.05%</td><td char=\".\" align=\"char\">31.77%</td><td char=\".\" align=\"char\">34.78%</td><td char=\".\" align=\"char\">6.78%</td><td char=\".\" align=\"char\">21.62%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.77</td><td char=\".\" align=\"char\">0.0669</td><td char=\".\" align=\"char\">37.90%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> White</td><td char=\".\" align=\"char\">11.19%</td><td char=\".\" align=\"char\">22.38%</td><td char=\".\" align=\"char\">34.06%</td><td char=\".\" align=\"char\">18.22%</td><td char=\".\" align=\"char\">14.15%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.87</td><td char=\".\" align=\"char\">0.4136</td><td char=\".\" align=\"char\">46.79%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Some other race alone</td><td char=\".\" align=\"char\">7.08%</td><td char=\".\" align=\"char\">27.15%</td><td char=\".\" align=\"char\">41.30%</td><td char=\".\" align=\"char\">15.81%</td><td char=\".\" align=\"char\">8.65%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.74</td><td char=\".\" align=\"char\">0.0339</td><td char=\".\" align=\"char\">44.79%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Two or more races</td><td char=\".\" align=\"char\">8.44%</td><td char=\".\" align=\"char\">18.07%</td><td char=\".\" align=\"char\">35.32%</td><td char=\".\" align=\"char\">19.25%</td><td char=\".\" align=\"char\">18.91%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.02</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">50.52%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Hispanic or Latino related</td><td char=\".\" align=\"char\">7.79%</td><td char=\".\" align=\"char\">18.18%</td><td char=\".\" align=\"char\">34.58%</td><td char=\".\" align=\"char\">21.02%</td><td char=\".\" align=\"char\">18.42%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.91</td><td char=\".\" align=\"char\" rowspan=\"2\">0.0089</td><td char=\".\" align=\"char\">48.26%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Otherwise</td><td char=\".\" align=\"char\">10.99%</td><td char=\".\" align=\"char\">21.74%</td><td char=\".\" align=\"char\">33.68%</td><td char=\".\" align=\"char\">18.56%</td><td char=\".\" align=\"char\">15.02%</td><td char=\".\" align=\"char\">0.87</td><td char=\".\" align=\"char\">45.54%</td></tr><tr><td align=\"left\"> Below median poverty ratio</td><td char=\".\" align=\"char\">8.95%</td><td char=\".\" align=\"char\">19.62%</td><td char=\".\" align=\"char\">33.11%</td><td char=\".\" align=\"char\">20.54%</td><td char=\".\" align=\"char\">17.77%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.93</td><td char=\".\" align=\"char\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">48.07%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Above median poverty ratio</td><td char=\".\" align=\"char\">12.21%</td><td char=\".\" align=\"char\">22.87%</td><td char=\".\" align=\"char\">35.06%</td><td char=\".\" align=\"char\">17.01%</td><td char=\".\" align=\"char\">12.85%</td><td char=\".\" align=\"char\">0.8</td><td char=\".\" align=\"char\">43.32%</td></tr><tr><td align=\"left\" colspan=\"11\">Middle school age (11–13 years)</td></tr><tr><td align=\"left\"> Female</td><td char=\".\" align=\"char\">6.09%</td><td char=\".\" align=\"char\">13.65%</td><td char=\".\" align=\"char\">30.32%</td><td char=\".\" align=\"char\">23.34%</td><td char=\".\" align=\"char\">26.60%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.88</td><td char=\".\" align=\"char\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">48.34%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Male</td><td char=\".\" align=\"char\">5.84%</td><td char=\".\" align=\"char\">10.64%</td><td char=\".\" align=\"char\">28.45%</td><td char=\".\" align=\"char\">24.64%</td><td char=\".\" align=\"char\">30.43%</td><td char=\".\" align=\"char\">1.05</td><td char=\".\" align=\"char\">50.16%</td></tr><tr><td align=\"left\"> Black or African American</td><td char=\".\" align=\"char\">5.75%</td><td char=\".\" align=\"char\">10.59%</td><td char=\".\" align=\"char\">27.40%</td><td char=\".\" align=\"char\">21.64%</td><td char=\".\" align=\"char\">34.63%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.91</td><td char=\".\" align=\"char\">0.0246</td><td char=\".\" align=\"char\">46.44%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Native American or Alaska Native</td><td char=\".\" align=\"char\">1.19%</td><td char=\".\" align=\"char\">14.89%</td><td char=\".\" align=\"char\">23.50%</td><td char=\".\" align=\"char\">25.19%</td><td char=\".\" align=\"char\">35.22%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.12</td><td char=\".\" align=\"char\">0.0188</td><td char=\".\" align=\"char\">47.15%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Asian</td><td char=\".\" align=\"char\">8.65%</td><td char=\".\" align=\"char\">13.11%</td><td char=\".\" align=\"char\">29.47%</td><td char=\".\" align=\"char\">18.92%</td><td char=\".\" align=\"char\">29.85%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.77</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">43.63%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Hawaiian or other Pacific Islander</td><td char=\".\" align=\"char\">10.47%</td><td char=\".\" align=\"char\">10.69%</td><td char=\".\" align=\"char\">33.27%</td><td char=\".\" align=\"char\">29.31%</td><td char=\".\" align=\"char\">16.25%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.03</td><td char=\".\" align=\"char\">0.4146</td><td char=\".\" align=\"char\">52.09%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> White</td><td char=\".\" align=\"char\">5.72%</td><td char=\".\" align=\"char\">12.61%</td><td char=\".\" align=\"char\">30.15%</td><td char=\".\" align=\"char\">24.47%</td><td char=\".\" align=\"char\">27.06%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.98</td><td char=\".\" align=\"char\">0.0555</td><td char=\".\" align=\"char\">50.12%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Some other race alone</td><td char=\".\" align=\"char\">3.56%</td><td char=\".\" align=\"char\">1.18%</td><td char=\".\" align=\"char\">40.27%</td><td char=\".\" align=\"char\">31.65%</td><td char=\".\" align=\"char\">23.35%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.96</td><td char=\".\" align=\"char\">0.8617</td><td char=\".\" align=\"char\">39.71%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Two or more races</td><td char=\".\" align=\"char\">7.20%</td><td char=\".\" align=\"char\">12.02%</td><td char=\".\" align=\"char\">25.34%</td><td char=\".\" align=\"char\">24.03%</td><td char=\".\" align=\"char\">31.42%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.02</td><td char=\".\" align=\"char\">0.0830</td><td char=\".\" align=\"char\">51.41%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Hispanic or latino related</td><td char=\".\" align=\"char\">5.34%</td><td char=\".\" align=\"char\">10.32%</td><td char=\".\" align=\"char\">28.55%</td><td char=\".\" align=\"char\">25.47%</td><td char=\".\" align=\"char\">30.33%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.98</td><td char=\".\" align=\"char\" rowspan=\"2\">0.4360</td><td char=\".\" align=\"char\">50.28%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Otherwise</td><td char=\".\" align=\"char\">6.18%</td><td char=\".\" align=\"char\">12.78%</td><td char=\".\" align=\"char\">29.68%</td><td char=\".\" align=\"char\">23.48%</td><td char=\".\" align=\"char\">27.88%</td><td char=\".\" align=\"char\">0.96</td><td char=\".\" align=\"char\">48.89%</td></tr><tr><td align=\"left\"> Below median poverty ratio</td><td char=\".\" align=\"char\">6.37%</td><td char=\".\" align=\"char\">11.52%</td><td char=\".\" align=\"char\">29.03%</td><td char=\".\" align=\"char\">24.04%</td><td char=\".\" align=\"char\">29.04%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.04</td><td char=\".\" align=\"char\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">51.42%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Above median poverty ratio</td><td char=\".\" align=\"char\">5.28%</td><td char=\".\" align=\"char\">13.21%</td><td char=\".\" align=\"char\">29.98%</td><td char=\".\" align=\"char\">23.92%</td><td char=\".\" align=\"char\">27.62%</td><td char=\".\" align=\"char\">0.85</td><td char=\".\" align=\"char\">45.60%</td></tr><tr><td align=\"left\" colspan=\"11\">High school age (14–17 years)</td></tr><tr><td align=\"left\"> Female</td><td char=\".\" align=\"char\">3.69%</td><td char=\".\" align=\"char\">8.29%</td><td char=\".\" align=\"char\">24.69%</td><td char=\".\" align=\"char\">23.16%</td><td char=\".\" align=\"char\">40.16%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.99</td><td char=\".\" align=\"char\" rowspan=\"2\">0.2530</td><td char=\".\" align=\"char\">52.31%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Male</td><td char=\".\" align=\"char\">3.33%</td><td char=\".\" align=\"char\">6.84%</td><td char=\".\" align=\"char\">23.66%</td><td char=\".\" align=\"char\">25.13%</td><td char=\".\" align=\"char\">41.04%</td><td char=\".\" align=\"char\">0.98</td><td char=\".\" align=\"char\">49.59%</td></tr><tr><td align=\"left\"> Black or African American</td><td char=\".\" align=\"char\">4.03%</td><td char=\".\" align=\"char\">5.29%</td><td char=\".\" align=\"char\">21.23%</td><td char=\".\" align=\"char\">24.09%</td><td char=\".\" align=\"char\">45.36%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.97</td><td char=\".\" align=\"char\">0.2984</td><td char=\".\" align=\"char\">48.20%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Native American or Alaska Native</td><td char=\".\" align=\"char\">2.14%</td><td char=\".\" align=\"char\">5.58%</td><td char=\".\" align=\"char\">24.61%</td><td char=\".\" align=\"char\">23.32%</td><td char=\".\" align=\"char\">44.34%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.2</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">57.65%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Asian</td><td char=\".\" align=\"char\">4.23%</td><td char=\".\" align=\"char\">9.94%</td><td char=\".\" align=\"char\">21.51%</td><td char=\".\" align=\"char\">21.92%</td><td char=\".\" align=\"char\">42.40%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.81</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">46.03%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Hawaiian or other Pacific Islander</td><td char=\".\" align=\"char\">3.02%</td><td char=\".\" align=\"char\">9.50%</td><td char=\".\" align=\"char\">33.23%</td><td char=\".\" align=\"char\">11.66%</td><td char=\".\" align=\"char\">42.59%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.91</td><td char=\".\" align=\"char\">0.1199</td><td char=\".\" align=\"char\">49.03%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> White</td><td char=\".\" align=\"char\">3.28%</td><td char=\".\" align=\"char\">7.84%</td><td char=\".\" align=\"char\">24.97%</td><td char=\".\" align=\"char\">24.79%</td><td char=\".\" align=\"char\">39.12%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.98</td><td char=\".\" align=\"char\">0.4719</td><td char=\".\" align=\"char\">51.24%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Some Other Race Alone</td><td char=\".\" align=\"char\">6.57%</td><td char=\".\" align=\"char\">13.48%</td><td char=\".\" align=\"char\">17.60%</td><td char=\".\" align=\"char\">32.26%</td><td char=\".\" align=\"char\">30.09%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">0.76</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">47.04%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Two or more races</td><td char=\".\" align=\"char\">3.71%</td><td char=\".\" align=\"char\">6.29%</td><td char=\".\" align=\"char\">23.50%</td><td char=\".\" align=\"char\">22.27%</td><td char=\".\" align=\"char\">44.22%</td><td align=\"left\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.19</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td char=\".\" align=\"char\">56.82%</td><td align=\"left\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Hispanic or Latino related</td><td char=\".\" align=\"char\">3.68%</td><td char=\".\" align=\"char\">7.50%</td><td char=\".\" align=\"char\">24.06%</td><td char=\".\" align=\"char\">22.21%</td><td char=\".\" align=\"char\">42.55%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.04</td><td char=\".\" align=\"char\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">51.55%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Otherwise</td><td char=\".\" align=\"char\">3.46%</td><td char=\".\" align=\"char\">7.59%</td><td char=\".\" align=\"char\">24.21%</td><td char=\".\" align=\"char\">24.80%</td><td char=\".\" align=\"char\">39.94%</td><td char=\".\" align=\"char\">0.97</td><td char=\".\" align=\"char\">50.75%</td></tr><tr><td align=\"left\"> Below median poverty ratio</td><td char=\".\" align=\"char\">4.16%</td><td char=\".\" align=\"char\">7.41%</td><td char=\".\" align=\"char\">23.84%</td><td char=\".\" align=\"char\">23.20%</td><td char=\".\" align=\"char\">41.39%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">1.04</td><td char=\".\" align=\"char\" rowspan=\"2\"> &lt; 0.0001</td><td char=\".\" align=\"char\">52.02%</td><td align=\"left\" rowspan=\"2\"> &lt; 0.0001</td></tr><tr><td align=\"left\"> Above median poverty ratio</td><td char=\".\" align=\"char\">2.52%</td><td char=\".\" align=\"char\">7.81%</td><td char=\".\" align=\"char\">24.68%</td><td char=\".\" align=\"char\">25.60%</td><td char=\".\" align=\"char\">39.39%</td><td char=\".\" align=\"char\">0.9</td><td char=\".\" align=\"char\">49.31%</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>GLS models 1 and 2 regression results for PWBIS and screen time or addition</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">PWBIS1 outcome</th><th align=\"left\" colspan=\"4\">Effect of screen time</th><th align=\"left\" colspan=\"4\">Effect of overuse (<italic>i.e.</italic> Screen time ≥ 4 h)</th></tr><tr><th align=\"left\"/><th align=\"left\" colspan=\"2\">Model 1</th><th align=\"left\" colspan=\"2\">Model 2</th><th align=\"left\" colspan=\"2\">Model 1</th><th align=\"left\" colspan=\"2\">Model 2</th></tr><tr><th align=\"left\">Covariates</th><th align=\"left\">β (95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">β (95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">β (95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">β (95% CI)</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\"><italic>Intercept</italic></td><td align=\"left\">0.340 (0.290, 0.40)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.330 (0.270, 0.390)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">1.070 (1.030, 1.120)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.050 (1.00, 1.100)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Screen time or overuse</italic></td><td align=\"left\">0.320 (0.310, 0.330)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.320 (0.310, 0.330)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.570 (0.550, 0.590)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.570 (0.540, 0.590)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Pandemic years (2020–21)</italic></td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">0.070 (0.040, 0.090)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">0.080 (0.050, 0.110)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Interaction term (Model2): Screen time or overuse</italic> × <italic>Pandemic years (2020–21)</italic></td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">0.000 (− 0.030, 0.030)</td><td char=\".\" align=\"char\">0.878</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">− 0.01 (− 0.06, 0.030)</td><td char=\".\" align=\"char\">0.626</td></tr><tr><td align=\"left\"><italic>Age</italic></td><td align=\"left\">− 3.58E-3 (− 6.59E-3, − 5.77E-4)</td><td align=\"left\">0.019</td><td align=\"left\">− 3.27E−3 (− 6.28E−3, − 2.60E−4)</td><td char=\".\" align=\"char\">0.033</td><td align=\"left\">− 1.47E−3 (− 4.46E−3, 1.52E−3)</td><td align=\"left\">0.336</td><td align=\"left\">− 1.16E−3 (− 4.15E−3, 1.83E-3)</td><td char=\".\" align=\"char\">0.447</td></tr><tr><td align=\"left\"><italic>Sex-male (ref: female)</italic></td><td align=\"left\">0.060 (0.040, 0.080)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.060 (0.040, 0.080)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.070 (0.050, 0.090)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.070 (0.050, 0.090)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Black or African American (ref. White)</italic></td><td align=\"left\">− 0.200 (− 0.230, − 0.170)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 0.200 (− 0.230, − 0.170)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">− 0.200 (− 0.230, − 0.170)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 0.200 (− 0.230, − 0.170)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><p><italic>Native American or Alaska Native</italic></p><p><italic>(ref. White)</italic></p></td><td align=\"left\">0.200 (0.130, 0.280)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.200 (0.130, 0.270)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.200 (0.130, 0.270)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.200 (0.130, 0.270)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Asian (ref. White)</italic></td><td align=\"left\">− 0.190 (− 0.240, − 0.150)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 0.190 (− 0.240, − 0.150)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">− 0.190 (− 0.240, − 0.150)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 0.190 (− 0.240, − 0.150)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Hawaiian or other Pacific Islander (ref. White)</italic></td><td align=\"left\">− 0.040 (− 0.110, 0.040)</td><td align=\"left\">0.317</td><td align=\"left\">− 0.050 (− 0.120, 0.030)</td><td char=\".\" align=\"char\">0.219</td><td align=\"left\">− 0.070 (− 0.150, 0.00)</td><td align=\"left\">0.067</td><td align=\"left\">− 0.080 (− 0.160, 0.00)</td><td char=\".\" align=\"char\">0.037</td></tr><tr><td align=\"left\"><italic>Some other race alone (ref. white)</italic></td><td align=\"left\">− 0.130 (− 0.210, − 0.050)</td><td align=\"left\">0.002</td><td align=\"left\">− 0.110 (− 0.190, − 0.030)</td><td char=\".\" align=\"char\">0.008</td><td align=\"left\">− 0.120 (− 0.200, − 0.040)</td><td align=\"left\">0.004</td><td align=\"left\">− 0.100 (− 0.180, − 0.020)</td><td char=\".\" align=\"char\">0.019</td></tr><tr><td align=\"left\"><italic>Two or more races (ref. white)</italic></td><td align=\"left\">0.090 (0.060, 0.130)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.09 (0.060, 0.130)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.090 (0.050, 0.130)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.090 (0.050, 0.120)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Hispanic or Latino related (ref. otherwise)</italic></td><td align=\"left\">− 0.070 (− 0.100, − 0.050)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 0.070 (− 0.100, − 0.050)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">− 0.070 (− 0.100, − 0.050)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 0.070 (− 0.100, − 0.050)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Poverty ratio</italic></td><td align=\"left\">− 9.04E−4 (− 9.89E-4, − 8.19E-4)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 9.07E−4 (− 9.92E−4, − 8.23E−4)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">− 9.07E−4 (− 9.92E−4, − 8.22E-4)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">− 9.10E− 4 (− 9.95E−4, − 8.25E − 4)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Adjusted R squared</td><td align=\"left\" colspan=\"2\">4.78%</td><td align=\"left\" colspan=\"2\">4.82%</td><td align=\"left\" colspan=\"2\">4.76%</td><td align=\"left\" colspan=\"2\">4.81%</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab6\"><label>Table 6</label><caption><p>Odds ratio (OR) estimates of multivariable logistic regression models for PWBIS and screen time or overuse</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">PWB1S2 outcome</th><th align=\"left\" colspan=\"4\">Effect of screen time</th><th align=\"left\" colspan=\"4\">Effect of overuse (<italic>i.e.</italic> Screen time ≥ 4 h)</th></tr><tr><th align=\"left\"/><th align=\"left\" colspan=\"2\">Model 3</th><th align=\"left\" colspan=\"2\">Model 4</th><th align=\"left\" colspan=\"2\">Model 3</th><th align=\"left\" colspan=\"2\">Model 4</th></tr><tr><th align=\"left\">Covariates</th><th align=\"left\">OR (95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">OR (95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">OR (95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">OR (95% CI)</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\"><italic>Screen time or overuse</italic></td><td align=\"left\">1.498 (1.497, 1.500)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.489 (1.488, 1.490)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">2.000 (1.997, 2.003)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.978 (1.974, 1.981)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Pandemic years (2020–21)</italic></td><td align=\"left\"><italic>NA</italic></td><td align=\"left\"><italic>NA</italic></td><td align=\"left\">1.094 (1.092, 1.096)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\"><italic>NA</italic></td><td align=\"left\"><italic>NA</italic></td><td align=\"left\">1.102 (1.100, 1.105)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Interaction term (Model4): Screen time or overuse</italic> × <italic>pandemic years</italic></td><td align=\"left\"><italic>NA</italic></td><td align=\"left\"><italic>NA</italic></td><td align=\"left\">1.012 (1.010, 1.014)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\"><italic>NA</italic></td><td align=\"left\"><italic>NA</italic></td><td align=\"left\">1.021 (1.018, 1.024)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Elementary school (ref. high school)</italic></td><td align=\"left\">1.016 (1.015, 1.018)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.013 (1.011, 1.015)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.992 (0.990, 0.993)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.989 (0.987, 0.990)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Middle School (ref. High School)</italic></td><td align=\"left\">1.044 (1.042, 1.046)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.042 (1.040, 1.044)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">1.040 (1.038, 1.042)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.038 (1.036, 1.039)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Sex-male (ref. female)</italic></td><td align=\"left\">1.016 (1.015, 1.018)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.016 (1.014, 1.017)</td><td char=\".\" align=\"char\">0.030</td><td align=\"left\">1.008 (1.006, 1.009)</td><td align=\"left\">0.002</td><td align=\"left\">1.007 (1.006, 1.008)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Black or African American (ref. White)</italic></td><td align=\"left\">0.688 (0.687, 0.69)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.688 (0.687, 0.69)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.693 (0.692, 0.695)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.694 (0.692, 0.695)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Native American or Alaska Native (ref. White)</italic></td><td align=\"left\">1.147 (1.142, 1.153)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.141 (1.135, 1.147)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">1.145 (1.139, 1.151)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.138 (1.132, 1.144)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Asian (ref. White)</italic></td><td align=\"left\">0.712 (0.709, 0.714)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.711 (0.709, 0.714)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.714 (0.711, 0.716)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.714 (0.711, 0.716)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Hawaiian or other Pacific Islander (ref. White)</italic></td><td align=\"left\">0.926 (0.921, 0.931)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.914 (0.91, 0.919)</td><td char=\".\" align=\"char\">0.146</td><td align=\"left\">0.888 (0.884, 0.893)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.877 (0.872, 0.882)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Some Other Race Alone(ref. White)</italic></td><td align=\"left\">0.900 (0.895, 0.905)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.923 (0.918, 0.929)</td><td char=\".\" align=\"char\">0.013</td><td align=\"left\">0.909 (0.904, 0.915)</td><td align=\"left\">0.062</td><td align=\"left\">0.935 (0.930, 0.940)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Two or More Races (ref. White)</italic></td><td align=\"left\">1.162 (1.159, 1.165)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.161 (1.158, 1.164)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">1.160 (1.158, 1.163)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">1.159 (1.156, 1.162)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Hispanic or latino related (ref. otherwise)</italic></td><td align=\"left\">0.911 (0.909, 0.913)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.909 (0.907, 0.911)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.915 (0.913, 0.917)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.913 (0.911, 0.915)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><italic>Poverty ratio</italic></td><td align=\"left\">0.999 (0.999, 0.999)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.999 (0.999, 0.999)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">0.999 (0.999, 0.999)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.999 (0.999, 0.999)</td><td align=\"left\"> &lt; 0.001</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Categorical demographic variables are shown as n (%) relative to the total population (N = 88,823), and the unweighted Poverty Ratio is shown as mean ± standard deviation (with a range of 50–400)</p></table-wrap-foot>", "<table-wrap-foot><p>Student’s t-test p-values are shown for the difference between the value of the current versus the previous year. Less than 1 h of screen time was recorded as 0.5, and four or more hours was recorded as 4</p></table-wrap-foot>", "<table-wrap-foot><p>Chi-square test p-values are shown for the difference between the distribution of the current versus the previous year’s recreational screen time. The mean and Student’s t-test p-values are shown for PWBIS1, and the proportions and Chi-square test p-values are shown for PWBIS2, for differences between the value of the current versus the previous year</p></table-wrap-foot>", "<table-wrap-foot><p>Proportions and chi-square test p-values are shown for distributions for recreational screen time and PWBIS2. The mean and Student’s t-test p-values are shown for PWBIS1. For the race category comparisons, p-values were calculated for each of the races with all the others. The median poverty ratio among all the samples used in this study was found to be 328, which was used as the cut-off to make comparisons between below and above median poverty ratios</p></table-wrap-foot>", "<table-wrap-foot><p>These analyses were performed using 71,302 observations of subjects with at least one hour of screen usage every weekday on average</p></table-wrap-foot>", "<table-wrap-foot><p>These analyses were performed using 71,302 observations of subjects with at least one hour of screen usage every weekday on average</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13034_2023_688_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13034_2023_688_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"13034_2023_688_MOESM1_ESM.pdf\"><caption><p><bold>Additional file 1: Table S1.</bold> Description of NSCH survey questions and answer choices and variables used in this study. <bold>Table S2.</bold> Description of the construction of the well-being scores, PWBIS1 and PWBIS2. <bold>Table S3.</bold> Description of the GLS and logistic regression models constructed.</p></caption></media>" ]
[{"label": ["10."], "surname": ["Riehm", "Feder", "Tormohlen", "Crum", "Young", "Green"], "given-names": ["KE", "KA", "KN", "RM", "AS", "KM"], "article-title": ["associations between time spent using social media and internalizing and externalizing problems among US youth"], "source": ["JAMA Psychiat"], "year": ["2019"], "volume": ["76"], "fpage": ["1266"], "lpage": ["1273"], "pub-id": ["10.1001/jamapsychiatry.2019.2325"]}, {"label": ["17."], "mixed-citation": ["AACAP. Screen Time and Children. n.d. URL: "], "ext-link": ["https://www.aacap.org/AACAP/Families_and_Youth/Facts_for_Families/FFF-Guide/Children-And-Watching-TV-054.aspx"]}, {"label": ["18."], "mixed-citation": ["American Psychiatric Association (APA). Diagnostic and statistical manual of mental disorders (DSM-5). 5th ed. American Psychiatric Pub.; 2013. n.d."]}, {"label": ["19."], "mixed-citation": ["Addictive behaviours: Gaming disorder. n.d. URL: "], "ext-link": ["https://www.who.int/news-room/questions-and-answers/item/addictive-behaviours-gaming-disorder"]}, {"label": ["20."], "surname": ["Ting", "Chen"], "given-names": ["C", "Y"], "source": ["Chapter 8\u2014Smartphone addiction practical resources for the mental health professional adolescent addiction"], "year": ["2020"], "publisher-loc": ["Cambridge"], "publisher-name": ["Academic Press"]}, {"label": ["21."], "surname": ["Jorgenson", "Hsiao", "Yen"], "given-names": ["AG", "RCJ", "CF"], "article-title": ["Internet addiction and other behavioral addictions"], "source": ["Child and Adolescent Psychiatric Clin North Am"], "year": ["2016"], "volume": ["25"], "fpage": ["509"], "lpage": ["20"], "pub-id": ["10.1016/j.chc.2016.03.004"]}, {"label": ["26."], "mixed-citation": ["Center of Disease Control and Prevention. Infographics\u2014Screen Time vs. Lean Time | DNPAO | CDC. 2019. URL: "], "ext-link": ["https://www.cdc.gov/nccdphp/dnpao/multimedia/infographics/getmoving.html"]}, {"label": ["28."], "surname": ["Jacob", "Berger", "Hart", "Loeb"], "given-names": ["B", "D", "C", "S"], "article-title": ["Can technology help promote equality of educational opportunities? RSF: the russell sage foundation"], "source": ["J Soc Sci"], "year": ["2016"], "volume": ["2"], "fpage": ["242"], "lpage": ["71"], "pub-id": ["10.7758/RSF.2016.2.5.12"]}, {"label": ["29."], "surname": ["Pandya", "Lodha"], "given-names": ["A", "P"], "article-title": ["Social connectedness, excessive screen time During COVID-19 and mental health: a review of current evidence"], "source": ["Front Human Dynamics"], "year": ["2021"], "pub-id": ["10.3389/fhumd.2021.684137"]}, {"label": ["42."], "mixed-citation": ["The United States Census. 2020 National Survey of Children\u2019s Health. Data Users Frequently Asked Questions (FAQs). n.d. URL: "], "ext-link": ["https://www2.census.gov/programs-surveys/nsch/technical-documentation/methodology/2020-NSCH-FAQs.pdf"]}, {"label": ["44."], "mixed-citation": ["The United States Census. 2020 National Survey of Children\u2019s Health. NSCH-T2. Topical Survey Questionnaire. n.d. URL: "], "ext-link": ["https://www.census.gov/content/dam/Census/programs-surveys/nsch/tech-documentation/questionnaires/2020/NSCH-T2.pdf"]}, {"label": ["46."], "surname": ["Sun", "Duan", "Yao", "Zhang", "Chinyani", "Niu"], "given-names": ["X", "C", "L", "Y", "T", "G"], "article-title": ["Socioeconomic status and social networking site addiction among children and adolescents: examining the roles of parents\u2019 active mediation and ICT attitudes"], "source": ["Comput Educ"], "year": ["2021"], "volume": ["173"], "fpage": ["104292"], "pub-id": ["10.1016/j.compedu.2021.104292"]}]
{ "acronym": [ "NSCH", "PWB", "PWBIS", "COVID-19" ], "definition": [ "National Survey of Children’s Health", "Psychological well-being", "Psychological well-being issue score", "Coronavirus disease of 2019" ] }
46
CC BY
no
2024-01-14 23:43:45
Child Adolesc Psychiatry Ment Health. 2024 Jan 13; 18:9
oa_package/5f/81/PMC10787397.tar.gz
PMC10787398
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Bacterial drug resistance has become a major challenge in the global public health sector. The emergence of multidrug resistance, extensive drug resistance, and pan-resistant bacteria have seriously threatened human health [##REF##27866944##1##]. At present, among many drug-resistant bacteria, the most important ones are carbapenem-resistant Enterobacteriaceae and <italic>Acinetobacter baumannii</italic> [##UREF##0##2##], which cause high mortality and few therapeutic medications. Antibiotic monotherapy for these bacteria is often unsatisfactory, and combination therapy is required. The combination of polymyxin and tigecycline is often adopted clinically for critically ill patients with pan-resistant bacterial infections. Colistin sulfate (also known as polymyxin E) is a cationic polypeptide antibiotic containing multiple components. It was isolated from <italic>E. coli</italic> in 1950. The two main components of colistin sulfate are polymyxin E<sub>1</sub> and polymyxin E<sub>2</sub>, which account for over 85% of the total content of colistin sulfate [##UREF##1##3##], which determines its blood concentration and clinical antibacterial activity [##UREF##2##4##]. Therapeutic drug monitoring (TDM) measures the combined concentration of these two components as the blood concentration of colistin sulfate. Tigecycline is a glycylcycline antibacterial drug that binds to the bacterial ribosomal subunit 30 S, blocking protein synthesis, and thus exhibiting antibacterial effects [##REF##16249141##5##]. It is mainly used clinically to treat severe infections caused by gram-positive and gram-negative bacteria (excluding <italic>Pseudomonas aeruginosa</italic>), especially those caused by multidrug-resistant bacteria and pan-resistant bacteria. The combined use of these two drugs is considered the last line of defense for the treatment of these multidrug-resistant bacterial infections in clinical practice [##UREF##3##6##]. Currently, there are two types of polymyxin E available for clinical use: polymyxin sulfate and colistin methanesulfonate (CMS). The two have different structures, with CMS being the inactive prodrug of polymyxin E, requiring in vivo metabolism to exert its antibacterial effect. In contrast to CMS, polymyxin sulfate acts directly in the body, showing superior in vivo bactericidal activity compared to CMS. Furthermore, only 20–25% of the CMS is converted to polymyxin in patients with normal renal function, and significant interindividual variability exists. Consequently, in critically ill patients, it takes a longer time and larger doses to achieve effective blood drug concentrations, potentially delaying the treatment of patients with infections. Moreover, CMS is primarily cleared through the kidney, leading to a greater renal burden, while polymyxin sulfate is mainly cleared through other routes. With the increasing occurrence of carbapenem-resistant organisms in clinical settings, the use of polymyxin has become more widespread, especially given its superior antibacterial activity and lower renal burden. Due to the early launch of colistin sulfate and lack of modern drug development procedures, it has limited pharmacokinetic, pharmacological, and toxicological data. Therefore, the therapeutic window of colistin sulfate is narrow, and the incidence of adverse reactions is high [##UREF##4##7##, ##UREF##5##8##]. There are significant individual differences in clinical practice, requiring blood concentration monitoring. With the increasing use of tigecycline, it has been found to have significant individual differences in blood concentration, and even an increased risk of death after use [##UREF##6##9##]. However, large individual differences exist during the clinical application of the two drugs, especially in patients with severe infection. Due to this pathophysiological condition, plasma drug concentration monitoring is necessary to achieve the correct individualized dosing [##REF##32383061##10##, ##REF##24985764##11##]. Currently, there are methods for determining the plasma concentration of polymyxin, including capillary electrophoresis, high-performance liquid chromatography (HPLC) [##REF##19372021##12##, ##UREF##7##13##], and HPLC–MS/MS positive ion mode [##REF##35784679##14##]; and for determining the plasma concentration of tigecycline, including HPLC, reversed-phase-HPLC, as well as HPLC–MS/MS positive ion mode. In addition, there are few methods available for simultaneous measurement of both drugs, and only Barco et al. reported a method for simultaneous measurement of 14 antibiotics, including colistin sulfate and tigecycline [##UREF##8##15##]. However, in Barco’s method, two different protein precipitation extraction methods were used for polymyxin sulfate and tigecycline sample processing, and different internal standard substances were selected for different drugs. Thus, it is not a simultaneous determination method for polymyxin sulfate and tigecycline. Moreover, in Barco’s method, the quantification limits for polymyxin E1, polymyxin E2, and tigecycline are 0.3 mg/L, 0.5 mg/L, and 1 mg/L, respectively, which do not fully meet the clinical testing requirements. This study aims to establish an HPLC–MS/MS method to simultaneously determine the plasma concentrations of colistin sulfate and tigecycline in human plasma. It is a simple experiment to operate, with a short analysis time and high sensitivity, and it could lay a foundation for individualized medication in the future.</p>" ]
[ "<title>Materials and methods</title>", "<title>Medications, instruments, and samples</title>", "<p id=\"Par6\">The medications used were a colistin sulfate reference substance (content: 95.1%, batch number: 833,621, Dr. Ehrenstorfer Co., Ltd., Germany), tigecycline reference substance (content: 99.6%, batch number: 04919009, Lianyungang Runzhong Pharmaceutical Co., Ltd.), and polymyxin B<sub>1</sub> (content: ≥95%, batch number: P037-01BL, TOKU-E, USA).</p>", "<p id=\"Par7\">The instruments used were an LC-20 C high-performance liquid chromatograph (Shimadzu Co., Japan), API4000 mass spectrometer (Applied Biosystem Co., USA), electronic analytical balance (Sartorius, Germany), high-speed centrifuge (ABBOTT Co., USA), and a low-temperature refrigerator (Sanyo, Japan).</p>", "<p id=\"Par8\">Plasma samples were collected from patients receiving simultaneous intravenous polymyxin and tigecycline treatment. Inclusion criteria: ① Patients receiving simultaneous intravenous polymyxin and tigecycline treatment; ② Age ≥ 18 years; ③ Patients who consent to the monitoring of polymyxin and tigecycline blood drug concentrations during treatment. Exclusion criteria: ① Pregnant or lactating women; ② Treatment duration &lt; 3 days; ③ Local administration; ④ Blood dialysis treatment. Once the blood drug concentration reached a steady state, 3 ml of venous blood was collected before and 30 min after the seventh administration to measure the peak and trough concentrations. This study was conducted with approval from the Ethics Committee of Second Hospital of Hebei Medical University (2020-R551). This study was conducted in accordance with the declaration of Helsinki.</p>", "<title>Detection conditions</title>", "<title>Chromatographic conditions</title>", "<p id=\"Par9\">The chromatographic column was a Dikma C18 chromatographic column (4.6 mm×150 mm, 5 μm). For the mobile phase, phase A was the 0.1% formic acid in aqueous solution, and phase B was the 0.1% formic acid in acetonitrile solution. The flow rate was 0.8 mL/min, the column temperature was 40 °C, and gradient elution was adopted. The elution method was as follows: 0–1 min 5% phase B solution; 1–5 min 5–60% phase B solution; 5–6 min 60–95% phase B solution; 6–7 min 95% phase B solution; 7–9 min 95–5% phase B solution; 9–10 min 5% phase B solution.</p>", "<title>Mass spectrometry conditions</title>", "<p id=\"Par10\">Electrospray ionization (ESI), multiple reaction ion monitoring, and the HPLC–MS/MS positive ion mode were adopted. The voltage of the ESI was 5500 V with a temperature of 550 °C. The curtain air pressure was 10 psi, the atomizer pressure was 55 psi, the auxiliary air pressure was 55 psi, and the impact air pressure was 4 psi. The mass-to-charge ratios (m/z) from the quantitative analysis of polymyxin E<sub>1</sub>, polymyxin E<sub>2</sub>, tigecycline, and internal standard polymyxin B<sub>1</sub> were 585.7→101.2, 578.8→101.2, 586.5→569.4 and 602.7→241.4, respectively, with de-clustering potentials of 61, 59, 110 and 68 V, respectively, and impact potentials of 47, 49, 30 and 33 V, respectively. The structural diagrams of polymyxin E<sub>1</sub>, polymyxin E<sub>2</sub>, tigecycline, and the internal standard are shown in Figs. ##FIG##0##1## and ##FIG##1##2##. Their mass spectrometry (MS) spectra are shown in Fig. ##FIG##2##3##.</p>", "<p id=\"Par11\">\n\n</p>", "<p id=\"Par12\">\n\n</p>", "<p id=\"Par13\">\n\n</p>", "<title>Solution preparation</title>", "<title>Reference solution</title>", "<p id=\"Par14\">Twenty milligrams of colistin sulfate reference substance were precisely weighed, placed in a 10 mL volumetric flask, and diluted to volume with 20% methanol-aqueous solution (<italic>v</italic>:<italic>v</italic>) to prepare a stock solution of colistin sulfate with a mass concentration of 2 mg/mL. Ten mg of tigecycline reference substance was precisely weighed, placed in a 10 mL volumetric flask, and diluted to volume with pure water to prepare a tigecycline stock solution with a mass concentration of 1 mg/mL. The above solutions were stored in a − 80 °C refrigerator in preparation for further assay.</p>", "<p id=\"Par15\">The colistin sulfate and tigecycline reference stock solutions were precisely aspirated, diluted, and mixed with 20% methanol-aqueous solution (<italic>v</italic>:<italic>v</italic>) to prepare the standard curve working solutions of a colistin sulfate mass with concentrations of 1, 2, 5, 10, 20, 50, and 100 µg/mL, and of tigecycline with concentrations of 0.5, 1, 2, 5, 10, 20, and 50 µg/mL, respectively. The quality control working solutions of colistin sulfate with concentrations of 1, 10, and 80 µg/mL and that of tigecycline with concentrations of 0.5, 5, and 40 µg/mL were prepared according to the above methods. The above working solutions were stored in a − 80 °C refrigerator for further assay.</p>", "<title>Internal standard solution</title>", "<p id=\"Par16\">Twenty milligrams of polymyxin B<sub>1</sub> reference substance was precisely weighed, placed in a 10 mL volumetric flask, and diluted to volume with 20% methanol-aqueous solution (<italic>v</italic>:<italic>v</italic>) to prepare an internal standard stock solution with a mass concentration of 2 mg/mL and was stored in a − 80 °C refrigerator for further assay. A certain amount of stock solution was then diluted to a solution with a concentration of 40 µg/mL with 20% methanol-aqueous solution (<italic>v</italic>:<italic>v</italic>).</p>", "<title>Plasma sample processing</title>", "<p id=\"Par17\">Two hundred microliters of the plasma sample were adopted, with 20 µL of the internal standard added, and it was vortexed for 20 s. Two hundred microliters of 5% trichloroacetic acid was added for acidification and vortexed for 10 s. Two hundred microliters of methanol was added for extraction, vortexed for 2 min, and centrifuged at 10,900 r/min for 5 min. Two hundred microliters of the supernatant were aspirated into the injection bottle, and 10 µL of the sample was injected for the HPLC–MS/MS analysis.</p>", "<title>Methodological investigation</title>", "<title>Specificity</title>", "<p id=\"Par18\">A total of 160 µL of blank plasma was taken, and 20 µL each of polymyxin working solution and tigecycline working solution were added. After vortex mixing, 200 mL of plasma samples from patients receiving simultaneous intravenous polymyxin and tigecycline treatment were taken and processed according to the “Plasma Sample Handling” procedure. Then, 200 µL of blank plasma was also taken and mixed with 20% methanol-water solution (<italic>v:v</italic>) 20 µL without internal standards. After adding 20 µL of internal standard working solution, it was used as a blank control for HPLC-MS/MS analysis, and the chromatogram was recorded.</p>", "<title>Standard curve and limits of quantitation</title>", "<p id=\"Par19\">One hundred eighty microliters of the blank plasma were adopted, with 20 µL of standard curve working solution and 20 µL of internal standard solution added, and it was vortexed for 20 s. Then, the standard curve plasma solutions of colistin sulfate with concentrations of 0.1, 0.2, 0.5, 1, 2, 5, and 10 µg/mL and those of tigecycline with concentrations of 0.05, 0.1, 0.2, 0.5, 1, 2, and 5 µg/mL were prepared according to the operations in the “plasma sample processing.” Three replicates were prepared for each concentration, and the HPLC–MS/MS analysis was conducted to determine the peak area. The concentration of the analyte was selected as the <italic>x</italic>-coordinate and the peak area ratio of the analyte to the internal standard as the <italic>y</italic>-coordinate, and the least squares method was adopted for weighted linear regression to obtain the standard curve. The peak area of colistin sulfate was calculated as the sum of the peak areas of polymyxin E<sub>1</sub> and polymyxin E<sub>2</sub>. The limits of quantitation (LOQ) for the concentration analysis of colistin sulfate and tigecycline were determined with a signal-to-noise (S/N) ≥ 10.</p>", "<title>Precision and accuracy</title>", "<p id=\"Par20\">One hundred eighty microliters of the blank plasma was adopted, with 20 µL of quality control working solution and 20 µL of internal standard solution added, and it was vortexed for 20 s. Three quality control plasma samples were then prepared with low, medium, and high mass concentrations (the mass concentrations of colistin sulfate were 0.1, 1, and 8 µg/mL, respectively, and those of tigecycline were 0.05, 0.5, and 4 µg/mL, respectively), according to the operations in “plasma sample processing.” Five replicates of each concentration were prepared in parallel and conducted according to the operations in “plasma sample processing” for three consecutive days. The obtained peak area was introduced into the standard curve of that day to calculate the relative standard deviation (RSD) and accuracy of the intra-day and inter-day precision of the two analytes.</p>", "<title>Extraction recovery rate and matrix effect</title>", "<p id=\"Par21\">One hundred eighty microliters of the blank plasma was adopted, with 20 µL of the quality control working solution and 20 µL of the internal standard solution added, and it was vortexed for 20 s to prepare the plasma samples with low, medium, and high mass concentrations (among which the mass concentrations of colistin sulfate were 0.1, 1, and 8 µg/mL, respectively, and those of tigecycline were 0.05, 0.5, and 4 µg/mL, respectively). The plasma samples were then processed according to the operations in “plasma sample processing” and labeled as sample (A) In addition, blank plasma was processed according to the operations in “plasma sample processing” and then added with a series of quality control solutions to obtain plasma samples with low, medium, and high mass concentrations (among which the concentrations of colistin sulfate were 0.1, 1, and 8 µg/mL, respectively, and those of cyclocycline were 0.05, 0.5, and 4 µg/mL, respectively), which were labeled as sample (B) A standard mixed solution with the same concentration was prepared as sample (C) Five replicates of each concentration were prepared. The three groups of samples were analyzed by HPLC–MS/MS in the same way. The extraction recovery rate was calculated by the ratio of the peak area of sample A to that of sample B, and the ratio of the peak area of sample B to that of sample C was used to calculate the matrix effect.</p>", "<title>Stability</title>", "<p id=\"Par22\">Plasma samples with low, medium, and high mass concentrations were prepared (the mass concentrations of colistin sulfate were 0.1, 1, and 8 µg/mL, respectively, and those of tigecycline were 0.05, 0.5, and 4 µg/mL, respectively). Five replicates of each concentration were prepared and placed in a refrigerator at 4 °C for 12 h, at room temperature for 6 h, and in an automatic sampler at 15 ℃ for 24 h. The samples were, on three occasions, frozen at − 80 °C and thawed at room temperature, and then placed in a − 80 °C refrigerator for seven days. The concentrations and RSDs of colistin sulfate and tigecycline in the plasma samples were calculated based on the accompanying standard curve of the day to evaluate their stabilities.</p>" ]
[ "<title>Results</title>", "<title>Methodological evaluation</title>", "<title>Specificity</title>", "<p id=\"Par23\">Under the chromatographic conditions in this experiment, the total running time of HPLC–MS/MS analysis was 10 min, and the retention times of the four substances, including polymyxin E<sub>1</sub>, polymyxin E<sub>2</sub>, tigecycline, and internal standard, were 5.11 min, 5.03 min, 4.84 min, and 5.18 min, respectively. The endogenous impurities in the plasma samples did not interfere with the analytes and internal standards and could be adopted for quantitative analysis. The chromatograms are shown in Figs. ##FIG##3##4##, ##FIG##4##5##, ##FIG##5##6## and ##FIG##6##7##.</p>", "<p id=\"Par24\">\n\n</p>", "<p id=\"Par25\">\n\n</p>", "<p id=\"Par26\">\n\n</p>", "<p id=\"Par27\">\n\n</p>", "<title>Standard curve and limits of quantitation</title>", "<p id=\"Par28\">A good linear relationship existed, with the concentration of colistin sulfate and tigecycline in the plasma within the range of 0.1–10 µg/mL and 0.05–5 µg/mL, respectively. The standard curve equations were <italic>y</italic> = 0.814<italic>x</italic> + 0.056 (R<sup>2</sup> = 0.9986), <italic>y</italic> = 5.012<italic>x</italic> − 0.052 (R<sup>2</sup> = 0.9987), and the LLOQs were 0.1 µg/mL and 0.05 µg/mL, respectively.</p>", "<title>Precision and accuracy</title>", "<p id=\"Par29\">The RSD of the intra-day and inter-day precision of colistin sulfate and tigecycline were both less than 15%, with the accuracy being within the range of 88.21–108.24%. The results are demonstrated in Table ##TAB##0##1##.</p>", "<p id=\"Par30\">\n\n</p>", "<title>Extraction recovery rate and matrix effect</title>", "<p id=\"Par31\">The extraction recovery rates of colistin sulfate and tigecycline were 87.75–91.22%, and the matrix effect was 99.40–105.26%. The RSD was all less than 15%. The results showed that the analytes had a high recovery rate and were not affected by the matrix effect. The details are illustrated in Table ##TAB##1##2##.</p>", "<p id=\"Par32\">\n\n</p>", "<title>Stability</title>", "<p id=\"Par33\">The RSD of the concentration of colistin sulfate was 0.75–9.14%, and that of the concentration of tigecycline was 0.72–11.76%. The results showed that the analytes had good stability under the above conditions. The results are shown in Table ##TAB##2##3##.</p>", "<p id=\"Par34\">\n\n</p>", "<title>Example of application</title>", "<p id=\"Par35\">This study included a total of 12 adult patients receiving intravenous polymyxin, consisting of 7 males and 5 females, with an average age of (58.67 ± 16.44) years. Two patients were administered an initial dose of 100 mg and a maintenance dose of 50 mg q12h for polymyxin, while the remaining 10 patients did not receive a doubled initial dose. All patients received an initial dose of 100 mg and a maintenance dose of 50 mg q12h for tigecycline. Three milliliters of venous blood were collected before and after the seventh administration to measure the peak and trough concentrations of the drugs. It was revealed that the trough concentration of colistin sulfate ranged from 0.15 to 2.51 µg/mL, the peak concentration ranged from 0.89 to 4.56 µg/mL, and the trough concentration of tigecycline ranged from 0.25 to 0.81 µg/mL, the peak concentration ranged from 0.92 to 1.78 µg/mL. The results of this method were all within the linear range of the study. The results are shown in Table ##TAB##3##4##.</p>", "<p id=\"Par36\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par37\">Currently, there is a lack of a internationally for simultaneously determining colistin sulfate and tigecycline in human plasma. Establishing the present method might provide a means of simultaneously determining the plasma drug concentrations for patients taking a combined medication of the two drugs, which could save costs and be convenient to operate without needing to switch the experimental methods. The present method saved the time of equilibrating the chromatographic column, preparing a new mobile phase, issuing a report, providing patients with plasma drug concentration data as soon as possible, and adjusting the individualized drug regimen in a timely manner. In addition, the present method had high accuracy, good reproducibility, and strong specificity, which could meet the requirements of pharmacokinetic investigations of colistin sulfate and tigecycline and lay a foundation for further pharmacokinetic/pharmacodynamic (PK/PD) investigations.</p>", "<p id=\"Par38\">This study compared two pretreatment methods, solid-phase extraction and protein precipitation of samples. The solid-phase extraction method involves cumbersome operations with a run time of 20 min, leading to relatively time-consuming and material-consuming processes. Therefore, the protein precipitation method was ultimately selected for the processing of blood samples. Five reagents, including methanol, acetonitrile, trichloroacetic acid, trifluoroacetic acid, and perchloric acid, were compared for protein precipitation. The results indicated that all of the aforementioned reagents could be used for precipitation, but the recovery rate of polymyxin sulfate using acetonitrile was lower than that using methanol. Considering the widespread distribution of tigecycline in the body tissues and the need to avoid using strong acid precipitation that could corrode the chromatographic column, a low concentration of methanol-5% trichloroacetic acid (50:50, V/V) was ultimately chosen for protein precipitation to ensure a higher extraction recovery rate and simplify the plasma pretreatment process. This selection improved the analysis efficiency, making it suitable for clinical analysis with a large sample size. For the mobile phase, investigations were conducted using 0.05% formic acid aqueous solution-acetonitrile, 0.1% formic acid aqueous solution-acetonitrile, 0.2% formic acid aqueous solution-acetonitrile, and 0.1% formic acid aqueous solution-0.1% acetonitrile, followed by isocratic or gradient elution. Finally, considering the peak shape, elution time, and corrosive effects on the instrument, a 0.1% formic acid aqueous solution-0.1% acetonitrile solution was selected as the mobile phase for gradient elution. Under these conditions, the drug exhibited good resolution and peak shape.</p>", "<p id=\"Par39\">The PK process of the drug in the body is often affected in patients with serious diseases accompanied by microcirculation disorders, hypoproteinemia, liver and kidney insufficiency, and other special pathophysiological states. Large fluctuations in plasma drug concentrations are commonly observed in these cases. TDM can aid in the optimization of administration dosage, individualized dosing, and anti-infective efficacy. Since colistin sulfate has not undergone modern drug development procedures, the current pharmacokinetic data remain unclear, and the plasma concentration is closely correlated with its antibacterial effect and nephrotoxicity [##REF##31364083##16##]. In <italic>Vitro</italic> and animal studies revealed that the free drug area under the concentration-time curve to the minimum inhibitory concentration ratio (fAUC/MIC) is the PK/PD index that best correlates with the efficacy of colistin sulfate [##REF##30710469##17##]. A study on the population PKs of colistin sulfate showed that when MIC ≤ 0.5 µg/mL, the recommended dosages of colistin sulfate were 500,000 IU q12h, 500,000 IU q8h, or 750,000 IU q12h, in which probability of target attainment (PTA) could reach &gt; 90% in all schedules. However, when MIC = 1 µg/mL, for patients with creatinine clearance (CrCL) &gt; 80 mL/min, there was a sub-optimal exposure risk at 500,000 IU q8h and 750,000 IU q12h; thus, a therapeutic schedule of 1,000,000 IU q12h was recommended. When MIC ≥ 2 µg/mL, all dosage schedules recommended in the instructions failed to achieve PTA ≥ 90% [##REF##22143524##18##]. The blood drug concentration of colistin sulfate in 12 patients was detected using this method, the trough concentration range was 0.15 to 2.51 µg/mL, and the peak concentration range was 0.89 to 4.56 µg/mL. The large difference is due to the fact that patient 2 and patient 11 were given a double-dose of colistin sulfate as the first dose, compared to the recommended dose of 500,000 IU q12h. Additionally, patient 2, patient 2 and patient 11 had renal insufficiency, and colistin sulfate is primarily excreted through the kidneys, with 40% of the administered dose excreted in the urine within 8 h after administration. In patients with renal insufficiency, the drug tends to accumulate in the body, leading to high blood concentrations, hence the simultaneous effect of the double-dose and renal insufficiency. The results showed that there was a large individual difference in the pharmacokinetics of colistin sulfate, and the patient’s renal function affected drug excretion. The dosing regimen of 500,000 IU q12h specified in the instructions is insufficient, and a double dose administration scheme should be adopted to increase the blood drug concentration and improve clinical efficacy. In this study, all 12 patients received tigecycline at the recommended doses as per the instructions, with an initial dose of 100 mg and a maintenance dose of 50 mg q12h. The trough concentration range of tigecycline was 0.25 to 0.81 µg/mL, while the peak concentration ranged from 0.92 to 1.78 µg/mL, demonstrating significant interindividual differences. A study on the clinical efficacy of tigecycline in patients with severe infections showed that when the albumin(ALB) level &lt; 26 g/L and the fAUC<sub>0–24 h</sub>/MIC &gt; 0.9, the clinical antibacterial efficacy was reduced by nearly half of that in patients with an albumin level &gt; 26 g/L [##REF##23679904##19##]. The reason for this is that hypoalbuminemia can reduce the binding of albumin to tigecycline, leading to an increase in free drug concentration and an apparent increase in the volume of distribution. An increase in the free form of the drug can enhance renal clearance, further reducing drug concentration, thus affecting the therapeutic effect. Therefore, the changes in a patient’s albumin levels affect its therapeutic efficacy. Another PK/PD investigation on tigecycline in patients with severe diseases confirmed that for patients with intra-abdominal infections and community-acquired pneumonia, when MIC ≥ 1 µg/mL, the AUC/MIC compliance rate of patients treated with conventional tigecycline (with the first dose of 100 mg and a maintenance dose of 50 mg q12h) was significantly reduced, thus an increase in dosage was necessary [##REF##23679904##19##, ##REF##23357775##20##]. Moreover, body mass index (BMI) can also affect the volume of distribution of polymyxin and tigecycline in the body, serving as an important determinant for the specific dosage administered. It has been claimed that patients with a high BMI may require increased antibiotic dosages; however, this point is still controversial and requires further exploration.</p>", "<p id=\"Par40\">This study had a relatively small sample size, with all patient BMIs falling within the normal range and all patient ALB values exceeding 26.00 g/L. Only three patients had renal insufficiency, indicating the need for a larger sample size and more comprehensive clinical data to obtain pharmacokinetic data and evaluate the relationship between blood drug concentration and clinical efficacy. The method established in this study for the simultaneous determination of polymyxin and tigecycline blood drug concentrations is accurate, sensitive, and easy to operate, meeting the requirements of TDM. It can serve as a foundation for further research on the pharmacokinetics of polymyxin and tigecycline, providing references for safe and effective clinical drug use.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par41\">The HPLC–MS/MS method established in this study could simultaneously determine the plasma concentrations of colistin sulfate and tigecycline. The detection method was efficient, convenient, and accurate. It could quickly provide patients with plasma concentration data, adjust individualized medication schedules, and meet the requirements of further PK investigations of colistin sulfate and tigecycline. However, this study has limitations regarding the number of case and blood collection points; therefore, expanding the sample size for further PK/PD investigations is necessary.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">To establish a high-performance liquid chromatography–tandem mass spectrometry method (HPLC–MS/MS) to simultaneously determine colistin sulfate and tigecycline in human plasma.</p>", "<title>Methods</title>", "<p id=\"Par2\">Polymyxin B<sub>1</sub> internal standard (20 µL) was added into 200 µL of plasma sample. The samples were treated with methanol-5% trichloroacetic acid (50:50, V/V) solution, and the protein precipitation method was adopted for post-injection analysis. The chromatographic column was a Dikma C18 (4.6 mm × 150 mm, 5 μm). For the mobile phase, 0.1% formic acid in aqueous solution was used for phase A, 0.1% formic acid in acetonitrile solution for phase B, and gradient elution was also applied. The flow rate was 0.8 mL/min, the column temperature was 40 °C, and the injection volume was 10 µL; Electrospray ionization and multiple reaction ion monitoring were adopted and scanned by the HPLC–MS/MS positive ion mode.</p>", "<title>Results</title>", "<p id=\"Par3\">The endogenous impurities in the plasma had no interference in the determination of the analytes. There existed a good linear relationship of colistin sulfate within the range of 0.1–10 µg/mL (R<sup>2</sup> = 0.9986), with the lower limit of quantification (LLOQ) of 0.1 µg/mL. There existed a good linear relationship of tigecycline within the range of 0.05–5 µg/ mL (R<sup>2</sup> = 0.9987), with the LLOQ of 0.05 µg/mL. The intra- and inter-day relative standard deviations of colistin sulfate and tigecycline were both less than 15%, and the accuracy was between 88.21% and 108.24%. The extraction had good stability, the extraction recovery rate was 87.75–91.22%, and the matrix effect was 99.40–105.26%.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">This study successfully established a method for simultaneously detecting colistin sulfate and tigecycline plasma concentrations. The method was simple, rapid, and highly sensitive and could be applied for therapeutic medication monitoring.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We would like to acknowledge the hard and dedicated work of all the staff that implemented the intervention and evaluation components of the study.</p>", "<title>Author contributions</title>", "<p>Conception and design of the research: YXL; Acquisition of data: WXK; Analysis and interpretation of the data: MYC; Statistical analysis: MYC; Writing of the manuscript: MYC; Critical revision of the manuscript for intellectual content: YXL, ZZQ. All authors read and approved the final draft.</p>", "<title>Funding</title>", "<p>No external funding received to conduct this study.</p>", "<title>Data availability</title>", "<p>All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par43\">I confirm that I have read the Editorial Policy pages. This study was conducted with approval from the Ethics Committee of Second Hospital of Hebei Medical University, (2020-R551). This study was conducted in accordance with the declaration of Helsinki. Written informed consent was obtained from all participants.</p>", "<title>Consent for publication</title>", "<p id=\"Par44\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par42\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Chemical structure of polymyxin E<sub>1,</sub> polymyxin E<sub>2,</sub> and polymyxin B<sub>1</sub>. Dab = L-α,γ-diaminobutyric acid. α and γ indicate the respective-NH<sub>2</sub> involved in the peptide linkage. Polymyxin B<sub>1</sub>: R = (+)-6-methyloctanoate, X = Phe; polymyxin E<sub>1</sub>: R = (+)-6-methyloctanoate, X = D-Leu; polymyxin E<sub>2</sub>: R = (+)-6-methylheptanoate, X = D-Leu</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Chemical structure of tigecycline</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>MS spectra of polymyxin E<sub>1</sub>, polymyxin E<sub>2</sub>, tigacycline and polymyxin B<sub>1</sub>. (<bold>A</bold>) precursor ion of Polymyxin E<sub>1</sub> and polymyxin E<sub>2</sub>; (<bold>B</bold>) precursor ion of tigecycline; (<bold>C</bold>) precursor ion of polymyxin B<sub>1</sub>; (<bold>D</bold>) product ion of polymyxin E<sub>1</sub>; (<bold>E</bold>) product ion of Polymyxin E<sub>2</sub>; (<bold>F</bold>) product ion of tigecycline; (<bold>G</bold>) product ion of Polymyxin B<sub>1</sub></p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>MRM chromatograms for blank plasma (<bold>A</bold> polymyxin E<sub>1</sub>; <bold>B</bold> polymyxin E<sub>2</sub>; <bold>C</bold> tigecycline; <bold>D</bold> polymyxin B<sub>1</sub>)</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>MRM chromatograms for blank plasma with LOQ levels of colistin sulfate, tigecycline, and internal standard (<bold>A</bold> polymyxin E<sub>1</sub>; <bold>B</bold> polymyxin E<sub>2</sub>; <bold>C</bold>, tigecycline; <bold>D</bold>, polymyxin B<sub>1</sub>)</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>MRM chromatograms for blank plasma with colistin sulfate (2 µg/mL), tigecycline (0.2 µg/mL), and internal standard (40 µg/mL) (<bold>A</bold> polymyxin E<sub>1</sub>; <bold>B</bold> polymyxin E<sub>2</sub>; <bold>C</bold> tigecycline; <bold>D</bold> polymyxin B<sub>1</sub>)</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>MRM chromatograms for clinical plasma with the internal standard (<bold>A</bold> polymyxin E<sub>1</sub>; <bold>B</bold> polymyxin E<sub>2</sub>; <bold>C</bold> tigecycline; <bold>D</bold> polymyxin B<sub>1</sub>)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>The intra- and inter-day relative standard deviation and accuracy (n = 5)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Analyte</th><th align=\"left\" rowspan=\"2\">Quality control concentration (µg/mL)</th><th align=\"left\" colspan=\"3\">Intra-day relative standard deviation</th><th align=\"left\" colspan=\"3\">Inter-day relative standard deviation</th></tr><tr><th align=\"left\">Measured value (µg/mL)</th><th align=\"left\">RSD<break/>(%)</th><th align=\"left\">Accuracy<break/>(%)</th><th align=\"left\">Measured value (µg/mL)</th><th align=\"left\">RSD<break/>(%)</th><th align=\"left\">Accuracy<break/>(%)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Colistin sulfate</td><td align=\"left\">0.1</td><td align=\"left\">0.09 ± 0.00</td><td align=\"left\">4.10</td><td align=\"left\">88.21</td><td align=\"left\">0.10 ± 0.01</td><td align=\"left\">8.45</td><td align=\"left\">97.77</td></tr><tr><td align=\"left\">1</td><td align=\"left\">1.08 ± 0.03</td><td align=\"left\">2.73</td><td align=\"left\">107.98</td><td align=\"left\">1.01 ± 0.07</td><td align=\"left\">6.60</td><td align=\"left\">101.12</td></tr><tr><td align=\"left\">8</td><td align=\"left\">7.89 ± 0.28</td><td align=\"left\">3.58</td><td align=\"left\">98.65</td><td align=\"left\">7.94 ± 0.27</td><td align=\"left\">3.37</td><td align=\"left\">99.30</td></tr><tr><td align=\"left\" rowspan=\"3\">Tigecycline</td><td align=\"left\">0.05</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">3.19</td><td align=\"left\">108.24</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">7.16</td><td align=\"left\">104.15</td></tr><tr><td align=\"left\">0.5</td><td align=\"left\">0.47 ± 0.02</td><td align=\"left\">3.24</td><td align=\"left\">93.97</td><td align=\"left\">0.48 ± 0.03</td><td align=\"left\">5.90</td><td align=\"left\">95.99</td></tr><tr><td align=\"left\">4</td><td align=\"left\">4.20 ± 0.39</td><td align=\"left\">9.32</td><td align=\"left\">104.97</td><td align=\"left\">4.13 ± 0.27</td><td align=\"left\">6.56</td><td align=\"left\">103.32</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>The extraction recovery rate and matrix effect (n = 5)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Analyte</th><th align=\"left\">Quality control concentration<break/>(µg/mL)</th><th align=\"left\">Extraction recovery rate<break/>(%)</th><th align=\"left\">RSD<break/>(%)</th><th align=\"left\">Matrix effect<break/>(%)</th><th align=\"left\">RSD<break/>(%)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Colistin sulfate</td><td align=\"left\">0.1</td><td char=\"?\" align=\"char\">87.75 ± 7.74</td><td char=\".\" align=\"char\">8.82</td><td char=\"?\" align=\"char\">99.40 ± 6.96</td><td char=\".\" align=\"char\">7.01</td></tr><tr><td align=\"left\">1</td><td char=\"?\" align=\"char\">88.61 ± 4.50</td><td char=\".\" align=\"char\">5.07</td><td char=\"?\" align=\"char\">101.24 ± 2.64</td><td char=\".\" align=\"char\">2.60</td></tr><tr><td align=\"left\">8</td><td char=\"?\" align=\"char\">91.22 ± 2.62</td><td char=\".\" align=\"char\">2.88</td><td char=\"?\" align=\"char\">102.53 ± 1.60</td><td char=\".\" align=\"char\">1.56</td></tr><tr><td align=\"left\" rowspan=\"3\">Tigecycline</td><td align=\"left\">0.05</td><td char=\"?\" align=\"char\">88.89 ± 2.38</td><td char=\".\" align=\"char\">2.68</td><td char=\"?\" align=\"char\">102.20 ± 5.37</td><td char=\".\" align=\"char\">5.25</td></tr><tr><td align=\"left\">0.5</td><td char=\"?\" align=\"char\">90.76 ± 4.56</td><td char=\".\" align=\"char\">5.02</td><td char=\"?\" align=\"char\">102.77 ± 11.46</td><td char=\".\" align=\"char\">11.16</td></tr><tr><td align=\"left\">4</td><td char=\"?\" align=\"char\">90.05 ± 4.65</td><td char=\".\" align=\"char\">5.17</td><td char=\"?\" align=\"char\">105.26 ± 2.37</td><td char=\".\" align=\"char\">2.25</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>The stability of two analytes under different conditions (n = 5)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Analyte</th><th align=\"left\" rowspan=\"2\">Quality control concentration (µg/mL)</th><th align=\"left\" colspan=\"2\">At 4℃ for 12 h</th><th align=\"left\" colspan=\"2\">At room temperature for 6 h</th><th align=\"left\" colspan=\"2\">Automatic sampler 15℃ for 24 h</th><th align=\"left\" colspan=\"2\">Freeze-thaw for 3 cycles</th><th align=\"left\" colspan=\"2\">Stored at -80℃ for 7 days</th></tr><tr><th align=\"left\">Measured value<break/>(µg/mL)</th><th align=\"left\">RSD (%)</th><th align=\"left\">Measured value<break/>(µg/mL)</th><th align=\"left\">RSD (%)</th><th align=\"left\">Measured value<break/>(µg/mL)</th><th align=\"left\">RSD (%)</th><th align=\"left\">Measured value<break/>(µg/mL)</th><th align=\"left\">RSD (%)</th><th align=\"left\">Measured value<break/>(µg/mL)</th><th align=\"left\">RSD (%)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Colistin sulfate</td><td align=\"left\">0.1</td><td align=\"left\">0.09 ± 0.01</td><td align=\"left\">8.21</td><td align=\"left\">0.10 ± 0.00</td><td align=\"left\">4.63</td><td align=\"left\">0.10 ± 0.00</td><td align=\"left\">4.47</td><td align=\"left\">0.09 ± 0.00</td><td align=\"left\">3.93</td><td align=\"left\">0.10 ± 0.00</td><td align=\"left\">4.15</td></tr><tr><td align=\"left\">1</td><td align=\"left\">0.93 ± 0.04</td><td align=\"left\">4.85</td><td align=\"left\">1.00 ± 0.05</td><td align=\"left\">5.11</td><td align=\"left\">0.93 ± 0.01</td><td align=\"left\">0.75</td><td align=\"left\">1.04 ± 0.04</td><td align=\"left\">3.93</td><td align=\"left\">0.98 ± 0.09</td><td align=\"left\">9.14</td></tr><tr><td align=\"left\">8</td><td align=\"left\">8.23 ± 0.61</td><td align=\"left\">7.39</td><td align=\"left\">8.26 ± 0.30</td><td align=\"left\">3.64</td><td align=\"left\">8.17 ± 0.19</td><td align=\"left\">2.38</td><td align=\"left\">8.70 ± 0.54</td><td align=\"left\">6.16</td><td align=\"left\">8.30 ± 0.32</td><td align=\"left\">3.86</td></tr><tr><td align=\"left\" rowspan=\"3\">Tigecycline</td><td align=\"left\">0.05</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">3.95</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">5.09</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">1.64</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">9.09</td><td align=\"left\">0.05 ± 0.00</td><td align=\"left\">2.55</td></tr><tr><td align=\"left\">0.5</td><td align=\"left\">0.46 ± 0.01</td><td align=\"left\">1.99</td><td align=\"left\">0.54 ± 0.03</td><td align=\"left\">4.91</td><td align=\"left\">0.49 ± 0.03</td><td align=\"left\">5.29</td><td align=\"left\">0.52 ± 0.04</td><td align=\"left\">7.47</td><td align=\"left\">0.46 ± 0.03</td><td align=\"left\">6.05</td></tr><tr><td align=\"left\">4</td><td align=\"left\">3.93 ± 0.36</td><td align=\"left\">9.19</td><td align=\"left\">4.87 ± 0.07</td><td align=\"left\">1.88</td><td align=\"left\">4.00 ± 0.26</td><td align=\"left\">6.46</td><td align=\"left\">3.82 ± 0.45</td><td align=\"left\">11.76</td><td align=\"left\">4.30 ± 0.03</td><td align=\"left\">0.72</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>The plasma drug concentration of colistin sulfate and tigecyclin</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">No.</th><th align=\"left\" rowspan=\"2\">Gender</th><th align=\"left\" rowspan=\"2\">BMI<break/>(kg/m<sup>2</sup>)</th><th align=\"left\" rowspan=\"2\">CrCL<sup>a</sup> (ml/min)</th><th align=\"left\" rowspan=\"2\">ALB<sup>b</sup><break/>(g/L)</th><th align=\"left\" rowspan=\"2\">Colistin sulfate dosage of administration</th><th align=\"left\" colspan=\"2\">Colistin sulfate</th><th align=\"left\" rowspan=\"2\">Tigecycline dosage of administration</th><th align=\"left\" colspan=\"2\">Tigecycline</th></tr><tr><th align=\"left\">Trough concentration(µg/mL)</th><th align=\"left\">Peak concentration(µg/mL)</th><th align=\"left\">Trough concentration(µg/mL)</th><th align=\"left\">Peak concentration(µg/mL)</th></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">27.04</td><td char=\".\" align=\"char\">107</td><td char=\".\" align=\"char\">33.8</td><td align=\"left\">500,000IU q12h</td><td char=\".\" align=\"char\">0.26</td><td char=\".\" align=\"char\">1.13</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.79</td><td char=\".\" align=\"char\">1.72</td></tr><tr><td align=\"left\">2</td><td align=\"left\">Female</td><td char=\".\" align=\"char\">27.69</td><td char=\".\" align=\"char\">36</td><td char=\".\" align=\"char\">30.35</td><td align=\"left\">First dose 1 million IU maintenance dose 500,000 IU q12h</td><td char=\".\" align=\"char\">2.02</td><td char=\".\" align=\"char\">4.56</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.81</td><td char=\".\" align=\"char\">1.68</td></tr><tr><td align=\"left\">3</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">23.88</td><td char=\".\" align=\"char\">90</td><td char=\".\" align=\"char\">26.80</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.28</td><td char=\".\" align=\"char\">1.22</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.77</td><td char=\".\" align=\"char\">1.67</td></tr><tr><td align=\"left\">4</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">18.72</td><td char=\".\" align=\"char\">111</td><td char=\".\" align=\"char\">32.50</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.28</td><td char=\".\" align=\"char\">1.39</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.69</td><td char=\".\" align=\"char\">1.47</td></tr><tr><td align=\"left\">5</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">22.14</td><td char=\".\" align=\"char\">84</td><td char=\".\" align=\"char\">28.00</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.84</td><td char=\".\" align=\"char\">2.51</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.58</td><td char=\".\" align=\"char\">1.17</td></tr><tr><td align=\"left\">6</td><td align=\"left\">Femaee</td><td char=\".\" align=\"char\">19.3</td><td char=\".\" align=\"char\">161</td><td char=\".\" align=\"char\">35.3</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.15</td><td char=\".\" align=\"char\">0.89</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.66</td><td char=\".\" align=\"char\">1.11</td></tr><tr><td align=\"left\">7</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">24.16</td><td char=\".\" align=\"char\">59</td><td char=\".\" align=\"char\">36.72</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.78</td><td char=\".\" align=\"char\">2.33</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.58</td><td char=\".\" align=\"char\">1.01</td></tr><tr><td align=\"left\">8</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">27.44</td><td char=\".\" align=\"char\">98</td><td char=\".\" align=\"char\">33.30</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.39</td><td char=\".\" align=\"char\">1.93</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.63</td><td char=\".\" align=\"char\">0.92</td></tr><tr><td align=\"left\">9</td><td align=\"left\">Female</td><td char=\".\" align=\"char\">20.91</td><td char=\".\" align=\"char\">106</td><td char=\".\" align=\"char\">32.71</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.44</td><td char=\".\" align=\"char\">2.27</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.65</td><td char=\".\" align=\"char\">1.22</td></tr><tr><td align=\"left\">10</td><td align=\"left\">Female</td><td char=\".\" align=\"char\">21.95</td><td char=\".\" align=\"char\">129</td><td char=\".\" align=\"char\">31.89</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.37</td><td char=\".\" align=\"char\">2.03</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.33</td><td char=\".\" align=\"char\">1.08</td></tr><tr><td align=\"left\">11</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">22.51</td><td char=\".\" align=\"char\">27</td><td char=\".\" align=\"char\">27.10</td><td align=\"left\">First dose 1 million IU maintenance dose 500,000 IU q12h</td><td char=\".\" align=\"char\">2.51</td><td char=\".\" align=\"char\">4.27</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.25</td><td char=\".\" align=\"char\">0.99</td></tr><tr><td align=\"left\">12</td><td align=\"left\">Female</td><td char=\".\" align=\"char\">23.71</td><td char=\".\" align=\"char\">170</td><td char=\".\" align=\"char\">32.50</td><td align=\"left\">500,000 IU q12h</td><td char=\".\" align=\"char\">0.17</td><td char=\".\" align=\"char\">1.09</td><td align=\"left\"><p>First dose 100 mg maintenance dose</p><p>50 mg q12h</p></td><td char=\".\" align=\"char\">0.48</td><td char=\".\" align=\"char\">1.78</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><sup>a</sup>Creatinine clearance on the day of blood collection</p><p><sup>b</sup>White blood cell count on the day of blood collection</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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{ "acronym": [], "definition": [] }
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2024-01-14 23:43:45
BMC Chem. 2024 Jan 13; 18(1):12
oa_package/e6/8d/PMC10787398.tar.gz
PMC10787399
38216860
[ "<title>Introduction</title>", "<p id=\"Par4\">Transcription factors are a class of DNA-binding proteins that regulate gene transcription by binding specifically to cis-acting elements in the promoter region of eukaryotic genes, through interactions with each other proteins [##REF##32553192##1##]. <italic>GRAS</italic> gene family is present only in higher plants [##REF##19820314##2##]. Its members have unique GRAS domains, and some of them also have DELLA protein structures. These domains are closely related to physiological processes such as plant growth, metabolism, and stress adaptation [##REF##19820314##2##]. GRAS protein is named after the characteristic letters of the three members initially discovered: <italic>GAI</italic> (GIBBERELLIN INSENSITIVE) [##REF##9389651##3##], <italic>RGA</italic> (REPRESSOR OF GAL-3) [##REF##9490740##4##], and <italic>SCR</italic> (SCARECROW) [##REF##8756724##5##]. The members of the GRAS protein family generally consist of 400 to 700 amino acid residues. The length and sequence of amino acids are highly complex due to their N-terminal structures, while the C-terminal amino acids are relatively conserved [##REF##10341448##6##]. In general, the typical structural domains of the GRAS family include LHR I (Leucine heptad repeat I), VHIID (Val-His-Ile-Ile-Asp), LHR II, PFYRE (Pro-Phe-Tyr-Arg-Glu), and SAW (Ser-Ala-Trp) [##REF##28303145##7##]. VHIID is considered the core region as it is highly conserved. It binds with two leucine heptad repeat regions to form LHR I - VHIID - LHR II complexes, regulating the binding activity with DNA and other proteins [##REF##10341448##6##, ##REF##10842311##8##]. Moreover, these two leucine-rich regions are composed of about 100 amino acid residues. In most cases, these two regions do not form a complete unit every seven residues, which distinguishes them from the Leucine zipper [##REF##21732203##9##]. There is a hypothetical nuclear localization signal in the LHR I region at the C - terminus, therefore the SV40-type sequence could be recognized [##REF##16653177##10##, ##REF##14760535##11##]. Some LHR I motifs in the N-terminal of GRAS proteins contain a conserved LXXLL sequence (Leu-X-X-Leu, X represents any amino acid), which is common in most GRAS proteins [##REF##9192902##12##–##REF##19252081##15##]. However, the roles of the LXXLL sequences in mediating the interactions of plant GRAS proteins with their regulators and co-activators are still unclear. PFYRE motif, which contains a tyrosine phosphorylation site, is not as conserved as the VHIID region, but still exhibits high similarity and collinearity in most GRAS proteins. This motif typically consists of three parts: proline residue (P), phenylalanine residue (F), tyrosine residue (Y), arginine residue (R), and glutamate residue (E) [##REF##10341448##6##, ##REF##14760535##11##]. The functions of the PFYRE and SAW motifs are not fully understood yet, but they both have conserved amino acid residues or pairs, suggesting that these two structural motifs are important for protein function or stability [##REF##22280012##16##]. N-terminal region of GRAS proteins is flexible and variable in length and sequence, forming inherently disordered regions (IDRs) that adopt specific molecular recognition features upon binding [##REF##21732203##9##]. The diverse N-terminal interacts with different target proteins during expression, acting cooperatively and exhibiting protein specificity, which plays a key role in signal transduction pathways, depending on the different members or expression conditions [##REF##21732203##9##, ##REF##22280012##16##, ##REF##35713799##17##].</p>", "<p id=\"Par5\">According to the members of the GRAS family in the genomes of <italic>Arabidopsis</italic> and rice, this family can be divided into eight branches, including SCL3 (SCARECROW - LIKE3), SHR (SHORT ROOT), PAT1 (PHYTOCHROME A SIGNAL TRANSACTION), LISCL (<italic>Lilium longiflorum</italic> SCR like), DELLA, SCR (GAI - RGA - SCR), LAS (LATERAL SUPPRESSOR), and HAM (HAIRY MERISTEM) [##REF##25101599##18##]. These subfamilies play their respective roles in plant growth, development, and metabolic regulation. Cenci and Rouard [##REF##28303145##7##] also analyzed the GRAS transcription factors in various angiosperms, who found that there were other subfamilies such as DLT (Dwarf and Low Tillering, NSP1 (Nodulation Signaling Pathway 1), NSP2 besides the above eight subfamilies. Currently, the GRAS family has been reported to exist in over 50 plants, including <italic>Arabidopsis thaliana</italic> (n = 33) [##REF##18500650##19##], <italic>Brachypodium distachyon</italic> (n = 48) [##UREF##0##20##], <italic>Brassica napus</italic> (n = 92) [##REF##31161396##21##], <italic>Capsicum annuum</italic> (n = 50) [##REF##29868257##22##], <italic>Chenopodium quinoa</italic> (n = 52) [##REF##34092279##23##], <italic>Citrullus lanatus</italic> (n = 37) [##REF##34123598##24##], <italic>Citrus sinensis</italic> (n = 50) [##UREF##1##25##], <italic>Fagopyrum tataricum</italic> (n = 47) [##REF##31387526##26##], <italic>Glycine max</italic> (n = 117) [##REF##32891114##27##], <italic>Hordeum vulgare</italic> (n = 62) [##REF##32423019##28##], <italic>Jatropha curcas</italic> (n = 48) [##REF##26782574##29##], <italic>Litchi chinensis</italic> (n = 48) [##REF##34535087##30##], <italic>Malus domestica</italic> (n = 127) [##REF##28503152##31##], <italic>Manihot esculenta</italic> (n = 77) [##UREF##2##32##], <italic>Medicago sativa</italic> (n = 51) [##UREF##3##33##], <italic>Oryza sativa</italic> (n = 57) [##REF##15316287##34##], <italic>Phaseolus vulgaris</italic> (n = 55) [##UREF##4##35##], <italic>Ricinus communes</italic> (n = 48) [##UREF##5##36##], <italic>Setaria italica</italic> (n = 57) [##REF##34732123##37##], <italic>Solanum lycopersicum</italic> (n = 54) [##REF##29134140##38##], <italic>Sorghum bicolor</italic> (n = 81) [##UREF##6##39##], <italic>Triticum aestivum</italic> (n = 188) [##REF##33665016##40##], <italic>Vitis vinifera</italic> (n = 52) [##REF##27065316##41##], <italic>Zea mays</italic> (n = 86) [##REF##28957440##42##], et al.</p>", "<p id=\"Par6\">The <italic>GRAS</italic> family comprises diverse subfamilies with distinct structural and functional features. Members of different subfamilies may participate in various processes of plant growth, development and environmental adaptation [##REF##11340177##43##–##REF##10817761##47##]. The <italic>SCR</italic> is co-localized with <italic>SHR</italic> in the vascular bundle sheath cells of leaves and roots [##REF##24517883##48##]. <italic>PAT1</italic>, <italic>SCL13</italic>, and <italic>SCL21</italic> are members of the PAT1 subfamily and are implicated in regulating light signal transduction [##REF##10817761##47##, ##REF##23109688##49##]. DELLA is involved in the response to plant hormone signals, such as gibberellin, jasmonic acid, and auxin [##REF##21549956##50##–##REF##22892320##52##]. The protein phosphorylation and dephosphorylation processes that regulate GA signaling in plants are generally mediated by the proteasome-dependent destabilization of DELLA protein repressors, which modulate the response to endogenous gibberellins. Leaf elongation in seedlings that relies on the gibberellin pathway is governed by the proteasome-mediated derepression of DELLA [##REF##12468736##53##]. <italic>LlDELLA1</italic> facilitates flower and pod development in <italic>Lupinus luteus</italic>. Its expression level slightly declines from the flower bud stage to anther opening, but rapidly elevates during pollination, fertilization, podding, and early grain development [##REF##32155757##54##]. <italic>LISCL</italic> is implicated in the meiosis of pollen and facilitates the formation of microspores in <italic>L. longiflorum</italic> [##REF##12657631##55##]. HAM family members from various flowering plants sustain the indeterminacy of shoot meristem and facilitate the formation of re-axillary meristem [##REF##12208843##45##, ##REF##21173022##56##–##UREF##7##59##]. The loss-of-function of <italic>HAM</italic> leads to a defect in shoot apical meristem in <italic>Capsicum annuum</italic> [##REF##23415323##58##]. <italic>PhHAM</italic> is specifically expressed in the vascular tissue of stem primordia in petunia, which plays a vital role in sustaining the activity of inter shoot apical meristem [##UREF##7##59##]. In <italic>Arabidopsis</italic>, DELLAs, SCL3, and IDDs constitute a “co-activator/co-repressor exchange regulation system” to fine-tune the feedback regulation of gibberellin [##REF##25763707##60##]. Through the interactions and transcriptional networks among these proteins, they partake in various signaling pathways and physiological events in multiple aspects. DLT, OSH1, and OsOFP19 form functional complexes that play a pivotal role in brassinolide signaling and determining cell division patterns during plant growth and grain development in rice [##REF##29205590##61##]. <italic>OsMOC1</italic> is one of the key factors in determining the number of tillers in rice, which is essential for axillary meristem (AM) formation and bud growth [##REF##12687001##62##]. Furthermore, salt, ultraviolet radiation, flooding, drought, and extreme temperatures can inflict irreversible damage to crop growth and development, ultimately impeding growth and diminishing yield [##REF##34561623##63##]. Some studies have demonstrated that <italic>GRAS</italic> genes play a crucial regulatory role in plant responses to stress. <italic>NtGRAS1</italic> partakes in the phosphorylation process of reactive oxygen species and nitric oxide stress induction in cells, thereby regulating the homeostasis of nutrient distribution within cells [##REF##17007961##64##]. <italic>PeSCL7</italic> is induced by drought and salt stress, which is repressed by gibberellic acid (GA) in poplar. The transgenic <italic>Arabidopsis</italic> plants over-expressing <italic>PeSCL7</italic> exhibited enhanced tolerance to drought and salt treatment due to the increased activity of superoxide dismutase (SOD) and α-amylase (FAA) [##REF##20616154##65##]. Compared with wild-type plants, <italic>OsGRAS23</italic>-overexpressing rice plants showed improved drought resistance and oxidative stress tolerance [##UREF##8##66##].</p>", "<p id=\"Par7\">Rye (<italic>Secale cereale</italic> L.) is a member of the <italic>Secale</italic> genus in the Poaceae family and contains various nutrients for human consumption, including starch, vitamins, dietary fiber, protein, mineral elements, and phenolic compounds [##REF##33737754##67##]. Rye has multiple applications in food, feed, bioenergy and alcohol production industries [##REF##34865784##68##, ##REF##23414336##69##] and exhibits probiotic activity that can lower the risk of cardiovascular and obesity diseases [##REF##35458231##70##–##REF##21411613##72##]. Rye is also a highly resilient crop that can withstand low temperatures, droughts, and poor soils [##UREF##9##73##]. As a diploid species in the Triticeae Dumortier, rye is of significant importance and closely related to barley and wheat [##REF##27888547##74##]. Therefore, systematic gene mining and functional characterization of rye are essential for elucidating the physiological functions, evolutionary relationships, and genetic improvement of gramineous crops. In this study, we performed a comprehensive analysis of the ScGRAS family based on the recently published whole genome sequences of rye [##REF##33737755##75##]. 67 GRAS genes were identified in <italic>S. cereale</italic> and assigned them to thirteen subfamilies. Further analysis was conducted on their gene structures, motif compositions, duplications, chromosome distributions, and phylogenetic relationships. We also characterized the expression patterns of selected <italic>ScGRAS</italic> members in different tissues and grain development stages, as well as under different stress and hormone induction. In addition, we investigated the paclobutrazol significantly reduced the plant height of rye, and promoted increase the weight of grains. Paclobutrazol may affect the filling process through the gibberellin pathway in rye.</p>" ]
[ "<title>Methods</title>", "<title>Gene identification</title>", "<p id=\"Par40\">The reference genome of rye was downloaded from the GenBank website of the National Center for Biotechnology Information, the accessed number was JADQCU000000000 [##REF##33737755##108##]. Firstly, all of GRAS proteins of <italic>Arabidopsis</italic> and rice were used to search for candidate GRAS proteins from the rye genome via the blastp program [##REF##9254694##109##]. Candidate genes were searched by blastp using a score value of ≥ 100 and e-value ≤ e − 10. Secondly, the Hidden Markov Model (HMM) file of the GRAS domain (PF03514) is downloaded from the Pfam protein family database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://pfam.sanger.ac.uk/\">http://pfam.sanger.ac.uk/</ext-link>). Based on the HMM model in the HMMER 3.0 online software, the GRAS protein sequence in <italic>S. cereale</italic> was identified with a decision value of 0.01 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://plants.ensembl.org/hmmer/index.html\">http://plants.ensembl.org/hmmer/index.html</ext-link>) [##UREF##12##110##]. Based on PFAM and SMART in thread sequencing, conserved motifs were found in the GRAS proteins in rye (<ext-link ext-link-type=\"uri\" xlink:href=\"http://smart.embl-heidelberg.de/\">http://smart.embl-heidelberg.de/</ext-link>) [##REF##10592242##111##, ##REF##29040681##112##]. Then, in the NCBI protein database, these ScGRAS proteins were used as the initial query for re-verification (<ext-link ext-link-type=\"uri\" xlink:href=\"https://blast.ncbi.nlm.nih.gov/Blast.cgi?\">https://blast.ncbi.nlm.nih.gov/Blast.cgi?</ext-link> PROGRAM = blastp&amp;PAGE_TYPE = BlastSearch&amp;LINK_LOC = blasthome). Finally, the ExPasy online program was used to identify the basic features of the <italic>GRAS</italic> genes in <italic>S. cereale</italic>, including sequence length, protein molecular weight, isoelectric points, and subcellular localization (<ext-link ext-link-type=\"uri\" xlink:href=\"http://web.expasy.org/protparam/\">http://web.expasy.org/protparam/</ext-link>). In addition, to further compare the similarity of these genes, we conducted pairwise sequence alignments on these proteins using the EMBOSS Need online website (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ebi.ac.uk/Tools/psa/emboss_needle/\">https://www.ebi.ac.uk/Tools/psa/emboss_needle/</ext-link>).</p>", "<title><italic>GRAS</italic> gene structures and conserved motif analysis</title>", "<p id=\"Par41\">Firstly, we conducted multiple sequence alignment projects on these GRAS proteins from rye to further analyze LHR I, VHIID, LHR II, PFYRE, and SAW domains within conserved domain intervals [##UREF##13##113##]. MEGA 7.0 and GeneDoc 2.7 software were used to manually adjust the conserved domain segments in the amino acid sequences of these GRAS proteins to elucidate their diversity and variability [##UREF##6##39##]. Specifically, these software tools were used for sequence alignment and manual modification of amino acid sequences to accurately identify conserved domains [##REF##17681935##114##]. Gene Structure Display Server online software was used to analyze the exon-intron substructures of these <italic>ScGRAS</italic> genes [##REF##34732123##37##]. Additionally, the MEME online program (<ext-link ext-link-type=\"uri\" xlink:href=\"http://meme.nbcr.net/\">http://meme.nbcr.net/</ext-link>) was used to analyze the conserved motifs and gene structure variations among these GRAS proteins [##UREF##14##115##]. The optimized parameters for the conserved motifs were as follows: a maximum of 10 motifs and the optimal width of residues ranging from 6 to 200 [##REF##34732123##37##]. Visualize Gene Structure is completed using TBtools software (v1.120) [##REF##32585190##116##]. Additionally, the PlantCARE online software was used to predict the physiological functions of cis-elements in the promoter regions (up-stream 2000 bp) of these 67 <italic>GRAS</italic> genes [##UREF##6##39##].</p>", "<title>Chromosomal distribution and gene duplication</title>", "<p id=\"Par42\">Firstly, based on the physical location of these genes in the annotation file, all <italic>ScGRAS</italic> genes have been designated as chromosomal details. Circos software was used to analyze these <italic>ScGRAS</italic> genes for chromosomal location information [##REF##19541911##117##]. The presence of two or more gene members from the same family within the 200 kb chromosome region is defined as the presence of tandem repeats [##REF##34732123##37##]. Multiple Collinear Scanning Toolkits (MCScanX) of TBtools software (v1.120) [##REF##32585190##116##] was used with default parameters to analyze gene duplication events for these <italic>GRAS</italic> genes [##UREF##12##110##]. Homology of the <italic>GRAS</italic> genes between <italic>S. cereale</italic> and six other plants (<italic>T. aestivum</italic>, <italic>A. tauschii</italic>, <italic>H. vulgare</italic>, <italic>O. sativa</italic> ssp. <italic>Indica</italic>, <italic>Z. mays</italic>, and <italic>A. thaliana</italic>) was analyzed by using the project of dual synteny plotter in TBtools software. To further analyze the possible selection pressure in the GRAS genes of rye [##REF##16140995##118##–##REF##31261768##120##], the Ka/Ks values of all gene pairs in different subfamilies were calculated using the Simple Ka/Ks Calculator (NG) program of TBtools.</p>", "<title>Phylogenetic analysis and classification of the <italic>ScGRAS</italic> family</title>", "<p id=\"Par43\">According to the classification of AtGRAS and OsGRAS proteins, 67 GRAS proteins in <italic>S. cereale</italic> are divided into 13 main subfamilies. In MEGA 7.0, the Jukes-Cantor model is used to construct NJ (neighbor-joining method) trees. Bootstrap value of the constructed phylogenetic tree was set to 1000, and assigned with Geneious R11 with BLOSUM62 cost matrix. To elucidate the evolutionary relationships between these GRAS proteins in several plants, the synteny maps based on homologous genes from rye and six representative plants were constructed. Five monocotyledonous plants were selected, containing three Triticeae Dumortier plants (<italic>T. aestivum</italic>, <italic>A. tauschii</italic>, <italic>H. vulgare</italic>), one model plant (<italic>O. sativa</italic>), and one C4 plant (<italic>Z. mays</italic>). Meanwhile, the dicotyledonous model plant (<italic>A. thaliana</italic>) was also included in the comparison, which was obtained from the UniProt website [##UREF##2##32##, ##UREF##3##33##].</p>", "<title>Plant materials, growth conditions, and abiotic stress in <italic>S. Cereale</italic></title>", "<p id=\"Par44\"><italic>S. cereale</italic> cv. <italic>Weining</italic>, a representative cultivated variety in Guizhou Province in southwest China was used. The cultivar was planted in a greenhouse at Chengdu University farm. At the early-ripening stage of rye, representative tissues were collected, including roots, stems, leaves, flowers, and grains. Additionally, to observe the expression levels of these representative genes in rye grain during the filling period, samples from five grain developmental stages were collected, i.e., 7 days (early-filling stage), 14 days (mid-filling stage), 21 days (early-ripening stage), 28 days (mid-ripening stage), and 35 days (full ripening stage). Many <italic>ScGRAS</italic> genes may be involved in the development of rye grains, thereby affecting the filling and nutritional structure of the grains. To determine these genes that may regulate the development of rye grains, the expression of these 19 <italic>ScGRAS</italic> members was evaluated during the five grain-filling stages after flowering. As far as possible, the selected members of different subfamilies exhibit significant differences in amino acid structures and distant clustering relationships. Except for the DELLA members, at least one member of different subfamilies was selected, depending on their topology and genetic structures. All the plants were grown under the same growth conditions, and these samples were collected from five plants. The collected samples were rapidly placed in liquid nitrogen and pre-cooled completely to fix their physiological status and stored at -80 °C until further use. Each sampling and stress treatment had three biological replicates. Meanwhile, these samples were performed by qRT-PCR with at least three technical repeats.</p>", "<p id=\"Par45\">The plant RNA extraction kit (RNA Easy Fast Plant Tissue RNA Rapid Extraction Kit, DP452) was selected for total RNA extraction. In addition, to investigate the expression patterns of these <italic>ScGRAS</italic> genes under different abiotic stresses and hormones, seedlings of rye were subjected to abiotic stress treatment at the seedling stage (4 weeks after germination). All seedlings were planted in seedling trays, and each tray was added with 50 mL of solution to fully soak the roots of the plants. The treatment for six different abiotic stresses were UV-A radiation (70 μW/cm<sup>2</sup>, 67 V, 30 W), flooding (all plants), salt (5% NaCl), drought (10% PEG6000), high temperature (40℃), and low temperature (4℃). Each stress treatment was repeated three times, and samples of leaves, roots, and stems were taken at 0, 1, 4, and 12 hours for qRT-PCR analysis. Finally, considering that there were different hormone response elements in the promoter region of these genes, we conducted three different hormone treatments at the flowering stage: gibberellic acid (GA<sub>3</sub>, 100μM), auxin (indole-3-acetic acid, IAA, 100μM), and abscisic acid (ABA, 50μM). Paclobutrazol, a plant growth regulator, participates in the expression of members of the <italic>GRAS</italic> gene family [##REF##34732123##37##, ##UREF##6##39##]. Therefore, it has also been considered as a candidate hormone. Whether there is a coordinated expression of these genes was observed. In addition, as a plant growth inhibitor, paclobutrazol regulates plant growth mainly by inhibiting biosynthesis of GAs by regulating DELLAs transcription [##REF##31387526##26##]. In order to further investigate the relationship between DELLAs, GAs and grain development in rye, the materials of ‘Weining’ with similar growth status were selected and sprayed with 50 mL paclobutrazol (250 mg·L<sup>− 1</sup>) and gibberellin (100 μM) during the flowering period. Controls (mock) were sprayed with the same amount of water. Further analysis was conducted on the plant height, 1000-grain weight, gibberellin content, and gene expression level of the DELLA subfamily in control, paclobutrazol, and gibberellin-treated plants at 7, 14, 21, 28, and 35 DPA (days post-anthesis).</p>", "<title>Endogenous GA analysis</title>", "<p id=\"Par46\">Regarding the method of Fan et al. [##REF##34732123##37##], the gibberellic acid (GA) content in rye grains was determined. Approximately 1 g of fresh tissue from the grain was collected and ground in liquid nitrogen. The ground powder was mixed with 50 mL of 80% ethanol and subjected to ultrasonic extraction three times for 1 h each time. Supernatant was concentrated at a low temperature, then mixed with water, and N-butanol was added to extract for 1 h. Finally, the n-butanol layer was dried under a stream of nitrogen (N<sub>2</sub>). Ten milligrams of the dried sample were accurately weighed and dissolved in 5 mL of methanol. The dissolved solution was filtered using a 0.22 μm microporous membrane, and LC / MS was used for content detection.</p>", "<title>Total RNA extraction, cDNA reverse transcription, and qRT-PCR analysis</title>", "<p id=\"Par47\">Fresh tissues of rye were extracted using a plant RNA extraction kit (RNA Easy Fast Plant Tissue RNA Rapid Extraction Kit, DP452) for total RNA extraction. Based on the primer sequences designed in Primer 5.0 software, the expression levels of different <italic>GRAS</italic> genes were detected (Table ##SUPPL##14##S15##). <italic>ACTIN</italic> as an internal reference gene [##REF##36509294##121##]. SYBR Premix ExTaqII (TaKaRa Bio) was used for standard expression detection, and experiments were performed with three replicates on a CFX96 real-time system (Bio-Rad). Real-time qPCR reaction included 40 cycles with parameter settings as follows: pre-denaturation at 95 ℃ for 30 s, denaturation at 95 ℃ for 5 s, annealing at 60 ℃ for 20 s, and extension at 72 ℃ for 20 s. All quantitative primers for genes were analyzed for their practicality through melting curves. The expression of these <italic>GRAS</italic> genes was analyzed using the 2<sup>− (ΔΔCt)</sup> method [##REF##11846609##122##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par48\">The least significant difference test (LSD) is further conducted using 0.05 and 0.01 significance levels to compare the means between the groups in JMP6.0 software (SAS Institute). Origin 2016 software (OriginLab Corporation, Northampton, Massachusetts, USA) has been employed to draw the histograms. Additionally, the Pearson correlation program was used to define the correlation coefficient of <italic>ScGRAS</italic> genes, and Sigmaplot 12.0 software (Systat Software, Inc, Point Richmond, CA) is utilized to calculate the correlation coefficient. A Pearson correlation matrix of the <italic>GRAS</italic> genes is generated using R2.11 (Bell Laboratories), and network analysis (CNA) of the correlation matrix is performed with the help of Cytoscape 2.7.0 software [##REF##14597658##123##]. The correlation coefficient is defined as statistically significant at a <italic>P</italic>-value of less than 0.05.</p>" ]
[ "<title>Results</title>", "<title>Identification of <italic>GRAS</italic> genes in <italic>S. Cereale</italic></title>", "<p id=\"Par8\">Based on their position on the rye chromosome, these GRAS members have been renamed <italic>ScGRAS1</italic> to <italic>ScGRAS67</italic> (Table ##SUPPL##0##S1##). Their basic features including gene coding sequence (CDS), protein molecular weight (MW), isoelectric point (PI), and subcellular localization are systematically analyzed. Of the 67 ScGRAS proteins, ScGRAS57 was the smallest with 395 amino acids. The largest was ScGRAS50 with 1453 amino acids. Molecular weight of the proteins ranged from 41.47 kDa (ScGRAS57) to 163.58 kDa (ScGRAS50). The pI ranged from 4.75 (ScGRAS28) to 10.56 (ScGRAS14), with a median of 5.98. All the putative proteins encoded by the ScGRAS genes, contained the GRAS domain, which is necessary for their function as transcription factors. Based on the predicted subcellular localization, 28 ScGRASs were located in the nucleus, 16 in the chloroplast, 29 in the cytoplasmic, three (<italic>ScGRAS33</italic>, <italic>ScGRAS44</italic>, and <italic>ScGRAS47</italic>) in the mitochondria, two (<italic>ScGRAS35</italic>, and <italic>ScGRAS59</italic>) in the endoplasmic reticulum, two (<italic>ScGRAS3</italic>, and <italic>ScGRAS41</italic>) in the peroxisome (Table ##SUPPL##0##S1##).</p>", "<title>Phylogenetic analysis, and multiple sequence alignment of ScGRAS putative proteins</title>", "<p id=\"Par9\">We constructed a phylogenetic tree encompassing <italic>S. cereale</italic> (67 ScGRASs), <italic>A. thaliana</italic> (33 AtGRASs), and <italic>O. sativa</italic> (46 OsGRASs) through the neighbor-joining method (Fig. ##FIG##0##1##, Table ##SUPPL##0##S1##). Following the classification methodology proposed by Cenci et al. [##REF##28303145##7##] and Tian et al. [##REF##15316287##34##], the 146 GRAS proteins were categorized into thirteen distinct topological branches. Notably, LISCL exhibited the largest number of members (18 ScGRAS proteins), while OS43 (ScGRAS5), SCL4/7 (ScGRAS30), and DLT (ScGRAS44) possessed the fewest representatives (solely one ScGRAS protein each). The topology tree reveals a remarkable genetic affinity between certain ScGRAS proteins and numerous AtGRAS and OsGRAS proteins (bootstrap support ≥ 70), exemplified by ScGRAS5, ScGRAS8, and ScGRAS58. This suggests that these homologous proteins may share comparable gene structures and physiological functionalities.</p>", "<p id=\"Par10\">\n\n</p>", "<p id=\"Par11\">To elucidate the conserved amino acid residues within different subfamilies, a subset of AtGRASs, OsGRASs, and ScGRASs from 13 distinct subfamilies were randomly chosen for comprehensive multi-sequence comparisons (Figure ##SUPPL##15##S1##, Table ##SUPPL##0##S1##). The intricate conserved domains, namely LHR I, VHIID, LHR II, PFYRE, and SAW, displayed remarkable complexity among various subfamily members of rye GRAS proteins. The diversity inherent in these amino acids contributes to structural and functional divergences. Notably, the VHIID domain serves as the pivotal region for functionality, exhibiting highly similar amino acid configurations that are readily identifiable across different species. With the exception of GRAS33, GRAS34, GRAS35, and GRAS43, the conservation of His and Asp residues within the VHIID domain remained consistent. Additionally, certain non-polar hydrophobic amino acid residues exhibited potential cross-substitution, hypothesized to have minimal impact on peptide formation. It is worth to named select GRAS members demonstrated alternating residues, oscillating between Ile and Val within the VHLLD region. An observation worth noting is the presence of a highly disordered region at the N-terminus of ScGRAS proteins, showcasing discernible similarities across different subfamilies.</p>", "<title>Gene structures, conserved motifs, and cis-acting elements analysis of <italic>ScGRAS</italic> genes</title>", "<p id=\"Par12\">A comparative analysis of exon-intron structures reveals variations in the number and sequencing among the 67 <italic>ScGRAS</italic> genes, ranging from 1 to 5 exons (Fig. ##FIG##1##2##A and B, Tables ##SUPPL##0##S1##). All <italic>ScGRAS</italic> genes contain the GRAS domain, with the majority (40, ~ 59.70%) lacking introns. Fifteen <italic>ScGRAS</italic> genes have one intron, while <italic>ScGRAS5</italic>, <italic>ScGRAS33</italic>, <italic>ScGRAS50</italic>, <italic>ScGRAS56</italic>, and <italic>ScGRAS63</italic> possess two introns. <italic>ScGRAS23</italic>, <italic>ScGRAS43</italic>, and <italic>ScGRAS67</italic> have up to four introns. Genes without introns exhibit compact structures and are widely distributed across all subfamilies, except for the Os43 subfamily, primarily in the LISCL subfamily. The DLT, LAS, DELLA, OS4, OS19, SCL4/7, SHR, and SCR subfamilies either lack introns or contain only one. PAT1 shows greater diversity in the number of exons, with five distinct exon types. Additionally, members within the same subfamily share similar gene structures, albeit with inconsistent exon and intron distributions.</p>", "<p id=\"Par13\">\n\n</p>", "<p id=\"Par14\">The motif analysis of the 67 ScGRAS proteins using MEME online software revealed ten conserved motifs (Fig. ##FIG##1##2##C, Table ##SUPPL##1##S2## ~ S4). These motifs exhibited varying distribution patterns among ScGRASs, with motifs 2, 3, and 4 being widespread, except in ScGRAS2, ScGRAS15, and ScGRAS43. Motifs 10, 6, 5, and 2 were often located in close proximity across most members. Generally, ScGRAS members within the same subfamily displayed similar motif compositions. The motifs 10, 6, 5, 2, 7, 3, and 4 were present in the DLT, LAS, LISCL, OS4, OS43, SCR, and SHR subfamilies. The DELLA, DLT, LISCL, OS4, OS43, SCL3, and SCR subfamilies shared motifs 3, 1, and 4. Certain subfamilies may lack specific motif compositions, such as the absence of motifs 8 and 9 in the Os19 subfamily. Additionally, specific motifs consistently occupy particular positions within the structures of these ScGRAS proteins. Motifs 10 and 6 consistently appear at the N-terminus of proteins in subfamilies DELLA, DLT, LAS, OS4, OS43, SCL3, SCL4/7, SCR, and SHR. Motif 2 is predominantly located at the beginning of OS19. Motif 4 is usually found near the C-terminus. Overall, the motif arrangement is generally similar within members of the same subfamily, supporting the classification observed in the phylogenetic trees. We further analyzed the conservation of specific amino acids in these motifs. Overall, some conserved amino acid sites have been identified (Figure ##SUPPL##15##S2##, Table ##SUPPL##2##S3##).</p>", "<p id=\"Par15\">A total of 107 cis-regulatory elements, encompassing 46 distinct physiological functions, were identified (Table ##SUPPL##4##S5##). These elements were classified into eight categories: development-related, light-responsive, site-binding, environmental stress-responsive, promoter-related, hormone-responsive, wound-responsive, and other elements. Among the promoter elements, light-responsive elements accounted for the largest proportion, including 25 cis-regulatory factors. Promoter-related elements, such as the TATA-box, were present in all <italic>ScGRAS</italic> genes. Sixteen hormone-responsive elements were identified, including those responsive to abscisic acid (AAGAA-motif, ABRE related), auxin (AuxRR-core, TGA-element, AuxRE, TGA-box), gibberellin (P-box, GARE-motif, TATC-box), MeJA (TGACG-motif, CGTCA-motif), and salicylic acid (TCA-element). Moreover, several cis-regulatory elements associated with anaerobic induction, drought, fungal elicitors, anoxic-specific inducibility, low-temperature, defense responses, and stress responsiveness were also discovered. Abscisic acid-responsive elements were present in nearly 98.51% of <italic>ScGRAS</italic> genes, while gibberellin-responsive elements existed in 61.19% of members, and auxin-responsive elements were found in approximately 44.78%. Twelve cis-acting elements were involved in the regulatory processes of different tissues (meristem, endosperm, root, leaf, and seed) during development in <italic>S. cereale</italic>. Consequently, <italic>ScGRAS</italic> genes are implicated not only in tissue development but also in responses to various abiotic stresses. It is worth pointing out that we have found that some cis acting elements may be unique to certain subfamilies. TGA-box was found to exist only in the DELLA subfamily (<italic>ScGRAS60</italic> / <italic>ScGRAS61</italic>), which is an auxin responsive element, suggesting that the physiological functions of members of the DELLA subfamily may be complex. GATT-motif is only found in the HAM subfamily, which is a part of a light responsive element.</p>", "<title>Chromosomal spread and gene duplication of <italic>ScGRAS</italic> genes</title>", "<p id=\"Par16\">The 65 <italic>ScGRAS</italic> genes are unevenly distributed across chromosomes 1R to 7R (Fig. ##FIG##2##3##, Table ##SUPPL##5##S6##). Additionally, two <italic>ScGRAS</italic> genes (<italic>ScGRAS66</italic> and <italic>ScGRAS67</italic>) were located on unassigned chromosomes (Un) Chromosome 2R contained the highest number of <italic>ScGRAS</italic> genes (18 genes, ~ 26.87%), followed by 4R (17 genes, ~ 25.37%). The lowest numbers were observed on 1R and 7R (4 genes, ~ 5.97%). Chromosomes 6R, 3R, and 5R harbored 5 (~ 7.46%), 6 (~ 8.96%), and 11 (~ 16.42%) <italic>ScGRAS</italic> genes, respectively. Nine gene duplication events were detected within the <italic>GRAS</italic> gene family in <italic>S. cereale</italic>. Tandem repeat events were observed on chromosomes 2R, 3R, 4R, and 6R, particularly in <italic>ScGRAS36</italic>, <italic>ScGRAS37</italic>, <italic>ScGRAS38</italic>, and <italic>ScGRAS39</italic>. A region enriched with tandem repeats was identified, encompassing genes <italic>ScGRAS35</italic> to <italic>ScGRAS40</italic>, all belonging to the LISCL subfamily. Three pairs of segmental duplications involving <italic>ScGRAS</italic> genes were detected (Fig. ##FIG##3##4##, Table ##SUPPL##7##S8##). Five collateral homologs were identified in <italic>ScGRAS</italic> genes, accounting for 8.96% of the total, suggesting that these genes may have originated from segmental expansion events. In general, the typical domain of <italic>GRAS</italic> family is a VHIID motif flanked by two Leucine rich regions. The ‘VHIID’ motif represents several important amino acids. However, the core regions of these proteins are replaced by ‘LHIVD’. Except for ScGRAS35, the SAW motifs of other members are composed of three conserved amino acid residues: R (x4) E, W (x7) G, and W (x10) W structures. ScGRAS37/SCGRAS38 (86.2%) and ScGRAS39/SCGRAS40 (85.7%) had high similarity (Table ##SUPPL##6##S7##). Chromosome 4R contained the most <italic>ScGRAS</italic> members (n = 3). In contrast to tandem duplication, two homologous expansion events involving four genes (<italic>ScGRAS32</italic> / <italic>ScGRAS47</italic>, and <italic>ScGRAS33</italic> / <italic>ScGRAS49</italic>) were discovered. These segmental duplications primarily involved the SCR and SCL3 subfamilies, while other groups exhibited greater conservation during evolution.</p>", "<p id=\"Par17\">\n\n</p>", "<p id=\"Par18\">\n\n</p>", "<title>Synteny analysis of <italic>ScGRAS</italic> genes</title>", "<p id=\"Par19\">A total of 52 <italic>ScGRAS</italic> genes showed homologous relationships with genes in <italic>A. thaliana</italic> (n = 3), <italic>O. sativa</italic> (n = 30), <italic>Z. mays</italic> (n = 34), <italic>Aegilops tauschii</italic> (n = 39), <italic>H. vulgare</italic> (n = 35), and <italic>T. aestivum</italic> (n = 49) (Fig. ##FIG##4##5##, Table ##SUPPL##8##S9##). The number of collinear gene pairs between rye and other representative species (<italic>A. thaliana</italic>, <italic>O. sativa</italic>, <italic>Z. mays</italic>, <italic>A. tauschii</italic>, <italic>T. aestivum</italic>, and <italic>H. vulgare</italic>) were 4, 42, 54, 49, 42, and 137, respectively. Rye exhibited a relatively high proportion of <italic>GRAS</italic> gene orthologous pairs with <italic>A. tauschii</italic> and <italic>H. vulgare</italic>, accounting for 79.59% and 83.33%, respectively. Some homologous gene pairs between rye and Triticeae Dumortier plants were not identified in <italic>A. thaliana</italic>, <italic>O. sativa</italic>, and <italic>Z. mays</italic>. For example, <italic>ScGRAS5</italic> had homologs <italic>AET1Gv20229700</italic> / <italic>ARI1A01G110900</italic> / <italic>HORVU1Hr1G020370</italic>, indicating possible expansion events specific to Triticeae Dumortier plants that differ from dicotyledonous plants like <italic>Arabidopsis</italic> and other monocotyledonous plants. Moreover, collateral homologous pairs were observed among dicotyledonous and monocotyledonous plants, with genes such as <italic>ScGRAS25</italic>, <italic>ScGRAS46</italic>, and <italic>ScGRAS64</italic> suggesting ancestral origins before plant differentiation. Tajima-D neutrality testing was conducted on the 67 <italic>ScGRAS</italic> genes to better understand their targeted or balanced selection. The D value obtained was 7.49 (Table ##SUPPL##9##S10##), significantly deviating from zero, indicating the involvement of the <italic>ScGRAS</italic> gene family in evolutionary neutral selection. Furthermore, we evaluated the Ka/Ks values within these subfamilies. This calculation will help estimate the selection pressure acting on these duplicated genes, advancing insights into three categories of selection: purifying, positive, and neutral. The results showed that most genes were subjected to purification selection (Table ##SUPPL##10##S11##). This result also exists in most genes involved in repetitive events.</p>", "<p id=\"Par20\">\n\n</p>", "<title>Evolutionary analysis of <italic>ScGRAS</italic> and <italic>GRAS</italic> genes of several different species</title>", "<p id=\"Par21\">To analyze the genetic relationship between GRAS proteins in rye and six representative plants (<italic>A. thaliana</italic>, <italic>O. sativa</italic>, <italic>Z. mays</italic>, <italic>A. tauschii</italic>, <italic>T. aestivum</italic>, and <italic>H. vulgare</italic>), an unrooted NJ tree was constructed. Ten conserved motifs were identified in the sequences of 601 GRAS proteins from these plants using MEME online service software (Fig. ##FIG##5##6## and ##SUPPL##15##S3##, Table ##SUPPL##1##S2## ~ S4). Detailed genetic correspondences are provided in Tables ##SUPPL##0##S1## and ##SUPPL##1##S2##. ScGRAS proteins tend to cluster with GRAS members of <italic>A. tauschii</italic>, <italic>T. aestivum</italic>, and <italic>H. vulgare</italic>. With a few exceptions such as ScGRAS14, ScGRAS16, ScGRAS43, and ScGRAS67, all other ScGRAS proteins contain motifs 2 and 3. The arrangements and structures of certain motifs exhibit specificity, differentiating genes from various subfamilies and forming distinct topological patterns. Motifs 1, 8, and 9 are absent in the subfamilies HAM and LAS. Members of the subfamily OS19 (ScGRAS14, ScGRAS15, and ScGRAS16) lack motifs 1, 7, 8, and 9. Overall, GRAS genes from Triticeae Dumortier plants and <italic>S. cereale</italic> that occupy the same topological branches share similar motif arrangements. Specific GRAS protein subfamilies in these plants often possess analogous motifs, indicating their evolutionary relationship. Motifs 8, 4, and 5 form a conserved structure and tend to cluster within the HAM and LAS subfamilies, while motifs 3, 7, 9, 8, 4, 1, and 5 tend to aggregate within the subfamilies DELLA, DLT, LISCL, OS4, OS43, PAT1, and SCL4/7.</p>", "<p id=\"Par22\">\n\n</p>", "<title>Expression patterns of <italic>ScGRAS</italic>s in several plant organs</title>", "<p id=\"Par23\">To investigate the physiological functions of <italic>GRAS</italic> genes in rye, real-time PCR was employed to detect the expression levels of 19 members during the 21 DPA (days post-anthesis) of rye grains. Transcript accumulation in five organs (leaves, stems, roots, flowers, and grains) was assessed (Fig. ##FIG##6##7##A). Most <italic>ScGRAS</italic> members exhibited preferential expression in specific tissues. The highest expression was observed in roots for seven genes (<italic>ScGRAS8</italic>, <italic>ScGRAS18</italic>, <italic>ScGRAS24</italic>, <italic>ScGRAS25</italic>, <italic>ScGRAS60</italic>, <italic>ScGRA61</italic>, and <italic>ScGRAS65</italic>), in stems for five genes (<italic>ScGRAS15</italic>, <italic>ScGRAS46</italic>, <italic>ScGRAS47</italic>, <italic>ScGRAS48</italic>, and <italic>ScGRAS61</italic>), in leaves for two genes (<italic>ScGRAS29</italic> and <italic>ScGRAS61</italic>), in flowers for two genes (<italic>ScGRAS5</italic> and <italic>ScGRAS27</italic>), and in grains for eight genes (<italic>ScGRAS6</italic>, <italic>ScGRAS8</italic>, <italic>ScGRAS30</italic>, <italic>ScGRAS32</italic>, <italic>ScGRAS44</italic>, <italic>ScGRAS47</italic>, <italic>ScGRAS64</italic>, and <italic>ScGRAS65</italic>).</p>", "<p id=\"Par24\">\n\n</p>", "<p id=\"Par25\">Expression levels of most <italic>ScGRAS</italic> genes varied significantly at different stages of grain development. In general, gene expression was higher before the early ripening stage (21 DPA) compared to the mid-full filling stages. Nine genes (<italic>ScGRAS5</italic>, <italic>ScGRAS8</italic>, <italic>ScGRAS15</italic>, <italic>ScGRAS18</italic>, <italic>ScGRAS25</italic>, <italic>ScGRAS29</italic>, <italic>ScGRAS44</italic>, <italic>ScGRAS47</italic>) exhibited highest expression at 7 DPA, while four genes (<italic>ScGRAS24, ScGRAS25</italic>, <italic>ScGRAS32</italic>, and <italic>ScGRAS46</italic>) highest expression at 21 DPA (Fig. ##FIG##6##7##B). Except for <italic>ScGRAS30</italic>, <italic>ScGRAS48</italic>, and <italic>ScGRAS60</italic>, most genes exhibited stable expression levels in grains, with the lowest expression generally observed during the fully ripened stage (35 DPA).</p>", "<p id=\"Par26\">Furthermore, certain <italic>ScGRAS</italic> members displayed coordinated expression patterns across multiple plant organs. The expression levels of some <italic>GRAS</italic> members exhibited significant positive correlations. For example, <italic>ScGRAS6</italic>, <italic>ScGRAS8</italic>, <italic>ScGRAS30</italic>, <italic>ScGRAS32</italic>, <italic>ScGRAS44</italic>, <italic>ScGRAS64</italic>, and <italic>ScGRAS65</italic> were co-expressed in various plant organs (Figure ##SUPPL##15##S4##), while <italic>ScGRAS5</italic>, <italic>ScGRAS8</italic>, <italic>ScGRAS15</italic>, <italic>ScGRAS18</italic>, <italic>ScGRAS29</italic>, <italic>ScGRAS30</italic>, <italic>ScGRAS44</italic>, <italic>ScGRAS47</italic>, and <italic>ScGRAS64</italic> were co-expressed in grains (Figure ##SUPPL##15##S5##). Notably, within the DELLA subfamily, the expression levels of <italic>ScGRAS24</italic>, <italic>ScGRAS29</italic>, and <italic>ScGRAS60</italic> exhibited a significant positive correlation in different tissues.</p>", "<title>Effects of grain developments and expression of DELLA subfamily genes after paclobutrazol and gibberellin treatments</title>", "<p id=\"Par27\">Compared to the control (Mock), plant height in rye significantly decreased with paclobutrazol treatment, while grain filling was promoted (Fig. ##FIG##7##8##A). This effect was particularly noticeable during the later stages of grain development. As the grain-filling process advanced, endogenous gibberellin content gradually decreased in all groups, including the treatment and control groups. The gibberellin content in the paclobutrazol treatment group exhibited a rapid decline at 14 DPA and 21 DPA, stabilizing thereafter at 35 DPA. Interestingly, plant height in rye significantly increased during gibberellin treatment, particularly during the middle and late stages of grain filling, while the 1000-grain weight significantly decreased. These findings suggest that paclobutrazol primarily influences the filling process through the gibberellin pathway in rye.</p>", "<p id=\"Par28\">\n\n</p>", "<p id=\"Par29\">Exogenous paclobutrazol and gibberellin treatments significantly influenced the expression of DELLA subfamily genes in rye (Fig. ##FIG##7##8##B). Expression levels of <italic>ScGRAS24</italic>, <italic>ScGRAS60</italic>, and <italic>ScGRAS61</italic> demonstrated an initial increase followed by gradual decline, reaching their lowest values at 35 DPA. <italic>ScGRAS29</italic>, on the other hand, exhibited a steady decrease in expression. Moreover, most DELLA members showed significant down-regulation during the filling period following gibberellin treatment, indicating a potential antagonistic relationship. The expression of <italic>ScGRAS24</italic> remained unchanged in the early stages of grain filling, highest expression at 28 DPA in the paclobutrazol treatment, suggesting its potential role in later filling stages. <italic>ScGRAS61</italic> expression significantly increased at 7 DPA, reaching its highest expression at 14 DPA. Interestingly, <italic>ScGRAS60</italic> expression was significantly up-regulated in nearly all induction treatments, indicating its sensitivity to paclobutrazol.</p>", "<title>Expression patterns of <italic>ScGRAS</italic> genes in response to different treatments</title>", "<p id=\"Par30\">Numerous <italic>ScGRAS</italic> members exhibited significant up-regulation or inhibition under various stress conditions due to specific treatments (Figure ##SUPPL##15##S6##). The expression of <italic>ScGRAS6</italic> and <italic>ScGRAS24</italic> significantly increased in roots, stems, and leaves after one hour of cold stress. The expression of certain <italic>GRAS</italic> genes displayed dynamic patterns, with differential expression levels observed across organs or treatment durations. <italic>ScGRAS6</italic>, <italic>ScGRAS24</italic>, and <italic>ScGRAS60</italic> were significantly up-regulated and subsequently down-regulated under heat stress. <italic>ScGRAS5</italic> expression gradually increased in roots while decreasing in stems and leaves. Many <italic>ScGRAS</italic> genes showed contrasting expression patterns under different stress treatments. The expression of <italic>ScGRAS6</italic>, <italic>ScGRAS8</italic>, and <italic>ScGRAS24</italic> was significantly up-regulated initially and then down-regulated in stems following UV-A, flooding, and heat treatments. Other genes exhibited distinct characteristics within specific tissues and exposure times. <italic>ScGRAS47</italic> displayed significant responses to cold and NaCl treatments in roots and stems but exhibited no change in leaves. The correlations between the expression patterns of <italic>ScGRAS</italic> genes were observed (Figure ##SUPPL##15##S7##). Most <italic>ScGRAS</italic> genes exhibited negative correlations, although certain genes demonstrated significant positive correlations, such as <italic>ScGRAS5</italic>, <italic>ScGRAS6</italic>, <italic>ScGRAS25</italic>, and <italic>ScGRAS47</italic> (<italic>P</italic> &lt; 0.05).</p>", "<p id=\"Par31\">Expression patterns of <italic>GRAS</italic> members during different stages of grain development were analyzed under various treatments. All genes containing corresponding hormone-responsive elements in their promoter regions were detected (Figure ##SUPPL##15##S8##, Table ##SUPPL##11##S12##). Based on significant correlation connections used to construct a network, it becomes evident that the expression of some genes may be synergistic. Positive co-expression was observed among <italic>ScGRAS8</italic>, <italic>ScGRAS15</italic>, <italic>ScGRAS18</italic>, <italic>ScGRAS27</italic>, <italic>ScGRAS46</italic>, <italic>ScGRAS64</italic>, and <italic>ScGRAS65</italic> under abscisic acid induction. Similarly, <italic>ScGRAS6</italic>, <italic>ScGRAS27</italic>, <italic>ScGRAS30</italic>, <italic>ScGRAS32</italic>, <italic>ScGRAS61</italic>, and <italic>ScGRAS64</italic> showed positive co-expression under auxin induction. The expression patterns of DELLA family members did not consistently align with gibberellin and paclobutrazol induction, suggesting diverse functions. Although some co-expressed genes might interact, such as <italic>ScGRAS65</italic> exhibiting positive correlation with <italic>ScGRAS24</italic>, <italic>ScGRAS29</italic>, and <italic>ScGRAS61</italic> under gibberellin induction, these results underscore the complexity of physiological functions within different subfamilies of the <italic>GRAS</italic> family.</p>" ]
[ "<title>Discussion</title>", "<title><italic>ScGRAS</italic> gene structures and evolutionary analyses</title>", "<p id=\"Par32\">The GRAS proteins in rye exhibit considerable structural diversity, particularly among the thirteen subfamilies, indicating that the physiological function of the GRAS gene family in rye is complex (Fig. ##FIG##0##1## and ##SUPPL##15##S1##, Table ##SUPPL##0##S1##). The proportion of GRAS genes in the rye genome is approximately 0.15%, which is lower than that in other plants such as <italic>G. max</italic> (0.21%) [##REF##32891114##27##], <italic>V. vinifera</italic> (0.17%) [##REF##27065316##41##], <italic>H. vulgare</italic> (0.16%) [##REF##32423019##28##], <italic>S. italica</italic> (0.16%) [##REF##34732123##37##], <italic>S. bicolor</italic> (0.24%) [##UREF##6##39##], <italic>T. aestivum</italic> (0.17%) [##REF##33665016##40##], <italic>Z. mays</italic> (0.22%) [##REF##28957440##42##], but higher than that in <italic>A. thaliana</italic> (0.11%) [##REF##18500650##19##]. Within the <italic>GRAS</italic> gene family of rye, there are thirteen subfamilies, including DELLA, DLT, HAM, LISCL, LAS, SCL3, SCL4/7, SCR, SHR, PAT1, OS4, OS43, and OS19 (Fig. ##FIG##0##1##, Table ##SUPPL##0##S1##). It is speculated that these thirteen subfamilies may be present in most Gramineae plants and have fundamental physiological functions that are conserved throughout evolution [##REF##15316287##34##]. Furthermore, the classification of the GRAS gene family may have become fixed in early higher plants and remained unchanged during plant evolution. However, the ancestral proteins within this family may continue to evolve, resulting in expansion and the emergence of new physiological functions in subsequent plant generations, depending on the specific plant species and environmental conditions [##REF##15316287##34##]. These certain ScGRAS proteins (ScGRAS5, ScGRAS14, ScGRAS15, ScGRAS16, ScGRAS26, and ScGRAS27) have been classified into rice-specific subfamilies, indicating that the GRAS family may undergo further differentiation in monocotyledonous plants. Among the subfamilies, LISCL have the highest number of members (18, ~ 26.87%), while OS43 (ScGRAS5), SCL4/7 (ScGRAS30), and DLT (ScGRAS44) have the fewest members. Similarly to other plants such as <italic>Arabidopsis</italic> [##REF##18500650##19##], rice [##REF##15316287##34##], <italic>S. italica</italic> [##REF##34732123##37##], <italic>S. bicolor</italic> [##UREF##6##39##], <italic>T. aestivum</italic> [##REF##33665016##40##], and <italic>Z. mays</italic> [##REF##28957440##42##], many subfamilies within the GRAS gene family of rye are likely to be conserved, whereas LISCL may exhibit greater differentiation ability. The differences in expansion among these subfamilies are speculated to be associated with the physiological functions of different proteins and their adaptation to the environment during evolution. However, more research is needed to determine whether the structural differences among these subfamilies are related to environmental adaptation. To further analyze the <italic>GRAS</italic> gene family in rye from different sources, we identified another important rye genome (Lo7) [##REF##33737754##67##]. A total of 72 independent GRAS proteins were identified in the ‘Lo7’. Similarly, these genes were primarily classified into 13 typical subfamilies (Figure ##SUPPL##15##S9##, Table ##SUPPL##0##S1##3). The GRAS proteins of ‘Weining’ was used to co construct the evolutionary tree, which was consistent with our original classification. To explain the differences and homology among these members, we constructed a comparative genome in the two rye (Figure ##SUPPL##15##S10##, Table ##SUPPL##0##S1##4). Most genes were assigned to the corresponding chromosomes (1R ~ 7R), indicating the overall reliability of the results. However, we observed that there are still some genes that have not been defined as corresponding homologues. We speculate that this may be a difference in genome assembly.</p>", "<p id=\"Par33\">Most of these GRAS genes in rye contain conserved domains, including LHR I, VHIID, LHR II, PFYRE, and SAW. As shown in Figure ##SUPPL##15##S1##, the VHIID domain is considered the central region and contains highly conserved histidine and aspartic acid residues, which serve as the base and supporting sites of GRAS proteins [##REF##32471952##76##–##REF##26081041##78##]. There may be cross-substitution of non-polar hydrophobic amino acid residues, such as histidine (His), leucine (Leu), isoleucine (Ile), and valine (Val), within the core region. These substitutions are likely the result of genetic mutations, although they may not significantly alter the peptide chain structure [##REF##23640422##79##]. Furthermore, some GRAS proteins belonging to the LISCL subfamily (ScGRAS34, ScGRAS35, and ScGRAS62) and PAT1 subfamily (ScGRAS43) do not contain conserved histidine and aspartic acid residues in the VHIID region. The structural differences of these genes may indicate further differentiation of GRAS proteins, as also observed in sorghum [##UREF##6##39##]. There are numerous variations in amino acid residues within the VHIID region of the LISCL and PAT1 subfamilies. It is speculated that the high activity of the LISCL and PAT1 subfamilies leads to structural differentiation in the domains, resulting in amino acid instability. This phenomenon may explain why these subfamilies have expanded and become the largest subfamily. Some conserved amino acid segments in the structural domain of ScGRAS43, the member of the PAT1 subfamily, have been lost, possibly due to chromosome fragment translocation or inversion [##REF##14760535##11##, ##REF##30691998##80##]. The acquisition and loss of structural domains are important driving forces for gene family expansion, as observed in other higher plants such as sorghum [##REF##34732123##37##] and maize [##REF##28957440##42##]. Inherently disordered regions, which can undergo conformational changes between order and disorder, are abundant in eukaryotic proteomes [##REF##34732123##37##, ##UREF##6##39##]. These functional regions, which contain short molecular recognition features (MORFs) in the N-terminal structural domain of GRAS proteins, play crucial roles in cell signal transduction and transcriptional regulation. Therefore, GRAS proteins possess functional specificity [##REF##22280012##16##]. Although the N-terminus of GRAS proteins exhibits high variability, some residues display similarities across different subfamilies. For example, the DELLA subfamily protein contains the DELL A structural domain at its N-terminus.</p>", "<p id=\"Par34\">The introns of these <italic>ScGRAS</italic> genes were examined, and it was found that each gene contains between 1 and 5 exons (Fig. ##FIG##1##2##A and B). Approximately 59.7% of <italic>ScGRAS</italic> genes do not contain introns, which is higher than in rice (~ 55%) [##REF##15316287##34##] and poplar (~ 54.7%) [##REF##20616154##65##], but lower than in millet (~ 64.9%) [##REF##34732123##37##], sorghum (~ 66.7%) [##UREF##6##39##], <italic>Arabidopsis</italic> (~ 67.6%) [##REF##18500650##19##], and buckwheat (~ 87%) [##REF##31387526##26##]. The gene structure of certain subfamily members may be compact, as some subfamilies such as DLT, LAS, and DELLA do not contain introns or have only one intron. Genes without introns are also observed in other gene families, including the small auxin-up RNA (SAUR) gene family [##REF##16707243##81##], F-box families [##REF##24341615##82##], and DEAD box RNA helicase [##REF##9862990##83##]. Generally, genes without introns or with few introns tend to have lower expression levels in plants. However, it has been suggested that <italic>GRAS</italic> genes in plants may have originated directly from prokaryotes through horizontal gene transfer and duplication events [##REF##28957440##42##]. Therefore, most GRAS members in plants may have compact gene structures [##UREF##10##84##]. Genes without introns can continuously encode proteins during transcription and translation, making them sensitive to the environment and capable of responding rapidly [##REF##20360214##85##–##REF##17578610##87##]. Furthermore, gene expression may not strongly depend on the density of introns in these genes, as evidenced by our research results [##REF##34865784##68##]. Some highly expressed genes have introns of average length (Fig. ##FIG##6##7## and ##SUPPL##15##S4##), indicating that the expression level may depend on specific developmental processes or environmental stress [##REF##23414336##69##]. For example, the expression of <italic>ScGRAS64</italic> in leaves increases rapidly under cold, salt, and PEG stresses, suggesting that it may be a response to these abiotic stresses. Genes with compact structures may contribute to rapid responses to stress or tissue development. Ten conserved motifs were identified in ScGRAS proteins, which can be used to predict the function of unknown proteins within the same subfamily [##UREF##6##39##].</p>", "<p id=\"Par35\">Tandemly repeated genes can rapidly expand or contract in response to environmental changes, maintaining a constant number of functionally related genes without increasing genetic complexity during evolution [##REF##22726208##88##]. Segmental duplications are also common in animal and plant genomes, contributing to genetic diversity [##REF##34732123##37##]. Thus, tandem repeats and segmental duplications play important roles in the expansion of gene families and genome evolution, enabling plants to adapt to their environment. For example, duplication events of <italic>OsSHR1</italic> led to diversification, and the expression of <italic>OsSHR2</italic> expanded in the endodermis and certain cortex cell layers, possibly acquiring additional functions in rice root development [##REF##12974810##89##]. In our study, nine tandem repeat events involving thirteen <italic>ScGRAS</italic> genes were identified (Fig. ##FIG##2##3##, Table ##SUPPL##5##S6##). Notably, a region of high-density tandem repeats was found on chromosome 4R, involving four members (<italic>ScGRAS36</italic>, <italic>ScGRAS37</italic>, <italic>ScGRAS38</italic>, and <italic>ScGRAS39</italic>) belonging to the LISCL subfamily. This may explain why LISCL is the largest subfamily in the <italic>ScGRAS</italic> family. Furthermore, three pairs of segmental duplications were observed in <italic>ScGRAS</italic> genes (Fig. ##FIG##3##4##, Table ##SUPPL##7##S8##). Consistent with other plants such as <italic>Arabidopsis</italic> [##REF##18500650##19##], rice [##REF##15316287##34##], millet [##REF##34732123##37##], and barley [##REF##12687001##62##], all duplicated genes are within the same subfamily, indicating that duplication events do not occur between different subfamilies. However, tandem replication of <italic>ScGRAS</italic> genes may be a more significant contributor to the expansion of the <italic>GRAS</italic> gene family in <italic>S. cereale</italic>, which is distinct from <italic>S. italica</italic> [##REF##34732123##37##] and may represent a unique evolutionary pattern in rye.</p>", "<title>Expression patterns and function prediction of <italic>ScGRAS</italic> genes</title>", "<p id=\"Par36\">The gene expression patterns were analyzed to preliminarily predict the physiological functions of these <italic>GRAS</italic> genes in rye. The expression of nineteen <italic>GRAS</italic> members was analyzed in different tissues and at different stages of grain filling (Fig. ##FIG##6##7##). Almost all <italic>ScGRAS</italic> genes exhibited significant differential expression (<italic>p</italic> &lt; 0.05). <italic>ScGRAS25</italic>, encoding a member of the LISCL, displayed specific expression in roots and flowers, consistent with the homologous gene <italic>At2G29060</italic> in <italic>Arabidopsis</italic>, which participates in root, flower, and seed development. Notably, <italic>ScGRAS18</italic>, encoding a member of the PAT1 subfamily, is specifically expressed in roots and flowers. PAT1 members primarily participate in the signal transduction of photoreceptor A, as demonstrated by the elongation of hypocotyls, closure of apical hooks, and folded cotyledons observed in the <italic>pat1</italic> mutant under far-red light conditions in <italic>Arabidopsis</italic> [##REF##10817761##90##]. <italic>ScGRAS46</italic> and <italic>ScGRAS48</italic>, both members of the same subfamily, exhibited similar expression patterns, with high expression levels in stems. Few studies have been conducted on LISCL subfamily members in higher plants, but evidence suggests that they may play roles in transcriptional regulation. The LiSCL transcription factor plays a crucial role in meiosis during the meiotic process of <italic>L. longiflorum</italic> [##REF##12657631##55##]. Similarly, <italic>PrSCL1</italic> in <italic>Pinus radiata</italic> and <italic>CsSCL1</italic> in <italic>Castanea sativa</italic> are mainly expressed in stems and roots, induced by exogenous auxin during cutting, and involved in early adventitious root formation [##REF##17669736##91##]. Furthermore, the expression pattern of <italic>ScGRA44</italic> was similar to that of <italic>GS6</italic>, a homologous gene belonging to the DLT in rice [##UREF##9##73##]. <italic>OsGS6</italic>, an important domestication gene, has been found to play a significant role in reducing the size of rice grains [##REF##23650998##92##]. The expression patterns of DELLA family members may be complex. For example, <italic>GRAS24</italic> is specifically expressed in roots, leaves, and grains, while <italic>GRAS29</italic> exhibits high expression levels in leaves. Therefore, it is necessary to systematically analyze their expression characteristics in different tissues and at different stages of grain development. The expression patterns of many <italic>ScGRAS</italic> genes showed positive correlations, indicating potential synergistic effects in five plant organs (Figure ##SUPPL##15##S4##). These findings provide insights into the function of the <italic>GRAS</italic> gene family in different tissues of rye, although further experiments are needed to verify their specific functions. Grain ripening is a critical process in rye, as it adapts to unfavorable climate and soil conditions and thrives in high-altitude, mountainous, and cold regions. The entire grain ripening process was divided into five representative stages, and the expression patterns of <italic>ScGRAS</italic> genes were analyzed to identify key candidate genes related to grain development. Most <italic>GRAS</italic> genes in rye are highly expressed before the early ripening stage (21 DPA), suggesting widespread involvement of the <italic>GRAS</italic> family in grain ripening. For instance, <italic>ScGRAS48</italic> and <italic>ScGRAS60</italic> are stably expressed in almost all stages.</p>", "<p id=\"Par37\">DELLA proteins not only regulate the gibberellin response pathway but also function as central hubs in signaling pathways that integrate signals from various hormones, such as jasmonic acid, auxins, abscisic acid, and ethylene [##REF##21549956##50##, ##REF##22820377##51##]. Gibberellins are central regulators of plant growth and behavior, acting by degrading DELLA proteins. Peng, et al. [##REF##10421366##93##] proposed that <italic>Rht-B1</italic> / <italic>Rht-D1</italic> and maize <italic>dwarf-8</italic> are homologous to the gibberellin-insensitive (GAI) gene in <italic>Arabidopsis</italic>. DELLA proteins act as negative regulators in the gibberellin signaling pathway, inhibiting gene expression and plant growth. However, DELLA proteins can also be degraded by gibberellins, thereby eliminating their inhibitory effects. The degradation of DELLA proteins occurs through binding with the GA-GAI complex protein, leading to degradation and relieving inhibition by gibberellin. This balance between gibberellins and DELLA proteins forms a dynamic regulatory mechanism for gibberellin activity levels in plant growth and development [##REF##21690205##94##, ##REF##11449051##95##]. Furthermore, DELLA plays a crucial role in grain development. For example, the expression of <italic>DELLA</italic> genes in tomato and <italic>Arabidopsis</italic> induces parthenocarpy [##REF##17883372##96##]. In rye grains, gibberellin can be detected throughout the entire developmental stage (Fig. ##FIG##7##8##). Therefore, it is hypothesized that young rye grains immediately produce gibberellin after fertilization to promote grain filling [##UREF##6##39##]. The endogenous gibberellin content in rye grains was analyzed and detected throughout the entire grain development stages, gradually decreasing as the grain ripens. In addition to <italic>ScGRAS60</italic>, <italic>ScDELLAs</italic> exhibit significantly higher expression levels during the early ripening stage (before 21 DPA) of grain development compared to the full ripening stage (35 DPA). These findings suggest that DELLA genes may play a role in the early to mid-stages of grain development. The plant growth regulator paclobutrazol, which regulates DELLA transcription and gibberellin biosynthesis, was used to treat rye plants [##REF##30121770##97##]. Paclobutrazol treatment significantly reduced plant height and gibberellin content while increasing grain weight (Fig. ##FIG##7##8##B). It is speculated that under paclobutrazol treatment, more photosynthetic products are directed towards grain development rather than stem elongation [##UREF##11##98##]. Furthermore, exogenous gibberellin treatment had opposite effects on plant height and grain weight compared to paclobutrazol treatment. Paclobutrazol significantly inhibits gibberellin biosynthesis, especially during the early to middle filling stage (7 DPA and 14 DPA), potentially influencing the expression patterns of DELLA members due to the down-regulation of gibberellin. Almost all DELLAs exhibited suppressed expression levels under gibberellin treatment compared to the control group. After paclobutrazol treatment, the expression level of <italic>ScGRAS24</italic> changed significantly at 28 DPA and 35 DPA, indicating potential sensitivity during the full ripening stage. Conversely, the expression level of <italic>ScGRAS61</italic> significantly increased at 7 DPA and 14 DPA. <italic>ScGRAS29</italic> displayed a unique expression pattern with fluctuating levels, possibly due to significant differences in amino acid structure and motif arrangement compared to other members. Notably, the expression level of <italic>ScGRAS60</italic> significantly increased throughout grain development after paclobutrazol treatment and was more sensitive than other DELLA members. This suggests that <italic>ScGRAS60</italic> may have potential value in breeding rye. Additionally, significant differences in the expression levels of four DELLA subfamily genes were observed during grain development after paclobutrazol treatment, indicating potential functional differentiation among different members of the DELLA. This is consistent with previous findings in <italic>Arabidopsis</italic>, where members of the DELLA exhibit differentiated functions while retaining some overlapping functions [##REF##11826299##99##].</p>", "<p id=\"Par38\">Rye possesses the ability to adapt to unfavorable climate and soil conditions, allowing it to thrive in high-altitude areas, mountainous regions, and cold environments. This adaptation may be regulated by a complex endogenous network and transcriptional signals that enable rye to respond to abiotic stresses [##REF##11319018##100##]. However, the stress response of rye to complex abiotic stresses has not been systematically analyzed. To explore the physiological roles of <italic>GRAS</italic> in environmental adaptation in rye, the expression of nineteen <italic>GRAS</italic> members in response to six different abiotic stresses and three representative hormone treatments was analyzed in rye seedlings (Figures ##SUPPL##15##S6## and ##SUPPL##15##S8##). Under cold stress, the expression levels of 11 <italic>ScGRAS</italic> genes in roots, 12 genes in leaves, and 13 genes in stems were significantly regulated, depending on the duration of the treatment. These responses may contribute to the adaptation of <italic>S. cereale</italic> to cold environments, which is consistent with its role as a cold-tolerant crop, as demonstrated in grape [##REF##33752238##101##] and millet [##REF##34732123##37##]. The member <italic>ScGRAS8</italic> of the SHR subfamily showed rapid induction under UV-A treatment. In wheat, <italic>TaSCL14</italic> is highly expressed in stems and roots in response to high light stress. Silencing <italic>TaSCL14</italic> leads to decreased tolerance of wheat to high light stress, resulting in dark-induced leaf senescence and poor development [##REF##25619599##102##]. <italic>SHOOT GRAVITROPISM 1</italic> (<italic>At3G54220</italic>) and <italic>ScGRAS6</italic> belong to the HAM and share similar basic sequence compositions. <italic>SGR1</italic> promotes cell elongation and endodermis differentiation outside the meristematic tissue, which is crucial for root growth. Furthermore, the <italic>sgr1</italic> mutant participates in the abscisic acid pathway and coordinates the oxidative stress response in plants by mediating the inhibition of cytokinin response in the meristematic tissue to promote root growth [##REF##34056773##103##]. <italic>ScGRAS18</italic> exhibits significant induction in roots under six different abiotic stresses. In rice, <italic>CIGR1</italic> and <italic>CIGR2</italic> are rapidly induced upon perception of N-acetylchitooligosaccharides elicitor, induced by exogenous gibberellins, which may play a key role(s) as transcriptional regulators in the early stages of defense signaling following fungal perception and pathogenesis [##REF##12591613##104##]. <italic>GmGRAS37</italic>, which responds to drought, salt stress, abscisic acid, and brassinosteroids, enhances drought and salt stress resistance when overexpressed in soybean hairy roots [##REF##33424904##105##]. In tomato, the HAM member <italic>SlGRAS40</italic> is induced by D-mannitol and NaCl, playing a role in promoter- and auxin- and gibberellin-mediated signal transduction in response to abiotic stresses [##REF##29018467##106##]. From the cluster tree, it can be seen that the HAM subfamily may have two highly differentiated sub-classes, similar to the HAM subfamily in sorghum we previously reported [##UREF##6##39##]. Therefore, two members of the HAM subfamily, <italic>ScGRAS6</italic> and <italic>ScGRAS14</italic>, were selected for expression pattern analysis. Their expression patterns differed somewhat, with <italic>ScGRAS6</italic> being highly expressed at 21 DPA and <italic>ScGRAS14</italic> being highly expressed at 7 DPA. Under heat stress, the expression of <italic>ScGRAS6</italic> increased and then decreased in stems, while the expression pattern of <italic>ScGRAS14</italic> was opposite. These findings suggest that different branches of the <italic>GRAS</italic> subfamily may exhibit distinct responses to environmental stress. Additionally, some genes may participate in the response to abiotic stress through hormone regulation. For example, the <italic>AtDLT</italic> gene regulates brassinosteroid signaling by binding in the promoter of the BZR1gene, thereby regulating leaf curling and embryo sheath elongation [##REF##19220793##107##]. Overall, different <italic>GRAS</italic> subfamilies have diverse biological functions, playing important roles in plant adaptation to abiotic stresses. This is supported by the correlation network (Table ##SUPPL##11##S12##, Figure ##SUPPL##15##S8##), which demonstrates that these <italic>GRAS</italic> transcription factors participate in a complex cross-regulatory network induced by stress and hormones.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par39\">In conclusion, this study identified 67 members of the <italic>GRAS</italic> gene family in rye and classified them into thirteen main subfamilies. Most <italic>ScGRAS</italic> genes do not contain introns, and their gene structures, conserved motifs, cis-acting elements, gene duplications, and expression patterns were analyzed. Overall, the gene structures of the same subfamily is always similar, including the number of exons, amino acid structures, and motif arrangements. Gene duplication events may have contributed to the emergence of certain <italic>ScGRAS</italic> genes, with tandem replication playing a more significant role in expanding the <italic>GRAS</italic> gene family compared to segmental duplication. Notably, a high-density tandem repeat region containing LISCL subfamily genes was discovered on chromosome 4R. The expression patterns of <italic>ScGRAS</italic> genes in different tissues and grain development stages were analyzed, and key candidate genes related to grain development were identified. Additionally, the relationship between DELLA genes, gibberellin content, and grain development was investigated. Furthermore, the expression patterns of <italic>ScGRAS</italic> genes under various abiotic stresses and hormone treatments were examined to shed light on their physiological functions in environmental adaptation. These findings provide valuable insights into the function and evolution of the <italic>GRAS</italic> gene family in rye.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The <italic>GRAS</italic> transcription factor family plays a crucial role in various biological processes in different plants, such as tissue development, fruit maturation, and environmental stress. However, the GRAS family in rye has not been systematically analyzed yet.</p>", "<title>Results</title>", "<p id=\"Par2\">In this study, 67 <italic>GRAS</italic> genes in <italic>S. cereale</italic> were identified and named based on the chromosomal location. The gene structures, conserved motifs, cis-acting elements, gene replications, and expression patterns were further analyzed. These 67 <italic>ScGRAS</italic> members are divided into 13 subfamilies. All members include the LHR I, VHIID, LHR II, PFYRE, and SAW domains, and some nonpolar hydrophobic amino acid residues may undergo cross-substitution in the VHIID region. Interested, tandem duplications may have a more important contribution, which distinguishes them from other monocotyledonous plants. To further investigate the evolutionary relationship of the <italic>GRAS</italic> family, we constructed six comparative genomic maps of homologous genes between rye and different representative monocotyledonous and dicotyledonous plants. The response characteristics of 19 <italic>ScGRAS</italic> members from different subfamilies to different tissues, grains at filling stages, and different abiotic stresses of rye were systematically analyzed. Paclobutrazol, a triazole-based plant growth regulator, controls plant tissue and grain development by inhibiting gibberellic acid (GA) biosynthesis through the regulation of DELLA proteins. Exogenous spraying of paclobutrazol significantly reduced the plant height but was beneficial for increasing the weight of 1000 grains of rye. Treatment with paclobutrazol, significantly reduced gibberellin levels in grain in the filling period, caused significant alteration in the expression of the DELLA subfamily gene members. Furthermore, our findings with respect to genes, <italic>ScGRAS46</italic> and <italic>ScGRAS60</italic>, suggest that these two family members could be further used for functional characterization studies in basic research and in breeding programmes for crop improvement.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">We identified 67 ScGRAS genes in rye and further analysed the evolution and expression patterns of the encoded proteins. This study will be helpful for further analysing the functional characteristics of <italic>ScGRAS</italic> genes.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12870-023-04674-1.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank all our colleagues for providing useful discussions and technical assistance. We are very grateful to the editor and reviewers for critically evaluating the manuscript and providing constructive comments for its improvement.</p>", "<title>Author contributions</title>", "<p>YF planned and designed the research and analyzed the data. YF and XZ wrote the manuscript. XW and JZ studied gene expression using qRT-PCR. CZ and QY identified the S. cereale GRAS gene family and analyzed its gene structures. LY and XL studied chromosome distribution, gene duplication, and syntenic analysis of the S. cereale GRAS genes. LF analyzed the evolutionary relationship between GRAS genes in several different species. YF and LF treated rye seedlings and tested their hormone content. LZ and DX supervised the study. DX revised the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This research was supported by the Talent Initiation Funding Project of Chengdu University (2081923007), Open Project Program of Irradiation Preservation Technology Key Laboratory of Sichuan Province, Sichuan Institute of Atomic Energy (FZBC206704), Ministry of Finance and Ministry of Agriculture and Rural Affairs: National Oat Buckwheat Industry Technology System (CARS-07-B-1).</p>", "<title>Data Availability</title>", "<p>The entire <italic>Secale cereale</italic> genome sequence information was obtained from the NCBI (National Center for Biotechnology Information) GenBank website, the access number is JADQCU000000000. rye materials (Weining) used in the experiment were supplied by Prof. Kuiying Li of Anshun University. The datasets supporting the conclusions of this study are included in the article and its additional files.</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to participate</title>", "<p id=\"Par60\">This article does not contain any studies involving human participants or animals performed by the authors. These methods were carried out by relevant guidelines and regulations. <italic>S. cereale</italic> cv. <italic>Weining</italic>, a traditional variety in Guizhou Province in southwest China. Based on international standards, all the experimental research and field studies on plants, including the collection of plant material were approved by Chengdu University. These materials are stored in the Sichuan Provincial Crop Germplasm Bank of Chengdu University, numbered Sc032.</p>", "<title>Consent for publication</title>", "<p id=\"Par61\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par59\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Unrooted phylogenetic tree showing relationships among GRAS domains of <italic>Secale cereale</italic> (Sc), <italic>Arabidopsis thaliana</italic> (At) and <italic>Oryza sativa</italic> (Os). The phylogenetic tree was derived using the neighbor-joining method in MEGA7.0. The tree shows the 13 phylogenetic subfamilies. GRAS proteins from S. cereale are highlighted in red</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Phylogenetic relationships, gene structure analysis, and motif distributions of <italic>S. cereale GRAS</italic> genes. <bold>A</bold> Phylogenetic tree was constructed using the neighbor-joining method with 1000 replicates for each node. <bold>B</bold> Exons and introns are indicated by yellow rectangles and grey lines, respectively. The green, yellow, and red rectangles represent the UTR, CDS, and GRAS conserved domains, respectively. <bold>C</bold> Amino acid motifs in the <italic>ScGRAS</italic> proteins (1–10) are represented by colored boxes. The black lines indicate relative protein lengths</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Schematic representation of the chromosomal distribution of the <italic>S. cereale GRAS</italic> genes. Vertical bars represent the chromosomes of <italic>S. cereale</italic>. The chromosome number is indicated to the left of each chromosome. The scale on the left represents chromosome length. Gene pairs with tandem repeat relationships are marked in red. The tandem gene pairs between pairs are connected by U-shaped lines</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Schematic representation of the chromosomal distribution and interchromosomal relationships of <italic>S. cereale GRAS</italic> genes. Colored lines indicate all synteny blocks in the <italic>S. cereale</italic> genome, and the red lines indicate duplicated <italic>GRAS</italic> gene pairs. The chromosome number is indicated at the bottom of each chromosome</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Synteny analyses of the <italic>GRAS</italic> genes between <italic>Secale cereale</italic> and six representative plant species (<italic>Triticum aestivum</italic>, <italic>Aegilops tauschii</italic>, <italic>Hordeum vulgare</italic>, <italic>Oryza sativa</italic> subsp. <italic>Indica</italic>, <italic>Zea mays</italic>, and <italic>Arabidopsi thaliana</italic>). Gray lines on the background indicate the collinear blocks in <italic>S. cereale</italic> and other plant genomes; red lines highlight the syntenic <italic>S. cereale GRAS</italic> gene pairs</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Phylogenetic relationship and motif composition of the <italic>GRAS</italic> proteins from <italic>S. cereale</italic> with six different plant species (<italic>T. aestivum</italic>, <italic>A. tauschii</italic>, <italic>H. vulgare</italic>, <italic>O. sativa</italic> subsp. <italic>Indica</italic>, <italic>Z. mays</italic>, and <italic>A. thaliana</italic>). Outer panel: an unrooted phylogenetic tree constructed using Geneious R11 with the neighbor-joining method. Inner panel: distribution of conserved motifs in <italic>GRAS</italic> proteins. The differently colored boxes represent different motifs and their positions in each <italic>GRAS</italic> protein sequence. The sequence information for each motif is provided in Table ##SUPPL##1##S2##</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Expression patterns of selected 19 <italic>S. cereale GRAS</italic> genes. <bold>A</bold> Expression patterns of 19 <italic>S. cereale GRAS</italic> genes in the root, stem, leave, flower, and grain were examined via qRT-PCR. Relative expression level was shown as mean (± SE) from three independent experiments. <bold>B</bold> Expression patterns of 19 <italic>S. cereale GRAS</italic> genes were examined during different grain development stages: 7 DPA (early-filling stage), 14 DPA (mid-filling stage), 21 DPA (early-ripening stage), 28 DPA (mid-ripening stage), and 35 DPA (full-ripening stage). Lowercase letters above the bars indicate significant differences (α = 0.05, LSD) among the treatments</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>Grain development of <italic>S. cereale</italic> under exogenous paclobutrazol and gibberellin treatment. <bold>A</bold> The plant height, 1000 grain weight, and gibberellin content during grain development. <bold>B</bold> Differences in the expression of DELLA subfamily genes under exogenous paclobutrazol and gibberellin treatment during grain development. Mock: the same amount of water treatment, Paclobutrazol: 250 mg/L paclobutrazol treatment. Gibberellin: 100 μm gibberellin treatment. Error bars were obtained from three measurements. We need information that asterisk described significant differences (α = 0.05/0.01/0.001, LSD) among the treatments. *, **, and *** indicate significant correlations at the 0.05, 0.01 and 0.001 levels, respectively</p></caption></fig>" ]
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[ "<media xlink:href=\"12870_2023_4674_MOESM1_ESM.xlsx\"><caption><p><bold>Supplementary Material 1: Table S1</bold>. List of the 67 <italic>S. cereale</italic> GRAS genes identified in this study</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM2_ESM.xls\"><caption><p><bold>Supplementary Material 2: Table S2</bold>. Analysis and distribution of conserved motifs in <italic>Secale cereale</italic> GRAS proteins</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM3_ESM.xlsx\"><caption><p><bold>Supplementary Material 3: Table S3</bold>. The distribution of amino acid sites in the motifs in rye</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM4_ESM.xlsx\"><caption><p><bold>Supplementary Material 4: Table S4</bold>. Analysis of Motif Enrichment in 67 GRAS proteins in rye</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM5_ESM.xlsx\"><caption><p><bold>Supplementary Material 5: Table S5</bold>. Cis-regulatory elements in the promoter region of <italic>ScGRAS</italic> genes</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM6_ESM.xlsx\"><caption><p><bold>Supplementary Material 6: Table S6</bold>. The tandem duplication events of <italic>ScGRAS</italic> genes in Weining</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM7_ESM.xlsx\"><caption><p><bold>Supplementary Material 7: Table S7</bold>. The gene pair similarity comparison in EMBOSS Needle</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM8_ESM.xls\"><caption><p><bold>Supplementary Material 8: Table S8</bold>. The three pairs of segmental duplicates in S. <italic>cereale GRAS</italic> genes</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM9_ESM.xlsx\"><caption><p><bold>Supplementary Material 9: Table S9</bold>. One-to-one orthologous relationships between <italic>Secale cereale</italic> and <italic>Arabidopsis</italic> thaliana</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM10_ESM.xlsx\"><caption><p><bold>Supplementary Material 10: Table S10</bold>. Results of Tajima’s D neutrality test</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM11_ESM.xlsx\"><caption><p><bold>Supplementary Material 11: Table S11</bold>. Ka/Ks ratio distribution of gene pairs in different subfamilies in Weininng</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM12_ESM.xlsx\"><caption><p><bold>Supplementary Material 12: Table S12</bold>. The relative expression levels of GRAS genes were detected at different stages of grain development under gibberellin treatment</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM13_ESM.xlsx\"><caption><p><bold>Supplementary Material 13: Table S13</bold>. List of the 72 ScGRAS genes identified in Lo7</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM14_ESM.xlsx\"><caption><p><bold>Supplementary Material 14: Table S14</bold>. One-to-one orthologous relationships between Lo7 and Weining</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM15_ESM.xlsx\"><caption><p><bold>Supplementary Material 15: Table S15</bold>. Primer sequences for qPCR</p></caption></media>", "<media xlink:href=\"12870_2023_4674_MOESM16_ESM.docx\"><caption><p><bold>Supplementary Material 16: Figure S1</bold>. Multiple sequence alignments of the <italic>GRAS</italic> domains of the members of 13 phylogenetic subfamilies of the <italic>ScGRAS</italic> protein family. The scheme at the top depicts the locations and boundaries of the LHR I, VHIID, LHR II, PFYRE, and SAW regions in the <italic>GRAS</italic> domain. <bold>Figure S2</bold>. Conserved sequence logo of GRAS proteins in rye. <bold>Figure S3</bold>. Conserved sequence logo in seven species. <bold>Figure S4</bold>. The correlations of 19 <italic>S. cereale</italic> GRAS genes in several plant organs. <bold>Figure S5</bold>. The correlations of 19 <italic>S. cereale</italic> GRAS genes during grain development. <bold>Figure S6</bold>. Gene expression of 19 <italic>S. cereale GRAS</italic> genes during six abiotic stresses (UV-A, flooding, PEG, NaCl, heat, and cold) at the seedling stage. The expression patterns of 19 <italic>S. cereale GRAS</italic> genes in leaf, root, and stem organs were examined via qRT-PCR. Error bars were obtained from three measurements. Lowercase letters above the bars indicate significant differences (? = 0.05, LSD) among the treatments. <bold>Figure S7</bold>. The correlations of 19 <italic>S. cereale GRAS</italic> genes in several abiotic stresses. <bold>Figure S8</bold>. Correlation network of the expression of <italic>ScGRAS</italic> family members in grains treated with different hormones. Among them, A, B, C and D are abscisic acid, gibberellin, auxin and paclobutrazol respectively. <bold>Figure S9</bold>. Unrooted phylogenetic tree showing relationships among GRAS genes of <italic>S. cereale</italic> (Weining and Lo7), <italic>A. thaliana</italic> and <italic>O. sativa</italic>. <bold>Figure S10</bold>. Synteny analyses of the GRAS genes between Weining and Lo7</p></caption></media>" ]
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{ "acronym": [], "definition": [] }
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2024-01-14 23:43:45
BMC Plant Biol. 2024 Jan 13; 24:46
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PMC10787400
0
[ "<title>Introduction</title>", "<p id=\"Par14\">Globally, around two million stillbirths and 2.5 million neonatal deaths occurred in 2015, with wide disparities in perinatal mortality between and within low- and middle-income countries (LMICs) and high-income countries (HICs) [##REF##34454675##1##–##REF##31915022##3##]. Stillbirth and neonatal mortality rates in sub-Saharan Africa are more than eight times higher than those in HICs [##REF##34454675##1##–##REF##31915022##3##]. While global perinatal mortality has reduced considerably in recent decades, this reduction still lags markedly behind that of under-five mortality. Stillbirth reduction is particularly slow [##REF##34454675##1##–##REF##31915022##3##]. Furthermore, systematic reviews report an increase in maternal deaths and stillbirths during the COVID-19 pandemic [##UREF##1##4##]. Importantly, while facility births have increased remarkably, perinatal survival has not followed suit and there is an urgent need for improved quality of maternal and perinatal healthcare [##REF##26794078##5##].</p>", "<p id=\"Par15\">Tanzania has a perinatal mortality of 39.5 per 1,000 total births compared to 34.5 per 1,000 total births in the rest of the Eastern African region [##UREF##2##6##]. Despite facility-based births in Tanzania's urban areas exceeding 95%, the national stagnation in hospital-based neonatal mortality rates persists alongside a higher incidence of neonatal deaths in urban areas compared to rural areas [##UREF##3##7##, ##UREF##4##8##]. Based on Demographic Health Survey data from 2015–2016, an urban perinatal mortality rate was reported of 56.6 per 1,000 total births as compared to 35.9 per 1,000 total births in rural areas and an urban neonatal mortality rate of 39.8/1,000 pregnancies as compared to 21.9/1,000 in rural areas [##UREF##5##9##, ##UREF##6##10##]. More specifically, Tanzania’s largest city, Dar es Salaam, comprises a particularly high-burden setting with the magnitude of maternal and perinatal deaths being considerably higher compared to other regions of the country [##UREF##7##11##–##UREF##8##13##]. Trends towards similar urban disadvantages are reported from other LMICs [##UREF##6##10##]. The need is clear: a new understanding of underlying causes and how to improve is warranted to accelerate progress in maternal and perinatal health for people living in urban areas [##REF##34980187##14##].</p>", "<p id=\"Par16\">Pathophysiological causal pathways for antepartum stillbirths in late pregnancy often involve impaired placental function, associated with fetal asphyxia, growth restriction and hypertensive disorders in pregnancy [##REF##26794078##5##, ##REF##30606156##15##]. The most vulnerable period for intrapartum stillbirths and neonatal deaths is the day of birth, with birth asphyxia, prematurity and perinatal sepsis being the leading causes [##REF##24853593##16##, ##REF##27109087##17##]. Poor diagnostics and record keeping, however, often challenge cause-analyses in LMICs and result in causes being classified as “unknown” [##REF##25236649##18##]. Despite this paucity of data, it is clear that perinatal deaths in LMICs can be prevented with basic maternity care [##REF##21496912##19##, ##REF##26794077##20##].</p>", "<p id=\"Par17\">Against this background, the objectives of the present study were : I. to assess the incidence of perinatal deaths in five overcrowded public maternity units in Dar es Salaam and classify these into a) pre-facility stillbirths (absence of fetal heart tones on admission to the study health facility) and intra-facility perinatal deaths (intrafacility stillbirths and pre-discharge early neonatal deaths, where fetal heart tones were heard on admission); and II. To identify determinants of perinatal deaths by comparing the two groups of perinatal deaths to controls (healthy newborns discharged home alive). The ultimate purpose was to inform and strengthen the ongoing quality improvement initiatives for maternal and perinatal care in which this study is embedded (The PartoMa project and the CCBRT-Dar es Salaam regional maternal and newborn healthcare strengthening program) [##REF##27109087##17##, ##REF##25236649##18##].</p>" ]
[ "<title>Methods</title>", "<title>Setting</title>", "<p id=\"Par18\">The study was carried out in the five busiest government hospitals in Dar es Salaam, Tanzania. In these five hospitals, 60–70% of all births in the city are estimated to take place, and in each health facility (HF) between 6,000 and 10,000 women give birth per year [##UREF##9##21##]. These HFs are part of a network of 22 HFs in Dar es Salaam region, which collaborate in a maternal and newborn healthcare strengthening program established in 2010 [##UREF##10##22##]. This program is implemented through a public–private partnership between the regional health authorities and the non-governmental organization ‘Comprehensive Community Based Rehabilitation in Tanzania’ (CCBRT). Furthermore, the five hospitals are the study sites of the PartoMa project, which seeks to achieve best possible maternal and newborn care by adapting clinical guidelines and skills training to the local context [##UREF##9##21##, ##UREF##11##23##].</p>", "<p id=\"Par19\">Three of the study HFs are Regional Referral Hospitals (RRHs): HF1, HF2 and HF3. The other two are upgraded health centers that serve as primary level maternity hospitals: HF4 and HF5. All five facilities provide comprehensive care during childbirth that includes vacuum assisted births, cesarean section (CS) and blood transfusions. While the three RRHs have neonatal high care units, the other two (HF4 and HF5) refer all sick newborns to the nearest RRH. All five hospitals receive referrals from dispensaries and health centers throughout the wider Dar es Salaam region. Due to resource-constraints, blood tests for hematology, liver function and renal function are not routinely performed for laboring women with hypertension. All five hospitals typically serve women of lower socio-economic status [##REF##8840594##24##]. Dispensaries and health centers provide a wide range of preventative and first line emergency care, which includes reproductive healthcare, antenatal care (ANC) and care during birth for low-risk pregnant women. Dispensaries are expected to refer all high-risk pregnancies, women with abnormal labor progress, obstetric complications and intrauterine fetal deaths.</p>", "<p id=\"Par20\">Figure ##FIG##0##1## presents the definitions of stillbirths and early neonatal deaths as defined by the World Health Organization (WHO) [##UREF##12##25##]. Additional terms used in this study, including pre-facility and intra-facility stillbirth are inspired by previous studies [##REF##26794078##5##, ##REF##27832753##26##]. Definitions e–g were applied instead of antepartum stillbirth, fresh stillbirth and macerated stillbirths due to the low reliability of the stillborn baby’s appearance to the time of fetal death [##UREF##13##27##, ##UREF##14##28##].</p>", "<title>Study population</title>", "<p id=\"Par21\">For our cohort study, in order to assess incidence of perinatal deaths, the study population consisted of all births in the five hospitals from 1<sup>st</sup> January 2020 to 31<sup>st</sup> December 2020, including all perinatal deaths diagnosed before discharge. For the embedded case-control study, we included a subset of singleton births with birthweight ≥ 2,000 g who had their medical case records available for analysis. Newborns with major congenital malformations were excluded. Within this category, cases of perinatal deaths were sub-categorized by presence or absence of the fetal heart tones on admission to the study HF, as follows:<list list-type=\"order\"><list-item><p id=\"Par22\">Pre-facility stillbirth, where no fetal heart tones were heard on admission to the maternity ward.</p></list-item><list-item><p id=\"Par23\">Intra-facility perinatal deaths refer to the sum of intra-facility stillbirths and early neonatal deaths where fetal heart tones were heard on admission. For intra-facility stillbirths, the fetus died before birth, and for early neonatal death, the newborn died before discharge<bold>.</bold></p></list-item></list></p>", "<p id=\"Par24\">Controls were defined as singleton, live newborns with a birthweight ≥ 2,000 g, Apgar score of ≥ 8 at one minute and ≥ 9 at five minutes, who did not require bag and mask resuscitation and who were discharged home alive [##UREF##15##30##]. Controls were selected to match the included intra-facility perinatal deaths by month and facility of birth.</p>", "<title>Data collection</title>", "<p id=\"Par25\">For calculation of perinatal mortality rates, we collected data on total births, livebirths, stillbirths, early neonatal deaths, CS, vacuum-assisted births and maternal deaths, which are available in the five hospitals’ routine National Health Information System (MTUHA). Additional information pertaining to perinatal deaths was extracted from the Perinatal Problem Identification (PPIP) database, which contains additional information on actual birthweight, multiple pregnancy and presence of congenital malformations [##UREF##9##21##].</p>", "<p id=\"Par26\">For the case–control study, all perinatal deaths that met the inclusion criteria were extracted from the PPIP database and their paper-based medical records were intensively searched for. If medical records were retrieved, women were included, and data extracted from their records. Controls were retrieved from the piles of medical records (mainly partographs) of all women with livebirths, which were separated by month of birth and divided into vaginal and cesarean births. The average CS rate in the study sites (2019 data) varied from 18 to 25% [##UREF##9##21##]. The ratio of vaginal to cesarean births was approximately 4:1. In accordance with the sample size calculation presented below, and by use of a random number generator, controls were then systematically sampled by inclusion of every 10<sup>th</sup> file, with each fifth of the included files being selected from the CS pile. When the selected controls did not meet the inclusion criteria, the next 10<sup>th</sup> file was selected.</p>", "<p id=\"Par27\">A data collection tool was developed on Open Data Kit (ODK) XForm using a data dictionary and deployed to an ODK app on smart devices (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.betterevaluation.org\">www.betterevaluation.org</ext-link>). Validation codes were incorporated in the tool to limit data errors and the tool was pilot tested in each study facility by BSD. Data extraction from files was performed by midwives and medical doctors working in the study sites who had all attended a three-day data entry training, conducted by BSD. The first 50 files were double entered by TWJ to check accuracy of data entry. Any discrepancy in double entry was re-checked. BSD reviewed data entry progress and related quality every week throughout the data collection period. All files were assigned a unique identification number and personal identifiers removed. The study database was stored in Ifakara Health Institute Data center, Tanzania.</p>", "<title>Sample size calculation for case-control study</title>", "<p id=\"Par28\">The sample size was estimated using an alpha of 0.05, power of 0.8, ratio of cases to control of 1:5 and assuming an odds of intra-facility perinatal deaths of 1.45. The estimated sample was 395 cases for intra-facility deaths. However, in this study we obtained only 287 cases for intra-facility deaths.</p>", "<title>Variables of interest for the case control study</title>", "<p id=\"Par29\">For the case-control study, the variables of interest are presented in Fig. ##FIG##1##2## and Table ##TAB##2##3##. These variables were selected from the literature to broadly assess antenatal and admission risk factors as well as intrapartum quality of care provision, including surveillance and associated treatment if needed related to maternal vital signs, fetal heart rate and labor progress [##REF##28892306##31##]. Notably, the selection of variables was limited to what could retrospectively be assessed in the case files.</p>", "<title>Data management and analyses</title>", "<p id=\"Par30\">Data cleaning and analysis was performed using Stata version 14.2 (Stata Corp, Texas, USA). Categorical data were summarized using frequencies and percentages while continuous data were summarized using mean and standard deviation. Stillbirth rate and perinatal mortality were obtained using total births from the five study HFs in the year 2020 per 1,000 total births. A Pearson chi-square test was used to determine associations between variables of interest and outcome variables. One-way ANOVA test was used to compare mean maternal age of the three groups in the case control study population (healthy women, pre-facility stillbirths and intra-facility perinatal deaths). Both bivariable and multivariable logistic regressions were performed to identify the presence of a significant association between independent variables and the dependent variable. Variables with a <italic>p</italic>-value of &lt; 0.2 were considered for multivariable analysis. Any variable whose univariable test has a <italic>p</italic>-value &lt; 0.25 along with all variables of known clinical importance should be included into multivariable analysis [##UREF##16##32##]. Furthermore, variables with a high proportion of missing cases above 10% were omitted from the multivariable analysis. Following fitting of the model, we assessed the importance of each covariate using p-values. Variables that did not contribute at traditional levels of statistical significance (<italic>p</italic> ≥ 0.05) were eliminated. Bivariate analyses were used for pre-facility stillbirths and multivariable analyses were used for analyses of intra-facility perinatal deaths. Crude Odds Ratio (cOR) and adjusted Odds Ratio (aOR) were calculated with 95% confidence interval (CI). Free text descriptions in women’s files on the care given in response to abnormal vital signs were manually extracted from the notes, categorized and presented. Results were presented using tables and figures.</p>" ]
[ "<title>Results</title>", "<p id=\"Par31\">From 1 January 2020 to 31 December 2020, the five public HFs in Dar es Salaam registered a total of 37,787 births. During this year, the perinatal death rate was 38.3 per 1,000 total births (1447 deaths). The stillbirth rate was 27.7 per 1,000 total births (1,048 stillbirths) of which 926 (88.4%) were pre-facility stillbirths and 122 (11.6%) intra-facility stillbirths. The pre-discharge neonatal death rate was 10.9 per 1,000 live births (399 neonatal deaths) (Table ##TAB##0##1##).\n</p>", "<p id=\"Par32\">As a subset of this population, the case–control study included 2,224 women with singleton births and with birthweights equal to or above 2000 g. Of the 1,048 stillbirths, 681 (65.0%) were eligible for inclusion, of which, 574 medical files (84.3%) were retrieved. Among the retrieved files, 452 were pre-facility stillbirths and 122 were intra-facility stillbirths. Of the 399 early neonatal deaths, 273 (68.4%) fulfilled the inclusion criteria, of which we retrieved 165/273 (60.4%) medical files for the in-depth review. As a result, the case control study included 452 pre-facility stillbirths; 287 intra-facility perinatal deaths (122 intra-facility stillbirths plus 165 intra-facility neonatal deaths); and 1,485 controls (a total of 2,224 women) (Fig. ##FIG##2##3##).</p>", "<p id=\"Par33\">The case-control study’s findings are presented in the sections below. Characteristics of the women in the study population are presented in Table ##TAB##1##2##. The factors associated with perinatal deaths are described in detail in Table ##TAB##2##3##. For reference, additional descriptive data are presented in Supplementary Tables ##SUPPL##0##1##, ##SUPPL##0##2## and ##SUPPL##0##3##.\n</p>", "<title>Characteristics of the women in the case–control study population</title>", "<p id=\"Par34\">Mean age of the women was 27.0 (SD ± 6.2). There was a small difference in mean age of women between the groups with healthy newborns and with pre-facility and intra-facility perinatal deaths, but no difference between pre-facility and intra-facility perinatal deaths groups. The history of a previous perinatal death among the 194/1,331 (14.6%) multiparous women was similar between controls (135/860; 15.7%) and pre-facility stillbirths (47/299; 15.7%). However, among multiparous women with a past history of previous perinatal death, a lower proportion of intra-facility perinatal deaths was observed (12/172; 7.0%; aOR 0.32; 95% CI: 0.13–0.81) (Supplementary Table 4).</p>", "<title>Description of antenatal care (ANC)</title>", "<p id=\"Par35\">All women in the case–control study, except eight, attended ANC with 1,627/2,153 (75.5%) attending four or more visits (Table ##TAB##1##2##). More than 90% of the women received routine testing for Human Immunodeficiency Virus (HIV) and syphilis, tetanus immunization and presumptive treatment for malaria. Of all women, 402 (18.1%) had an ultrasound examination, but only 21/402 (5.2%) before 24 weeks of gestation. Among the 1850 (83.1%) women with available hemoglobin test results, mean hemoglobin (Hb) was 10.9 g/dl ± 1.3 SD and severe anemia (Hb ≤ 8 g/dl) occurred in 45 (2.4%) women<bold>.</bold> There was no difference in mean hemoglobin in the three outcome groups (Supplementary Table ##SUPPL##0##1##).</p>", "<title>Referral status and management on admission</title>", "<p id=\"Par36\">Among the case control study population, self-referrals from home occurred in 1,807/2,224 (81.3%) women and 283/2,224 (12.7%) were referred from other non-study HFs (mainly health centers and dispensaries). More specifically, among pre-facility stillbirths, 109 (24.1%) were referred from lower-level HFs, and our data did not indicate if the fetal heart tone was present when the women were admitted in the primary-level HF.</p>", "<p id=\"Par37\">While more than 86% of women had their vital signs measured on admission, very few among those with abnormal vital signs had documentation of any action taken in response. For example, a blood pressure measurement on admission was recorded for 2,060 (92.6%) of women. Among the 71 women with severe hypertension (SBP ≥ 160 and/or DBP ≥ 110 mmHg) measured on admission, 16 (22.5%) of their case-notes had specific treatment recorded.</p>", "<p id=\"Par38\">Concerning the stage of labor on admission, 621 (30.1%) were admitted in the latent stage, 748 (36.3%) were admitted in early active labor (cervical dilatation between 4 and 6cms) and 694 (33.7%) were admitted in late active labor with cervical dilation between 7 to 10 cms. There were no statistically significant differences between the groups.</p>", "<title>Surveillance and management during labor and childbirth</title>", "<p id=\"Par39\">We reviewed 2,085 available partographs. All three sections of the partograph (maternal vital signs, labor progress and fetal heart rate) were completely filled in for 874/2,085 (41.9%) women. </p>", "<p id=\"Par40\">We noted that women with fetal death prior to admission (pre-facility stillbirth) had significantly increased odds of experiencing challenges during the second stage of labor ( cOR 11.52; 95%CI: 8.63-15.36), and breech presentation with vaginal birth (cOR 9.41;95% CI: 3.02-29.36) (Table ##TAB##2##3##).</p>", "<p id=\"Par41\">CS was performed in 533/2,224 (23.9%) women. Out of the total CSs, 469/533 (88%) were performed as emergencies. The commonest indication for CS was previous CS in 136/533 (25.5%) women, followed by obstructed labor in 103/533 (19.3%) and fetal distress in 70/533 (13.1%). The study design ensured that for the control group, the random selection included CSs that approximated the CS rate in the study hospitals, there were no statistical or clinically relevant differences in CS as mode of birth and birth outcomes. Among the 533 women with CS birth, we noted 188 (35.2%) perinatal deaths, distributed as follows: pre-facility stillbirths (74/452; 16.4%), intra-facility stillbirths (54/122; 44.3%) and intra-facility early neonatal deaths (60/165; 36.4%).</p>", "<title>Maternal birth outcomes</title>", "<p id=\"Par42\">Among our study population, 1,862/2,224 (83.7%) women reported no complications during labor and childbirth, while 412 complications were extracted from the remaining 362 women, some of whom reported more than one complication. Hypertension was reported most frequently (165/412, 40.0%) followed by anemia (69/412, 16.7%) and hemorrhage (51/412, 12.3%). Within the study population, there was one maternal death due to hemorrhage from placental abruption in the intra-facility stillbirth group. Uterine rupture occurred in 18 women, including in six among women with pre-facility stillbirth, 11 women with intra-facility perinatal death, and one woman in the control group.</p>", "<title>Factors associated with increased odds ratio for pre-facility stillbirths</title>", "<p id=\"Par43\">Compared to healthy newborns, factors associated with increased odds of pre-facility stillbirths included the following: any hypertension as a complication during intrapartum care (cOR 4.72; 95% CI: 3.30–6.76); low birth weight (newborns within the lowest included birthweight category between 2,000 and 2,500 g), (cOR 4.40; 95% CI: 3.13–6.18); presence of at least one risk factor detected during ANC (cOR 2.68; 95% CI 2.02- 3.56) and if the pregnant woman was referred from peripheral HFs (cOR 1.88; 95% CI 1.17–3.03) (Table ##TAB##2##3##).</p>", "<p id=\"Par44\">Furthermore, a sub-analysis of maternal blood pressure measured on admission (adjusted for age of the woman, parity and newborn birthweight), revealed increased odds of pre-facility stillbirths compared to healthy newborns: mild high blood pressure measurement on admission (cOR 1.93; 95% CI: 1.42–2.62); severe high blood pressure measured on admission (cOR 3.04; 95% CI: 1.83–5.06) (Table ##TAB##2##3## and Supplementary table ##SUPPL##0##2##).</p>", "<title>Factors associated with increased odds ratio for intra‑facility perinatal deaths</title>", "<p id=\"Par45\">Compared to healthy newborns (controls), determinants of intra-facility perinatal death included: breech birth (aOR 40.3; 95% CI: 8.75–185.61); complications in the second stage of labor (aOR 20.04; 95% CI: 12.02–33.41); vacuum-assisted birth (aOR 6.23; 95% CI: 1.6–23.55); low birth weight or late preterm birth with birthweight between 2,000 and 2,500 g (aOR 5.57; 95% CI: 2.62–11.84); cervical dilation that crossed the partograph’s action line (aOR 4.16; 95% CI:2.29–7.56); meconium liquor on admission (aOR 4.44; 95% CI:1.86–10.57); at least one risk factor detected during ANC (aOR 3.7; 95% CI 1.96–6.98) and maternal hypertension during intrapartum care (aOR 2.9; 95% CI 1.03–8.14) (Table ##TAB##2##3##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par46\">In these five overcrowded maternity hospitals in the rapidly urbanizing city of Dar es Salaam, we found a high overall facility-based perinatal mortality rate of 38.3 per 1,000 births (stillbirth rate 27.7 per 1,000 total births, pre-discharge neonatal death rate 10.9 per 1,000 live births). Of all stillbirths, 88.4% were pre-facility, and this is in an urban context of almost 100% antenatal clinic attendance and above 95% facility birth rates [##UREF##17##33##].</p>", "<p id=\"Par47\">Among women in the embedded case–control study, the determinants that raised the odds for both pre-facility stillbirths and intra-facility perinatal deaths included: low birth weight and maternal hypertension. Among women with intra-facility perinatal deaths, breech presentation, complications in the second stage of labor, prolonged labor (cervical dilatation crossing the action line on the partograph), presence of any antenatal risk factor (particularly relevant for multiparous women) and meconium-stained liquor were additional significant determinants for perinatal death. These findings are comparable to reports from other low-resource settings [##REF##28049520##34##, ##REF##34149288##35##].</p>", "<p id=\"Par48\">The higher than expected proportion of pre-facility stillbirths stands in contrast to regional estimates, based on which we expected that only half would fall into this category [##REF##17217119##36##]. This may be partially explained by the local referral criterion, requiring pregnant women with intrauterine fetal death to be referred to a secondary level hospital. In the embedded case-control sub-study, however, 68.1% of women with pre-facility stillbirths came directly from home. Our data do not allow conclusions on whether fetal death occurred at home, before labor, at the referring dispensary, during transit to the study HF or while waiting to be assessed and admitted in the study HFs.</p>", "<p id=\"Par49\">While the pre-versus intra-facility proportions differ, the stillbirth rate is similar to that reported in Northern Tanzania [##REF##35275941##37##, ##UREF##18##38##], but lower compared to facility-based stillbirth rates in referral hospitals in Tanzania: Kilimanjaro Christian Medical Centre (38/1,000 births) and Zanzibar (37.5/1,000 births) [##REF##31915022##39##, ##REF##28813528##40##]. It is however higher compared to rates reported from hospitals in Asia, 16 per 1,000 births in India and 17.6 per 1,000 births in Nepal [##UREF##19##41##, ##REF##26728505##42##].</p>", "<p id=\"Par50\">The neonatal death rate reported in this study is comparable to the 10.4 per 1,000 births reported previously for 35 zonal, regional and district hospitals in Tanzania [##REF##32975558##12##]. Our findings support emerging evidence for high risk of neonatal and perinatal mortality in hospitals in the densely populated urban areas in Dar es Salaam, which may be similar to other urban centers in East Africa [##UREF##5##9##, ##UREF##6##10##, ##REF##32975558##12##].</p>", "<p id=\"Par51\">The high pre-facility stillbirth rate serves as a stark reminder of the imperative to enhance antenatal care to encompass vigilant monitoring and swift response to maternal and fetal complications, especially during the third trimester of pregnancy. This is not only crucial to the study hospitals but also in all referring healthcare facilities [##REF##35686582##43##]. Women with high-risk pregnancies, including those with hypertension require timely diagnosis, more frequent visits, accurate gestational age dating, monitoring of fetal growth and wellbeing, and planned birth often by 39 weeks gestation or earlier when required [##REF##28029221##44##–##REF##19656558##46##]. Notably, we found an excessive number of women with unknown gestational age either due to unknown last menstrual period or missing data, and very few women (5.2%) had access to an early ultrasound. This presents a challenge in planning the time of birth for women with high risk pregnancies or with complications such as hypertension [##UREF##20##47##]. Also, lack of clarity in the guidelines regarding when to induce labor may have contributed to the high burden of pre-facility stillbirth related to hypertensive disorders [##REF##31915022##39##, ##REF##35363951##45##, ##UREF##21##48##–##UREF##26##53##].</p>", "<p id=\"Par52\">Furthermore, we found a strong association between neonates with birthweights between 2,000 to 2,500 g and risks of perinatal death, confirming findings from other studies that low birth weight and prematurity are independent risk factors for poor perinatal outcome [##REF##29632623##54##]. We also recognize that due to the unreliability of gestational age, we could not differentiate co-existent intrauterine fetal growth restriction [##REF##35624505##55##, ##UREF##27##56##].</p>", "<p id=\"Par53\"> Importantly, pregnant women need quality care throughout the continuum of pregnancy and birth. Increasing the number of visits in the third trimester without strategic investments to address structural gaps in resources and healthcare provider’s skills will add to the workload and is unlikely to reduce the burden of preventable stillbirths and the socioeconomic benefits from lowered mortality [##REF##26794073##57##].</p>", "<p id=\"Par54\">Our study sheds light on the operations of high-volume maternity units in an urban setting where a wide spectrum of both low and high-risk pregnancies are managed, including potentially life-threatening obstetric complications such as hypertension and uterine rupture [##REF##28049520##34##, ##UREF##28##58##]. This scenario suggests a high-intensity work environment where our study noted that 88% of all CSs were performed as urgent procedures. Within these specific five hospitals, there are notable constraints due to the presence of only one operating theater, high staff turnover, and limited available workforce, which are considerably impeding effective monitoring of women during labor and birth [##REF##31915022##39##]. This situation vividly illustrates the interconnected complex interplay between obstetric complications, infrastructural limitations, insufficient skills, delayed response, adverse perinatal outcomes and an urban healthcare system functioning under immense pressure. Notwithstanding the critical shortage of staff, the findings from our study strongly underscore the pressing necessity to enhance the skills of healthcare providers in managing the second stage of labor, particularly in the case of breech presentation.</p>", "<p id=\"Par55\">Finally, it must be noted that this study was conducted in 2020, where the onset of the COVID-19 pandemic intensified stress on existing fragile low-resource urban health systems [##UREF##29##59##]. This may have worsened maternity care provision compared to previous years. The COVID-stressor, however, may also be seen as yet another of the many stressors on the urban healthcare system, such as massive urbanization, climate change and political changes. They each, and in combination, expose weaknesses in the provision of maternal healthcare, as here shown, and they require a call for inter-sectoral collaboration to deliver action to ensure safe care for women and children.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par56\">This study includes extensive data on facility births from multiple busy public maternity hospitals that receive women with a mix of low- and high-risk pregnancies, predominantly of lower-socio economic status, and referred from the entire Dar es Salaam region, thereby providing an in-depth understanding of the urban disadvantage experienced by women during pregnancy and childbirth in Dar es Salaam. There are, however, limitations to this study.</p>", "<p id=\"Par57\">This was a retrospective study using data from routine health information systems. Previous studies report that hospital registers may have a high sensitivity and specificity for reporting perinatal outcomes [##REF##30052662##60##, ##REF##33765942##61##]. Furthermore, the Dar es Salaam quality improvement initiative has invested in strengthening routine data at the study HFs since 2010 [##UREF##9##21##]. Yet, we recognize that the quality of data may not be optimal. We acknowledge that facility-based pre-discharge neonatal mortality, although high, may still be an underestimate, as we could not include neonates who may have died after discharge or referral. We recognize that stillbirths and early neonatal deaths are prone to misclassification, particularly in understaffed facilities where fetal motion, heart rate or respiration in a liveborn infant may not have been observed [##REF##31915022##3##, ##REF##27832753##26##].</p>", "<p id=\"Par58\">Even though we included all eligible cases, the 287 intra-facility perinatal deaths fell short of the 395 required in the initial power calculation. (A proportion of these could not be included due to missing case files). Furthermore, concerning hypertensive disorders, our data and practices in the study HFs did not allow for clinical classification of hypertension with or without severe features. Also, mild cases of hypertension may have been under-reported due to poor documentation. Consequently, the more severe types of hypertensive disorders may more likely have been captured, resulting in selection bias. Lack of storage capacity, poor protection of case notes (particularly during the COVID-19 pandemic), deficient documentation and missing files contributed to shortfall in intra-facility perinatal deaths and may also have resulted in selection bias, which potentially could have resulted in an underestimation of the strength of the associations between the determinants and perinatal deaths. The targeted care for teenagers, grand multiparous women of advanced maternal age and women with previous adverse obstetric outcomes is part of the decade long quality improvement initiative at the five study HFs and may explain the unexpected lower odds for intra-facility deaths in these high-risk groups [##UREF##10##22##].</p>", "<p id=\"Par59\">We used the term pre-facility stillbirth, where the point of reference was presence or absence of fetal heart sounds on admission [##REF##28892306##31##]. The term pre-facility stillbirth is not entirely synonymous to ‘antepartum stillbirths’ (pre- labor) or ‘macerated stillbirths’, which is based on fetal appearance [##REF##26794078##5##]. Gold et al. consider fetal appearance an unreliable surrogate marker for determining the time of fetal death [##UREF##14##28##]. These differences in terminology may make comparison of our findings with other studies challenging. Our categorization was the most feasible in the setting and provides a reliable distinction between stillbirths that occurred before or after admission to HFs during labor and birth, but requires accurate fetal heart rate documentation on admission [##REF##30052662##60##].</p>" ]
[ "<title>Conclusion and recommendations</title>", "<p id=\"Par60\">This study unfolds a high burden of preventable perinatal deaths among urban women in Tanzania with potentially viable newborns in a setting of high antenatal care attendance and high institutional birth rates. The determinants of perinatal death were linked to substandard quality of antenatal and intrapartum care. Context-specific interventions to strengthen the skills and resources for health providers to manage high-risk pregnancies and the second stage of labor are required to address the tremendous burden of perinatal loss in urban maternal health. Further prospective studies that include the wider referral system are recommended to understand and address the complexity of urban perinatal deaths. Each perinatal death is a preventable tragedy requiring urgent mitigation through global, national, regional and city-based prioritization, which has the potential of major socioeconomic return on investment.</p>" ]
[ "<title>Introduction</title>", "<p id=\"Par1\">Tanzania has one of the highest burdens of perinatal mortality, with a higher risk among urban versus rural women. To understand the characteristics of perinatal mortality in urban health facilities, study objectives were: I. To assess the incidence of perinatal deaths in public health facilities in Dar es Salaam and classify these into a) pre-facility stillbirths (absence of fetal heart tones on admission to the study health facilities) and b) intra-facility perinatal deaths before discharge; and II. To identify determinants of perinatal deaths by comparing each of the two groups of perinatal deaths with healthy newborns.</p>", "<title>Methods</title>", "<p id=\"Par2\">This was a retrospective cohort study among women who gave birth in five urban, public health facilities in Dar es Salaam. I. Incidence of perinatal death in the year 2020 was calculated based on routinely collected health facility records and the Perinatal Problem Identification Database. II. An embedded case–control study was conducted within a sub-population of singletons with birthweight ≥ 2000 g (excluding newborns with congenital malformations); pre-facility stillbirths and intra-facility perinatal deaths were compared with ‘healthy newborns’ (Apgar score ≥ 8 at one and ≥ 9 at five minutes and discharged home alive). Descriptive and logistic regression analyses were performed to explore the determinants of deaths.</p>", "<title>Results</title>", "<p id=\"Par3\">A total of 37,787 births were recorded in 2020. The pre-discharge perinatal death rate was 38.3 per 1,000 total births: a stillbirth rate of 27.7 per 1,000 total births and an intra-facility neonatal death rate of 10.9 per 1,000 live births. Pre-facility stillbirths accounted for 88.4% of the stillbirths. The case-control study included 2,224 women (452 pre-facility stillbirths; 287 intra-facility perinatal deaths and 1,485 controls), 99% of whom attended antenatal clinic (75% with more than three visits). Pre-facility stillbirths were associated with low birth weight (cOR 4.40; (95% CI: 3.13-6.18) and with maternal hypertension (cOR 4.72; 95% CI: 3.30-6.76). Intra-facility perinatal deaths were associated with breech presentation (aOR 40.3; 95% CI: 8.75-185.61), complications in the second stage (aOR 20.04; 95% CI: 12.02-33.41), low birth weight (aOR 5.57; 95% CI: 2.62-11.84), cervical dilation crossing the partograph’s action line (aOR 4.16; 95% CI:2.29-7.56), and hypertension during intrapartum care (aOR 2.9; 95% CI 1.03-8.14), among other factors. </p>", "<title>Conclusion</title>", "<p id=\"Par4\">The perinatal death rate in the five urban hospitals was linked to gaps in the quality of antenatal and intrapartum care, in the study health facilities and in lower-level referral clinics. Urgent action is required to implement context-specific interventions and conduct implementation research to strengthen the urban referral system across the entire continuum of care from pregnancy onset to postpartum. The role of hypertensive disorders in pregnancy as a crucial determinant of perinatal deaths emphasizes the complexities of maternal-perinatal health within urban settings. </p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12884-023-06096-1.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>The authors would like to recognize the leadership, collaboration and tremendous support of DSM Regional and Municipal health offices, the health facility management teams of the five study HF’s and the management of CCBRT. The authors sincerely appreciate the efforts of the Dar es Salaam perinatal case-control study team for their significant time, effort, and commitment in supporting the perinatal deaths case-file retrieval, case-file audits, and data entry. The participating health facilities and list of members of the perinatal case control study team are here listed: Regional Referral Hospital: Daniel Nkungu, Luzango Maembe, Ester Hyera, Hilda Haule, Aurelia Temba, Lumuliko Nyika and Julius Nyambarino, Zainabu Muniro, Subira Maulid, Nuswe Ambokile, Mayasa S. Issah, Mtingele Sangalala, Scolastica Bayongo. Municipal Maternity Hospitals: Rukia Msumi, Judith Mrosso, Meri Kebwe, John Shayo, Idrissa Kabanda, Joyce Lema, Mashaka John. We thank Imani Iremi for development of the perinatal case control database and the data entry form, as well as supporting data quality and cleaning. We are also grateful to Sidney Mboya, who manages the perinatal problem identification database (2014- 2020) and provided the annual birth and perinatal outcome data. We appreciate the extensive work done by Anna Macha in completing data entry and data cleaning. We thank Andreas Kryger Jensen, PhD, Associate Professor, University of Copenhagen, Section of Biostatistics, for reviewing the paper.</p>", "<title>Patient and public involvement</title>", "<p id=\"Par61\">Patients and public were not involved.</p>", "<title>Authors’ contributions</title>", "<p>Conceived and designed the study: BSD, NM. Implementation of the study: BSD, TWJ, ZM, IK, RM, LM, MS. Data processing: BSD, CF; Statistical analysis: BSD, TWJ, JM. Wrote the first draft of the paper: BSD. Developed tables/figures: BSD, TWJ, MLK. All authors had full access to the study protocol, results and contributed to multiple revisions of the draft and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This article forms part of the PhD thesis for BSD, and contributes to the situational analysis of the PartoMa project, which is funded by the Danida Fellowship center, Ministry of Foreign Affairs, Denmark (Danida project 18–08-KU).BSD is employed at CCBRT as Technical Advisor of the maternal and newborn healthcare program through the generous support from Global Affairs Canada that supported the Maternal and newborn healthcare program and the perinatal death audits in Dar es Salaam before and during the COVID-19 pandemic (2014–2021).</p>", "<p>Donors had no role in the design, data collection, analysis, decision to publish or preparation of the manuscript.</p>", "<title>Availability of data and materials</title>", "<p>The data generated from this study are available in this published article (and the supplementary tables). Additional information is available on request from the corresponding author.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par62\">Ethical approval was obtained from the ethics committee, Tanzanian National Health Research Ethics Review Committee (NatHREC), of the Tanzanian National Institute for Medical Research (NIMR/HQ/R.8c/Vol. I/1950). Letters of permission for the study were obtained from the Ministry of Health (Tanzania), the management of the Dar es salaam regional health authorities and the management of the participating health facilities. The study is a retrospective review of medical records. All patient identities were anonymized and assigned a research number. The authors confirm that during this study no patients were interviewed, nor were any experiments performed on humans or human tissue samples. Individually obtained informed consent was therefore deemed not required. A waiver for informed consent was obtained from the ethics review committee (NatHREC) of the Tanzanian National Institute for Medical Research. The authors declare that this study was performed in accordance with relevant guidelines and regulations.</p>", "<title>Consent for publication</title>", "<p id=\"Par63\">Permission to publish was obtained from the director of research information and regulatory affairs, Tanzanian National Institute for Medical Research (Ref. No: NIMR/HQ/P.12 VOL XXXV/110).</p>", "<title>Competing interests</title>", "<p id=\"Par64\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Definition of stillbirths and perinatal deaths in this study, based on the WHO International Classification of Disease and other studies [##UREF##12##25##, ##REF##27832753##26##, ##REF##21496911##29##]</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Variables of interest included in the embedded case-control study</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Flow chart for selection of the case-control study population</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Description of total births, perinatal deaths, maternal deaths, cesarean births, and vacuum assisted births in five urban health facilities in Dar es Salaam in 2020<sup>a</sup></p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\"><bold>Total</bold></th><th align=\"left\" colspan=\"3\"><bold>Regional Referral Hospitals</bold></th><th align=\"left\" colspan=\"2\"><bold>Primary Maternity Hospitals</bold></th></tr><tr><th align=\"left\">ALL</th><th align=\"left\">HF1</th><th align=\"left\">HF2</th><th align=\"left\">HF3</th><th align=\"left\">HF4</th><th align=\"left\">HF5</th></tr></thead><tbody><tr><td align=\"left\">Total Births (TB)</td><td align=\"left\"><bold>37,787</bold></td><td align=\"left\">5,803</td><td align=\"left\">8,384</td><td align=\"left\">5,826</td><td align=\"left\">10,337</td><td align=\"left\">7,437</td></tr><tr><td align=\"left\">Live Births (LB)</td><td align=\"left\"><bold>36,758</bold></td><td align=\"left\">5,617</td><td align=\"left\">8,128</td><td align=\"left\">5,589</td><td align=\"left\">10,127</td><td align=\"left\">7,297</td></tr><tr><td align=\"left\">Cesarean section births (n)</td><td align=\"left\"><bold>10,375</bold></td><td align=\"left\">2,118</td><td align=\"left\">2,043</td><td align=\"left\">2,406</td><td align=\"left\">2,211</td><td align=\"left\">1,597</td></tr><tr><td align=\"left\">Cesarean section rates (%)</td><td align=\"left\"><bold>27.5</bold></td><td align=\"left\">36.5</td><td align=\"left\">24.4</td><td align=\"left\">41.3</td><td align=\"left\">21.4</td><td align=\"left\">21.5</td></tr><tr><td align=\"left\">Vacuum assisted births (n)</td><td align=\"left\"><bold>934</bold></td><td align=\"left\">121</td><td align=\"left\">355</td><td align=\"left\">151</td><td align=\"left\">177</td><td align=\"left\">130</td></tr><tr><td align=\"left\">Vacuum assisted rates (%)</td><td align=\"left\"><bold>2.5</bold></td><td align=\"left\">2.1</td><td align=\"left\">4.2</td><td align=\"left\">2.6</td><td align=\"left\">1.7</td><td align=\"left\">1.7</td></tr><tr><td align=\"left\">Neonatal deaths (1)</td><td align=\"left\"><bold>399</bold></td><td align=\"left\">92</td><td align=\"left\">179</td><td align=\"left\">74</td><td align=\"left\">26</td><td align=\"left\">28</td></tr><tr><td align=\"left\">Stillbirths (2)</td><td align=\"left\"><bold>1,048</bold></td><td align=\"left\">186</td><td align=\"left\">256</td><td align=\"left\">237</td><td align=\"left\">210</td><td align=\"left\">159</td></tr><tr><td align=\"left\">Perinatal deaths (sum of 1 and 2)</td><td align=\"left\"><bold>1,447</bold></td><td align=\"left\">278</td><td align=\"left\">435</td><td align=\"left\">311</td><td align=\"left\">236</td><td align=\"left\">187</td></tr><tr><td align=\"left\">Maternal deaths</td><td align=\"left\"><bold>42</bold></td><td align=\"left\">9</td><td align=\"left\">7</td><td align=\"left\">9</td><td align=\"left\">15</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Neonatal death rate/1000 LB</td><td align=\"left\"><bold>10.9</bold></td><td align=\"left\">16.4</td><td align=\"left\">22.0</td><td align=\"left\">13.2</td><td align=\"left\">2.6</td><td align=\"left\">3.8</td></tr><tr><td align=\"left\">Stillbirth rate/1000 TB</td><td align=\"left\"><bold>27.7</bold></td><td align=\"left\">32.1</td><td align=\"left\">30.5</td><td align=\"left\">40.7</td><td align=\"left\">20.3</td><td align=\"left\">21.4</td></tr><tr><td align=\"left\">Perinatal death rate/1000 TB</td><td align=\"left\"><bold>38.3</bold></td><td align=\"left\">47.9</td><td align=\"left\">51.9</td><td align=\"left\">53.4</td><td align=\"left\">22.8</td><td align=\"left\">25.1</td></tr><tr><td align=\"left\">Maternal Mortality Ratio/100000 LB</td><td align=\"left\"><bold>114.3</bold></td><td align=\"left\">160.2</td><td align=\"left\">86.1</td><td align=\"left\">161.0</td><td align=\"left\">148.1</td><td align=\"left\">27.4</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Background characteristics in the case–control population, 2,224 singleton pregnancies with birthweight ≥ 2000 g, (excluding congenital malformations) in five urban health facilities in Dar es Salaam</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Total n (%)</th><th align=\"left\">Healthy babies n (%)</th><th align=\"left\">Pre-facility stillbirths n (%)</th><th align=\"left\">Intra-facility perinatal deaths n (%)</th><th align=\"left\"><italic>p-</italic>value</th></tr></thead><tbody><tr><td align=\"left\"><bold>Total</bold></td><td align=\"left\">2,224</td><td align=\"left\">1,485 (66.8)</td><td align=\"left\">452 (20.3)</td><td align=\"left\">287 (12.9)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"6\"><bold>Age groups (years)</bold></td></tr><tr><td align=\"left\"> 15–19</td><td align=\"left\">211 (9.5)</td><td align=\"left\">164 (11.0)</td><td align=\"left\">25 (5.5)</td><td align=\"left\">22 (7.7)</td><td align=\"left\"><bold> &lt; 0.001</bold></td></tr><tr><td align=\"left\"> 20—35</td><td align=\"left\">1,760 (79.1)</td><td align=\"left\">1,174 (79.1)</td><td align=\"left\">361 (79.7)</td><td align=\"left\">225 (78.4)</td><td align=\"left\"/></tr><tr><td align=\"left\"> 36—45</td><td align=\"left\">253 (11.4)</td><td align=\"left\">147 (9.9)</td><td align=\"left\">66 (14.6)</td><td align=\"left\">40 (13.9)</td><td align=\"left\"/></tr><tr><td align=\"left\"><bold>Mean Age (SD)</bold></td><td align=\"left\">27 (6.2)</td><td align=\"left\">26.5 (6.1)</td><td align=\"left\">28.2 (6.3)</td><td align=\"left\">27.5 (6.3)</td><td align=\"left\"><bold> &lt; 0.001</bold></td></tr><tr><td align=\"left\" colspan=\"6\"><bold>Parity after current birth</bold></td></tr><tr><td align=\"left\"> Para 1</td><td align=\"left\">893 (40.2)</td><td align=\"left\">625 (42.1)</td><td align=\"left\">153 (33.8)</td><td align=\"left\">115 (40.1)</td><td align=\"left\"><bold>0.009</bold></td></tr><tr><td align=\"left\"> Para 2—4</td><td align=\"left\">1,197 (53.8)</td><td align=\"left\">775 (52.2)</td><td align=\"left\">262 (57.9)</td><td align=\"left\">160 (55.7)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Para ≥ 5</td><td align=\"left\">134 (6.03)</td><td align=\"left\">85 (5.7)</td><td align=\"left\">37 (8.2)</td><td align=\"left\">12 (4.2)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"5\"><bold>Gestation age (weeks)</bold></td><td align=\"left\"/></tr><tr><td align=\"left\"> &lt; 37</td><td align=\"left\">305 (13.7)</td><td align=\"left\">119 (8.0)</td><td align=\"left\">143 (31.6)</td><td align=\"left\">43 (14.9)</td><td align=\"left\"><bold> &lt; 0.001</bold></td></tr><tr><td align=\"left\"> 37–40</td><td align=\"left\">1,022 (45.9)</td><td align=\"left\">751 (50.6)</td><td align=\"left\">150 (33.2)</td><td align=\"left\">121 (42.2)</td><td align=\"left\"/></tr><tr><td align=\"left\"> &gt; 40</td><td align=\"left\">721 (32.4)</td><td align=\"left\">514 (34.6)</td><td align=\"left\">116 (25.7)</td><td align=\"left\">91 (31.7)</td><td align=\"left\"/></tr><tr><td align=\"left\">Missing information</td><td align=\"left\">176 (7.9)</td><td align=\"left\">101 (6.8)</td><td align=\"left\">43 (9.5)</td><td align=\"left\">32 (11.2)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"6\"><bold>Antenatal clinic attendance</bold></td></tr><tr><td align=\"left\"> Never attended</td><td align=\"left\">8 (0.4)</td><td align=\"left\">2 (0.1)</td><td align=\"left\">3 (0.7)</td><td align=\"left\">3 (1.0)</td><td align=\"left\"><bold> &lt; 0.001</bold></td></tr><tr><td align=\"left\"> 1–3 visits</td><td align=\"left\">518 (23.3)</td><td align=\"left\">317 (21.3)</td><td align=\"left\">153 (33.8)</td><td align=\"left\">48 (16.7)</td><td align=\"left\"/></tr><tr><td align=\"left\"> 4–6 visits</td><td align=\"left\">1,471 (66.1)</td><td align=\"left\">1,021 (68.8)</td><td align=\"left\">260 (57.5)</td><td align=\"left\">190 (66.2)</td><td align=\"left\"/></tr><tr><td align=\"left\"> &gt; 6 visits</td><td align=\"left\">156 (7.0)</td><td align=\"left\">115 (7.7)</td><td align=\"left\">23 (5.1)</td><td align=\"left\">18 (6.2)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">71 (3.2)</td><td align=\"left\">30 (2.0)</td><td align=\"left\">13 (2.9)</td><td align=\"left\">28 (9.7)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"6\"><bold>Past history of perinatal death</bold></td></tr><tr><td align=\"left\"> Yes-previous perinatal death</td><td align=\"left\">194 (14.6)</td><td align=\"left\">135 (15.7)</td><td align=\"left\">47 (15.7)</td><td align=\"left\">12 (7.0)</td><td align=\"left\"><bold>0.001</bold></td></tr><tr><td align=\"left\"> No previous perinatal death</td><td align=\"left\">1,137 (85.4)</td><td align=\"left\">725 (84.3)</td><td align=\"left\">252 (84.3)</td><td align=\"left\">160 (93.0)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Para 1 (First pregnancy-excluded)</td><td align=\"left\">893 (40.2)</td><td align=\"left\">625 (42.1)</td><td align=\"left\">153 (33.9)</td><td align=\"left\">115 (40.1)</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Determinants of perinatal death in the case-control study’s 2224 singleton pregnancies with birthweight ≥ 2000 grams in five urban health facilities in Dares Salaam (excluding congenital malformations)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\"><bold>Total</bold></th><th align=\"left\"><bold>Healthy babies</bold></th><th align=\"left\"><bold>Pre-facility stillbirths</bold><sup><bold>a</bold></sup></th><th align=\"left\"><bold>Intra-facility perinatal deaths</bold><sup><bold>b</bold></sup></th><th align=\"left\"><bold>Bivariate logistic regression (compared to healthy babies)</bold></th><th align=\"left\"><bold>Multivariable logistic regression (compared to healthy babies)</bold></th></tr><tr><th align=\"left\"><italic>N</italic>=2,224 (%)</th><th align=\"left\"><italic>N</italic>=1,485 (%)</th><th align=\"left\"><italic>N</italic>=452 (%)</th><th align=\"left\"><italic>N</italic>=287 (%)</th><th align=\"left\">*Pre-facility stillbirths</th><th align=\"left\">**Intra-facility perinatal deaths</th></tr></thead><tbody><tr><td align=\"left\"><bold>Age (years)</bold></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">cOR (95%CI)</td><td align=\"left\">aOR (95%CI)</td></tr><tr><td align=\"left\"> 15- 19 years</td><td align=\"left\">211 (9.5)</td><td align=\"left\">164 (11.0)</td><td align=\"left\">25 (5.5)</td><td align=\"left\">22 (7.7)</td><td align=\"left\"><bold>0.50 (0.32-0.77)</bold></td><td align=\"left\">0.45 (0.18-1.13)</td></tr><tr><td align=\"left\"> 20 - 35 years</td><td align=\"left\">1,760 (79.1)</td><td align=\"left\">1,174 (79.1)</td><td align=\"left\">361 (79.7)</td><td align=\"left\">225 (78.4)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> 36 - 45 years</td><td align=\"left\">253 (11.4)</td><td align=\"left\">147 (9.9)</td><td align=\"left\">66 (14.6)</td><td align=\"left\">40 (13.9)</td><td align=\"left\">1.46 (1.07-2.02)</td><td align=\"left\">0.89 (0.42-1.89)</td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"><bold>Parity</bold></td><td align=\"left\" colspan=\"6\"/></tr><tr><td align=\"left\"> Para 1</td><td align=\"left\">893 (40.2)</td><td align=\"left\">625 (42.1)</td><td align=\"left\">153 (33.8)</td><td align=\"left\">115 (40.1)</td><td align=\"left\">0.72 (0.58-0.91)</td><td align=\"left\">1.02 (0.60-1.76)</td></tr><tr><td align=\"left\"> Para 2-4</td><td align=\"left\">1,197 (53.8)</td><td align=\"left\">775 (52.2)</td><td align=\"left\">262 (57.9)</td><td align=\"left\">160 (55.7)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Para ≥ 5</td><td align=\"left\">134 (6.0)</td><td align=\"left\">85 (5.7)</td><td align=\"left\">37 (8.2)</td><td align=\"left\">12 (4.2)</td><td align=\"left\">1.29 (0.85-1.94)</td><td align=\"left\">0.99 (0.37-2.65)</td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"><bold>Referral status</bold></td><td align=\"left\" colspan=\"6\"/></tr><tr><td align=\"left\"> Self-referred from home</td><td align=\"left\">1,807 (81.3)</td><td align=\"left\">1,281 (86.3)</td><td align=\"left\">308 (68.1)</td><td align=\"left\">218 (75.9)</td><td align=\"left\">0.53 (0.35-0.80)</td><td align=\"left\">0.86 (0.30-2.48)</td></tr><tr><td align=\"left\"> Study HFs<sup>c</sup></td><td align=\"left\">134 (6.0)</td><td align=\"left\">77 (5.2)</td><td align=\"left\">35 (7.7)</td><td align=\"left\">22 (7.7)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Peripheral HFs (lower-level HFs)</td><td align=\"left\">283 (12.8)</td><td align=\"left\">127 (8.5)</td><td align=\"left\">109 (24.1)</td><td align=\"left\">47 (16.4) </td><td align=\"left\"><bold>1.89 (1.17-3.03)</bold></td><td align=\"left\">1.05 (0.32-3.47)</td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"6\"><bold>Antenatal risk factor</bold><sup>d</sup></td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">1,930 (86.8)</td><td align=\"left\">1,346 (90.7)</td><td align=\"left\">354 (78.3)</td><td align=\"left\">230 (80.1)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">  294 (13.2)</td><td align=\"left\">139 (9.4)</td><td align=\"left\">  98 (21.7)</td><td align=\"left\">   57 (19.9)</td><td align=\"left\"><bold>2.68 (2.02-3.56)</bold></td><td align=\"left\">3.70 (1.96-6.98)</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Admission danger sign documented</bold><sup>e</sup></td></tr><tr><td align=\"left\"> None</td><td align=\"left\">1,720 (77.3)</td><td align=\"left\">1,315 (88.5)</td><td align=\"left\">200 (44.2)</td><td align=\"left\">205 (71.4)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Yes-danger sign</td><td align=\"left\">504 (22.7)</td><td align=\"left\">170 (11.4)</td><td align=\"left\">252 (55.7)</td><td align=\"left\">82 (28.6)</td><td align=\"left\"><bold>9.75 (7.63-12.45)</bold></td><td align=\"left\">1.51 (0.76-2.99)</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Any hypertension (hypertensive disorders described as a complication during labor and birth)</bold><sup><bold>f</bold></sup></td></tr><tr><td align=\"left\"> No hypertension</td><td align=\"left\">2,059 (92.6)</td><td align=\"left\">1,425 (95.9)</td><td align=\"left\">377 (83.4)</td><td align=\"left\">257 (89.6)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Any hypertension</td><td align=\"left\">165 (7.4)</td><td align=\"left\">60 (4.1)</td><td align=\"left\">75 (16.6)</td><td align=\"left\">30 (10.5)</td><td align=\"left\"><bold>4.72 (3.30-6.76)</bold></td><td align=\"left\"><bold>2.90 (1.03-8.14)</bold></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Stage of labour on admission (according to cervical dilatation)</bold></td></tr><tr><td align=\"left\"> Latent phase or earlier (0-3 cms)</td><td align=\"left\">621 (27.9)</td><td align=\"left\">387 (26.1)</td><td align=\"left\">138 (30.5)</td><td align=\"left\">96 (33.4) </td><td align=\"left\">1.77 (1.34-2.34)</td><td align=\"left\">1.22 (0.68-2.20)</td></tr><tr><td align=\"left\"><p> Early active phase</p><p>(4-6cms)</p></td><td align=\"left\">748 (33.6)</td><td align=\"left\">571 (38.4)</td><td align=\"left\">115 (25.4)</td><td align=\"left\">62 (21.6)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Late active phase &gt;6 cms</td><td align=\"left\">694 (31.2)</td><td align=\"left\">494 (33.3)</td><td align=\"left\">138 (30.5)</td><td align=\"left\">62 (21.6)</td><td align=\"left\">1.39 (1.05-1.83)</td><td align=\"left\">1.16 (0.65-2.07)</td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">161 (7.2)</td><td align=\"left\">33 (2.2)</td><td align=\"left\">61 (13.5)</td><td align=\"left\">67 (23.3)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"7\"><bold>Status of liquor on admission</bold></td></tr><tr><td align=\"left\"> Intact membranes</td><td align=\"left\">1,274 (57.3)</td><td align=\"left\">929 (62.5)</td><td align=\"left\">224 (49.6)</td><td align=\"left\">121 (42.2)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Clear liquor</td><td align=\"left\">486 (21.8)</td><td align=\"left\">392 (17.6)</td><td align=\"left\">44 (9.7)</td><td align=\"left\">50 (17.4)</td><td align=\"left\"><bold>0.47 (0.33-0.66)</bold></td><td align=\"left\">1.12 (0.65-1.91)</td></tr><tr><td align=\"left\"> Meconium liquor</td><td align=\"left\">125 (5.6)</td><td align=\"left\">39 (2.6)</td><td align=\"left\">60 (13.3)</td><td align=\"left\">26 (9.1) </td><td align=\"left\"><bold>6.38 (4.16-9.80)</bold></td><td align=\"left\"><bold>4.44 (1.86-10.57)</bold></td></tr><tr><td align=\"left\"> Blood-stained liquor</td><td align=\"left\">8 (0.4)</td><td align=\"left\">0</td><td align=\"left\">8 (1.7)</td><td align=\"left\">0</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">331 (14.9)</td><td align=\"left\">125 (8.4)</td><td align=\"left\">116 (25.6)</td><td align=\"left\">90 (31.3)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"7\"><bold>Prolonged labour, the partograph’s action line crossed</bold><sup><bold>g</bold></sup></td></tr><tr><td align=\"left\"> No</td><td align=\"left\">1,738 (78.1)</td><td align=\"left\">1,282 (86.3)</td><td align=\"left\">314 (69.5)</td><td align=\"left\">142 (49.5)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">168 (7.6)</td><td align=\"left\">89 (5.9)</td><td align=\"left\">30 (6.6)</td><td align=\"left\">49 (17.1)</td><td align=\"left\">1.38 (0.89-2.12)</td><td align=\"left\"><bold>4.16 (2.29-7.56)</bold></td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">318 (14.3)</td><td align=\"left\">114 (7.7)</td><td align=\"left\">108 (23.9)</td><td align=\"left\">96 (33.4)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"7\"><bold>Induction of labour</bold></td></tr><tr><td align=\"left\"> No induction</td><td align=\"left\">2,095 (94.2)</td><td align=\"left\">1,443 (97.2)</td><td align=\"left\">391 (86.5)</td><td align=\"left\">261 (90.9)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Induction of labour</td><td align=\"left\">129 (5.8)</td><td align=\"left\">42 (2.8)</td><td align=\"left\">61 (13.5)</td><td align=\"left\">26 (9.1)</td><td align=\"left\"><bold>5.36 (3.56-8.07)</bold></td><td align=\"left\"><bold>2.74 (0.97-7.72)</bold></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Mode of birth</bold></td></tr><tr><td align=\"left\"> Spontaneous vaginal birth</td><td align=\"left\">1,620 (72.8)</td><td align=\"left\">1,120 (75.4)</td><td align=\"left\">357 (78.9)</td><td align=\"left\">143 (49.8)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Vacuum extraction</td><td align=\"left\">28 (1.3)</td><td align=\"left\">12 (0.8)</td><td align=\"left\">4 (0.9)</td><td align=\"left\">12 (4.2)</td><td align=\"left\">1.05 (0.34-3.26)</td><td align=\"left\"><bold>6.23 (1.65-23.55)</bold></td></tr><tr><td align=\"left\"> Caesarean section</td><td align=\"left\">533 (24.0)</td><td align=\"left\">345 (23.2)</td><td align=\"left\">74 (16.4)</td><td align=\"left\">114 (39.7)</td><td align=\"left\"><bold>0.67 (0.51-0.89)</bold></td><td align=\"left\">0.93 (0.53-1.63)</td></tr><tr><td align=\"left\"> Breech</td><td align=\"left\">33 (1.5)</td><td align=\"left\">4 (0.3)</td><td align=\"left\">12 (2.7)</td><td align=\"left\">17 (5.9)</td><td align=\"left\"><bold>9.41 (3.02-29.36)</bold></td><td align=\"left\"><bold>40.3 (8.75-185.61)</bold></td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">10 (0.4)</td><td align=\"left\">4 (0.3)</td><td align=\"left\">5(1.1)</td><td align=\"left\">1 (0.3)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"7\"><bold>Challenges in the second stage of labour</bold><sup><bold>h</bold></sup></td></tr><tr><td align=\"left\"> No challenges documented</td><td align=\"left\">1,780 (80.0)</td><td align=\"left\">1,400 (94.3)</td><td align=\"left\">266 (58.9)</td><td align=\"left\">114(39.7)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">444 (19.7)</td><td align=\"left\">85 (5.7)</td><td align=\"left\">186 (41.2)</td><td align=\"left\">173 (60.3) </td><td align=\"left\"><bold>11.52 (8.63-15.36)</bold></td><td align=\"left\"><bold>20.04 (12.02-33.41)</bold></td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Birthweight</bold></td></tr><tr><td align=\"left\"> 2000-2499</td><td align=\"left\">251 (11.3)</td><td align=\"left\">73 (4.9)</td><td align=\"left\">122 (27.0)</td><td align=\"left\">56 (19.5)</td><td align=\"left\"><bold>4.40 (3.13-6.18)</bold></td><td align=\"left\"><bold>5.57 (2.62-11.84)</bold></td></tr><tr><td align=\"left\"> 2500-3000</td><td align=\"left\">683 (30.7)</td><td align=\"left\">434 (29.2)</td><td align=\"left\">165 (36.5)</td><td align=\"left\">84 (29.3)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> 3000-3499</td><td align=\"left\">829 (37.3)</td><td align=\"left\">634 (42.7)</td><td align=\"left\">96 (21.2)</td><td align=\"left\">99 (34.5)</td><td align=\"left\">0.41 (0.30-0.53)</td><td align=\"left\">0.76 (0.43-1.35)</td></tr><tr><td align=\"left\"> 3500-3999</td><td align=\"left\">355 (16.0)</td><td align=\"left\">281 (18.9)</td><td align=\"left\">41 (9.1)</td><td align=\"left\">33 (11.5)</td><td align=\"left\">0.38 (0.26-0.56)</td><td align=\"left\">0.44 (0.2-0.94)</td></tr><tr><td align=\"left\"> Greater than 4000</td><td align=\"left\">106 (4.7)</td><td align=\"left\">63 (4.2)</td><td align=\"left\">28 (6.2)</td><td align=\"left\">15 (5.2)</td><td align=\"left\">1.17 (0.72-1.89)</td><td align=\"left\">1.36 (0.49-3.82)</td></tr><tr><td align=\"left\"> Missing information</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">-</td><td align=\"left\">-</td></tr><tr><td align=\"left\" colspan=\"7\"><bold>Description and sub-analysis of Blood pressure measurement on admission</bold> (variable excluded from the main multivariable analysis)<sup>i</sup></td></tr><tr><td align=\"left\"> No hypertension</td><td align=\"left\">1,740 (78.2)</td><td align=\"left\">1,235 (83.2)</td><td align=\"left\">316 (69.9)</td><td align=\"left\">189 (65.9)</td><td align=\"left\">1<sup>^</sup></td><td align=\"left\">1<sup>^</sup></td></tr><tr><td align=\"left\"> Mild hypertension</td><td align=\"left\">249 (11.2)</td><td align=\"left\">146 (9.8)</td><td align=\"left\">72 (16.0)</td><td align=\"left\">31 (10.8)</td><td align=\"left\"><bold>1.93 (1.42-2.62)</bold></td><td align=\"left\">0.8 (0.36-1.78)</td></tr><tr><td align=\"left\"> Severe hypertension</td><td align=\"left\">71 (3.2)</td><td align=\"left\">36 (2.4)</td><td align=\"left\">28 (6.2)</td><td align=\"left\">7 (2.4)</td><td align=\"left\"><bold>3.04 (1.83-5.06)</bold></td><td align=\"left\">1.37 (0.32-5.77)</td></tr><tr><td align=\"left\"> Missing</td><td align=\"left\">164 (7.4)</td><td align=\"left\">68 (4.6)</td><td align=\"left\">36 (7.9)</td><td align=\"left\">60 (21.0)</td><td align=\"left\"/><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>HF</italic> Health facility</p><p><sup>a</sup>From Facility birth registers (MTUHA 12)</p></table-wrap-foot>", "<table-wrap-foot><p><italic>• due to rounding to one decimal place, the total percentages may not add up to exactly 100%</italic></p></table-wrap-foot>", "<table-wrap-foot><p>Notes: Statistically significant Odds Ratio and 95% confidence intervals have been bolded. Some of the percentages may be over 100% due to rounding up to one decimal place</p><p>1<sup>^</sup>refers to the reference sub-group</p><p><sup>*</sup>For the pre-facility stillbirths’ bivariate logistic regression is applied (some variables concern management after death, for instance, prolonged labour, challenges in second stage and mode of birth were intra-facility practices, among women who had no fetal heart tones on admission to the study HF (pre-facility stillbirths). This illustrates that women suffering from intrauterine fetal death prior to admission simultaneously had increased odds for suffering from prolonged labour and challenges in the second stage</p><p><sup>**</sup>For the Intra-facility perinatal deaths, a multivariable logistic regression is presented. Adjusted Odds Ratio (aOR) has been adjusted for age, parity, referral status, antenatal risk factors, admission danger signs, stage of labor on admission, status of liquor on admission, partograph use with labour crossing the action line, induction of labor, mode of birth, çhallenges second stage of labor, baby birthweight, any hypertension during labour or birth</p><p><sup>a</sup>Pre-facility stillbirths- arriving at the health facility (HF), without a fetal heart tone detected</p><p><sup>b</sup>Intra-facility perinatal death includes intra-facility stillbirths and early neonatal deaths before discharge</p><p><sup>c</sup>Admission from the antenatal ward of one of the five study health facilities</p><p><sup>d</sup>Antenatal risk factors obstetric history or past obstetric or medical risk factors derived from the Tanzanian Ministry of health antenatal clinic card (RCH card number 4, e.g., previous caesarean section, previous perinatal death, less than 20 years of age, long birth interval (more than 10 years), Rhesus negative blood group, pelvic deformity, maternal height less than 150 cm, diabetes, heart disease, tuberculosis, history of obstetric hemorrhage etc.); The 294 women, who answered yes to this question, reported more than one risk factor</p><p><sup>e</sup>Danger signs on admission: These include signs of maternal fetal complications (reduced fetal movements, vaginal bleeding, severe headache, blurred vision, severe abdominal pain, fits, or severe body weakness/fainting or fits</p><p><sup>f</sup>Any hypertension was obtained as a yes/no categorical variable, following audit of the medical notes. (It includes all forms of hypertension, mild, severe and nine women with eclampsia). The proportion appears lower than the variable \"measurement of hypertension on admission\", perhaps due to poor documentation, milder forms of hypertension maybe under recorded in the case-notes as explained in the limitation section)</p><p><sup>g</sup>The action line on the partograph is an arbitrarily line drawn 4 hours after the start of active labour, assuming that active labour starts at 4 cms and the cervix dilates at one cm per hour. In study HFs, cervical dilatation crossing the action line is considered prolonged labor</p><p><sup>h</sup>Challenges during the second stage included duration of second stage more than 2 h; cord around the neck, stuck head, shoulder dystocia, fetal distress, hemorrhage, rupture of uterus, perineal tear more than second degree, obstructed labor</p><p><sup>i</sup>Blood pressure on admission was the actual blood pressure on admission (continuous numeric) that was then categorized into three categories: no hypertension, mild hypertension and severe hypertension. The data collected for this variable did not enable classifying hypertension with or without severe features. A sub-analysis was performed with this variable (adjusted for age, parity and birthweight). This variable was excluded from the main multivariable model for intra-facility perinatal deaths</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12884_2023_6096_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12884_2023_6096_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12884_2023_6096_Fig3_HTML\" id=\"MO3\"/>" ]
[ "<media xlink:href=\"12884_2023_6096_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1:</bold>\n<bold> Supplementary Table 1.</bold> Routine antenatal clinic investigations and prophylaxis among 2224 women with singleton pregnancies ≥ 2000gms included in the case-control study population. <bold> Supplementary Table 2.</bold> Logistic regression for Pre-facility Stillbirths against live healthy newborns. <bold>Supplementary Table 3.</bold> Logistic regression for Intra-facility perinatal deaths (intrafacility stillbirths and early pre discharge neonatal deaths) compared to live healthy newborns.</p></caption></media>", "<media xlink:href=\"12884_2023_6096_MOESM2_ESM.pdf\"><caption><p><bold> Additional file 2.</bold> Perinatal case control study data collection tool.</p></caption></media>" ]
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{ "acronym": [ "LMIC", "HF", "HIC", "CCBRT", "CEmONC", "CS", "MTUHA", "PPIP", "WHO" ], "definition": [ "Low-and-middle income countries", "Health facility", "High-income countries", "Comprehensive Community Based Rehabilitation in Tanzania", "Comprehensive Emergency Obstetric and Newborn Care", "Cesarean Section", "Mfuma wa Taarifa za Uendeshaji Huduma za Afya—Swahili word referring to the Tanzania national health information system", "Perinatal Problem Identification Program", "World Health Organization" ] }
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2024-01-14 23:43:45
BMC Pregnancy Childbirth. 2024 Jan 13; 24:62
oa_package/5b/68/PMC10787400.tar.gz
PMC10787401
0
[ "<title>Introduction</title>", "<p id=\"Par12\">Neonatal hyperthyroidism (NH) is an uncommon condition that affects 1–5% of newborns born to mothers who have active or past Graves’ disease (GD) [##REF##21787128##1##], and it affects 22% of pregnant women who need to take long-term antithyroid drugs (ATDs) treatment. Autoimmune NH is related to the transplacental passage of maternal anti-thyrotropin receptor antibodies (TRAbs) [##REF##1356056##2##]. The fetal thyroid gland becomes responsive to thyroid-stimulating hormone (TSH) and TRAbs at around 20 weeks of gestation [##UREF##0##3##], those antibodies stimulating the fetal thyroid, cause in-utero and/or postnatal hyperthyroidism. Fetal hyperthyroidism can cause goiter, heart failure with nonimmune hydrops, advanced bone maturation, intrauterine growth retardation, preterm birth, and even fetal death [##REF##34863412##4##]. When fetal hyperthyroidism is present, there is a high probability of neonatal thyrotoxicosis, which is usually temporary and goes away in 4 to 6 months after birth following clearance of maternal TRAbs. Signs and symptoms of neonatal hyperthyroidism include goiter, tachycardia, poor feeding, irritability, tremors, sweating, and difficulty sleeping [##REF##34894265##5##]. There are occasional cases of proptosis, craniosynostosis, and microcephaly. Without prompt treatment with antithyroid drugs, cardiac failure and death may occur [##REF##29406005##6##].</p>", "<p id=\"Par13\">At present, there are only more than 50 cases of NH reported in China. Due to the diversity and lack of specificity of the clinical manifestations of the disease, clinicians lack understanding of the disease, which is easy to be overlooked or misdiagnosed [##UREF##1##7##]. To improve knowledge of early identification and treatment of NH, our study presented one case of NH with prominent clinical signs of liver and cardiac dysfunction, whose mother had received GD therapy with radioactive iodine four years prior.</p>" ]
[ "<title>Materials and methods</title>", "<title>Patient and clinical data</title>", "<p id=\"Par14\">This study analyzed one newborn with confirmed hyperthyroidism who was hospitalized in Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology and has been discharged. The study was appproved by the Tongji Hospital ethics committee. Informed consent was obtained from the patient’s parents.</p>", "<title>Data collection</title>", "<p id=\"Par15\">Clinical, and laboratory data, as well as therapeutic medication and clinical outcomes, were obtained from the electronic medical records.</p>", "<title>Definitions</title>", "<p id=\"Par16\">The enrolled newborn in this study was diagnosed with hyperthyroidism, according to the “Practice of Neonatology, 5th Ed”.</p>", "<p id=\"Par17\">The diagnostic criteria of NH were as follows: (1) The mother had a history of autoimmune thyroid disease, especially hyperthyroidism. (2) The newborn had typical symptoms and signs [##UREF##2##8##]: excitement, irritability, tremors; skin flushing, sweating; increased appetite, accompanied by vomiting and diarrhea, and unsatisfactory weight gain; he or she likes opening eyes, periorbital edema, eyelid contracture, and exophthalmos; goiter may be present; increased heart rate and respiration, hypertension, enlargement of liver and spleen, etc. Severe cases may have a fever, arrhythmia, heart failure and jaundice, liver failure, and coagulation disorders. (3) With laboratory examination: serum T3, and T4 increased, and TSH decreased. This neonate met the diagnostic criteria of NH.</p>" ]
[ "<title>Results</title>", "<title>Patient history and clinical features</title>", "<p id=\"Par18\">The neonate was delivered prematurely at 32<sup>+ 6</sup> weeks of gestation as the first offspring of unrelated parents. Her weight measured 2220 g (80%), length measured 47.5 cm (97%) and head circumference measured 28.5 cm (20%). Due to exhibiting symptoms of “moaning and foaming” immediately after birth, she was admitted to the Neonatal Intensive Care Unit (NICU). After admission, the neonate’s blood oxygen saturation was 65% without oxygen inhalation, and her shin wascyanotic, so CPAP (Continuous Positive Airway Pressure) assisted ventilation was given, but her dyspnea persisted after 4 h, and she developed “convulsion”. Consequently, invasive ventilator-assisted ventilation was initiated. The examination findings after admission are presented in Table ##TAB##0##1##, encompassing thrombocytopenia; elevated transaminase and total bilirubin, particularly direct bilirubin; hepatosplenomegaly, bile sludge formation; right heart enlargement, and the presence of pulmonary hypertension. The primary diagnoses are neonatal respiratory distress syndrome (NRDS) and intrauterine infection(?). In addition to respiratory support, administration of blood products, anti-infection agents, cardiac and hepatic protection, cholang-removing blood stasis, reduction of pulmonary artery pressure, and enhancement of circulation were implemented.</p>", "<p id=\"Par36\">\n\n</p>", "<title>Diagnosis</title>", "<p id=\"Par19\">After 2 weeks, the patient no longer requires oxygen assistance. However, there was no notable enhancement in liver and cardiac functionality. Additionally, the patient tended to open her eyes, an increased appetite but inadequate weight gain, and a rapid heart rate. Following consultation and pertinent examinations, we ruled out infection based on normal levels of inflammatory markers, negative results from blood culture, blood NGS-DNA, and a comprehensive panel of viral and other related pathogenic tests. Furthermore, inherited metabolic diseases were excluded based on normal levels of blood ammonia, lactic acid, pyruvate, blood amino acids, and urine organic acids. Lastly, rheumatic immune diseases were ruled out based on a negative complete set of rheumatism and the absence of any history of rheumatic immune system diseases in the patient’s family. We suspected that she had a genetic mutation-caused syndrome, so we advised the family to undergo comprehensive genetic testing. On the 15th day of her hospitalization, we conducted a routine screening for thyroid function and discovered that her TSH levels were below the normal range (TSH &lt; 0.05uIU/mL), while FT4 levels were significantly elevated (34.9ng/dL) (Table ##TAB##0##1##). Additionally, her thyroglobulin levels were above 500 ng/ml (reference range: 3.5–77 ng/ml), thyroglobulin antibody levels were 15.6 IU/ml (reference range: &lt;115 IU/ml), thyroid peroxidase antibody levels were 43 IU/ml (reference range: &lt;34 IU/ml), and Thyrotropin receptor antibody levels were 29.7 IU per liter (reference value, &lt; 1.75IU per liter). A thyroid ultrasound showed an increase in thyroid volume and abundant blood flow, leading to a diagnosis of NH.</p>", "<p id=\"Par20\">A thorough examination of the neonate’s mother’s medical history was conducted: her thyroid function (11/26, 2019): TSH 0.01 uIU/mL, T3 14.63 pg/mL, T4 3.56 ng/dL, TPOAb 44 U/mL, TGAb &lt; 15 U/mL. After Iodine 131 treatment, she has been treated with euthyrox orally until now, which further supported the neonate’s diagnosis of hyperthyroidism. Methimazole (0.5 mg/kg/d, Bid) and propranolol (1.8 mg/kg/d, Tid) were promptly added to the treatment regimen, and the neonate’s thyroid function was periodically reassessed. After taking methimazole and propranolol orally for 1 week, the levels of FT3 and FT4 decreased (Table ##TAB##0##1##). Additionally, the patient experienced a decrease in heart rate and an improvement in liver function (as indicated by decreased ALT, AST, and direct bilirubin levels), as well as a significant decrease in pulmonary artery pressure. The patient was discharged with medicine after 27 days of hospitalization.</p>", "<title>Follow-up examination</title>", "<p id=\"Par21\">After 25 days of medication, the levels of FT3 and FT4 (except TSH) returned to the normal range (Table ##TAB##0##1##; Fig. ##FIG##0##1##A). Methimazole and propranolol were discontinued after 29 days and 36 days of oral medication, respectively. The patient’s thyroid function completely returned to normal 13 days after withdrawal of methimazole, subsequent intermittent reexaminations confirmed the maintenance of normal thyroid function.</p>", "<p id=\"Par33\">\n\n</p>", "<p id=\"Par22\">With the improvement of thyroid function, catch-up growth of body weight and length was achieved. On day 72 after birth (postmenstrual age 42<sup>+ 6</sup> weeks), the neonates’ weight and length were at the 24.9 percentile and 92.9 percentile for their sex and gestational age, respectively. The neonatal behavioral neurological assessment (NBNA) score was 38. Notably, the patient’s cardiac function, liver function (Fig. ##FIG##0##1##B), and hepatosplenomegaly showed significant improvement. During the whole treatment period of hyperthyroidism, no adverse reactions such as granulocytopenia or liver function damage were observed.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par23\">In this study, we report a typical case of NH with critical condition and impaired liver and cardiac function as the main clinical manifestations. The patient’s mother had been receiving oral euthyrox treatment since undergoing Iodine 131 radiotherapy for GD four years ago. However, TRAbs levels were not monitored during pregnancy. NH was diagnosed on the 15th day after birth. During the period, a multi-disciplinary consultation was conducted to screen for infectious diseases, inherited metabolic diseases, rheumatic immune diseases, and, other conditions. The diagnosis process was complex, providing valuable experience for future NH diagnoses.</p>", "<p id=\"Par24\">The prevalence of hyperthyroidism in pregnancy ranges from 0.7 to 2.8% worldwide [##REF##27280373##9##, ##UREF##3##10##], with GD as the most common etiology [##REF##2635396##11##]. During pregnancy, thyroid autoantibodies can cross the placenta and either stimulate (thyroid stimulating antibody - TSAb) or block (thyroid blocking antibody - TBAb) the fetal thyroid gland [##REF##34863412##4##]. Maternally transferred antibodies can temporarily affect the thyroid function of the fetus and newborn until they are metabolized. High levels of TSAb transmission are associated with fetal and neonatal thyrotoxicosis, while maternal TBAb can lead to congenital hypothyroidism [##REF##8772590##12##]. The impact on thyroid function in the fetus and newborn depends not only on the type of maternal antibodies but also on their levels. Autoimmune hyperthyroidism can also occur in children born to mothers who were treated for GD in the past and still have detectable circulating TRAbs [##REF##32669187##13##], similar to our patient. TRAbs measurement is not routinely performed in mothers with hyperthyroidism in our hospital, which presents a challenge in identifying those who may develop NH. In our case, the mother’s TRAb levels were not regularly monitored during the 4 years after Iodine-131 radiotherapy, including pregnancy, although she was taking oral euthyrox and had stable thyroid hormone levels within the normal range. Obstetricians and neonatologists often overlook mothers with high-risk factors, leading to misdiagnosis and delayed diagnosis in newborns born to such mothers due to a lack of sufficient understanding in managing these cases.</p>", "<p id=\"Par25\">In China, it is recommended that TRAb should be monitored from 20 to 24 weeks of gestation in pregnant women with a history of Graves’ disease or delivery of a newborn with hyperthyroidism, regardless of whether they have received effective treatment. The American Thyroid Association (ATA) 2016 guidelines [##REF##27521067##14##] recommend that patients with Graves’ disease should be tested for serum TRAb in the first trimester of pregnancy. If TRAb levels are elevated, reexamination should take place at 18–22 and 30–34 weeks of gestation. A TRAb level of ≥ 5 IU/L or &gt; 3 times the upper limit of the reference value indicates a high risk of fetal/neonatal hyperthyroidism. Pregnant women with positive TRAb results should undergo a fetal thyroid ultrasound examination to further evaluate fetal thyroid function. Therefore, for high-risk pregnant women with a history of thyroid disease, it is crucial to detect thyroid function and serum TRAb as early as possible. Close observation of early symptoms of hyperthyroidism is the key to early diagnosis.</p>", "<p id=\"Par26\">The clinical manifestations of NH are non-specific and diverse [##UREF##2##8##], including tachycardia, irritability, irritability, thrombocytopenia, liver damage, jaundice, shortness of breath, hypoglycemia, hyperhidrosis, premature synostosis, intrauterine growth restriction, growth retardation, goiter, exophthalmia, pulmonary hypertension, hip dysplasia, etc. In severe cases, microcephaly, heart failure, long-term neurodevelopmental delay, and even death may occur. In our study, the neonate presented with growth retardation, tachycardia, cardiac insufficiency, dyspnea, thrombocytopenia, liver injury, and hepatosplenomegaly. Similar cases are often mistaken for intrauterine infection, sepsis, meconium aspiration, and other diseases. The main clinical manifestation in our case is damage to liver and heart function, particularly cholestatic hepatitis [##REF##32166702##15##], which is rare in NH and complicates the clinical diagnosis. Therefore, the crucial aspect in treating liver damage induced by hyperthyroidism is to manage hyperthyroidism itself. Once diagnosed, prompt administration of anti-hyperthyroidism treatment is essential.</p>", "<p id=\"Par27\">Due to the unique nature of the neonatal period, delayed diagnosis and treatment can hurt the physical growth and neurodevelopment of newborns. It is recommended to use ATDs early in neonates showing clinical symptoms of hyperthyroidism, with MMI being the preferred choice. PTU (propylthiouracil) should only be used for a short period in patients experiencing hyperthyroidism crises or severe adverse reactions to MMI. In this case, the patient was administered oral MMI at a dose of 0.5 mg/ kg, Bid. Propranolol (1–2 mg /(kg·d), Bid) can help reduce heart rate and inhibit the conversion of peripheral T4 to T3, especially in patients with increased heart rate. The patient’s heart rate significantly decreased after propranolol was added to her treatment plan. For patients with respiratory and heart failure, it is important to provide respiratory and circulatory support. Short-term glucocorticoids [hydrocortisone 2.5–10 mg /(kg·d), Tid; prednisone 1–2 mg /(kg·d), Bid] can be used to reduce T4 synthesis and peripheral T4 to T3 conversion [##UREF##4##16##]. In severe cases, intravenous immunoglobulin (1 g/kg for 2 days) may be administered [##REF##28439194##17##]. Adequate caloric supply is crucial in the nutritional support of neonatal hyperthyroidism, and the average course of ATDs treatment for NH is 1 to 3 months. During the initial stage of treatment, thyroid function should be regularly monitored every 1 to 2 weeks to adjust the drug dose. The symptoms gradually disappear with the decrease of TRAb concentration, and treatment can be discontinued when TRAb is negative [##UREF##4##16##]. In our patient’s case, the total duration of methimazole treatment was 29 days, and the first improvements were FT3 and FT4 levels, with TSH returning to normal levels 13 days after discontinuation of the medication.</p>", "<p id=\"Par28\">Pregnancy complicated with hyperthyroidism has hypermetabolism, increased nerve and muscle excitability, which can lead to uterine contraction and vasospasm, affect placental development, and cause intrauterine growth retardation, low birth weight, premature delivery, asphyxia, and even stillbirth or abortion [##UREF##1##7##, ##REF##31345521##18##]. In this particular case, the mother had thyroid disease and gave birth to a test-tube baby who was premature and experienced asphyxia after birth. This suggests that maternal thyroid disease can result in complications for the neonate or fetus. Normally, NH is transient and self-limited, resolving within 3–12 weeks. However, in cases of hyperthyroidism crisis, the mortality rate can be as high as 15-20% [##REF##29406005##6##]. Persistent cases are rare, mostly caused by gene mutations such as TSHR and GNAS, which can be inherited dominantly or occur as de novo mutations [##REF##29406005##6##]. Fortunately, in this case, the child was considered to have transient hyperthyroidism, and her thyroid function returned to normal at the age of 57 days without any lasting effects. It is important to regularly monitor the physical and neurodevelopment of children with hyperthyroidism after discharge.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par30\">NH encompasses gynecology, obstetrics, and neonatology. It is important to enhance the monitoring of thyroid function and TRAb in pregnant women with a history of thyroid disease. This will help assess the risk of neonatal hyperthyroidism. Additionally, it is crucial to promptly screen high-risk infants for thyroid function after birth. Early diagnosis and treatment can then be initiated before clinical symptoms worsen, thereby preventing the occurrence of a hyperthyroidism crisis and any potentially serious consequences.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">To outline the clinical signs, diagnosis, and course of care for a single case of neonatal hyperthyroidism while also summarizing common diagnostic errors related to this condition.</p>", "<title>Methods</title>", "<p id=\"Par2\">Medical records of the neonate of hyperthyroidism were collected and analyzed in combination with literature.</p>", "<title>Results</title>", "<p id=\"Par3\">The neonate’s mother had thyroid disease, but her thyrotropin receptor antibody (TRAb) levels were not monitored during pregnancy. The neonate exhibited typical symptoms of hyperthyroidism on the day of birth but was not diagnosed until 15 days later. Impaired liver (cholestasis, elevated liver enzymes) and cardiac function (pulmonary hypertension, right heart enlargement) are the main manifestations. Treatment with methimazole (1.0 mg /kg·d) and propranolol (2.0 mg /kg·d) led to recovery, and the neonate stayed in the hospital for 27 days before being discharged with medication. The diagnosis was temporary hyperthyroidism, and the medication was discontinued at 72 days of age.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">It is important to strengthen the management of high-risk pregnant women with thyroid disease. Monitoring TRAb levels in both mothers and neonates should be done dynamically to enable early prediction and diagnosis of neonatal hyperthyroidism. Most neonates with hyperthyroidism have a good prognosis when timely and appropriate medical treatment is provided.</p>", "<title>Impact</title>", "<p id=\"Par9\">The tortuous diagnosis processes of one case of NH.</p>", "<p id=\"Par10\">In the absence of specific clinical manifestations of NH, how to quickly diagnose it.</p>", "<p id=\"Par11\">Reminding clinicians of the importance of early identification of NH, as well as the management of pregnant women with abnormal thyroid function.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We thank the patients, their families, referral physicians, and investigators for their cooperation and contribution.</p>", "<title>Author contributions</title>", "<p>Concept and design: Lin Zhu and Wei Liu. Acquisition, analysis, or interpretation of data: Lin Zhu and Jing Wang. Statistical analysis: Lin Zhu. Drafting the paper: Lin Zhu and Jing Wang.</p>", "<title>Funding</title>", "<p>None.</p>", "<title>Data availability</title>", "<p>The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Authorship</title>", "<p id=\"Par39\">All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.</p>", "<title>Ethical approval and consent to participate</title>", "<p id=\"Par42\">All procedures performed in studies involving human participants were approved by the ethical standards of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology ethics committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from the patient’s parents.</p>", "<title>Conflict of interest</title>", "<p id=\"Par41\">The authors declare that they have no conflict of interest.</p>", "<title>Consent for publication</title>", "<p id=\"Par43\">NA.</p>", "<title>Competing interests</title>", "<p id=\"Par38\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The thyroid function (<bold>A</bold>) and liver function (<bold>B</bold>) of the neonate were followed up with age</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>The demographic, clinical and biochemical characteristics of the patient</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Age (Days)</th><th align=\"left\">0</th><th align=\"left\">1</th><th align=\"left\">4</th><th align=\"left\">6</th><th align=\"left\">8</th><th align=\"left\">15</th><th align=\"left\">23</th><th align=\"left\">40</th><th align=\"left\">57</th><th align=\"left\">72</th><th align=\"left\">93</th><th align=\"left\">108</th></tr></thead><tbody><tr><td align=\"left\">\n<bold>Corrected gestational age (weeks)</bold>\n</td><td align=\"left\">32<sup>+ 6</sup></td><td align=\"left\">33</td><td align=\"left\">33<sup>+ 3</sup></td><td align=\"left\">33<sup>+ 5</sup></td><td align=\"left\">34</td><td align=\"left\">35</td><td align=\"left\">35<sup>+ 6</sup></td><td align=\"left\">38<sup>+ 2</sup></td><td align=\"left\">40<sup>+ 5</sup></td><td align=\"left\">42<sup>+ 6</sup></td><td align=\"left\">45<sup>+ 6</sup></td><td align=\"left\">48</td></tr><tr><td align=\"left\">\n<bold>Weight (g)/%*</bold>\n</td><td align=\"left\">2220(80)</td><td align=\"left\">2200(77.8)</td><td align=\"left\">2020(69.5)</td><td align=\"left\">2090(46.1)</td><td align=\"left\">2120(46.5)</td><td align=\"left\">2060(23.3)</td><td align=\"left\">2100(13.1%)</td><td align=\"left\">2700(18.5)</td><td align=\"left\">NA</td><td align=\"left\">3600(24.9)</td><td align=\"left\">NA</td><td align=\"left\">5300(67.6)</td></tr><tr><td align=\"left\">\n<bold>Height (cm)/%*</bold>\n</td><td align=\"left\">47.5(97)</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">48(95.1)</td><td align=\"left\">NA</td><td align=\"left\">48(85.2)</td><td align=\"left\">49.6(90%)</td><td align=\"left\">50.1(69.7)</td><td align=\"left\">NA</td><td align=\"left\">55.5(92.2)</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\">\n<bold>Head circumference (cm)/%*</bold>\n</td><td align=\"left\">28.5(20)</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">31.6(6.5)</td><td align=\"left\">NA</td><td align=\"left\">34.2(0.0)</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\">\n<bold>NBNA</bold>\n</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">36</td><td align=\"left\">NA</td><td align=\"left\">38</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\">\n<bold>Blood biochemical parameters</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Leukocytes (3.5–9.5) 10<sup>9</sup>/ L</td><td align=\"left\">13.5</td><td align=\"left\">10.29</td><td align=\"left\">7.5</td><td align=\"left\">7.47</td><td align=\"left\">9</td><td align=\"left\">18.45</td><td align=\"left\">9.25</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Neutrophils (1.8–6.3) 10<sup>9</sup>/ L</td><td align=\"left\">10</td><td align=\"left\">6.29</td><td align=\"left\">3.94</td><td align=\"left\">3.2</td><td align=\"left\">3.89</td><td align=\"left\">7.97</td><td align=\"left\">3.37</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Hemoglobin (130–175 g/ L</td><td align=\"left\">187</td><td align=\"left\">177</td><td align=\"left\">190</td><td align=\"left\">173</td><td align=\"left\">170</td><td align=\"left\">167</td><td align=\"left\">142</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Platelets (125–350) 10<sup>9</sup>/ L</td><td align=\"left\">53</td><td align=\"left\">63</td><td align=\"left\">92</td><td align=\"left\">144</td><td align=\"left\">195</td><td align=\"left\">251</td><td align=\"left\">164</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Alanine aminotransferase (9–50) U/ L</td><td align=\"left\">86</td><td align=\"left\">95</td><td align=\"left\">80</td><td align=\"left\">94</td><td align=\"left\">137</td><td align=\"left\">212</td><td align=\"left\">175</td><td align=\"left\">105</td><td align=\"left\">77</td><td align=\"left\">93</td><td align=\"left\">21</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Aspartate aminotransferase (15–40) U/ L</td><td align=\"left\">366</td><td align=\"left\">298</td><td align=\"left\">273</td><td align=\"left\">334</td><td align=\"left\">331</td><td align=\"left\">355</td><td align=\"left\">232</td><td align=\"left\">109</td><td align=\"left\">63</td><td align=\"left\">71</td><td align=\"left\">46</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Total bilirubin (2-20.4) µmol/ L</td><td align=\"left\">149.3</td><td align=\"left\">177.1</td><td align=\"left\">279.1</td><td align=\"left\">326.4</td><td align=\"left\">315.6</td><td align=\"left\">258.5</td><td align=\"left\">173</td><td align=\"left\">108.7</td><td align=\"left\">42.3</td><td align=\"left\">22.2</td><td align=\"left\">6</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Direct bilirubin (2-20.4) µmol/ L</td><td align=\"left\">121.7</td><td align=\"left\">128</td><td align=\"left\">222.9</td><td align=\"left\">247.9</td><td align=\"left\">252.1</td><td align=\"left\">215.6</td><td align=\"left\">146.6</td><td align=\"left\">93.4</td><td align=\"left\">35.6</td><td align=\"left\">15.1</td><td align=\"left\">5.2</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> C-reactive protein (0-0.5) mg/ dL</td><td align=\"left\">1.4</td><td align=\"left\">1.5</td><td align=\"left\">1.48</td><td align=\"left\">1.9</td><td align=\"left\">2.15</td><td align=\"left\">&lt;0.5</td><td align=\"left\">&lt;0.5</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> TSH (0.27–4.2) uIU/mL</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.005</td><td align=\"left\">&lt; 0.005</td><td align=\"left\">&lt; 0.005</td><td align=\"left\">0.261</td><td align=\"left\">1.19</td><td align=\"left\">0.845</td><td align=\"left\">2.18</td></tr><tr><td align=\"left\"> FT3 (3.1–6.8) pmol/L</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">6.2</td><td align=\"left\">5.92</td><td align=\"left\">2.68</td><td align=\"left\">3.07</td><td align=\"left\">3.26</td><td align=\"left\">4</td><td align=\"left\">3.92</td></tr><tr><td align=\"left\"> FT4 (12–22) pmol/L</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">34.9</td><td align=\"left\">30.1</td><td align=\"left\">9.54</td><td align=\"left\">8.7</td><td align=\"left\">9.34</td><td align=\"left\">9.56</td><td align=\"left\">10</td></tr><tr><td align=\"left\">\n<bold>Echocardiography</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Transverse diameter of the right atrium (mm)</td><td align=\"left\">NA</td><td align=\"left\">16</td><td align=\"left\">15</td><td align=\"left\">NA</td><td align=\"left\">17</td><td align=\"left\">16</td><td align=\"left\">16</td><td align=\"left\">12</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\" colspan=\"2\"> Transverse diameter of the right ventricle (mm) NA</td><td align=\"left\">16</td><td align=\"left\">16</td><td align=\"left\">NA</td><td align=\"left\">17</td><td align=\"left\">16</td><td align=\"left\">15</td><td align=\"left\">12</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Tricuspid regurgitation</td><td align=\"left\">NA</td><td align=\"left\">severe</td><td align=\"left\">severe</td><td align=\"left\">NA</td><td align=\"left\">severe</td><td align=\"left\">severe</td><td align=\"left\">severe</td><td align=\"left\">moderate</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Pulmonary artery pressure (mmHg)</td><td align=\"left\">NA</td><td align=\"left\">64</td><td align=\"left\">64</td><td align=\"left\">NA</td><td align=\"left\">64</td><td align=\"left\">60</td><td align=\"left\">44</td><td align=\"left\">37</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Patent ductus arteriosus (mm)</td><td align=\"left\">NA</td><td align=\"left\">2.5</td><td align=\"left\">1.7</td><td align=\"left\">NA</td><td align=\"left\">1.7</td><td align=\"left\">1.4</td><td align=\"left\">1.6</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"> Patent foramen ovale (mm)</td><td align=\"left\">NA</td><td align=\"left\">2.3</td><td align=\"left\">2</td><td align=\"left\">NA</td><td align=\"left\">2</td><td align=\"left\">2</td><td align=\"left\">2</td><td align=\"left\">3</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\"/></tr><tr><td align=\"left\"> Ejection fraction (%)</td><td align=\"left\">NA</td><td align=\"left\">70</td><td align=\"left\">70</td><td align=\"left\">NA</td><td align=\"left\">64</td><td align=\"left\">67</td><td align=\"left\">67</td><td align=\"left\">70</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Abdominal ultrasonography</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"><p> Distance between the right inferior</p><p> border of the liver and the subcostal</p><p> margin of the right midclavicular line (cm)</p></td><td align=\"left\">NA</td><td align=\"left\">4.7</td><td align=\"left\">4.8</td><td align=\"left\">NA</td><td align=\"left\">4.9</td><td align=\"left\">3.8</td><td align=\"left\">4.2</td><td align=\"left\">3.8</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\"/></tr><tr><td align=\"left\"> Spleen pachydiameter (cm)</td><td align=\"left\">NA</td><td align=\"left\">1.5</td><td align=\"left\">1.6</td><td align=\"left\">NA</td><td align=\"left\">1.5</td><td align=\"left\">1.3</td><td align=\"left\">1.2</td><td align=\"left\">1.7</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\"/></tr><tr><td align=\"left\"> Biliary sludge</td><td align=\"left\">NA</td><td align=\"left\">Yes</td><td align=\"left\">Yes</td><td align=\"left\">NA</td><td align=\"left\">Yes</td><td align=\"left\">Yes</td><td align=\"left\">Yes</td><td align=\"left\">No</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\"/></tr><tr><td align=\"left\"> Gallstone</td><td align=\"left\">NA</td><td align=\"left\">No</td><td align=\"left\">No</td><td align=\"left\">NA</td><td align=\"left\">No</td><td align=\"left\">No</td><td align=\"left\">Yes</td><td align=\"left\">Yes</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Treatment</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Methimazole</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">→</td><td align=\"left\">→</td><td align=\"left\">→</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Propranolol</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">→</td><td align=\"left\">→</td><td align=\"left\">→</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>*Percentile for children of the same gender and gestational age; NBNA: neonatal behavioral neurological assessment; NA: Not available.</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12887_2024_4531_Figa_HTML\" id=\"d32e1251\"/>" ]
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{ "acronym": [], "definition": [] }
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CC BY
no
2024-01-14 23:43:45
BMC Pediatr. 2024 Jan 13; 24:43
oa_package/99/77/PMC10787401.tar.gz
PMC10787402
0
[ "<title>Background</title>", "<p id=\"Par5\">The triangular fibrocartilage complex (TFCC) is a fibrocartilaginous structure located between the medial surface of the distal radius and the ulnar head, comprising the articular disc, the meniscus homologue, the dorsal and palmar radioulnar ligaments, the ulnolunate and ulnotriquetral ligaments, and the extensor carpi ulnaris tendon sheath [##REF##22745082##1##, ##REF##8915049##2##]. TFCC functions as the primary stabilizer of the ulnar aspect of the wrist [##REF##19620186##3##]. Injuries of TFCC commonly occur following a fall on the upper limb or a rotational forearm injury. They often manifest as ulnar-sided wrist pain and are frequently associated with distal radioulnar joint (DRUJ) instability, leading to functional decline [##REF##2363780##4##]. Degenerative alterations are also a main pathogenic factor of TFCC injuries, usually associated with age changes, prolonged labor work, and ulnar positive variance [##REF##33932158##5##, ##REF##670069##6##].</p>", "<p id=\"Par6\">According to Palmer’s classification, TFCC injuries can be subtyped into traumatic (type 1) or degenerative (type 2) injuries [##REF##2666492##7##]. However, this classification is unable to cover all kinds of TFCC injuries. For instance, volar and dorsal TFCC injuries were not categorized, and Palmer’s classification does not encompass frequently encountered combined injuries observed in clinical practice [##REF##22745082##1##, ##REF##25575720##8##, ##REF##28865983##9##]. Moreover, in 2009, Atzei introduced a treatment-oriented classification of TFCC peripheral injuries, in virtue of advances in radiocarpal and DRUJ diagnostic arthroscopy [##REF##19620186##3##]. In 2022, Schmitt et al. introduced a novel “CUP” classification system designed specifically for TFCC lesions, but it does not consider the adjacent distal radioulnar joint and ulnar carpus [##REF##36113053##10##]. To our knowledge, there’s limited research on the proportion of different types of TFCC injuries or the prevalence of various types of combined injuries.</p>", "<p id=\"Par7\">Physical, radiological, and clinical examinations are all valuable for determining the diagnosis of TFCC injuries. Physical examinations such as the “ulnar fovea sign” and “ulnar grinding test” can assist in diagnosing TFCC injuries, but there is a need to enhance their specificity and sensitivity [##REF##25575720##8##, ##REF##32742122##11##, ##REF##26969464##12##]. MRI scan is commonly utilized as diagnostic tool for evaluating TFCC due to its non-invasiveness, accessibility, and spatial resolution [##REF##32372253##13##, ##UREF##0##14##]. But MRI scan may not be able to accurately assess the size and location of TFCC injuries [##REF##30972480##15##]. As the “gold standard” for identifying TFCC injuries, wrist arthroscopy is the only diagnostic tool that dynamically can assess the grade of instability and the healing capacity of the injury, serving both for diagnosis and repair of the injured TFCC [##REF##26566794##16##–##REF##31387739##18##].</p>", "<p id=\"Par8\">Therefore, the objectives of this study are to evaluate the value of MRI in the qualitative diagnosis and localization of traumatic (Palmer type 1) TFCC injuries compared with arthroscopy in a normal clinical setting, and to determine the distribution of different subtypes of TFCC injuries at our center.</p>" ]
[ "<title>Methods</title>", "<title>Patients</title>", "<p id=\"Par9\">This retrospective study included a total of 193 consecutive patients from July 2020 to May 2022. The inclusion criteria were as follows: explicit trauma history, preoperative MRI, underwent wrist arthroscopy, arthroscopically verified traumatic TFCC injuries, and that time interval between preoperative MRI and wrist arthroscopy was limited to 6 months. The exclusion criteria were as follows: previous surgical treatment for wrist joint diseases, wrist or forearm fracture history. Out of the 214 patients meeting the inclusion criteria, 21 were excluded due to the exclusion criteria.</p>", "<p id=\"Par10\">Patients confirmed to have Palmer 1 (traumatic) TFCC injuries through wrist arthroscopy were included in this study. After arthroscopy, their preoperative MRI diagnoses were retrospectively retrieved for statistical analysis. Detailed information of 193 patients with traumatic TFCC tears are listed in Table ##TAB##0##1##.</p>", "<p id=\"Par11\">\n\n</p>", "<title>MRI</title>", "<p id=\"Par12\">To capture the detailed and delicate structures of the TFCC, a high-field 3 Tesla MR scanner (GE MR750) was utilized to acquire high-resolution and high-contrast imaging data. Patients were placed in the “Superman position”, where the hand was raised above the head to ensure the wrist was positioned at the isocenter of the magnetic field for scanning purposes [##REF##32999697##19##]. The wrists were scanned using an eight-channel wrist coil, which enhanced the clarity of high-resolution imaging and provided detailed visualization of the small structures of the TFCC. High-resolution proton density coronal sequences with both fat and non-fat suppression, sagittal T2-weighted fat-suppression sequences, and axial proton-density fat-suppression sequences were employed. Three orthogonal planes were obtained to ensure a good correlation between them. We only performed native MRI examinations and did not use contrast-enhanced examinations such as ceMRI or MR arthrography. Specific MRI settings can be found in Table ##TAB##1##2##.</p>", "<p id=\"Par13\">\n\n</p>", "<p id=\"Par15\">MRI of the injured wrists were examined by two radiologists from our center, and they both assessed all 193 patients. The interrater correlation (ICC) between the assessments of two radiologists was 0.97. MRI manifestations of traumatic TFCC injuries were shown in Fig. ##FIG##0##1##.</p>", "<p id=\"Par16\">\n\n</p>", "<title>Wrist arthroscopy</title>", "<p id=\"Par17\">All 193 patients underwent wrist arthroscopy by three hand surgeons at our center. To preserve the integrity of the study and ensure unbiased arthroscopic evaluations, all hand surgeons involved in the wrist arthroscopy procedures could view the MRI images before the surgery, but they were blinded to the MRI diagnoses made by radiologists, especially the specific classifications. This procedure ensured that all the surgeons’ intraoperative observations and judgments were not influenced by prior knowledge of the MRI diagnoses.</p>", "<p id=\"Par18\">Comprehensive surgical examination was conducted on all wrist joints, including the distal radioulnar joint, radiocarpal joint, and midcarpal joint. All arthroscopically observed ligament injuries were recorded, including TFCC injuries, lunotriquetral ligament injuries, and scapholunate ligament injuries. The subtypes of TFCC injuries were initially diagnosed by the operating surgeon during wrist arthroscopy and then reconfirmed by two other hand surgeons by reviewing surgical video records to ensure inter-observer reliability, according to Palmer’s and Atzei’s classification. These two reviewers who assessed the arthroscopy videos were blinded to the operating surgeons’ diagnoses. The ICC between these three hand surgeons was 0.95.</p>", "<p id=\"Par19\">As extensively detailed by Aztei [##REF##19620186##3##], TFCC injuries were observed through radiocarpal arthroscopy and assessed using the 6-R portal. The tension of TFCC was evaluated through the trampoline test and the hook test using the 4–5 or 6-R portal. Distal radioulnar joint arthroscopy was also performed because it remains the best method for identifying ligamentous tears of the pc-TFCC or avulsion of its foveal attachment. This procedure is deemed necessary when a positive hook test is observed and/or when the TFCC tear is associated with DRUJ instability. To assess the pc-TFCC, an 18-gauge hypodermic needle was employed to probe the foveal insertion. To assess the midcarpal joint, both the midcarpal radial portal and the midcarpal ulnar portal were used.</p>", "<title>Statistical analysis</title>", "<p id=\"Par20\">The MRI findings were compared to the wrist arthroscopic findings, and the sensitivity, specificity and accuracy were calculated. In order to interpret the overall agreement, the investigators adhered to the criteria published by Landis and Koch [##REF##843571##20##], the comparison of proportions and agreement analysis was evaluated by Chi-square test and Cohen’s kappa [##REF##6062590##21##]. Kappa values between 0.81 and 1.00 indicate almost perfect strength of agreement; 0.61–0.80 indicate substantial; 0.41–0.60 indicate moderate; 0.21–0.40 indicate fair. Sensitivity, specificity, positive and negative predictive values, and accuracy (defined as the sum of concordant cells divided by the sum of all cells in the 2-by-2 table) [##REF##35248425##22##], along with their corresponding 95% confidence intervals, were calculated from the standard statistical tables. Among these evaluation indicators, negative predictive value (NPV) was particularly emphasized as it defines how many cases of TFCC injury were missed during MRI diagnostics.</p>" ]
[ "<title>Results</title>", "<title>Proportion of different types of traumatic TFCC tears verified by arthroscopy</title>", "<p id=\"Par21\">According to wrist arthroscopy in our center, traumatic TFCC injuries were subtyped into four types according to Palmer’s classification and two kinds of mixed types (1 A + 1B and 1B + 1D). The detailed proportion of different TFCC injuries can be found in Table ##TAB##2##3##.</p>", "<p id=\"Par22\">\n\n</p>", "<title>Ratio of different types of TFCC peripheral tears verified by arthroscopy</title>", "<p id=\"Par23\">Peripheral TFCC tears (Palmer 1B) can be further classified into four classes, according to Atzei’s classification. In this study, the investigators analyzed the proportion of each class of Atzei’s classification in 174 patients with peripheral TFCC tears (including type Palmer 1B, 1 A + 1B, 1B + 1D). The remaining 19 patients without Palmer 1B TFCC injuries, who were classified as Palmer 1 A, 1 C, or 1D, were not included in this section. The detailed proportion was shown in Table ##TAB##3##4##.</p>", "<p id=\"Par24\">\n\n</p>", "<title>Diagnostic value of MRI in the qualitative and localization diagnosis of TFCC tears compared with arthroscopy</title>", "<p id=\"Par25\">The diagnostic results of wrist arthroscopy were used as the “gold standard”. NPV, the most important evaluation indicator, reached up to 0.97 in traumatic TFCC injuries, indicating the extremely high diagnostic value of MRI. The accuracy for dc-TFCC and pc-TFCC was only moderate to fair. The detailed diagnostic value of MRI is shown in Table ##TAB##4##5##.</p>", "<p id=\"Par26\">\n\n</p>", "<title>Occurrence rates of associated injuries of TFCC tears detected by arthroscopy and radiological examination</title>", "<p id=\"Par27\">Apart from directly observable tears of the TFCC, some associated injuries of wrist joint found in arthroscopy and radiological examinations, such as lunate and triangular cysts, may also be conducive to diagnose TFCC injuries. The epicenter method [##REF##3823954##23##] was used in CT evaluation to ascertain the ulna’s position relative to the radius, and to assess DRUJ instability [##REF##37191922##24##]. In this study, we selected several of the most frequently occurring associated injuries, and their occurrence rates are presented in Table ##TAB##5##6##.</p>", "<p id=\"Par28\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par29\">This study evaluated the diagnostic value of MRI for TFCC injuries in comparison to wrist arthroscopy, and reported the proportions of various subtypes of TFCC injuries in regular clinical practice using a large sample dataset. The most common TFCC injury subtype was peripheral injury (Palmer 1B), accounting for 67.9% of cases. This was followed by combined injuries, with 14% classified as Palmer 1 A + 1B and 8.3% as Palmer 1B + 1D. MRI has shown almost perfect diagnostic value in traumatic TFCC injuries compared to wrist arthroscopic evaluation. However, it has limitations in providing detailed classification of TFCC tears.</p>", "<p id=\"Par30\">Certain atypical TFCC injuries do not fit into Palmer’s classification, and combined injuries, which are frequently encountered in clinical practice, are also not accounted for in Palmer’s classification. Abe et al. reported a prevalence of 18.5% (32 out of 173 wrists) for combined tears, but specific subtypes of these combined tears were not specified [##REF##22745082##1##]. In this study, we identified two primary types of combined TFCC injuries: those involving a combination of peripheral tear and central / radial TFC disc tear, predominantly categorized as Palmer 1B + 1 A and 1B + 1D. In such scenarios, an optimized management strategy should be devised to address TFCC injuries, with particular attention given to tears located at the distal radioulnar joint (DRUJ).</p>", "<p id=\"Par31\">Following the precise elucidation of the anatomical structure of the TFCC [##REF##8915049##2##] and advancements in surgical techniques for wrist arthroscopy, Atzei introduced a treatment-oriented classification of peripheral tears of the TFCC in 2009 [##REF##19620186##3##]. In this study, distal tears (58.6%) and complete tears (involving both the distal and proximal regions, 29.9%) were relatively common in peripheral TFCC tears (Table ##TAB##3##4##). In wrist arthroscopy, arthroscopic-assisted TFCC foveal reattachment is performed through a dedicated DRUJ working portal, known as the direct foveal portal. Furthermore, the management of combined proximal and distal TFCC tears with TFC disc central and radial tears (Palmer 1 A + 1B and 1B + 1D) could be considered as an addition to Atzei’s classification due to their high prevalence of DRUJ instability, with proportions of 37% and 50%, respectively (Table ##TAB##4##5##). Simple dc-TFCC tear (Atzei Class 1) can be repaired by directly suturing of the injury. However, in cases where pc-TFCC tear (Atzei Class 2/3) associated with DRUJ instability is present, more complex surgical procedures are required to ensure TFCC reattachment to the fovea. Therefore, the diagnostic ability to localize the TFCC tear preoperatively would provide valuable guidance for developing an operative plan.</p>", "<p id=\"Par32\">As suggested in the interdisciplinary consensus statements proposed by Luis Cerezal et al. [##REF##37191922##24##], MRI is considered the most valuable technique for diagnosing TFCC injuries. In our study, there was almost perfect agreement between MRI and wrist arthroscopic examination in detecting traumatic TFCC injuries. Although, for localized TFCC peripheral tears, the agreement was moderate for dc-TFCC tears and fair for pc-TFCC tears (Table ##TAB##4##5##). This indicates that MRI is effective in detecting TFCC injuries but may not precisely determine the location of peripheral tears, particularly in the pc-TFCC tears. These findings align with results reported in other MRI studies pertaining to TFCC injuries, the most challenging aspect of detecting TFCC tears is identifying peripheral abnormalities such as tears at the ulnar side, the ulnar styloid, and foveal attachments [##REF##16829252##25##, ##REF##29922507##26##].</p>", "<p id=\"Par33\">The Atzei classification we performed was based on direct observation during wrist arthroscopy, allowing us to clearly determine whether it’s a proximal or distal tear. However, when diagnosing TFCC injuries solely through MRI images, it may not provide the fine-grained details required for specific subtyping, which is important in clinical decision-making and treatment planning. Factors such as anatomical complexity, limitations in imaging techniques, variations in injury size, and local inflammation contribute to the challenges in accurately identifying these specific injury subtypes via MRI. In such circumstances, MR arthrography and CT play a crucial role as complementary examinations for diagnostic classification, as they can provide essential insights into structural abnormalities and potential ligamentous injuries that support the clinical diagnosis of DRUJ instability [##REF##30941259##27##–##REF##23812413##29##]. By MR arthrography, the rupture ends of the foveal and styloid lamina are distended, and thus IB ruptures according to Palmer become visible at all [##REF##17179363##30##]. CT is the most useful and accurate imaging technique for assessing DRUJ instability, as it directly evaluates the dorsal subluxation of the ulnar head [##REF##37191922##24##]. Moreover, in contrast-enhanced MRI, intravenous gadolinium contrast agent can facilitate higher diagnostic accuracy and confidence the detection of fresh lamina ruptures of the TFCC due to focal hypervasularization [##REF##34392004##31##].</p>", "<p id=\"Par34\">This study has some limitations due to its retrospective design and single-center setting. If it had included different clinical practitioners, institutions, and countries, the research results might have resulted in variation of the research findings. Moreover, the study only focused on patients with traumatic TFCC injuries, thereby excluding degenerative injuries, which could potentially restrict the generalizability of our findings. MRI has limited diagnostic value in further localizing tears in peripheral TFCC injuries, requiring other diagnostic methods to address this challenge. Regarding associated injuries such as lunotriquetral dissociation, we only reported their occurrence rates among different Palmer types and did not analyze their correlation. In the future, more targeted clinical studies will be needed to determine their specific diagnostic value in TFCC injuries.</p>", "<p id=\"Par35\">Although MRI remains the most useful technique for diagnosing TFCC injuries, wrist arthroscopy, performed after a comprehensive clinical examination, remains the most effective procedure for the assessment and treatment of TFCC injuries in a contemporary practice. Furthermore, wrist arthroscopy is the only diagnostic tool that dynamically can assess the grade of instability and the healing capacity of the injury.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par36\">The diagnostic value of MRI in traumatic TFCC injuries has been confirmed to be almost perfect using Palmer’s classification. In more detailed classification of TFCC injuries, such as pc-TFCC tears classified by Atzei’s classification, the diagnostic accuracy of MRI remains lower compared to wrist arthroscopy. Radiological associated injuries may offer additional diagnostic value in cases with diagnostic uncertainty.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Triangular fibrocartilage complex (TFCC) injuries commonly manifest as ulnar-sided wrist pain and can be associated with distal radioulnar joint (DRUJ) instability and subsequent wrist functional decline. This study aimed to assess the diagnostic value of MRI compared to wrist arthroscopy in identifying traumatic TFCC injuries and to determine the distribution of different TFCC injury subtypes in a normal clinical setting.</p>", "<title>Methods</title>", "<p id=\"Par2\">The data of 193 patients who underwent both preoperative wrist MRI and wrist arthroscopy were retrospectively reviewed. The analysis focused on the proportion of subtypes and the diagnostic value of MRI in traumatic TFCC injuries, utilizing Palmer’s and Atzei’s classification with wrist arthroscopy considered as the gold standard.</p>", "<title>Results</title>", "<p id=\"Par3\">The most prevalent subtype of TFCC injuries were peripheral injuries (Palmer 1B, 67.9%), followed by combined injuries (Palmer 1 A + 1B, 14%; Palmer 1B + 1D, 8.3%). Compared with wrist arthroscopy, the diagnostic sensitivity, specificity, negative predictive value (NPV), and Kappa value of MRI was as follows: traumatic TFCC tears 0.99 (95% CI: 0.97-1), 0.90 (0.78-0.96), 0.97 (0.87-1), and 0.93; styloid lamina tears 0.93 (0.88-0.96), 0.53 (0.30-0.75), 0.47 (0.26-0.69), and 0.44; and foveal lamina tears 0.85 (0.74-0.92), 0.38 (0.29-0.49), 0.79 (0.65-0.89), and 0.21.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The diagnostic value of MRI in traumatic TFCC injuries has been confirmed to be almost perfect using Palmer’s classification. In more detailed classification of TFCC injuries, such as pc-TFCC tears classified by Atzei’s classification, the diagnostic accuracy of MRI remains lower compared to wrist arthroscopy. Radiological associated injuries may offer additional diagnostic value in cases with diagnostic uncertainty.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>XZ, AY, and HZ were involved in the conception, design, interpretation of the data, and drafting of the paper. YQ was involved in design of the study, drafting and revision of the paper. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>The investigation was supported by the National Natural Science Foundation of China (81972157), CAMS Innovation Fund for Medical Sciences (2019-I2M-5-007).</p>", "<title>Data Availability</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par38\">Our study was performed according to the Declaration of Helsinki and approved by the Institutional Review Board of Jing’an District Central Hospital (2022-22). Due to the nature of this retrospective study and the preserved anonymity of patients, a waiver of informed consent was obtained. This waiver was granted by the Institutional Review Board of Jing’an District Central Hospital.</p>", "<title>Consent for publication</title>", "<p id=\"Par39\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par37\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>MRI images of the traumatic TFCC injuries according to Palmer’s classification. pc, proximal component; dc, distal component; MRI, magnetic resonance imaging; TFCC, triangular fibrocartilage complex</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Demographic characteristics of 193 patients with traumatic TFCC tears</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"2\">Demographic Characteristics</th></tr></thead><tbody><tr><td align=\"left\">Average age (years) (SD)</td><td align=\"left\">38 (12.2)</td></tr><tr><td align=\"left\">Gender, female (n) (%)</td><td align=\"left\">103 (53)</td></tr><tr><td align=\"left\">Gender, male (n) (%)</td><td align=\"left\">90 (47)</td></tr><tr><td align=\"left\">Mean duration from injury to surgery (months) (SD)</td><td align=\"left\">13 (14.7)</td></tr><tr><td align=\"left\">Mean duration from MRI to surgery (months) (SD)</td><td align=\"left\">2 (1.8)</td></tr><tr><td align=\"left\">Affected side, right (n) (%)</td><td align=\"left\">118 (61)</td></tr><tr><td align=\"left\">Affected side, left (n) (%)</td><td align=\"left\">75 (39)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>MRI sequence parameters</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Sequence</th><th align=\"left\">FoV (mm)</th><th align=\"left\">Slice thickness<break/>/Interslice gap (mm)</th><th align=\"left\">Resolution</th><th align=\"left\">TR (ms)</th><th align=\"left\">TE (s)</th><th align=\"left\">Time (min)</th></tr></thead><tbody><tr><td align=\"left\">Ax T2 FSE</td><td char=\".\" align=\"char\">10</td><td align=\"left\">2 mm/0 mm</td><td align=\"left\">320*256</td><td align=\"left\">2923</td><td align=\"left\">110</td><td align=\"left\">2.5</td></tr><tr><td align=\"left\">OCor 3D MRGE T2</td><td char=\".\" align=\"char\">10</td><td align=\"left\">0.6 mm/0 mm</td><td align=\"left\">300*300</td><td align=\"left\">linimum</td><td align=\"left\">18</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Cor CUBE T2</td><td char=\".\" align=\"char\">10</td><td align=\"left\">1 mm/0 mm</td><td align=\"left\">256*224</td><td align=\"left\">1500</td><td align=\"left\">aximum</td><td align=\"left\">4</td></tr><tr><td align=\"left\">OSag CUBE T2</td><td char=\".\" align=\"char\">10</td><td align=\"left\">1 mm/0 mm</td><td align=\"left\">256*224</td><td align=\"left\">1500</td><td align=\"left\">aximum</td><td align=\"left\">3.5</td></tr><tr><td align=\"left\">Radial T2 GRE</td><td char=\".\" align=\"char\">12</td><td align=\"left\">1 mm/0.2 mm</td><td align=\"left\">256*224</td><td align=\"left\">440</td><td align=\"left\">15</td><td align=\"left\">5</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Proportion of different subtypes of traumatic TFCC injuries in arthroscopy (Palmer’s classification)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Palmer’s classification</th><th align=\"left\">No. (%), n = 193</th></tr></thead><tbody><tr><td align=\"left\">1 A</td><td align=\"left\">14 (7)</td></tr><tr><td align=\"left\">1B</td><td align=\"left\">131 (68)</td></tr><tr><td align=\"left\">1 C</td><td align=\"left\">1 (1)</td></tr><tr><td align=\"left\">1D</td><td align=\"left\">4 (2)</td></tr><tr><td align=\"left\">1 A + 1B</td><td align=\"left\">27 (14)</td></tr><tr><td align=\"left\">1B + 1D</td><td align=\"left\">16 (8)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Proportion of different types of TFCC peripheral tears in arthroscopy (Atzei’s classification)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Atzei’s classification</th><th align=\"left\">Styloid lamina<break/>(Distal component)</th><th align=\"left\">Foveal lamina<break/>(Proximal component)</th><th align=\"left\">DRUJ instability</th><th align=\"left\">No. (%), n = 174</th></tr></thead><tbody><tr><td align=\"left\">Class 1 Distal tear</td><td align=\"left\">Tear</td><td align=\"left\">Intact</td><td align=\"left\">No</td><td align=\"left\">102 (59)</td></tr><tr><td align=\"left\">Class 2 Foveal avulsion</td><td align=\"left\">Intact</td><td align=\"left\">Tear</td><td align=\"left\">Yes</td><td align=\"left\">17 (10)</td></tr><tr><td align=\"left\">Class 3 Complete tear</td><td align=\"left\">Tear</td><td align=\"left\">Tear</td><td align=\"left\">Yes</td><td align=\"left\">52 (30)</td></tr><tr><td align=\"left\">Class 4 Massive rupture irreparable</td><td align=\"left\">Tear</td><td align=\"left\">Tear</td><td align=\"left\">Yes</td><td align=\"left\">3 (2)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Diagnostic value of MRI in the diagnosis of TFCC tears compared with arthroscopy</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Types</th><th align=\"left\">Sensitivity</th><th align=\"left\">Specificity</th><th align=\"left\">PPV</th><th align=\"left\">NPV</th><th align=\"left\">Accuracy</th><th align=\"left\">Kappa Value</th><th align=\"left\">Agreement Degree</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Traumatic</td><td char=\".\" align=\"char\">0.99</td><td char=\".\" align=\"char\">0.90</td><td char=\".\" align=\"char\">0.98</td><td char=\".\" align=\"char\">0.97</td><td char=\".\" align=\"char\">0.98</td><td char=\".\" align=\"char\" rowspan=\"2\">0.93</td><td align=\"left\" rowspan=\"2\">Almost perfect</td></tr><tr><td char=\".\" align=\"char\">0.97-1</td><td char=\".\" align=\"char\">0.78-0.96</td><td char=\".\" align=\"char\">0.95-0.99</td><td char=\".\" align=\"char\">0.87-1</td><td char=\".\" align=\"char\">0.95-0.99</td></tr><tr><td align=\"left\" rowspan=\"2\">dc-TFCC</td><td char=\".\" align=\"char\">0.93</td><td char=\".\" align=\"char\">0.53</td><td char=\".\" align=\"char\">0.95</td><td char=\".\" align=\"char\">0.47</td><td char=\".\" align=\"char\">0.89</td><td char=\".\" align=\"char\" rowspan=\"2\">0.44</td><td align=\"left\" rowspan=\"2\">Moderate</td></tr><tr><td char=\".\" align=\"char\">0.88-0.96</td><td char=\".\" align=\"char\">0.30-0.75</td><td char=\".\" align=\"char\">0.9-0.97</td><td char=\".\" align=\"char\">0.26-0.69</td><td char=\".\" align=\"char\">0.83-0.93</td></tr><tr><td align=\"left\" rowspan=\"2\">pc-TFCC</td><td char=\".\" align=\"char\">0.85</td><td char=\".\" align=\"char\">0.38</td><td char=\".\" align=\"char\">0.49</td><td char=\".\" align=\"char\">0.79</td><td char=\".\" align=\"char\">0.57</td><td char=\".\" align=\"char\" rowspan=\"2\">0.21</td><td align=\"left\" rowspan=\"2\">Fair</td></tr><tr><td char=\".\" align=\"char\">0.74-0.92</td><td char=\".\" align=\"char\">0.29-0.49</td><td char=\".\" align=\"char\">0.39-0.58</td><td char=\".\" align=\"char\">0.65-0.89</td><td char=\".\" align=\"char\">0.49-0.65</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab6\"><label>Table 6</label><caption><p>Occurrence rates of associated injuries of TFCC tears</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Type</th><th align=\"left\" rowspan=\"2\">No. (%)</th><th align=\"left\">Surgical probe</th><th align=\"left\" colspan=\"2\">MRI</th><th align=\"left\">CT</th></tr><tr><th align=\"left\">Lunotriquetral injury</th><th align=\"left\">Lunate cysts</th><th align=\"left\">Triangular cysts</th><th align=\"left\">DRUJ instability</th></tr></thead><tbody><tr><td align=\"left\">IA</td><td align=\"left\">14 (7)</td><td align=\"left\">4 (29)</td><td align=\"left\">5 (36)</td><td align=\"left\">4 (29)</td><td align=\"left\">5 (36)</td></tr><tr><td align=\"left\">IB</td><td align=\"left\">131 (68)</td><td align=\"left\">17 (13)</td><td align=\"left\">28 (21)</td><td align=\"left\">31 (24)</td><td align=\"left\">44 (34)</td></tr><tr><td align=\"left\">IC</td><td align=\"left\">1 (1)</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">1 (100)</td></tr><tr><td align=\"left\">ID</td><td align=\"left\">4 (2)</td><td align=\"left\">0</td><td align=\"left\">2 (50)</td><td align=\"left\">1 (25)</td><td align=\"left\">2 (50)</td></tr><tr><td align=\"left\">IA + IB</td><td align=\"left\">27 (14)</td><td align=\"left\">6 (22)</td><td align=\"left\">4 (15)</td><td align=\"left\">4 (15)</td><td align=\"left\">10 (37)</td></tr><tr><td align=\"left\">IB + ID</td><td align=\"left\">16 (8)</td><td align=\"left\">5 (31)</td><td align=\"left\">6 (38)</td><td align=\"left\">6 (38)</td><td align=\"left\">8 (50)</td></tr><tr><td align=\"left\">Total</td><td align=\"left\">193</td><td align=\"left\">32 (17)</td><td align=\"left\">45 (23)</td><td align=\"left\">46 (24)</td><td align=\"left\">70 (36)</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>FoV, field of view; TR, repetition time; TE, echo time</p></table-wrap-foot>", "<table-wrap-foot><p>Abbreviations: PPV, positive predictive value; NPV, negative predictive value; pc, proximal component; dc, distal component; TFCC, triangular fibrocartilage complex</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Xuanyu Zhao, Aiping Yu, and Huali Zhao contributed equally to the manuscript.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12891_2023_7140_Fig1_HTML\" id=\"d32e505\"/>" ]
[]
[{"label": ["14."], "mixed-citation": ["Nozaki T, Rafijah G, Yang L, Ueno T, Horiuchi S, Hitt D et al. High-resolution 3 T MRI of traumatic and degenerative triangular fibrocartilage complex (TFCC) abnormalities using Palmer and Outerbridge classifications. Clin Radiol. 2017;72(10):904.e1-.e10."]}]
{ "acronym": [ "dc-TFCC", "DRUJ", "ICC", "MRI", "NPV", "pc-TFCC", "PPV", "TFCC" ], "definition": [ "Distal component of TFCC", "Distal radioulnar joint", "Interrater correlation", "Magnetic resonance imaging", "Negative predictive value", "Proximal component of TFCC", "Positive predictive value", "Triangular fibrocartilage complex" ] }
31
CC BY
no
2024-01-14 23:43:45
BMC Musculoskelet Disord. 2024 Jan 13; 25:63
oa_package/44/17/PMC10787402.tar.gz
PMC10787403
0
[ "<title>Introduction</title>", "<p id=\"Par5\">The growth and development of the unborn child/fetus is a multifaceted course and is relay on the many factors. Restricted fetal growth is the manifestation of a fundamental problem preventing the growth and development ability of unborn child. Fetal growth restriction (FGR) is a debatable problem [##UREF##0##1##]. The advancement of imaging technology such as ultrasound machines, are enabling to identify and understand more about this fetal problem.</p>", "<p id=\"Par6\">Previously the word FGR is allotted to neonates with a birth/estimated fetal weight and/or length below the 10th percentile for their gestational age and whose abdominal circumference is below the 2.5th percentile [##UREF##1##2##], and it is a pathologic condition.</p>", "<p id=\"Par7\">Currently, further parameters such as placental factors, biochemical factors and biometrics such as skin fold thickness and other anthropometric parameters of neonates like head circumference, biparietal diameter and others have been additionally considered to assess this disorder [##UREF##2##3##, ##REF##29986308##4##]. On the other hand, small for gestational age (SGA) newborns are declared based on birth weight and/or length below the 10th percentile or less than 2 standard deviations (SD) for gestational age [##UREF##3##5##], and it may not be a pathologic state. Because SGA takes into account of only size and sex at birth, data on intrauterine growth status are not possible to obtain and hence, SGA may contain normal babies having only statures problem but with no pathological growth restriction. It has been reported that, there may be newborns which are simply genetically small, but normal without having increased morbidity and mortality [##UREF##4##6##]. Hence, SGA may be seen in fetal growth restricted newborn or non-restricted newborn, and thus not synonymous but highly related. It has been reported that, the smaller the unborn fetus or neonate, the higher the chance of being growth restricted [##UREF##5##7##]. The diagnosis of FGR is usually made during the prenatal period through the use of ultrasound.</p>", "<p id=\"Par8\">Worldwide, fetal growth restriction have been observed in 5–10% of all pregnancies [##REF##28285426##8##, ##REF##15717289##9##], however its rate of occurrence is higher which is about 16–34% of births in low socioeconomic settings [##UREF##6##10##]. A cross sectional study conducted in northern parts of Ethiopia reported 23.5% prevalence of fetal growth restriction and 19.7% prevalence of SGA [##REF##31908777##11##]. This variations in the occurrence of fetal growth restrictions may depends on the population under study, the geographic location of the study participants, the measurements and the standard growth curves used as a reference to compare [##UREF##7##12##].</p>", "<p id=\"Par9\">Globally, fetal growth restriction is a leading cause of stillbirth, neonatal mortality, and short- and long-term morbidity [##REF##31376293##13##, ##REF##21520312##14##]. As such, FGR is the second leading cause of perinatal morbidity and mortality, next to preterm births and is accountable for about 20–30% of stillborn neonates [##REF##28285426##8##, ##UREF##6##10##]; It is also the commonest cause of premature births and birth asphyxia [##REF##28285426##8##].</p>", "<p id=\"Par10\">Fetal growth and wellbeing are reliant on genetic/fetal, placental, and maternal factors. A relatively higher occurrence of fetal growth restriction in low- and middle-income countries may be attributed to nonharmony act of the fetal, placental, and maternal factors [##UREF##8##15##], so as to fulfill the needs of the unborn child through supporting the physiologic fluctuations of the women. Existing scientific evidence have documented the effects of maternal drugs use, alcohol drinking, tobacco smoke, cocaine, and heroin use on fetal growth restriction [##REF##28285426##8##, ##REF##8017537##16##]. However, data is lacking on the effects of khat chewing during pregnancy on fetal growth status and newborn size at birth. In addition, data on fetal growth restriction and SGA among births in Ethiopia is highly limited and nil in the present study area where khat chewing is highly practiced, including pregnant mothers. More importantly, there exists no previous study in Ethiopia conducted in a prospective study approach aimed at revealing the effect of khat chewing during pregnancy on fetal growth and size among deliveries in Ethiopia. Hence, the aim of the present study was to measure the effect of chewing khat during pregnancy on fetal growth and size in eastern Ethiopia.</p>" ]
[ "<title>Methods and materials</title>", "<title>Study design and setting</title>", "<p id=\"Par11\">A prospective cohort study of pregnant women who chewed khat and not chewed khat was conducted from August to December 2022 in selected health institutions of Dire Dawa administration, Harari region and Jigjiga city administration, eastern Ethiopia. Participants at high risk of adverse birth outcomes like having known major chronic illness such as diabetes mellitus and cardiovascular diseases; and having previous history of congenital anomalies were excluded. Moreover, those pregnant mothers with multiple pregnancy were also excluded.</p>", "<title>Sample size and sampling procedures</title>", "<p id=\"Par12\">Open Epi version 3 statistical package was used to calculate the sample size by using 28.6% proportion of low birth weight in khat chewer groups (exposed) and 9.8% in non-khat chewers (non-exposed) from previous local study [##UREF##9##17##] and based on the assumptions of 95%, 80% power and r 1:1. The final sample size after using design effect 2 and adding 10% for loss to follow up is calculated to be 344 (172 non exposed and 172 exposed). Dire Dawa administration, Harari regional state and Jigjiga city were purposively selected due to exposure of interest. Then, 4 hospitals; 2 from Harari regional state, one from Dire Dawa administration and one from Jigjiga were taken. Pregnant mothers being in the second trimester and early third trimester (24–28 weeks) of pregnancy who visited the selected hospitals for the 1st or 2nd time during the study period was included until the required sample size of exposed and unexposed groups are fulfilled. The pregnancy follow-up contact period/time was at antenatal care appointments.</p>", "<title>Data collection procedures</title>", "<p id=\"Par13\">Socio-demographic characteristics, past obstetrics related characteristics, substance use related characteristics and personal factors data was collected using structured and semi-structured questionnaire at entry to the study. The questionnaire was first prepared in English and then translated to local languages to facilitate understanding and ensure consistency during administration. In addition, anthropometric and clinical measurements were performed at entry, follow up time and delivery (end of pregnancy) to collect the necessary data for the independent variables.</p>", "<p id=\"Par14\">Measurement of the exposure variable (khat chewing during pregnancy) was performed through maternal self-report. All pregnant women to be included in the study was first assessed for khat use at the first or second prenatal visit with the use of validated questionnaire. The WHO also suggested for identification of substance use during pregnancy by interview at antenatal care visits [##UREF##10##18##].</p>", "<p id=\"Par15\">Khat use during current pregnancy is defined as ever chewing of khat during current pregnancy for at least 4 days per week which lasts for at least 4 h per chewing day or chewing for at least 4 days per week of at least 50–75 g of khat leaves per chewing day. This is based on previous local study [##REF##31689323##19##] which found chewer’s of khat spend on average 3.75 h while chewing khat and chewed more than 75 g of khat leaves on single session.</p>", "<p id=\"Par16\">Information regarding alcohol use comprising frequency and number of consumptions were obtained using questionnaire. Alcohol content standards for each beverage (beer, wine) was estimated and added to fix the total exposure volume of absolute alcohol (in grams per week). It is defined in previous literature that one standard drink is nearly equal to 0.5 ounces (14 g) absolute alcohol [##REF##25453352##20##, ##REF##22050262##21##]. Therefore, alcohol exposure status of participants can be categorized as &lt; 1.5 drinks/week, 1.5–3.5 drinks/week, &gt; 3.5-7 drinks/week, and &gt; 7 drinks/week [##REF##25453352##20##]. Furthermore, participants can be categorized as low (&lt; 1.5 drinks/week), moderate (1.5–3.5 drinks/week) and high (&gt; 3.5 drinks/week) alcohol drinkers. Nonuser of alcohol was those who did not report the use of any alcohol type during the current pregnancy.</p>", "<p id=\"Par17\">In the present study, fetal growth restriction (FGR) is identified using (1) ultrasound when the estimated fetal weight is below 10th percentile for gestational age [##REF##7863900##22##]. The major ultrasound parameters considered for identification of FGR were head circumference to abdominal circumference ratio (HC/AC), femur length to abdominal circumference ratio (FL/AC), amniotic fluid volume, and placental grading. In addition, (2) birth weight, sex of the neonates and gestational age at birth were used to determine small for gestational age [##UREF##3##5##] among all births; since FGR and SGA are highly related [##UREF##3##5##]. Small for gestational age at birth was declared when birth weight is below 10th percentile of the sex specific birth weight for gestational age reference curve [##UREF##3##5##]. Gestational age was calculated in terms of weeks using maternal recall of last menstrual period (LMP). Moreover, symphysis-fundal height (SFH) measurement in centimeters was conducted to approve LMP-based estimation of gestational age. All the measurement procedures were completed in accordance with relevant guidelines and regulations.</p>", "<title>Data quality management</title>", "<p id=\"Par18\">To maintain data quality, training was given for data collectors and supervisors. Data were collected by qualified health professionals working on the selected hospitals. Different literatures have been reviewed to properly designed data collection material. Completeness and consistency of data was checked by the strict supervision of the supervisors and principal investigator.</p>", "<title>Statistical analysis</title>", "<p id=\"Par19\">Data analyses were performed by SPSS version 27 and STATA version 16 software. Descriptive statistics such as median, interquartile range (IQR), and mean and standard deviation (SD) for continuous data and frequency distribution for categorical data is used to summarize the characteristics of the cohorts. Characteristics differences between khat chewers and non-khat chewer participants were examined using chi-square test (Pearson, <italic>P</italic>-values tested two-sided). The generalized linear model for the binomial family analysis were performed to estimate the crude and adjusted relative risk and attributable risk (AR) with corresponding 95% CI of chewing khat during pregnancy on fetal growth restriction. Variables with a univariate <italic>p</italic> value less than or equal to 0.25 was used in the multivariable model to estimate the aRR of chewing khat during pregnancy on fetal growth restriction. The relative risk with 95% confidence interval and <italic>p</italic>-values was used to measure the strength of association and to declare statistically significant association. In multivariable analysis model chewing khat during pregnancy was considered a statistically significant associated variable with fetal growth restriction at <italic>p</italic>-value less than 5%. Further mediation analysis was performed for observing the mediation effects of the possible mediators (gestational hypertension and maternal anemia) between the exposure variable (i.e., khat chewing during pregnancy) and outcome variable (i.e., fetal growth restriction). The analysis was performed using the Stata ‘gsem’ command on the drop-down menu bar. In addition, direct, indirect and total effects of khat chewing on fetal growth restriction has been calculated using the Stata ‘nlcom’ command.</p>", "<title>Ethical considerations</title>", "<p id=\"Par20\">Ethical approval was obtained from Institutional Review Board of College of Health Sciences, Addis Ababa University. Permission was also obtained from the concerned bodies of Dire Dawa administration, Harari region and Somalia region. Moreover, informed written consent was obtained from the study cohorts.</p>" ]
[ "<title>Results</title>", "<p id=\"Par21\">Three hundred forty-four study participants were enrolled (172 non-khat chewers and 172 khat chewers) at the start of the study. Out of them, 320 (164 non-khat chewers and 156 khat chewers) finished the follow up resulting in a loss to follow up rate of 7%. The reasons of loss to follow up in the present study were refusal to continue (7 enrolled respondents; 5 chewers and 2 non-chewers), moved to other places (3 enrolled respondents; 2 chewers and 1 non-chewer), death (3 enrolled respondents; 2 chewers and 1 non-chewer) and home delivery (11 enrolled respondents; 7 chewers and 4 non-chewers).</p>", "<title>Sociodemographic characteristics of the study cohorts</title>", "<p id=\"Par22\">In the present study, the mean (SD) age of the cohort mothers was 26.29 ± 5.49 years (range 17–45 years), with the majority (38.1%) aged between 25 and 29 years old. Most of the study cohorts was ethnic Oromo, 147 (45.9%); Muslim religion followers, 216 (67.5%) and living in urban area, 176 (55%). Of the study cohorts, 99 (30.9%) had no formal education and 80 (25%) had primary education level while 93 (29.1%) and 90(28.1%) of them were merchant and farmer in occupation respectively. The great majority, 269 (84.1%) of the study cohorts was married. The median [inter quartile range (IQR)] monthly household income of the study cohorts was 4800.0 ± 3500.0 Ethiopian birr (range 1,000.0–15,000.0 Ethiopian birr).</p>", "<title>Khat chewing characteristics of chewer study cohorts</title>", "<p id=\"Par23\">The mean (SD) duration of khat chewing for chewer cohorts in this study was 34.77 ± 15.37 months (range 12–60 months), with the higher duration of chewing, 76 (48.7%) for 12–24 months. More than half, 82 (52.6%) of chewer cohorts had a khat chewing frequency of greater or equal to 4 days per a week. The median [inter quartile range (IQR)] amount of khat consumed at a single khat chewing session was 90 ± 50 g. Fifty-eight (37.2%), 56 (35.9%) and 42 (26.9%) of chewer cohorts consumed 50–75, 76–100 and &gt; 100 g of khat per single khat chewing session respectively. The mean (SD) duration of khat chewing in a single chewing session was 3.95 ± 0.69 h, with the duration for majority of chewer cohorts, 122 (78.2%) 3–4 h.</p>", "<title>Comparison of behavioral characteristics of study cohorts</title>", "<p id=\"Par24\">In total, 43; 31 (72.1%) chewer and 12 (27.9%) non-khat chewer study cohorts were consumers of alcohol of any type during their current pregnancy. Of them, 27(8.44%), 13 (4.1%) and 9 (2.81%) consumed beer, wine, and locally prepared alcohol (Tela) respectively. In terms of amount, 6 (15%) of the cohorts consumed 16.5 g of alcohol in a week; 14 (35%) of the study cohorts consumed 27.5-33 g of alcohol in a week, and the remaining cohorts, which is 20 (50%) consumed 49.5–55 g of alcohol in a week. Out of the total, 18 (5.63%) of the cohorts were practiced smoking of tobacco products, and almost all (95%) of the study cohorts were consumed coffee (Table ##TAB##0##1##).</p>", "<p id=\"Par25\">\n\n</p>", "<title>Obstetric distribution patterns of study cohorts</title>", "<p id=\"Par26\">The majority, 174 (54.4%) of the study cohorts were multigravida (having &gt; = 3 pregnancies); of them, 106 (60.9%) were chewer cohorts, and the rest 68 (39.1%) were non-chewer cohorts. Of total, 148 (46.3%) of the study cohorts were multipara (having &gt; = 2 children); of them, 87 (58.8%) were chewer cohorts and the remaining, 61 (41.2%) non-chewer cohorts. One hundred four (32.5%) of the study cohorts had a previous history of spontaneous abortion; of them, 84 (81%) were khat chewer cohorts. Fifty (15.6%) of the study cohorts had a previous history of still birth; with 26 (52%) chewer cohorts and 24 (48%) non-chewer cohorts. The majority, 264 (82.5%) of the study cohorts gestational age at time of enrollment to the study was 24–26 weeks and the majority, 240 (75%) of the study cohorts had the first time visit of the hospitals at time of enrollment to the study. Only 37 (11.6%) of the study cohorts had at least 4 ANC visits at the end of delivery; of this, the majority (87%) of them was non-khat chewer cohorts (Table ##TAB##1##2##).</p>", "<p id=\"Par27\">\n\n</p>", "<title>Physical measurements and umbilical cord status of the study cohorts</title>", "<p id=\"Par28\">The overall mean (SD) weight of study cohorts was 63.28 ± 9.19 kg; of this 150 (46.9%) of them weighed between 61 and 70 kg. The mean (SD) height of the study cohorts was 157.46 ± 13.34 cm; with the highest cohorts, 205 (64.1%) measured above 157 cm high. The overall mean (SD) BMI of the cohorts was 25.7 ± 3.9 kg/m<sup>2</sup> (range 17.6–37.8 kg/m<sup>2</sup>); of this, 8 (2.5%) of them had BMI &lt; 18.5 kg/m<sup>2</sup> and 50 (15.6%) had BMI &gt; = 30 kg/m<sup>2</sup>. The mean (SD) MUAC of the cohorts was 26.92 ± 3.49 cm; of this, 46 (14.4%) of them had less than 23 cm and 19 (5.9%) had &gt; = 33 cm (Table ##TAB##2##3##).</p>", "<p id=\"Par29\">Moreover, the umbilical cord of 253 (79.1%) study cohorts was normally twisted; and the magnitude of under and hyper coiled umbilical cords among the study cohorts was 41 (12.8%), and 26 (8.1%) respectively. In addition, true knot was identified in 43 (13.4%) umbilical cords of the study cohorts (Table ##TAB##2##3##).</p>", "<p id=\"Par30\">\n\n</p>", "<title>The incidence of fetal growth restriction and small for gestational age and their association with khat chewing</title>", "<p id=\"Par32\">The incidence of fetal growth restriction among the study cohorts was 95 (29.7%); of this, 81 (85.3%) were among khat chewer cohorts, and the remaining 14 (14.7%) were among non-khat chewer cohorts. Moreover, the incidence of small for gestational age at birth among the present study cohorts was 100 (31.3%); 84 (84%) were from khat chewer cohorts’ deliveries. More importantly, in the present study, 98.95% of the ultrasound-identified fetuses with FGR were found to be SGA at birth. Hence, in the current study, FGR was highly associated with SGA at birth.</p>", "<p id=\"Par33\">As explained in Table ##TAB##3##4##, the GLM for the binomial family analysis revealed that, the adjusted relative risk of fetal growth restriction among khat chewer cohort mothers was about 4 times higher (aRR = 4.32; 95%CI 2.62–7.12) (<italic>p</italic> &lt; 0.001) compared to non-khat chewer cohorts. In addition, the attributable risk of fetal growth restriction due to khat chewing was 43.4% (95%CI 34.46–52.32). Lastly, area of residence, cigarette smoking and true knots in umbilical cord was found to be significant variables associated with fetal growth restriction.</p>", "<p id=\"Par34\">In the same way, analysis of the present study revealed that, the adjusted relative risk of small for gestational age among khat chewer cohorts was almost 4 times higher (aRR = 3.89; 95%CI 2.38–6.38) (<italic>p</italic> &lt; 0.001) compared to non-khat chewer cohorts. Moreover, the attributable risk of small for gestational age due to khat chewing was 44.1% (95%CI 35-53.1) (<italic>p</italic> &lt; 0.001). A similar pattern of findings is observed in the analysis of SGA and other variables considered in the FGR analysis. Accordingly, area of residence, urban (aRR = 0.43; 95%CI 0.25–0.75), cigarette smoking (aRR = 2.26; 95%CI 1.14–4.48) and true knots (aRR = 2.26; 95%CI 1.05–4.88) were the variables which showed a significant association with SGA.</p>", "<p id=\"Par35\">\n\n</p>", "<title>Mediation analysis results</title>", "<p id=\"Par36\">The mediation analysis results of the effect of khat chewing during pregnancy on fetal growth restriction is detailed in Tables ##TAB##4##5## and Fig. ##FIG##0##1##. Khat chewing during pregnancy was significantly associated with FGR (path o, β = 0.43, p &lt; 0.001). More importantly significant associations were also observed between khat chewing during gestation and gestational hypertension (path k, β = 0.15, p = 0.001), gestational hypertension and FGR (path l, β = 0.09, p &lt; 0.05), khat chewing during gestation and maternal anemia (path m, β = 0.19, p &lt; 0.001), maternal anemia and FGR (path n, β = 0.105, p &lt; 0.05). After adjusting for gestational hypertension and maternal anemia, the regression coefficient of khat chewing during pregnancy has been decreased in size from path o, β = 0.43, p &lt; 0.001 to path o’, β = 0.32, <italic>p</italic> &lt; 0.001 (Fig. ##FIG##0##1##). Therefore, the present study revealed that the effect of khat chewing during pregnancy on fetal growth restriction was partially mediated by gestational hypertension and maternal anemia.</p>", "<p id=\"Par37\">\n\n</p>", "<p id=\"Par38\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par40\">In the present follow-up study, the incidence of fetal growth restriction among the study cohorts was 29.7%. Moreover, the incidence of small for gestational age at birth among the present study cohorts was 31.3%. Although, the study populations and the study approaches are not comparable to discuss, a lower prevalence of FGR (23.5%) and SGA (19.7%) have been reported in a previous local study [##REF##31908777##11##].</p>", "<p id=\"Par41\">A significantly higher incidence and increased relative risk of fetal growth restriction was observed among khat chewer participants as compared to their non-khat chewer counterparts in the present follow up study. The probable explanations for this finding may be associated with extrauterine and intrauterine factors. The extrauterine environment may be a factor in the following ways. One, there may be differences in daily dietary intake of chewers and non-khat chewers. It was reported [##UREF##11##23##] that chewing khat may decrease the food appetite of pregnant mothers and hence, chewer pregnant mothers may consume less which may highly decreases the nutrient quantity needed for unborn fetus and then will affect its growth. In addition, since chewer pregnant mothers, even the poor, may give priority for buying khat, chewer pregnant mothers may be in lack of nutritious foods at household and then consume less food that may not satisfy the need of unborn fetus and as result will affect its growth [##UREF##11##23##]. In agreement with these elaborations’ additional mediation analysis in the present study found a significant association between khat chewing during pregnancy and maternal anemia and maternal anemia and fetal growth restriction. The other an increased relative risk of fetal growth restriction may be associated intra uterine environment such as placental and umbilical cord abnormalities. An experimental animal study has reported a decrease in placental blood flow due to vasoconstriction in the uteroplacental vessels among khat fed animals as compared to controls [##REF##3419201##24##] and then this may lead to fetal growth restriction. This may be because the active constituent of khat, principally cathinone, an amphetamine like substance, might be associated with vessels constriction [##REF##15255816##25##]. In line with this finding further mediation analysis of the present study found a significant association between khat chewing during pregnancy and gestational hypertension and gestational hypertension and fetal growth restriction. Normal growth of unborn fetus in the intrauterine life greatly depend on the healthy growth and appropriate attachment of umbilical cord to the placenta [##UREF##12##26##, ##UREF##13##27##]. In the present study abnormal cord insertion (marginal), abnormal umbilical cord coiling (both hypo and hyper coiling) and umbilical cord true knots were significantly higher among births of khat chewer cohorts compared to births of non-khat chewer counterparts. Cord abnormalities are highly related with abnormalities in development and function of the placenta [##UREF##14##28##]. In addition, impaired vascular development in placenta is closely associated with cord abnormalities [##UREF##15##29##, ##REF##3247833##30##]. As reported in a previous study [##UREF##16##31##] the peripheral cord insertion compared to central cord insertion was significantly associated with fetal growth restriction. This may be due to the fact that central insertion of cords to the placenta will enables vessels to be stable and hence, will shelter from rotational and pressing forces [##UREF##17##32##] which will interrupt the blood flow, unlike with that of peripheral insertions. In addition, central cord insertions will better enable a sizeable distribution and flow of blood in different placental parts, that will then enable for better growth of the fetus [##UREF##16##31##]. Previous studies documented both hypo-coiled [##UREF##17##32##–##UREF##19##34##] and hyper-coiled [##UREF##20##35##, ##UREF##21##36##] umbilical cord being significantly associated with the occurrence of fetal growth restriction. The possible justification could be due to the fact that, hypo-coiling may be associated with solidity of cord and hyper-coiling may lead to rotation of the cord; in both cases may be associated with interfering to fetoplacental blood flow which in turn leads to fetal growth restriction.</p>", "<p id=\"Par42\">The present study established an association between khat chewing during pregnancy and fetal growth restriction, but the association may not be causal. This is the major limitation of the current study. Therefore, in the interpretations of the present finding this limitation must be considered. However, this study has the following strengths. One is being a prospective cohort, as it establishes temporal relationships between khat chewing during pregnancy and fetal growth restriction. In addition, being a prospective cohort, the chance of missing data will be significantly reduced. The other strength is that the present study showed the mediation analysis model, thereby explaining the mechanism through which khat chewing during pregnancy can influence fetal growth restriction. At last, up to our effort, the present study is primary in its nature, especially in demonstrating the effect of khat chewing during pregnancy on fetal growth restriction in a prospective cohort study design approach in Ethiopia.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par43\">In sum, the present study showed khat chewing during pregnancy is not simply affected the mothers, but it also affected the unborn fetuses. Therefore, the health workers as well as the local community and religious leaders should give high emphasis on provision of health education regarding the damage of chewing khat by pregnant mothers, with especial focus of the effects on their fetuses.</p>" ]
[ "<title>Introduction</title>", "<p id=\"Par1\">Restriction in the growth of the fetus is a leading cause of stillbirth, neonatal mortality, and short- and long-term morbidity. Documented existing scientific evidence have shown the effects of maternal drugs use, alcohol drinking, tobacco smoking, cocaine use and heroin use on fetal growth restriction. However, data is lacking on the effects of khat chewing during pregnancy on fetal growth status and newborn size at birth. Therefore, the aim of the present study was to measure the effect of chewing khat during pregnancy on fetal growth and size at birth in eastern Ethiopia.</p>", "<title>Method</title>", "<p id=\"Par2\">A cohort study was conducted in selected health institutions in eastern Ethiopia. All pregnant women fulfilled the eligibility criteria in the selected health institutions was the source population. The calculated sample size of exposed and unexposed groups included in the study, in total, was 344. Data collection was performed prospectively by interviewers administered questionnaires, and anthropometric, clinical and ultrasound measurements. Data was analyzed using SPSS version 27 and STATA version 16 software. The survival analysis (cox proportional hazards model) and generalized linear model (GLM) for the binomial family analysis were performed to estimate the crude and adjusted relative risk and attributable risk (AR) with corresponding 95% CI of chewing khat on fetal growth restriction. The mediation effect has been examined through Generalized Structural Equation Modeling (GSEM) analysis using the Stata ‘gsem’ command. Statistically significant association was declared at <italic>p</italic>-value less than 5%.</p>", "<title>Results</title>", "<p id=\"Par3\">In the present study, the incidence of fetal growth restriction (FGR) among the study cohorts was 95 (29.7%); of this, 81 (85.3%) were among khat chewer cohorts. The relative risk of fetal growth restriction among khat chewer cohort mothers was significantly higher (aRR = 4.32; 95%CI 2.62–7.12). Moreover, the incidence of small for gestational age at birth among the present study cohorts was 100 (31.3%); 84 (84%) were from khat chewer cohorts’ deliveries. More importantly, in the present study, 98.95% of the ultrasound-identified fetuses with FGR were found to be SGA at birth. Hence, in the current study, FGR was highly associated with SGA at birth. In additional analysis, the regression coefficient of khat chewing during pregnancy on fetal growth restriction has been decreased in size from path o, β = 0.43, p &lt; 0.001 to path o’, β = 0.32, <italic>p</italic> &lt; 0.001, after adjusting for gestational hypertension and maternal anemia.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">In sum, the present study showed khat chewing during pregnancy is not simply affected the mothers, but it also affected the unborn fetuses. Therefore, the health workers as well as the local community and religious leaders should give high emphasis on provision of health education regarding the damage of chewing khat by pregnant mothers, with especial focus of the effects on their fetuses.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>The authors would like to acknowledge Addis Ababa University and Debre Markos University for providing financial support to conduct this study. Moreover, the authors would also like to acknowledge the study participants for their willingness to participate in the study.</p>", "<title>Author contributions</title>", "<p>A.T.W.: conception and designing of the research protocol, literature review, data collection, data entry, data analysis, interpretation, and drafting of the manuscript. M.A.: designing of the research protocol, data entry, data analysis, and manuscript editing. M.B.: literature review, data collection, supervision on data collection, data analysis, and manuscript editing. Y.B.: data collection, data analysis, interpretation, and manuscript editing. All authors have read and approved the manuscript.</p>", "<title>Funding</title>", "<p>Financial support for this research was obtained from Addis Ababa University and Debre Markos University.</p>", "<title>Data availability</title>", "<p>Data will be available upon request of the corresponding author.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participant</title>", "<p id=\"Par45\">Ethical approval was obtained from Institutional Review Board of College of Health Sciences, Addis Ababa University. All the study methods were carried out in accordance with relevant guidelines and regulations that is Declaration of Helsinki. In addition, informed written consent was obtained from all subjects and/or their legal guardian(s).</p>", "<title>Consent for publication</title>", "<p id=\"Par46\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par44\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Showed the adjusted effect sizes of khat chewing during pregnancy on fetal growth restriction through the potential mediators. β(<italic>p</italic>-value) of path k, 1, m and n is the indirect effects of khat chewing during pregnancy on FGR through gestational hypertension and maternal anemia. β(<italic>p</italic>-value) of path o and o’ is the direct effects of khat chewing during pregnancy on FGR before and after adjusting for gestational hypertension and maternal anemia respectively</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Comparison of behavioral characteristics of khat chewer and non-chewer cohorts in eastern Ethiopia, 2022 (<italic>N</italic> = 320)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Characteristics</th><th align=\"left\" colspan=\"2\">Khat chewing practices of cohorts</th><th align=\"left\"><italic>p</italic>-value</th></tr><tr><th align=\"left\">Chewers, Frequency (%)</th><th align=\"left\">Nonchewers, Frequency (%)</th><th align=\"left\"/></tr></thead><tbody><tr><td align=\"left\">Alcohol intake in last 1 months of pregnancy</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">31 (72.1%)</td><td align=\"left\">12 (27.9%)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.001</td></tr><tr><td align=\"left\">No</td><td align=\"left\">125 (45.1%)</td><td align=\"left\">152 (54.9%)</td></tr><tr><td align=\"left\">Beer intake in last 1 months of pregnancy</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">21 (77.8%)</td><td align=\"left\">6 (22.2%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.002</td></tr><tr><td align=\"left\">No</td><td align=\"left\">135 (46.1%)</td><td align=\"left\">158 (53.9%)</td></tr><tr><td align=\"left\">Amount of beer consumed (in bottle and gram equivalents) in a week</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">1 bottle (16.5 g of alcohol)</td><td align=\"left\">5 (83.3%)</td><td align=\"left\">1 (16.7%)</td><td char=\".\" align=\"char\" rowspan=\"3\">0.755</td></tr><tr><td align=\"left\">2 bottles (33 g of alcohol)</td><td align=\"left\">7 (70%)</td><td align=\"left\">3 (30%)</td></tr><tr><td align=\"left\">3 bottles (49.5 g of alcohol)</td><td align=\"left\">9 (81.8%)</td><td align=\"left\">2 (18.2%)</td></tr><tr><td align=\"left\">Wine intake in last 1 months</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">8 (61.5%)</td><td align=\"left\">5 (38.5%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.346</td></tr><tr><td align=\"left\">No</td><td align=\"left\">148 (48.2%)</td><td align=\"left\">159 (51.8%)</td></tr><tr><td align=\"left\">Amount of wine consumed (in glass and gram equivalents) in a week</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">1 glass (27.5 g of alcohol)</td><td align=\"left\">2 (50%)</td><td align=\"left\">2 (50%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.569</td></tr><tr><td align=\"left\">2 glasses (55 g of alcohol)</td><td align=\"left\">6 (66.7%)</td><td align=\"left\">3 (33.3%)</td></tr><tr><td align=\"left\">Homemade alcohol drinks (Tela)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">6 (66.7%)</td><td align=\"left\">3 (33.3%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.275</td></tr><tr><td align=\"left\">No</td><td align=\"left\">150 (48.2%)</td><td align=\"left\">161 (51.8%)</td></tr><tr><td align=\"left\">Overall levels of alcohol consumed in a week (converted to standard measures)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 1.5drinks (16.5 g of alcohol) (low)</td><td align=\"left\">5 (83.3%)</td><td align=\"left\">1 (16.7%)</td><td char=\".\" align=\"char\" rowspan=\"3\">0.641</td></tr><tr><td align=\"left\">1.5-3.5drinks (27.5–33 g of alcohol) (moderate)</td><td align=\"left\">9 (64.3%)</td><td align=\"left\">5 (35.7%)</td></tr><tr><td align=\"left\">&gt; 3.5drinks (49.5–55 g of alcohol) (high)</td><td align=\"left\">15 (75%)</td><td align=\"left\">5 (25%)</td></tr><tr><td align=\"left\">Smoking of any tobacco products</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">14 (77.8%)</td><td align=\"left\">4 (22.2%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.011</td></tr><tr><td align=\"left\">No</td><td align=\"left\">142 (47%)</td><td align=\"left\">160 (53%)</td></tr><tr><td align=\"left\">Frequency of tobacco smoking</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Daily</td><td align=\"left\">4 (57.1%)</td><td align=\"left\">3 (42.9%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.093</td></tr><tr><td align=\"left\">More than one day per a week</td><td align=\"left\">10 (90.9%)</td><td align=\"left\">1 (9.1%)</td></tr><tr><td align=\"left\">Coffee use of study cohorts</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">151 (49.7%)</td><td align=\"left\">153 (50.3%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.151</td></tr><tr><td align=\"left\">No</td><td align=\"left\">5 (31.3%)</td><td align=\"left\">11 (68.8%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Distribution of obstetric characteristics of study cohorts by their khat chewing practices in eastern Ethiopia, 2022 (<italic>N</italic> = 320)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Obstetric characteristics</th><th align=\"left\" colspan=\"2\">Khat chewing status of study cohorts</th><th align=\"left\" rowspan=\"2\"><italic>p</italic>-value</th></tr><tr><th align=\"left\">Chewers, Frequency (%)</th><th align=\"left\">Non-chewers, Frequency (%)</th></tr></thead><tbody><tr><td align=\"left\">Gravida</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">1 (primigravida)</td><td align=\"left\">24 (28.6%)</td><td align=\"left\">60 (71.4%)</td><td char=\".\" align=\"char\" rowspan=\"3\">&lt; 0.001</td></tr><tr><td align=\"left\">2 (secundigravida)</td><td align=\"left\">26 (41.9%)</td><td align=\"left\">36 (58.1%)</td></tr><tr><td align=\"left\">&gt;=3 (multigravida)</td><td align=\"left\">106 (60.9%)</td><td align=\"left\">68 (39.1%)</td></tr><tr><td align=\"left\">Para</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">0 (nullipara)</td><td align=\"left\">42 (38.2%)</td><td align=\"left\">68 (61.8%)</td><td char=\".\" align=\"char\" rowspan=\"3\">0.003</td></tr><tr><td align=\"left\">1 (primipara)</td><td align=\"left\">27 (43.5%)</td><td align=\"left\">35 (56.5%)</td></tr><tr><td align=\"left\">&gt;=2(multipara)</td><td align=\"left\">87 (58.8%)</td><td align=\"left\">61 (41.2%)</td></tr><tr><td align=\"left\">Spontaneous abortion history</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">84 (80.8%)</td><td align=\"left\">20 (19.2%)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.001</td></tr><tr><td align=\"left\">No</td><td align=\"left\">72 (33.3%)</td><td align=\"left\">144 (66.7%)</td></tr><tr><td align=\"left\">Previous still birth history</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">26 (52%)</td><td align=\"left\">24 (48%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.617</td></tr><tr><td align=\"left\">No</td><td align=\"left\">130 (48.1%)</td><td align=\"left\">140 (51.9%)</td></tr><tr><td align=\"left\">Gestational age at time of enrollments</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">24–26 weeks</td><td align=\"left\">125 (47.3%)</td><td align=\"left\">139 (52.7%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.276</td></tr><tr><td align=\"left\">27–28 weeks</td><td align=\"left\">31 (55.4%)</td><td align=\"left\">25 (44.6%)</td></tr><tr><td align=\"left\">ANC visits at time of enrollments</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">1st</td><td align=\"left\">126 (52.5%)</td><td align=\"left\">114 (47.5%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.02</td></tr><tr><td align=\"left\">2nd</td><td align=\"left\">30 (37.5%)</td><td align=\"left\">50 (62.5%)</td></tr><tr><td align=\"left\"><p>Number of ANC visits attended at the</p><p>end of delivery</p></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 4 ANC visits</td><td align=\"left\">151 (53.4%)</td><td align=\"left\">132 (46.6%)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.001</td></tr><tr><td align=\"left\">&gt;=4 ANC visits</td><td align=\"left\">5 (13.5%)</td><td align=\"left\">32 (86.5%)</td></tr><tr><td align=\"left\">History of malaria</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">5 (45.5%)</td><td align=\"left\">6 (54.5%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.824</td></tr><tr><td align=\"left\">No</td><td align=\"left\">151 (48.9%)</td><td align=\"left\">158 (51.1%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Comparison of bodily measurements and umbilical cord status of khat chewer and non-khat chewer study cohorts in eastern Ethiopia, 2022 (<italic>N</italic> = 320)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Measurements</th><th align=\"left\" colspan=\"2\">Khat chewing characteristics of study cohorts</th><th align=\"left\" rowspan=\"2\"><italic>p</italic>-value</th></tr><tr><th align=\"left\">Chewers, Frequency (%)</th><th align=\"left\">Nonchewers, Frequency (%)</th></tr></thead><tbody><tr><td align=\"left\">Weight (in kg)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 50 kg</td><td align=\"left\">8 (47.1%)</td><td align=\"left\">9 (52.9%)</td><td char=\".\" align=\"char\" rowspan=\"4\">&lt; 0.001</td></tr><tr><td align=\"left\">50-60 kg</td><td align=\"left\">63 (57.3%)</td><td align=\"left\">47 (42.7%)</td></tr><tr><td align=\"left\">61-70 kg</td><td align=\"left\">54 (36%)</td><td align=\"left\">96 (64%)</td></tr><tr><td align=\"left\">&gt; 70 kg</td><td align=\"left\">31 (72.1%)</td><td align=\"left\">12 (27.9%)</td></tr><tr><td align=\"left\">Mean (SD) weight (in kg)</td><td align=\"left\">63.48 ± 10.67</td><td align=\"left\">63.08 ± 7.55</td><td char=\".\" align=\"char\">0.697</td></tr><tr><td align=\"left\">Height (in cm)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 145 cm</td><td align=\"left\">18 (48.6%)</td><td align=\"left\">19 (51.4%)</td><td char=\".\" align=\"char\" rowspan=\"3\">0.967</td></tr><tr><td align=\"left\">145-157 cm</td><td align=\"left\">39 (50%)</td><td align=\"left\">39 (50%)</td></tr><tr><td align=\"left\">&gt; 157 cm</td><td align=\"left\">99 (48.3%)</td><td align=\"left\">106 (51.7%)</td></tr><tr><td align=\"left\">Mean (SD) height (in cm)</td><td align=\"left\">157.31 ± 13.92</td><td align=\"left\">157.59 ± 12.81</td><td char=\".\" align=\"char\">0.85</td></tr><tr><td align=\"left\">BMI (in kg/m<sup>2</sup>)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 18.5</td><td align=\"left\">4 (50%)</td><td align=\"left\">4 (50%)</td><td char=\".\" align=\"char\" rowspan=\"4\">&lt; 0.001</td></tr><tr><td align=\"left\">18.5–24.9</td><td align=\"left\">82 (53.9%)</td><td align=\"left\">70 (46.1%)</td></tr><tr><td align=\"left\">25-29.9</td><td align=\"left\">35 (31.8%)</td><td align=\"left\">75 (68.2%)</td></tr><tr><td align=\"left\">&gt;=30</td><td align=\"left\">35 (70%)</td><td align=\"left\">15 (30%)</td></tr><tr><td align=\"left\">Mean (SD) BMI (in kg/m<sup>2</sup>)</td><td align=\"left\">25.86 ± 4.29</td><td align=\"left\">25.61 ± 3.39</td><td char=\".\" align=\"char\">0.559</td></tr><tr><td align=\"left\">MUAC (in cm)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 23 cm</td><td align=\"left\">22 (47.8%)</td><td align=\"left\">24 (52.2%)</td><td char=\".\" align=\"char\" rowspan=\"4\">0.013</td></tr><tr><td align=\"left\">23-27.9 cm</td><td align=\"left\">77 (55.4%)</td><td align=\"left\">62 (44.6%)</td></tr><tr><td align=\"left\">28-32.9 cm</td><td align=\"left\">44 (37.9%)</td><td align=\"left\">72 (62.1%)</td></tr><tr><td align=\"left\">&gt;=33 cm</td><td align=\"left\">13 (68.4%)</td><td align=\"left\">6 (31.6%)</td></tr><tr><td align=\"left\">Mean (SD) MUAC (in cm)</td><td align=\"left\">26.96 ± 3.77</td><td align=\"left\">26.81 ± 3.24</td><td char=\".\" align=\"char\">0.701</td></tr><tr><td align=\"left\">Twists of umbilical cord</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Under coiled</td><td align=\"left\">29 (70.7%)</td><td align=\"left\">12 (29.3%)</td><td char=\".\" align=\"char\" rowspan=\"3\">0.002</td></tr><tr><td align=\"left\">Normal</td><td align=\"left\">111 (43.9%)</td><td align=\"left\">142 (56.1%)</td></tr><tr><td align=\"left\">Hyper twisted</td><td align=\"left\">16 (61.5%)</td><td align=\"left\">10 (38.5%)</td></tr><tr><td align=\"left\">True knots identified in umbilical cords</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">27 (62.8%)</td><td align=\"left\">16 (37.2%)</td><td char=\".\" align=\"char\" rowspan=\"2\">0.048</td></tr><tr><td align=\"left\">No</td><td align=\"left\">129 (46.6%)</td><td align=\"left\">148 (53.4%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Comparison of the effects of khat chewing during pregnancy on fetal growth restriction among study cohorts in eastern Ethiopia, 2022 (<italic>N</italic> = 320)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variables</th><th align=\"left\" colspan=\"2\">Fetal growth restriction</th><th align=\"left\" rowspan=\"2\">aRR (95%CI)</th><th align=\"left\" rowspan=\"2\"><italic>p</italic>-value</th></tr><tr><th align=\"left\">Yes, N<underline>o</underline> (%)</th><th align=\"left\">No, N<underline>o</underline> (%)</th></tr></thead><tbody><tr><td align=\"left\">\n<bold>Khat chewing status</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Chewers</td><td char=\".\" align=\"char\">81 (85.3%)</td><td align=\"left\">75 (33.3%)</td><td align=\"left\">4.32 (2.62–7.12)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.001</td></tr><tr><td align=\"left\">Non chewers</td><td char=\".\" align=\"char\">14 (14.7%)</td><td align=\"left\">150 (66.7%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\"><p>\n<bold>Age group of</bold>\n</p><p>\n<bold>study participants</bold>\n</p></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt;=24 years</td><td char=\".\" align=\"char\">28 (29.5%)</td><td align=\"left\">94 (41.8%)</td><td align=\"left\">0.85 (0.42–1.73)</td><td char=\".\" align=\"char\" rowspan=\"4\">&gt; 0.05</td></tr><tr><td align=\"left\">25–29 years</td><td char=\".\" align=\"char\">35 (36.8%)</td><td align=\"left\">87 (38.7%)</td><td align=\"left\">1.29 (0.67–2.5)</td></tr><tr><td align=\"left\">30–34 years</td><td char=\".\" align=\"char\">14 (14.7%)</td><td align=\"left\">30 (13.3%)</td><td align=\"left\">1.55 (0.6–3.97)</td></tr><tr><td align=\"left\">&gt;=35 years</td><td char=\".\" align=\"char\">18 (18.95%)</td><td align=\"left\">14 (6.2%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>Participants area of residence</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Urban</td><td char=\".\" align=\"char\">27 (28.4%)</td><td align=\"left\">149 (66.2%)</td><td align=\"left\">0.46 (0.26–0.81)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.05</td></tr><tr><td align=\"left\">Rural</td><td char=\".\" align=\"char\">68 (71.6%)</td><td align=\"left\">76 (33.8%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>Participants educational status</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">No formal education</td><td char=\".\" align=\"char\">43 (45.3%)</td><td align=\"left\">56 (24.9%)</td><td align=\"left\">1.4 (0.57–3.52)</td><td char=\".\" align=\"char\" rowspan=\"4\">&gt; 0.05</td></tr><tr><td align=\"left\">Primary education</td><td char=\".\" align=\"char\">24 (25.3%)</td><td align=\"left\">56 (24.9%)</td><td align=\"left\">1.98 (0.78–5.04)</td></tr><tr><td align=\"left\">Secondary education</td><td char=\".\" align=\"char\">16 (16.8%)</td><td align=\"left\">57 (25.3%)</td><td align=\"left\">1.2 (0.49–3.09)</td></tr><tr><td align=\"left\">Tertiary education</td><td char=\".\" align=\"char\">12 (12.6%)</td><td align=\"left\">56 (24.9%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>Participants Occupation</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">House wife/ Homemaker</td><td char=\".\" align=\"char\">15 (15.8%)</td><td align=\"left\">53 (23.6%)</td><td align=\"left\">0.93 (0.29–3.04)</td><td char=\".\" align=\"char\" rowspan=\"5\">&gt; 0.05</td></tr><tr><td align=\"left\">Farmer</td><td char=\".\" align=\"char\">29 (30.5%)</td><td align=\"left\">61 (27.1%)</td><td align=\"left\">1.16 (0.41–3.26)</td></tr><tr><td align=\"left\">Employee</td><td char=\".\" align=\"char\">10 (10.5%)</td><td align=\"left\">40 (17.8%)</td><td align=\"left\">0.35 (0.10–1.18)</td></tr><tr><td align=\"left\">Merchant</td><td char=\".\" align=\"char\">35 (36.8%)</td><td align=\"left\">58 (25.8%)</td><td align=\"left\">1.35 (0.48–3.75)</td></tr><tr><td align=\"left\">Daily laborer</td><td char=\".\" align=\"char\">6 (6.3%)</td><td align=\"left\">13 (5.8%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>Alcohol use during current pregnancy</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td char=\".\" align=\"char\">20 (21.1%)</td><td align=\"left\">23 (10.2%)</td><td align=\"left\">1.72 (0.89–3.27)</td><td char=\".\" align=\"char\" rowspan=\"2\">&gt; 0.05</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">75 (78.9%)</td><td align=\"left\">202 (89.8%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>Cigarette smoking during current pregnancy</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td char=\".\" align=\"char\">14 (14.7%)</td><td align=\"left\">4 (1.8%)</td><td align=\"left\">2.14 (1.03–4.44)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.05</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">81 (85.3%)</td><td align=\"left\">221 (98.2%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>Total ANC visits attended</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 4 ANC visits</td><td char=\".\" align=\"char\">88 (92.6%)</td><td align=\"left\">195 (86.7%)</td><td align=\"left\">0.85 (0.34–2.14)</td><td char=\".\" align=\"char\" rowspan=\"2\">&gt; 0.05</td></tr><tr><td align=\"left\">&gt;=4 ANC visits</td><td char=\".\" align=\"char\">7 (7.4%)</td><td align=\"left\">30 (13.3%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>MUAC (in cm)</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 23 cm</td><td char=\".\" align=\"char\">16 (16.8%)</td><td align=\"left\">30 (13.3%)</td><td align=\"left\">1.12 (0.34–3.74)</td><td char=\".\" align=\"char\" rowspan=\"4\">&gt; 0.05</td></tr><tr><td align=\"left\">23-27.9 cm</td><td char=\".\" align=\"char\">53 (55.8%)</td><td align=\"left\">86 (38.2%)</td><td align=\"left\">1.19 (0.42–3.39)</td></tr><tr><td align=\"left\">28-32.9 cm</td><td char=\".\" align=\"char\">17 (17.9%)</td><td align=\"left\">99 (44%)</td><td align=\"left\">0.77 (0.26–2.30)</td></tr><tr><td align=\"left\">&gt;=33 cm</td><td char=\".\" align=\"char\">9 (9.5%)</td><td align=\"left\">10 (4.4%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>BMI (in kg/m</bold>\n<sup><bold>2</bold></sup>\n<bold>)</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 18.5</td><td char=\".\" align=\"char\">4 (4.2%)</td><td align=\"left\">4 (1.8%)</td><td align=\"left\">1.43 (0.40–5.09)</td><td char=\".\" align=\"char\" rowspan=\"4\">&gt; 0.05</td></tr><tr><td align=\"left\">18.5–24.9</td><td char=\".\" align=\"char\">31 (32.6%)</td><td align=\"left\">121 (53.8%)</td><td align=\"left\">0.83 (0.44–1.57)</td></tr><tr><td align=\"left\">25-29.9</td><td char=\".\" align=\"char\">30 (31.6%)</td><td align=\"left\">80 (35.6%)</td><td align=\"left\">1.95 (0.97–3.92)</td></tr><tr><td align=\"left\">&gt;=30</td><td char=\".\" align=\"char\">30 (31.6%)</td><td align=\"left\">20 (8.9%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\">\n<bold>True knots in umbilical cords</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td char=\".\" align=\"char\">33 (34.7%)</td><td align=\"left\">10 (4.4%)</td><td align=\"left\">2.35 (1.08–5.12)</td><td char=\".\" align=\"char\" rowspan=\"2\">&lt; 0.05</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">62 (65.3%)</td><td align=\"left\">215 (95.6%)</td><td align=\"left\">1</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>The relationship between khat chewing during pregnancy, potential mediators and fetal growth restriction of the study cohorts in eastern Ethiopia, 2022 (<italic>N</italic> = 320): A generalized structural equation modeling analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Model</th><th align=\"left\"/><th align=\"left\">β*(95% CI)</th><th align=\"left\"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align=\"left\">Fetal growth restriction</td><td align=\"left\">Khat consumption effect on gestational hypertension</td><td char=\".\" align=\"char\">0.15 (0.06–0.24)</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\"/><td align=\"left\">Gestational hypertension effect on FGR</td><td char=\".\" align=\"char\">0.09 (0.011–0.11)</td><td char=\".\" align=\"char\">&lt; 0.05</td></tr><tr><td align=\"left\"/><td align=\"left\">Khat consumption effect on maternal anemia</td><td char=\".\" align=\"char\">0.19 (0.089–0.29)</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr><tr><td align=\"left\"/><td align=\"left\">Maternal anemia effect on FGR</td><td char=\".\" align=\"char\">0.105 (0.016–0.19)</td><td char=\".\" align=\"char\">&lt; 0.05</td></tr><tr><td align=\"left\"/><td align=\"left\">Khat consumption effect on FGR before adjustment for gestational hypertension and maternal anemia</td><td char=\".\" align=\"char\">0.43 (0.35–0.52)</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr><tr><td align=\"left\"/><td align=\"left\">Khat consumption effect on FGR after adjustment for gestational hypertension and maternal anemia</td><td char=\".\" align=\"char\">0.32 (0.24–0.43)</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>aRR: adjusted relative risk</p></table-wrap-foot>", "<table-wrap-foot><p>*=adjusted for maternal age, residence, education status, occupation status, alcohol use, tobacco smoke, ANC visits, MUAC, BMI, oligohydramnios, placental abruptio, true knots in umbilical cord</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12884_2024_6243_Fig1_HTML\" id=\"d32e1837\"/>" ]
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{ "acronym": [ "ARR", "ANC", "AR", "BMI", "CI", "FGR", "GLM", "IQR", "LMP", "MUAC", "PROM", "SGA", "SD", "WHO" ], "definition": [ "Adjusted Relative Risk", "Ante Natal Care", "Attributable Risk", "Body Mass Index", "Confidence Interval", "Fetal Growth Restriction", "Generalized Linear Model", "Inter Quartile Range", "Last Menstrual Period", "Mid-Upper Arm Circumference", "Pre-labor Rupture of Membranes", "Small for Gestational Age", "Standard deviation", "World Health Organization" ] }
36
CC BY
no
2024-01-14 23:43:45
BMC Pregnancy Childbirth. 2024 Jan 13; 24:63
oa_package/09/e0/PMC10787403.tar.gz
PMC10787404
0
[ "<title>Background</title>", "<p id=\"Par4\">The term “Ophelia syndrome” was first used by Carr in 1982 to describe the limbic encephalitis in his daughter associated with Hodgkin’s lymphoma [##UREF##0##1##]. It was until 2011 that the metabolic glutamate receptor5 (mGluR5) antibody was finally identified in this syndrome in two patients [##REF##22013185##2##]. The disease was mostly accompanied by tumors, mainly Hodgkin's lymphoma. There are limited numbers of mGluR5 encephalitis, cases in children are particularly rare. No reports of other tumors, such as gangliocytoma have been reported to associate with anti-mGlur5 encephalitis so far. This paper reported a case of gangliocytoma-associated autoimmune encephalitis (AE) with positive mGluR5 antibodies in a boy, which suggests clinicians to pay attention to the possibility of anti-mGluR5 encephalitis associated with other tumors except Hodgkin's lymphoma.</p>" ]
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[ "<title>Discussion</title>", "<p id=\"Par9\">The mGluR5 is a pro-metabolic glutamate receptor, located in the postsynaptic terminal of neurons and microglia cells, which is an important mediator of excitatory synaptic transmission. It mainly expresses in the amygdala and hippocampus [##REF##30707437##3##, ##REF##27112679##4##], and plays a role in memory and behavioral learning [##REF##20055706##5##, ##REF##22113957##6##]. The mGluR5 antibodies belong to the antineuronal cell surface antigen antibodies, binding to mGluR5 on the cell surface, resulting in the decrease of mGluR5 cluster density, which is speculated to be the possible pathogenic mechanism. However, the exact mechanism of mGluR5 is still unknown [##UREF##1##7##, ##REF##29777761##8##].</p>", "<p id=\"Par10\">At present, only few cases of anti-mGluR5 encephalitis described (18 patients in total, only 5 children among them) worldwide, which occurred at different ages, but the median age was 35 years [##REF##22013185##2##, ##UREF##1##7##, ##REF##25194012##9##–##REF##35386694##17##]. The observed clinical phenotype previously reported showed that most cases were subacute onset, including prodromal symptoms such as low fever, weight loss, headache, respiratory system and digestive system diseases. Limbic system symptoms were mainly manifested, including seizures, cognitive and mental disorders, sleep disorders, language disorders, movement disorders, etc.</p>", "<p id=\"Par11\">In our study, the patient was a 12-year-old boy with subacute onset, with headache, low fever and other prodromal symptoms. The neurological symptoms mainly included mental disorders (hallucinations, mood changes, etc.) and sleep disorders. Among the 18 reported cases, mental symptoms was the main manifestations (90%), but the child had no obvious seizures, cognitive disorders, movement disorders and cranial nerve involvement, which were quite unique compared with previous reported cases. For cerebrospinal fluid of patients of anti-mGluR5 encephalitis, the number of white blood cells was increased, and the specific oligoclonal zones were mostly positive. Electroencephalogram in some patients may have abnormal findings, such as diffuse or localized slow wave, visible epileptic discharge. MRI in some patients may be positive, with limbic system lesions, but thalamus, pontine, cerebellum and fronto-parietal occipital lobe may also be involved. Cerebrospinal fluid examination of this patient showed pleocytosis (&gt; 5 × 10<sup>6</sup>/L) and lymphocytic inflammation. Cerebrospinal fluid oligonclonal zone was positive, and MRI showed a few abnormal enhanced signal shadows in the right insular lobe, which consistent with the manifestations of marginal lobe encephalitis. However, no significant abnormalities in multiple electroencephalograms were found in this patient, which was different as previous reported cases. It suggests that autoimmune encephalitis may not result in EEG background wave slowing and epileptic wave release. After first-line immunotherapy (immunoglobulin combined with glucocorticoid), ganglion cell tumor resection and other treatments, the symptoms of the child were gradually relieved. During follow-up, the neurological symptoms were recurrence, but they were relieved after active treatment again. The recurrence may be related to the low dose or short course of the first methylprednisolone shock therapy. Among the previously reported cases, 2 patients had recurrent neurological symptoms during follow-up, including 1 patient with tumor recurrence. Overall, all reported cases achieved complete or partial remission except for one death, suggesting prognosis of this disease is good. However, close follow-up is necessary in order to pay attention to neurological symptoms and the possibility of tumor recurrence. Clinical information, results from ancillary tests, treatment, and outcome at last follow-up in 6 children are detailed in Table ##TAB##0##1##.</p>", "<p id=\"Par12\">In addition, among the 18 cases reported so far, more than half of them were accompanied by Hodgkin's lymphoma, and 1 case was small cell lung cancer. The mechanism by which Hodgkin's lymphoma or other malignancies are associated with autoimmune encephalitis is not well understood. In fact, in the majority cases of autoimmune encephalitis, a clear triggering factor is elusive. There is evidence from cohort studies that age, ethnicity, and HLA type may increase susceptibility [##REF##29572931##18##]. Recently, Guo et. al reported that over half of the Western patients with anti-mGluR5 encephalitis had associated tumors (mainly Hodgkin’s disease), however, only 13% of Chinese patients had associated tumors, and none of them had Hodgkin’s disease at the last follow-up [##UREF##8##19##].</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par13\">Taken together we report the first patient with anti-mGlur5 encephalitis complicated with gangliocytoma. It suggests that in addition to paying attention to the common lymphoma associated with anti-mGlur5 encephalitis, we should also screen the possibility of other tumors for early detection of the cause, active treatment and prevention of recurrence.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">There are very limited reports on anti-metabolic glutamate receptor5 (mGluR5) encephalitis, especially lacking of pediatric research. The disease was mostly accompanied by tumors, mainly Hodgkin's lymphoma. No reports of other tumors, such as gangliocytoma have been reported to associate with anti-mGluR5 encephalitis so far.</p>", "<title>Case presentation and literature reviews</title>", "<p id=\"Par2\">We reported a case of a 12-year-old boy with anti-mGluR5 encephalitis complicated with gangliocytoma. The patient suffered from mental disorders including auditory hallucination, and sleep disorders. His cranial magnetic resonance imaging (MRI) showed an abnormality in the right insular lobe. Autoimmune encephalitis antibodies testing was positive for mGluR5 IgG antibody both in cerebrospinal fluid and serum (1:3.2, 1:100 respectively). Abdominal CT indicated a mass in left retroperitoneal confirmed with gangliocytoma via pathology. The patient underwent resection of gangliocytoma. After first-line immunotherapy (glucocorticoid, gamma globulin), his condition was improved. Furthermore, we provide a summary of 6 pediatric cases of Anti-mGluR5 encephalitis. Most of them complicated with Hodgkin's lymphoma, except the case currently reported comorbid with gangliocytoma. The curative effect is satisfactory.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">We report the first patient with anti-mGlur5 encephalitis complicated with gangliocytoma. It suggests that in addition to paying attention to the common lymphoma associated with anti-mGlur5 encephalitis, we should also screen the possibility of other tumors for early detection of the cause, active treatment and prevention of recurrence.</p>", "<title>Keywords</title>" ]
[ "<title>Case presentation</title>", "<p id=\"Par5\">The patient was a 12-year-old boy. He was admitted to hospital on May 06, 2022. The patient had intermittent headache 20 days ago, with intermittent fever 10 days ago, accompanied by mental symptoms such as irritability, auditory hallucinations, and sleep disorders. His memory and comprehension decreased. He had auditory hallucination. The muscle force, muscle tone of limbs and tendon reflexes were normal. The coordination movement and sensation detection were normal. Meningeal stimulation signs and pathological signs were negative.</p>", "<p id=\"Par6\">Brain MRI showed a few speckled abnormal enhanced signal shadows in the right insular lobe, suggesting inflammatory changes (Fig. ##FIG##0##1##). Abdominal CT indicated a mass in left retroperitoneal (Fig. ##FIG##1##2##). Resection of the mass in left retroperitoneal was performed, and the pathological immunohistochemistry was consistent with gangliocytoma (Fig. ##FIG##2##3##). Cerebrospinal fluid (CSF) analysis showed WBC count 90.0 × 10^6/L with a lymphocytic predominance, normal levels of protein and glucose. The oligoclonal bands both in the CSF and serum were positive. The IgG content in CSF and serum was 135.0 mg/L (10-30 mg/L) and 31.67 g/L (7–16 g/L) respectively. Electroencephalogram (EEG) demonstrated no epileptiform discharges or seizures. Serum and CSF autoimmune encephalitis antibodies, including anti-NMDAR, anti-AMPAR1, anti-AMPAR2, anti-LGI1, anti-CASPR2, anti-GABABR, anti-DPPX, anti-igLON5, and anti-GAD65 were all negative by cell-based assay, with the exception of anti-mGluR5 being positive either in the cerebrospinal fluid (1:3.2) or serum (1:100) (Fig. ##FIG##3##4##), while tissue-based assay in monkey cerebellum was negative. They were all carried out at Guangzhou V-Medical Laboratory Co., Ltd., China using an autoimmune encephalitis IgG antibody kit manufactured by EUROIMMUN AG, Luebeck, Germany. Laboratory indirect immunofluorescence procedures are as follows: 1. Preparation: The samples and reagent are balanced to room temperature. 2. Incubation: Add samples in the reaction area of sample adding according to the sample adding scheme. Cover the side of the slide covered with biological sheet in the groove of sample adding, and incubate for 30 min at room temperature. 3. Washing: Rinse the slide with a flush of PBS-Tween using a beaker and immerse them immediately afterwards in a cuvette containing PBS-Tween for at least 5 min. 4. Incubation: Apply fluorescein labelled anti-human globulin and incubate at room temperature for 30 min away from light. 5. Washing: same cleaning steps as above. 6. Mounting: Place mounting medium onto a cover glass. Use a polystyrene mounting tray. Put the BIOCHIP slide, with the BIOCHIPs facing downwards, onto the prepared cover glass. 7. Evaluation: Read the fluorescence with the microscope. A package of CSF infectious studies were negative including herpes simplex virus polymerase chain reaction.</p>", "<p id=\"Par7\">The clinical diagnosis was paraneoplastic autoimmune encephalitis. For treatment of AE, the patient received intravenous immunoglobulin (0.4 g/kg/d*5 days) for blocking relevant antibodies, and resection of the gangliocytoma subsequently. Then intravenous methylprednisolone (10 mg/kg/d-5 mg/kg/d-2.5 mg/kg/d for 3 days respectively). Oral prednisone was then initiated, starting at 2 mg/kg/d and the amount was gradually reduced. After 1 month of treatment, the patient's mental symptoms improved significantly and was discharged from hospital.</p>", "<p id=\"Par8\">However, the patient re-hospitalized again on June 28, 2022 due to poor medication compliance. The brain MRI showed no encephalitis lesions. The mGluR5 antibody IgG in serum and cerebrospinal fluid were re-tested and no obvious changes were shown. Abdominal ultrasonography was normal. The IVIg (0.4 g/kg/d*5 days) and glucocorticoids (500 mg/d-400 mg/d-300 mg/d-200 mg/d-100 mg/d for 2 days respectively). Oral prednisone was then initiated, starting at 2 mg/kg/d and the amount was gradually reduced. He was discharged after condition improved significantly. Follow-up revealed the symptoms of patient were relatively stable, with occasional hallucinations mentioned.</p>" ]
[ "<title>Acknowledgements</title>", "<p>The authors thank the patient for his participation in this study.</p>", "<title>Authors’ contributions</title>", "<p>KLS and HMZ: searched and screened the literature, extracted and analyzed the data, drafting the manuscript. YL, WXC, XJL: collate the data and guide manuscript writing. WXC: revising the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>Not applicable.</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par14\">This study was approved by the Committee of Guangzhou Women and Children’s Medical Center and conducted ethically in accordance with the World Medical Association Declaration of Helsinki. Written informed consent was obtained from his parents.</p>", "<title>Consent for publication</title>", "<p id=\"Par15\">Written informed consent regarding the submission and potential publication of this manuscript was obtained from his parents. Additionally, consent for treatment was likewise obtained in the usual fashion during the course of the patient’s hospitalization.</p>", "<title>Competing interests</title>", "<p id=\"Par16\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The brain MRI image of the patient. Red arrow showed a few speckled abnormal enhanced signal shadows in the right insular lobe</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Abdominal CT images of the patient. Red arrows showed a soft tissue mass on the left side of the retroperitoneal abdominal aorta (3.8*2.0*1.8 cm)</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Pathological examination of the abdominal mass suggested gangliocytoma, mature and medium-sized</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Testing of cerebrospinal fluid and serum for antibodies to metabotropic Glutamate receptor 5 was positive on cell based assay. <bold>A</bold> cerebrospinal fluid (1:3.2); <bold>B</bold> serum (1:100)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Main clinical features, examination, treatment and prognosis in 6 children with anti-mGluR5 encephalitis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Patient sex, age (y)</th><th align=\"left\">Prodromal features</th><th align=\"left\">Main clinical features</th><th align=\"left\">Tumor</th><th align=\"left\">CSF analysis</th><th align=\"left\">MRI</th><th align=\"left\">Treatment</th><th align=\"left\">Last follow-up, mo; outcome;</th></tr></thead><tbody><tr><td align=\"left\">Patient1 M,15</td><td align=\"left\">Headache, nausea</td><td align=\"left\">Confusion, auditory and visual hallucinations, decreased verbal output, attention deficit, status epilepticus</td><td align=\"left\">Hodgkin's lymphoma</td><td align=\"left\">114 WBC, OCB</td><td align=\"left\">Bilateral (left &gt; right) posterior cortical diffusion restriction</td><td align=\"left\">Chemotherapy, RT</td><td align=\"left\">72; Complete recovery</td></tr><tr><td align=\"left\">Patient2 F,16</td><td align=\"left\">Headache</td><td align=\"left\">Psychosis, hallucinations, poor sleep, dystonia, generalized seizures</td><td align=\"left\">Hodgkin's lymphoma</td><td align=\"left\">31 WBC, OCB</td><td align=\"left\">Normal</td><td align=\"left\">Steroids, chemotherapy, PE</td><td align=\"left\">48; Symptoms of Neurological symptom and tumor recurrence</td></tr><tr><td align=\"left\">Patient3 F,6</td><td align=\"left\">Rash, headache, flulike symptoms</td><td align=\"left\">Status epilepticus, dLOC, memory loss, poor sleep with altered sleep–wake cycle, followed by dystonia and oculogyric crisis, psychomotor slowness, ataxia, speech and motor regression, hypoventilation</td><td align=\"left\">None</td><td align=\"left\">21WBC OCB negative</td><td align=\"left\">Bilateral frontal (left &gt; right) and right occipital lobes, cerebellum</td><td align=\"left\">Steroids, IVIg, RTX</td><td align=\"left\">19; Partial, improved aphasia, cannot walk unassisted</td></tr><tr><td align=\"left\">Patient4 M,15</td><td align=\"left\">None</td><td align=\"left\">Facial paralysis, then developed altered behavior, memory loss, anxiety, irritability, visual hallucinations, insomnia</td><td align=\"left\">Hodgkin's lymphoma</td><td align=\"left\">45 WBC, OCB</td><td align=\"left\">Normal</td><td align=\"left\">Steroids, IVIg, chemotherapy</td><td align=\"left\">12; Moderate memory problems</td></tr><tr><td align=\"left\">Patient5 F,15</td><td align=\"left\">loss of appetite</td><td align=\"left\">Psychobehavioral abnormalities, seizures, generalized myoclonus</td><td align=\"left\">None</td><td align=\"left\">Normal</td><td align=\"left\">Mild cerebral atrophy</td><td align=\"left\">Steroids, IVIg</td><td align=\"left\">3; Lethargy</td></tr><tr><td align=\"left\">Patient6 M,12 this case</td><td align=\"left\">headache, intermittent fever</td><td align=\"left\">hallucination and auditory hallucination, mental disorders, sleep disorder</td><td align=\"left\">gangliocytoma </td><td align=\"left\">90.0 WBC, OCB</td><td align=\"left\">encephalitis in limbic</td><td align=\"left\">Steroids, IVIg resection of gangliocytoma</td><td align=\"left\">3;occasional hallucinations mentioned</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>Abbreviations:</italic> dLOC decreased level of consciousness, IgG immunoglobulin G, IVIg IV immunoglobulin, mGluR5 metabotropic glutamate receptor 5, OCB CSF oligoclonal bands, PE plasma exchange, RT radiotherapy, RTX rituximab, WBC white blood cells per mm</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Kaili Shi and Huimin Zhao are joint first authors.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12883_2024_3528_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12883_2024_3528_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12883_2024_3528_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"12883_2024_3528_Fig4_HTML\" id=\"MO4\"/>" ]
[]
[{"label": ["1."], "surname": ["Carr"], "given-names": ["I"], "article-title": ["The Ophelia syndrome:memory loss in Hodgkin's disease"], "source": ["Lancet"], "year": ["1982"], "volume": ["10"], "fpage": ["844"], "lpage": ["845"], "pub-id": ["10.1016/S0140-6736(82)91887-6"]}, {"label": ["7."], "surname": ["Spatola", "Sabater", "Planagum\u00e0"], "given-names": ["M", "L", "J"], "article-title": ["Encephalitis with mGluR5 antibodies: symptoms and antibody effects"], "source": ["Neurology"], "year": ["2018"], "volume": ["90"], "fpage": ["1964"], "lpage": ["1972"], "pub-id": ["10.1212/WNL.0000000000005614"]}, {"label": ["10."], "surname": ["Chen", "Gu", "Xu"], "given-names": ["YQ", "H", "G"], "article-title": ["An electroencephalogram manifested as a delta brush of antimetabolic glutamate receptor 5 encephalitis in one case"], "source": ["Chin J Neurol"], "year": ["2021"], "volume": ["54"], "fpage": ["131"], "lpage": ["135"]}, {"label": ["11."], "surname": ["Guo", "Lin", "Hong"], "given-names": ["KD", "J", "Z"], "article-title": ["Anti-mglur5 encephalitis: a case report"], "source": ["Chin J Nerv ment Dis"], "year": ["2021"], "volume": ["47"], "fpage": ["44"], "lpage": ["47"]}, {"label": ["12."], "mixed-citation": ["Huang QM,Tang YL. Autoimmune encephalitis with mGluR5 antibody overlap: a case report. Chin Med Case Repository. 2022;04(01):E02924."]}, {"label": ["13."], "surname": ["Guevara", "Farias", "Silva-Rosas"], "given-names": ["C", "G", "C"], "article-title": ["Encephalitis Associated to Metabotropic Glutamate Receptor 5 (mGluR5) Antibodies in Cerebrospinal Fluid"], "source": ["Front Immunol"], "year": ["2018"], "volume": ["5"], "fpage": ["2568"], "pub-id": ["10.3389/fimmu.2018.02568"]}, {"label": ["14."], "surname": ["Fu", "Peng", "Yang"], "given-names": ["J", "L", "Y"], "article-title": ["Case report: Overlapping syndrome mimicking infectious meningoencephalitis in a patient with coexistent MOG, NMDAR, mGluR5 antibody positivity"], "source": ["Front Immunol"], "year": ["2022"], "volume": ["5"], "issue": ["13"], "fpage": ["919125"], "pub-id": ["10.3389/fimmu.2022.919125"]}, {"label": ["15."], "surname": ["Huo", "Zhao", "Wang"], "given-names": ["T", "J", "T"], "article-title": ["A Chinese female patient with LGI1 and mGluR5 antibodies: A case report"], "source": ["Medicine (Baltimore)."], "year": ["2022"], "volume": ["43"], "fpage": ["e31063"], "pub-id": ["10.1097/MD.0000000000031063"]}, {"label": ["19."], "mixed-citation": ["Guo K, Liu X, Gong X, et al. Autoimmune encephalitis with mGluR5 antibodies: A case series from China and review of the literature. Front Immunol. 2023;14:1146536."]}]
{ "acronym": [], "definition": [] }
19
CC BY
no
2024-01-14 23:43:45
BMC Neurol. 2024 Jan 13; 24:27
oa_package/df/b3/PMC10787404.tar.gz
PMC10787405
0
[ "<title>Background</title>", "<p id=\"Par6\">Diabetic foot ulcers are serious sequelae of diabetes that occur in 19 to 34% of patients during their lifetime [##REF##28614678##1##], with recurrence rates of ~ 65% at 3–5 years [##REF##36548709##2##]. Ulcers are commonly classified by etiology into ischemic, neuropathic, or neuro-ischemic, depending on whether they result from peripheral artery disease (PAD), diabetic peripheral neuropathy (DPN), or both, with PAD and DPN also causing gangrene and Charcot arthropathy, respectively, which are frequently associated with foot ulcers [##REF##36548709##2##]. In addition, ~ 50% of ulcers are complicated by superimposed infection [##REF##37395769##3##], though foot infections involving soft tissue or bone can rarely have an hematogenous origin and develop in the absence of an ulcer [##REF##21537457##4##]. All these manifestations of the so-called “diabetic foot” may require minor or major amputations, with an estimated lifetime incidence of 20% [##REF##36548709##2##]. Data from multiple sources showed a 51% decline in the incidence of lower limb amputations among US adults from 1990 to 2010 [##REF##24738668##5##], though a more recent survey indicated a resurgence in this and other diabetic complications between 2010 and 2015, especially in younger individuals [##REF##30985875##6##].</p>", "<p id=\"Par7\">Diabetic foot ulcers are associated with high morbidity and mortality, especially from cardiovascular disease (CVD) [##REF##28971322##7##–##UREF##0##10##], with a pooled relative risk of 2.45, as reported in a recent meta-analysis [##REF##31613404##11##]. Death rates were shown to be ~ 45% at 5 years and ~ 70% at 10 years [##REF##36548709##2##, ##REF##36054820##12##–##REF##25601358##14##], higher for ischemic (and neuro-ischemic) than for neuropathic ulcers [##REF##12547887##15##–##UREF##1##17##], and with an apparently declining trend [##REF##18697900##16##, ##REF##31400509##18##, ##REF##30606164##19##], which however was not consistently observed [##REF##22815299##13##]. The high mortality rates associated with foot ulcers (and the diabetic foot in general) have been attributed to the coexistence of other micro and macrovascular complications of the disease [##REF##28971322##7##]. In fact, CVD in the lower limb and other vascular beds as well as chronic kidney disease or dialysis were found to be independent risk factors for mortality, together with age, male sex, smoking habits, long diabetes duration, high HbA<sub>1c</sub> and low hemoglobin and albumin levels [##REF##22815299##13##, ##REF##18697900##16##–##REF##26666583##26##]. Risk of death was also related to ulcer duration [##REF##31400509##18##], recurrence [##REF##30606164##19##, ##REF##24877985##23##], severity [##REF##32961974##24##], and need for amputation [##UREF##1##17##, ##REF##30515957##21##, ##REF##31316149##22##]. However, only a few studies assessed the impact of foot ulcer per se, showing that it remained significantly associated with death after adjusting for confounders, suggesting a direct and independent relationship with mortality [##REF##19729524##20##, ##REF##8946155##25##, ##REF##26666583##26##]. However, these surveys provided discordant figures, which may reflect differences in the national health systems, settings, and time-periods.</p>", "<p id=\"Par8\">The present analysis aimed at assessing the extent of association of history of diabetic foot, including but not limited to foot ulcers, with all-cause mortality in patients with type 2 diabetes, independent of CVD risk factors, other complications and comorbidities.</p>" ]
[ "<title>Methods</title>", "<title>Design</title>", "<p id=\"Par9\">The Renal Insufficiency And Cardiovascular Events (RIACE) Italian Multicenter Study was an observational, prospective, cohort study on the impact of estimated glomerular filtration rate (eGFR) on morbidity and mortality in individuals with type 2 diabetes [##REF##21738053##27##]. The study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the locally appointed ethics committees and participants gave informed consent.</p>", "<title>Patients</title>", "<p id=\"Par10\">The RIACE study enrolled 15,933 Caucasian patients with type 2 diabetes, consecutively attending 19 hospital-based, tertiary referral Diabetes Clinics of the National Health Service throughout Italy, most of them in the years 2006–2008 (first patients 6 October 2005 - last patient 17 December 2008). Exclusion criteria were dialysis or renal transplantation. As 160 patients (1.0%) were excluded due to missing or implausible values, the study population consisted of the remaining 15,773 individuals.</p>", "<title>Baseline data</title>", "<p id=\"Par11\">Baseline data were collected using a standardized protocol across participating centers [##REF##21738053##27##].</p>", "<p id=\"Par12\">Participants underwent a structured interview to collect the following information: age at the time of the interview, smoking status, physical activity (PA) level, known diabetes duration, severe co-morbidities, and current glucose-, lipid-, and blood pressure (BP)-lowering treatments. Patients were categorized by smoking status as never, former, or current smokers and by moderate-to-vigorous PA level as physically inactive or moderately inactive (&lt; 60 min·week<sup>− 1</sup>), moderately active (60–150 min·week<sup>− 1</sup>), or highly active (&gt; 150 min·week<sup>− 1</sup>). Comorbidities included chronic obstructive pulmonary disease (COPD), chronic liver disease, and cancer.</p>", "<p id=\"Par13\">Body mass index (BMI) was calculated from weight and height, whereas waist circumference was estimated from log-transformed BMI values. Then, BP was measured with a sphygmomanometer with the patients seated with the arm at the heart level.</p>", "<p id=\"Par14\">Hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) was measured by HPLC using DCCT-aligned methods; triglycerides and total and HDL cholesterol were determined in fasting blood samples by standard colorimetric enzymatic methods. Then, non-HDL cholesterol level was computed by subtracting HDL cholesterol from total cholesterol, whereas LDL cholesterol concentration was estimated using the Friedewald formula, i.e., LDL cholesterol = total cholesterol – HDL cholesterol – (triglycerides/5) (in mg/dl).</p>", "<p id=\"Par15\">Previous major adverse CVD events, including myocardial infarction, stroke, foot ulcer/gangrene, non-traumatic amputation, and cerebrovascular, carotid, and lower limb revascularization, were adjudicated based on hospital discharge records by an ad hoc committee in each center [##REF##22124714##28##]. Manifestations of diabetic foot included ulcer/gangrene, amputation, and lower limb revascularization, either alone or in combination. Amputation was defined as minor or major depending on whether it was below or above the ankle joint, respectively. Lower limb revascularization procedures were classified as endovascular or surgical. While lower limb revascularization was considered a CVD event, as myocardial infarction, stroke, and coronary or carotid revascularization, the cause of foot ulcer/gangrene and amputation could not be established, as no information was available regarding the presence and severity of PAD (except for revascularization), DPN, and/or foot infection in the RIACE participants. However, foot ulcer/gangrene were hypothesized to be ischemic (or neuro-ischemic) if occurred in individuals who underwent a lower limb revascularization procedure and amputation was hypothesized to be caused by infection if occurred in patients without ulcer/gangrene. In contrast, no assumption could be made regarding the etiology of ulcer/gangrene in patients who were not revascularized, as this does not necessarily imply a neuropathic origin, as well as of amputation in those with ulcer/gangrene, as it was impossible to establish the role of infection versus that of PAD in guiding decision to proceed with surgery.</p>", "<p id=\"Par16\">The presence of diabetic kidney disease (DKD) was assessed by measuring albuminuria and serum creatinine, as previously detailed [##REF##21738053##27##, ##REF##21441399##29##]. Briefly, albumin excretion rate was obtained from 24-hour urine collections or calculated from albumin-to-creatinine ratio in early-morning, first-voided urine samples; albumin concentration in urines was measured by immunonephelometry or immunoturbidimetry, in the absence of interfering clinical conditions. Serum (and urine) creatinine was measured by the modified Jaffe method, traceable to IDMS, and eGFR was calculated by the 2009 Chronic Kidney Disease Epidemiology Collaboration equation [##REF##19414839##30##]. Patients were then assigned to one of the following DKD phenotypes [##REF##30032426##31##]: no DKD, albuminuria alone (albuminuric DKD with preserved eGFR), reduced eGFR alone (non-albuminuric DKD), or both albuminuria and reduced eGFR (albuminuric DKD with reduced eGFR).</p>", "<p id=\"Par17\">The presence of diabetic retinopathy (DR) was assessed in each center by an expert ophthalmologist by dilated fundoscopy [##REF##36460217##32##]. On the basis of the actual fundus appearance or the retinal disease condition that had eventually required previous photocoagulation or surgical treatment, patients were graded into the following categories: no DR; mild, moderate, or severe non-proliferative DR; proliferative DR; or diabetic macular edema. Patients with mild or moderate non-proliferative DR were classified as having non-advanced DR, whereas those with severe non-proliferative DR, proliferative DR, or diabetic macular edema were grouped into the advanced, sight threatening DR category. DR grade was assigned based on the worse eye.</p>", "<title>All-cause mortality</title>", "<p id=\"Par18\">The vital status of study participants on 31 October 2015 was verified by interrogating the Italian Health Card database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://sistemats1.sanita.finanze.it/wps/portal/\">http://sistemats1.sanita.finanze.it/wps/portal/</ext-link>), which provides updated and reliable information on all current Italian residents [##REF##29582548##33##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par19\">Data are expressed as mean ± SD or median (interquartile range) for continuous variables, and number of cases and percentage for categorical variables. Patients were stratified by absence or presence of (a) history of diabetic foot event; (b) ulcer/gangrene and/or amputation; and (c) ulcer/gangrene/amputation and/or lower limb revascularization. Comparisons among the above categories were performed by unpaired Student’s t test or one-way ANOVA or Kruskal-Wallis test, according to the parametric or non-parametric distribution of continuous variables, and Pearson’s χ<sup>2</sup> test, for categorical variables. Binary non-conditional multivariable logistic regression analysis with backward stepwise selection of variables was applied to assess the independent correlates of previous manifestations of diabetic foot; covariates were age, sex, smoking status, PA level, diabetes duration, HbA<sub>1c</sub>, BMI, triglycerides, total and HDL cholesterol, systolic and diastolic BP, anti-hyperglycemic, lipid-lowering, and anti-hypertensive therapy, DKD phenotype, DR grade, any coronary and cerebrovascular event, and any comorbidity. Data are presented as odds ratios (ORs) and their 95% Cis.</p>", "<p id=\"Par20\">Crude mortality rates were described as events per 1,000 patient-years from start of follow-up to censoring, with 95% exact Poisson confidence intervals (CIs) and adjusted for age and sex by a Poisson regression model. Kaplan-Meier survival probabilities for all-cause mortality were estimated according to the above categories and differences were analyzed using the log-rank statistic. The hazard ratios (HRs) and their 95% CIs were estimated by Cox proportional hazards regression with backward selection of variables. These analyses were sequentially adjusted for age and sex (model 1), plus other CVD risk factors, i.e., smoking status, PA level, diabetes duration, HbA<sub>1c</sub>, BMI, triglycerides, total and HDL cholesterol, systolic and diastolic BP, and anti-hyperglycemic, lipid-lowering, and anti-hypertensive therapy (model 2), and plus presence of other complications (DKD, DR, and any coronary and cerebrovascular event), and any severe comorbidity (model 3).</p>", "<p id=\"Par21\">All <italic>p</italic> values were two-sided, and a <italic>p</italic> &lt; 0.05 was considered statistically significant. Statistical analyses were performed using SPSS version 13.0 (SPSS Inc., Chicago, IL, USA).</p>" ]
[ "<title>Results</title>", "<title>History of diabetic foot at baseline</title>", "<p id=\"Par22\">At baseline, 895 patients (5.7%) had a history of any diabetic foot event, 431 of them (48.3%) more than one. Of these individuals, 565 (3.58%) had ulcer/gangrene (412, 2.61%), amputation (33, 0.21%), or both (120, 0.76%); 126 (0.80%) of them were revascularized (69 with endovascular, 48 with surgical, and 9 with both procedures), whereas 439 (2.78%) were not. The remaining 330 patients (2.09%) underwent lower limb revascularization (123 with endovascular, 197 with surgical, and 10 with both procedures) without any ulcer/gangrene and/or amputation.</p>", "<p id=\"Par23\">As shown in Table ##TAB##0##1##, patients with any foot event were older and more frequently males and former or current smokers, as compared with those without. In addition, they had longer diabetes duration, higher levels of HbA<sub>1c</sub>, triglycerides, TG:HDL ratio, systolic BP, pulse pressure, and albuminuria, and higher prevalence of dyslipidemia, hypertension, insulin, lipid-lowering, anti-hypertensive, anti-platelet, and anti-coagulant treatment, albuminuric and non-albuminuric DKD, non-advanced and advanced DR, any coronary and cerebrovascular event, including myocardial infarction, stroke, and revascularization procedures, COPD, and chronic liver disease. In contrast, they had lower levels of total, HDL, non-HDL, and LDL cholesterol, diastolic BP, and eGFR as well as lower prevalence of cancer.</p>", "<p id=\"Par24\">\n\n</p>", "<p id=\"Par25\">The baseline clinical features of participants stratified by history of ulcer/gangrene and/or amputation are shown in Additional file 2: Table ##SUPPL##0##S1##, whereas those of participants stratified by history of ulcer/gangrene/amputation and/or lower limb revascularization are shown in Additional file 3: Table ##SUPPL##1##S2##.</p>", "<p id=\"Par26\">History of diabetic foot was independently associated with age, male sex, smoking, diabetes duration, anti-hyperglycemic and lipid-lowering treatment, DKD, DR, any coronary and cerebrovascular event and, inversely, PA level and HDL cholesterol (Additional file 4: Table ##SUPPL##2##S3##).</p>", "<title>Association between history of diabetic foot at baseline and all-cause mortality</title>", "<p id=\"Par27\">As previously reported, valid information on vital status was retrieved for 15,656 participants (99.3% of the cohort). Of these individuals, 12,054 (76.99%) were alive, whereas 3,602 (23.01%) had deceased (follow-up duration: 7.42 ± 2.05 years, range 0–10.07; death rate: 31.02 per 1,000 person-years) [##REF##30032426##31##, ##REF##29574497##34##].</p>", "<p id=\"Par28\">As shown in Table ##TAB##1##2##, unadjusted death rate was markedly higher in patients with than in those without a history of diabetic foot event and remained 2-fold higher after adjustment for age and sex. Moreover, age- and sex-adjusted death rates were higher in patients with amputation vs. those with ulcer/gangrene alone and in patients with ulcer/gangrene/amputation vs. those with lower limb revascularization alone, with the highest rates observed in participants with both ulcer/gangrene and amputation and in those with both ulcer/gangrene/amputation and lower limb revascularization. Likewise, the Kaplan-Meier curves (Figs. ##FIG##0##1##A and ##FIG##1##2##A, and ##FIG##2##3##A) and unadjusted Cox proportional hazards regression showed an increased mortality in patients with any diabetic foot event (Table ##TAB##2##3##), ulcer/gangrene and/or amputation, and ulcer/gangrene/amputation and/or lower limb revascularization (not shown). When sequentially adjusting for confounders, risk of death remained ~ 50% higher in participants with any diabetic foot event (Fig. ##FIG##0##1##B–D; Table ##TAB##2##3##). In addition, it was higher in those with amputation with or without ulcer/gangrene than in those with ulcer/gangrene alone (Fig. ##FIG##1##2##B–D) and in those with ulcer/gangrene/amputation with or without lower limb revascularization than in those with lower limb revascularization alone, who only showed a ~ 23% increase in the adjusted mortality risk (Fig. ##FIG##2##3##B–D).</p>", "<p id=\"Par29\">\n\n</p>", "<p id=\"Par30\">\n\n</p>", "<p id=\"Par31\">\n\n</p>", "<p id=\"Par32\">\n\n</p>", "<p id=\"Par33\">\n\n</p>", "<p id=\"Par34\">Other factors independently associated with mortality were age, male sex, current smoking, HbA<sub>1c</sub>, anti-hyperglycemic (especially insulin) and anti-hypertensive treatment, other complications, particularly DKD, and comorbidities; moreover, PA level, total and HDL cholesterol, lipid-lowering treatment, and diastolic BP showed an inverse association with mortality. In contrast, triglycerides showed no significant association, whereas diabetes duration, BMI, and systolic BP did not enter the model (Table ##TAB##2##3##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par35\">This analysis of the RIACE cohort provides strong evidence that having an history of diabetic foot, including ulcer/gangrene, amputation, and lower limb revascularization, markedly increases the risk of death independent of CVD risk factors, other complications and severe comorbidities.</p>", "<p id=\"Par36\">These findings add to those of the few studies that previously showed an independent effect of foot ulcers only on mortality [##REF##19729524##20##, ##REF##8946155##25##, ##REF##26666583##26##]. The Nord-Trøndelag Health (HUNT) 2 Study, a population-based Norwegian study including 1,494 patients with diabetes (155 with and 1,339 without an history of foot ulcer) and 63,632 nondiabetic individuals, showed that the adjusted mortality risk in those with a history of foot ulcer was more than double (+ 129%) of that of nondiabetic individuals, but only 47% higher than in those without foot ulcer [##REF##19729524##20##], similar to the ~ 50% increase in the adjusted mortality risk observed in the RIACE cohort. Conversely, the analysis of data from 414,523 people with diabetes enrolled in practices associated with The Health Improvement Network in the UK showed that the adjusted risk of death was increased 2.48-fold among the 20,737 individuals who developed diabetic foot ulcers versus those who did not [##REF##26666583##26##]. These data are in keeping with the greater than two-fold adjusted risk of death in a previous small-sized study in veterans of the American military services with diabetes with versus without foot ulcer [##REF##8946155##25##], suggesting an even higher impact of foot ulcer per se.</p>", "<p id=\"Par37\">The excess risk of death may be attributed to factors associated with history of diabetic foot that were not detected in the RIACE cohort and, hence, were not considered in the multivariable analyses. One of these factors may be infection complicating foot ulcer/gangrene, consistent with the findings that sepsis is one of the main causes of death after CVD [##REF##27213157##9##, ##REF##32961974##24##, ##REF##35255070##35##] and that polymicrobial growth in deep tissue culture was found to be independently associated with mortality [##REF##32196927##36##] in patients with diabetic foot. Moreover, diabetic foot may represent a marker of medical frailty [##REF##26666583##26##] and is known to be associated in a bidirectional manner with depression [##REF##32219987##37##, ##REF##20670730##38##], which was shown to be an independent risk factor for mortality in these individuals [##REF##19729524##20##, ##REF##32690575##39##]. Another unmeasured confounder may be the socio-economic status, which has been shown to be a major determinant of foot ulcer development and outcomes [##REF##31848633##40##, ##REF##35446395##41##].</p>", "<p id=\"Par38\">The 47% death rate in patients with any manifestation of diabetic foot, with differences according to the type(s) of event(s) (from 42% of lower limb revascularization alone to 61% of its combination with ulcer/gangrene/amputation) over a 7.42-year follow-up does not support the reported declining trend in mortality [##REF##18697900##16##, ##REF##31400509##18##, ##REF##30606164##19##] and is rather in keeping with the study demonstrating no significant improvement [##REF##22815299##13##]. The other factors independently associated with death in addition to history of diabetic foot are consistent with other studies [##REF##28971322##7##, ##REF##22815299##13##, ##REF##18697900##16##–##REF##26666583##26##] and support the concept that the presence of other micro and macrovascular complications plays a major role [##REF##28971322##7##, ##REF##22890823##8##], in keeping with the findings that CVD is the main cause of death among diabetic people [##REF##21366474##42##] and that DKD is a major risk factor for morbidity and mortality from CVD [##REF##19443635##43##].</p>", "<p id=\"Par39\">Another finding of our study is the demonstration that, among the manifestations of diabetic foot, amputation had the greatest impact on mortality. This is consistent with previous studies showing that amputation was an independent correlate of death, together with age and albumin [##UREF##1##17##], and conferred a high mortality risk with an adjusted OR of 6.42 [##REF##31316149##22##]. Likewise, a longitudinal cohort study of patients cared for in the Health Improvement Network showed a 2.37 higher adjusted mortality risk of death in those who had undergone a lower extremity amputation [##REF##26203063##44##]. However, we found that mortality risk was increased in patients with amputation regardless of whether it was preceded by an ulcer/gangrene, possibly suggesting a major role for infection, which may have caused amputation in individuals without an ulcer/gangrene and, in combination with ischemia, also in some of those with an ulcer/gangrene. Conversely, the impact of lower limb revascularization was found to be relatively modest, as undergoing a revascularization procedure without having an ulcer/gangrene/amputation was associated with a ~ 23% increase in the adjusted risk of death, suggesting the importance of timely revascularization for reducing the risk of ulcer development and related mortality. Moreover, mortality risk increased only slightly for combined ulcer/gangrene/amputation and revascularization compared with ulcer/gangrene/amputation alone.</p>", "<p id=\"Par40\">The apparently low prevalence of any diabetic foot event in the RIACE cohort (~ 6%) as compared with the reported lifetime prevalence of 19 to 34% [##REF##28614678##1##] may be explained by the characteristics of the study participants. In particular, a diabetes duration of  <underline>≤</underline> 10 years in almost 50% of participants and the exclusion of patients on dialysis might have also contributed to such a low prevalence, which is indeed similar to the ~ 5% prevalence of foot ulcers among individuals with diabetes enrolled in the UK study mentioned above [##REF##32961974##24##].</p>", "<p id=\"Par41\">The independent correlates of history of diabetic foot event are consistent with the known risk factors for the development of foot ulcers, including CVD in the coronary or cerebrovascular beds, microvascular complications, and CVD risk factors [##REF##28614678##1##, ##REF##36548709##2##]. In addition, the relationship with PA level is consistent with a recent prospective study showing that sedentary behavior is significantly and independently associated with the occurrence of a diabetic foot ulcer [##REF##34058300##45##].</p>", "<p id=\"Par42\">Strength of our study include the large sample size, the completeness of baseline and follow-up data and, particularly, the assessment of a wide range of clinical parameters which allowed accounting for several confounding factors. However, there are several limitations. First, the lack of information on the causes of death did not allow detecting differences in CVD versus non-CVD deaths and the impact of other causes of death that might be associated with diabetic foot, such as infections. Second, the lack of information regarding the presence and severity of PAD (except for history of lower limb revascularization), DPN, and/or foot infection did not allow to establish the cause of foot ulcer/gangrene and amputation in the RIACE participants. Third, the lack of information on the occurrence of diabetic foot events during the follow-up may have led to an underestimation of the prevalence of this complication and of its impact on mortality. Fourth, the study findings may not be applicable to the general ambulatory population, as only part of the individuals with type 2 diabetes attend Diabetes Clinics in Italy; however, the RIACE cohort is representative of patients followed by diabetes specialists in these clinics [##REF##24398892##46##]. Finally, the observational design makes causal interpretation impossible.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par43\">In Caucasian patients with type 2 diabetes from the RIACE cohort, an history of diabetic foot event, including ulcer/gangrene, amputation, and lower limb revascularization, was associated with a ~ 50% increased risk of subsequent death from any cause, independent of CVD risk factors, other complications and severe comorbidities, which were also significantly associated with mortality. The association with mortality was greatest for amputation, whereas that for revascularization alone was relatively modest.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Foot ulcers and/or infections are common long-term complications of diabetes and are associated with increased mortality, especially from cardiovascular disease, though only a few studies have investigated the independent contribution of these events to risk of death. This study aimed at assessing the association of history of diabetic foot with all-cause mortality in individuals with type 2 diabetes, independent of cardiovascular risk factors, other complications, and comorbidities.</p>", "<title>Methods</title>", "<p id=\"Par2\">This prospective cohort study enrolled 15,773 Caucasian patients in 19 Italian centers in the years 2006–2008. Prior lower extremity, coronary, and cerebrovascular events and major comorbidities were ascertained by medical records, diabetic retinopathy by fundoscopy, diabetic kidney disease by albuminuria and estimated glomerular filtration rate, cardiovascular risk factors by standard methods. All-cause mortality was retrieved for 15,656 patients on 31 October 2015.</p>", "<title>Results</title>", "<p id=\"Par3\">At baseline, 892 patients (5.7%) had a history of diabetic foot, including ulcer/gangrene and/or amputation (n = 565; 3.58%), with (n = 126; 0.80%) or without (n = 439; 2.78%) lower limb revascularization, and revascularization alone (n = 330; 2.09%). History of diabetic foot was associated with all-cause death over a 7.42-year follow-up (adjusted hazard ratio, 1.502 [95% confidence interval, 1.346–1.676], <italic>p</italic> &lt; 0.0001), independent of confounders, among which age, male sex, smoking, hemoglobin A<sub>1c</sub>, current treatments, other complications, comorbidities and, inversely, physical activity level and total and HDL cholesterol were correlated independently with mortality. Both ulcer/gangrene and amputation alone were independently associated with death, with a higher strength of association for amputation than for ulcer/gangrene (1.874 [1.144–3.070], <italic>p</italic> = 0.013 vs. 1.567 [1.353–1.814], <italic>p</italic> &lt; 0.0001). Both ulcer/gangrene/amputation and lower limb revascularization alone were independently associated with death; mortality risk was much higher for ulcer/gangrene/amputation than for revascularization (1.641 [1.420–1.895], <italic>p</italic> &lt; 0.0001 vs. 1.229 [1.024–1.475], <italic>p</italic> = 0.018) and further increased only slightly for combined ulcer/gangrene/amputation and revascularization (1.733 [1.368–2.196], <italic>p</italic> &lt; 0.0001).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">In patients with type 2 diabetes, an history of diabetic foot event, including ulcer/gangrene, amputation, and lower limb revascularization, was associated with a ~ 50% increased risk of subsequent death, independent of cardiovascular risk factors, other complications and severe comorbidities, which were also significantly associated with mortality. The association with mortality was greatest for amputation, whereas that for revascularization alone was relatively modest.</p>", "<title>Trial registration</title>", "<p id=\"Par5\">ClinicalTrials.gov, NCT00715481, retrospectively registered 15 July, 2008.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02107-9.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>The Authors thank the RIACE Investigators for participating in this study (see the complete list in the Additional file 1: The RIACE Study Group).</p>", "<title>Author contributions</title>", "<p>MVi, EO, AS, GPe, and GPu conceived and designed the study.All authors contributed to data acquisition, analysis, or interpretation.GPu drafted the article and had full access to all the data and took responsibility for the integrity of data and accuracy of the data analysis in this study.MVi, EO, AS, MG, VR, EB, CF, RT, MVe, and GPe revised the manuscript critically for essential intellectual content.All authors approved the submitted version of the manuscript and agreed to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.</p>", "<title>Funding</title>", "<p>This research was supported by the Research Foundation of the Italian Diabetes Society (Diabete Ricerca) and the Diabetes, Endocrinology and Metabolism (DEM) Foundation, and by unconditional grants from Eli-Lilly, Sigma-Tau, Takeda, Chiesi Farmaceutici, and Boehringer-Ingelheim. The funding sources had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.</p>", "<title>Data availability</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par45\">The study was conducted in accordance with the Declaration of Helsinki. The research protocol was approved by the ethics committee of the coordinating centre (Sant’Andrea Hospital, Rome, Italy) on 25 September 2006 (number 43/2006) and subsequently by the ethics committee of each participating centre. Participants provided an informed consent.</p>", "<title>Consent for publication</title>", "<p id=\"Par46\">Not applicable.</p>", "<title>Additional file 1</title>", "<p id=\"Par47\">The RIACE Study Group.</p>", "<title>Additional file 2: table S1</title>", "<p id=\"Par48\">Baseline clinical features of study participants by history of ulcer/gangrene and/or amputation.</p>", "<title>Additional file 3: table S2</title>", "<p id=\"Par49\">Baseline clinical features of study participants by history of ulcer/gangrene/amputation and/or lower limb revascularization.</p>", "<title>Additional file 4: table S3</title>", "<p id=\"Par50\"> Binary backward logistic regression analysis of the independent correlates of history of diabetic foot.</p>", "<title>Competing interests</title>", "<p id=\"Par44\">MVi: lecture fees from MundiPharma and Novo Nordisk. EO: consultant fees from Eli Lilly and Novo Nordisk, and lecture fees from Astellas. AS: consultant fees from Axxam, Bayer, and Novo Nordisk, and lecture fees from Eli Lilly, Novo Nordisk, and Sanofi-Aventis. MG: consultant fees from Eli Lilly, and lecture fees from Eli Lilly, Merck Sharp &amp; Dohme, and Novo Nordisk. VR: lecture fees from Astra-Zeneca, Eli Lilly, and Sanofi-Aventis. EB: consultant fees from Abbott, Bayer, Becton Dickinson, Boehringer Ingelheim, Daiichi-Sankyo, Eli Lilly, and Novo Nordisk. CF: lecture fees from Abbot, Boehringer Ingelheim, Daiichi Sankyo, Eli Lilly, Merck Sharp &amp; Dohme, Mundipharma, and Theras Lifetech. RT: consultant fees from AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Merck Sharp &amp; Dohme, Novo Nordisk, and Sanofi-Aventis, and lecture fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, and Novo Nordisk. MVe: lecture fees from Lifescan and Novo Nordisk. GPe: consultant fees from Bayer and Eli Lilly, and lecture fees from AstraZeneca, Boerhinger Ingelheim, Eli-Lilly, Merck Sharp &amp; Dohme, Mundipharma, Novo Nordisk, and Takeda. GPu: consultant fees from Abbot, Bayer, and Novo Nordisk, and lecture fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Mundipharma, and Novo Nordisk.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Survival analysis by presence or absence of history of diabetic foot. Kaplan Meier analysis (<bold>A</bold>) and Cox proportional hazards regression, adjusted for age and sex (model 1, <bold>B</bold>), plus smoking status, PA level, diabetes duration, HbA<sub>1c</sub>, BMI, triglycerides, total and HDL cholesterol, systolic and diastolic BP, and anti-hyperglycemic, lipid-lowering, and anti-hypertensive therapy (model 2, <bold>C</bold>), plus presence of other complications (DKD phenotypes, DR grades, any coronary and cerebrovascular event) and severe comorbidities (COPD, chronic liver disease, cancer) (model 3, <bold>D</bold>). Numbers (percentages) of deaths and HRs (95% CI) for mortality are shown for each group. PA = physical activity; HbA<sub>1c</sub> = hemoglobin A<sub>1c</sub>; BMI = body mass index; BP = blood pressure; DKD = diabetic kidney disease; DR = diabetic retinopathy; COPD = chronic obstructive pulmonary disease; HR = hazard ratio; CI = confidence interval</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Survival analysis by presence or absence of history of ulcer/gangrene and/or amputation. Kaplan Meier analysis (<bold>A</bold>) and Cox proportional hazards regression, adjusted for age and sex (model 1, <bold>B</bold>), plus smoking status, PA level, diabetes duration, HbA<sub>1c</sub>, BMI, triglycerides, total and HDL cholesterol, systolic and diastolic BP, and anti-hyperglycemic, lipid-lowering, and anti-hypertensive therapy (model 2, <bold>C</bold>), plus presence of other complications (DKD phenotypes, DR grades, any coronary and cerebrovascular event) and severe comorbidities (COPD, chronic liver disease, cancer) (model 3, <bold>D</bold>). Numbers (percentages) of deaths and HRs (95% CI) for mortality are shown for each group. PA = physical activity; HbA<sub>1c</sub> = hemoglobin A<sub>1c</sub>; BMI = body mass index; BP = blood pressure; DKD = diabetic kidney disease; DR = diabetic retinopathy; COPD = chronic obstructive pulmonary disease; HR = hazard ratio; CI = confidence interval</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Survival analysis by presence or absence of history of ulcer/gangrene/amputation and/or lower limb revascularization. Kaplan Meier analysis (<bold>A</bold>) and Cox proportional hazards regression, adjusted for age and sex (model 1, <bold>B</bold>), plus smoking status, PA level, diabetes duration, HbA<sub>1c</sub>, BMI, triglycerides, total and HDL cholesterol, systolic and diastolic BP, and anti-hyperglycemic, lipid-lowering, and anti-hypertensive therapy (model 2, <bold>C</bold>), plus presence of other complications (DKD phenotypes, DR grades, any coronary and cerebrovascular event) and severe comorbidities (COPD, chronic liver disease, cancer) (model 3, <bold>D</bold>). Numbers (percentages) of deaths and HRs (95% CI) for mortality are shown for each group. PA = physical activity; HbA<sub>1c</sub> = hemoglobin A<sub>1c</sub>; BMI = body mass index; BP = blood pressure; DKD = diabetic kidney disease; DR = diabetic retinopathy; COPD = chronic obstructive pulmonary disease; HR = hazard ratio; CI = confidence interval</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline clinical features of study participants by history of diabetic foot</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variables</th><th align=\"left\" colspan=\"2\">History of diabetic foot</th><th align=\"left\" rowspan=\"2\">\n<italic>P</italic>\n</th></tr><tr><th align=\"left\">No</th><th align=\"left\">Yes</th></tr></thead><tbody><tr><td align=\"left\">N (%)</td><td align=\"left\">14,878 (94.3)</td><td align=\"left\">895 (5.7)</td><td align=\"left\"/></tr><tr><td align=\"left\">Ulcer/gangrene</td><td align=\"left\">–</td><td align=\"left\">532 (59.4)</td><td align=\"left\"/></tr><tr><td align=\"left\">Amputation</td><td align=\"left\">–</td><td align=\"left\">153 (17.1)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Minor</td><td align=\"left\">–</td><td align=\"left\">129 (14.4)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Major</td><td align=\"left\">–</td><td align=\"left\">24 (2.7)</td><td align=\"left\"/></tr><tr><td align=\"left\">Ulcer/gangrene/amputation</td><td align=\"left\">–</td><td align=\"left\">565 (63.1)</td><td align=\"left\"/></tr><tr><td align=\"left\">Lower limb revascularization</td><td align=\"left\">–</td><td align=\"left\">456 (50.9)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Endovascular</td><td align=\"left\">–</td><td align=\"left\">192 (21.5)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Surgical</td><td align=\"left\">–</td><td align=\"left\">245 (27.4)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Both</td><td align=\"left\">–</td><td align=\"left\">19 (2.1)</td><td align=\"left\"/></tr><tr><td align=\"left\">Age, years</td><td align=\"left\">66.4 ± 10.4</td><td align=\"left\">70.1 ± 9.6</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Sex, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Females</td><td align=\"left\">6,522 (43.8)</td><td align=\"left\">292 (32.6)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Males</td><td align=\"left\">8,356 (56.2)</td><td align=\"left\">603 (67.4)</td><td align=\"left\"/></tr><tr><td align=\"left\">Smoking, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Never</td><td align=\"left\">8,511 (57.2)</td><td align=\"left\">417 (46.6)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Former</td><td align=\"left\">4,101 (27.6)</td><td align=\"left\">333 (37.2)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Current</td><td align=\"left\">2,266 (15.2)</td><td align=\"left\">145 (16.2)</td><td align=\"left\"/></tr><tr><td align=\"left\">PA level, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Inactive or moderately inactive</td><td align=\"left\">9,314 (62.6)</td><td align=\"left\">712 (79.6)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Moderately active</td><td align=\"left\">5,333 (35.8)</td><td align=\"left\">178 (19.9)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Highly active</td><td align=\"left\">231 (1.6)</td><td align=\"left\">5 (0.6)</td><td align=\"left\"/></tr><tr><td align=\"left\">Diabetes duration, years</td><td align=\"left\">12.8 ± 10.0</td><td align=\"left\">19.2 ± 10.6</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">HbA<sub>1c</sub>, %</td><td align=\"left\">7.53 ± 1.50</td><td align=\"left\">7.92 ± 1.59</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">BMI, kg·m<sup>− 2</sup></td><td align=\"left\">29.0 ± 5.2</td><td align=\"left\">28.8 ± 5.0</td><td align=\"left\">0.351</td></tr><tr><td align=\"left\">Waist circumference, cm</td><td align=\"left\">102.5 ± 11.1</td><td align=\"left\">102.9 ± 11.3</td><td align=\"left\">0.210</td></tr><tr><td align=\"left\">Triglycerides, mmol·l<sup>− 1</sup></td><td align=\"left\">1.33 (0.97–1.88)</td><td align=\"left\">1.39 (1.02–2.01)</td><td align=\"left\">0.031</td></tr><tr><td align=\"left\">Total cholesterol, mmol·l<sup>− 1</sup></td><td align=\"left\">4.80 ± 0.99</td><td align=\"left\">4.59 ± 1.01</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">HDL cholesterol, mmol·l<sup>− 1</sup></td><td align=\"left\">1.30 ± 0.35</td><td align=\"left\">1.20 ± 0.36</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Non-HDL cholesterol, mmol·l<sup>− 1</sup></td><td align=\"left\">3.50 ± 0.95</td><td align=\"left\">3.36 ± 0.94</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">LDL cholesterol, mmol·l<sup>− 1</sup></td><td align=\"left\">2.80 ± 0.84</td><td align=\"left\">2.63 ± 0.85</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Dyslipidemia, n (%)</td><td align=\"left\">12,214 (82.1)</td><td align=\"left\">746 (83.4)</td><td align=\"left\">0.340</td></tr><tr><td align=\"left\">Systolic BP, mmHg</td><td align=\"left\">138.0 ± 17.9</td><td align=\"left\">139.3 ± 19.7</td><td align=\"left\">0.039</td></tr><tr><td align=\"left\">Diastolic BP, mmHg</td><td align=\"left\">78.8 ± 9.4</td><td align=\"left\">77.4 ± 9.9</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Pulse pressure, mmHg</td><td align=\"left\">59.1 ± 15.6</td><td align=\"left\">61.9 ± 16.9</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Hypertension, n (%)</td><td align=\"left\">12,369 (83.1)</td><td align=\"left\">820 (91.6)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Anti-hyperglycemic treatment, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Lifestyle</td><td align=\"left\">2,076 (14.0)</td><td align=\"left\">50 (5.6)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Non-insulin</td><td align=\"left\">9,229 (62.0)</td><td align=\"left\">452 (50.5)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Insulin</td><td align=\"left\">3,573 (24.0)</td><td align=\"left\">393 (43.9)</td><td align=\"left\"/></tr><tr><td align=\"left\">Lipid-lowering treatment, n (%)</td><td align=\"left\">6,746 (45.3)</td><td align=\"left\">540 (60.3)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Anti-hypertensive treatment, n (%)</td><td align=\"left\">10,398 (69.9)</td><td align=\"left\">751 (83.9)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Albuminuria, mg·day<sup>− 1</sup></td><td align=\"left\">13.1 (6.5–31.0)</td><td align=\"left\">25.6 (10.5–100.0)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Serum creatinine, µmol·l<sup>− 1</sup></td><td align=\"left\">80.1 ± 33.3</td><td align=\"left\">97.4 ± 47.1</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">eGFR, ml·min<sup>− 1</sup>·1.73 m<sup>− 2</sup></td><td align=\"left\">80.9 ± 20.7</td><td align=\"left\">69.4 ± 22.7</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">DKD phenotype, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> No DKD</td><td align=\"left\">9,697 (65.2)</td><td align=\"left\">350 (39.1)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Albuminuric DKD with preserved eGFR</td><td align=\"left\">2,767 (18.6)</td><td align=\"left\">228 (25.5)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Non-albuminuric DKD</td><td align=\"left\">1,366 (9.2)</td><td align=\"left\">125 (14.0)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Albuminuric DKD with reduced eGFR</td><td align=\"left\">1,048 (7.0)</td><td align=\"left\">192 (21.5)</td><td align=\"left\"/></tr><tr><td align=\"left\">DR, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> No DR</td><td align=\"left\">11,797 (79.3)</td><td align=\"left\">479 (53.5)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Non-advanced DR</td><td align=\"left\">1,758 (11.8)</td><td align=\"left\">199 (22.2)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Advanced DR</td><td align=\"left\">1,323 (8.9)</td><td align=\"left\">217 (24.2)</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"4\">CVD, n (%)</td></tr><tr><td align=\"left\"> Myocardial infarction</td><td align=\"left\">1,503 (10.1)</td><td align=\"left\">255 (28.5)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Coronary revascularization</td><td align=\"left\">1,246 (8.4)</td><td align=\"left\">338 (37.8)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Any coronary event</td><td align=\"left\">2,020 (13.6)</td><td align=\"left\">395 (44.1)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Stroke</td><td align=\"left\">463 (3.1)</td><td align=\"left\">52 (5.8)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Carotid revascularization</td><td align=\"left\">589 (4.0)</td><td align=\"left\">278 (31.1</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Any cerebrovascular event</td><td align=\"left\">1,001 (6.7)</td><td align=\"left\">304 (34.0)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Any coronary or cerebrovascular event</td><td align=\"left\">2,715 (18.4)</td><td align=\"left\">460 (52.1)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\" colspan=\"4\">Comorbidities n (%)</td></tr><tr><td align=\"left\"> Any</td><td align=\"left\">2,614 (17.6)</td><td align=\"left\">189 (21.1)</td><td align=\"left\">0.007</td></tr><tr><td align=\"left\"> COPD</td><td align=\"left\">621 (4.2)</td><td align=\"left\">57 (6.4)</td><td align=\"left\">0.002</td></tr><tr><td align=\"left\"> Chronic liver disease</td><td align=\"left\">1,264 (8.5)</td><td align=\"left\">106 (11.8)</td><td align=\"left\">0.001</td></tr><tr><td align=\"left\"> Cancer</td><td align=\"left\">990 (6.7)</td><td align=\"left\">45 (5.0)</td><td align=\"left\">0.056</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Mortality rates in study participants by history of diabetic foot, ulcer/gangrene and/or amputation, and ulcer/gangrene/amputation and/or lower limb revascularization</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">N</th><th align=\"left\">Events</th><th align=\"left\">Percent events</th><th align=\"left\">Events per 1,000 patient-years (95% CI),<break/>unadjusted</th><th align=\"left\">\n<italic>P</italic>\n</th><th align=\"left\">Events per 1,000 patient-years (95% CI),<break/>age- &amp; sex-adjusted</th><th align=\"left\">\n<italic>p</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">History of diabetic foot no</td><td char=\".\" align=\"char\">14,773</td><td char=\".\" align=\"char\">3,186</td><td char=\".\" align=\"char\">21.6</td><td char=\".\" align=\"char\">28.78 (27.80–29.80)</td><td align=\"left\">Ref.</td><td align=\"left\">12.50 (11.10-14.09)</td><td align=\"left\">Ref.</td></tr><tr><td align=\"left\">History of diabetic foot yes</td><td char=\".\" align=\"char\">883</td><td char=\".\" align=\"char\">416</td><td char=\".\" align=\"char\">47.1</td><td char=\".\" align=\"char\">76.83 (69.79–84.58)</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">25.51 (21.84–29.79)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Ulcer/gangrene no – Amputation no</td><td char=\".\" align=\"char\">15,100</td><td char=\".\" align=\"char\">3,324</td><td char=\".\" align=\"char\">22.0</td><td char=\".\" align=\"char\">29.47 (28.49–30.49)</td><td align=\"left\">Ref.</td><td align=\"left\">12.53 (11.12–14.12)</td><td align=\"left\">Ref.</td></tr><tr><td align=\"left\">Ulcer/gangrene yes – Amputation no</td><td char=\".\" align=\"char\">407</td><td char=\".\" align=\"char\">198</td><td char=\".\" align=\"char\">48.6</td><td char=\".\" align=\"char\">81.27 (70.70-93.42)</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">25.05 (20.87–30.07)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Ulcer/gangrene no – Amputation yes</td><td char=\".\" align=\"char\">33</td><td char=\".\" align=\"char\">16</td><td char=\".\" align=\"char\">48.5</td><td char=\".\" align=\"char\">77.46 (47.45-126.43)</td><td align=\"left\">0.013</td><td align=\"left\">32.48 (19.59–53.84)</td><td align=\"left\">0.014</td></tr><tr><td align=\"left\">Ulcer/gangrene yes – Amputation yes</td><td char=\".\" align=\"char\">116</td><td char=\".\" align=\"char\">64</td><td char=\".\" align=\"char\">55.2</td><td char=\".\" align=\"char\">94.01 (73.58-120.11)</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">36.89 (27.96–486.7)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Ulcer/gangrene/amput no – Revasc no</td><td char=\".\" align=\"char\">14,773</td><td char=\".\" align=\"char\">3,186</td><td char=\".\" align=\"char\">21.6</td><td char=\".\" align=\"char\">28.78 (2780 − 29.80)</td><td align=\"left\">Ref.</td><td align=\"left\">12.50 (11.10-14.09)</td><td align=\"left\">Ref.</td></tr><tr><td align=\"left\">Ulcer/gangrene/amput yes – Revasc no</td><td char=\".\" align=\"char\">433</td><td char=\".\" align=\"char\">203</td><td char=\".\" align=\"char\">46.9</td><td char=\".\" align=\"char\">76.23 (66.43–87.47)</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">26.31 (21.95–31.54)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Ulcer/gangrene/amput no – Revasc yes</td><td char=\".\" align=\"char\">327</td><td char=\".\" align=\"char\">138</td><td char=\".\" align=\"char\">42.2</td><td char=\".\" align=\"char\">66.01 (55.87-78.00)</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">21.74 (17.65–26.78)</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Ulcer/gangrene/amput yes – Revasc yes</td><td char=\".\" align=\"char\">123</td><td char=\".\" align=\"char\">75</td><td char=\".\" align=\"char\">61.0</td><td char=\".\" align=\"char\">113.50 (90.51-142.33)</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">33.46 (25.80-43.39)</td><td align=\"left\">&lt; 0.0001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Survival analysis by Cox proportional hazards regression with backward selection of variables, unadjusted and adjusted for confounders (model 3)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">HR</th><th align=\"left\">95% CI</th><th align=\"left\">\n<italic>p</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Any diabetic foot event (unadjusted)</td><td align=\"left\">2.73</td><td align=\"left\">2.46–3.02</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Any diabetic foot event</td><td align=\"left\">1.50</td><td align=\"left\">1.35–1.68</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Age, years</td><td align=\"left\">1.09</td><td align=\"left\">1.08–1.09</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Male sex</td><td align=\"left\">1.30</td><td align=\"left\">1.20–1.40</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Smoking status</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">0.001</td></tr><tr><td align=\"left\"> Never</td><td align=\"left\">1.00</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> Former</td><td align=\"left\">1.07</td><td align=\"left\">0.99–1.16</td><td align=\"left\">0.074</td></tr><tr><td align=\"left\"> Current</td><td align=\"left\">1.22</td><td align=\"left\">1.10–1.35</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">PA level</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">0.010</td></tr><tr><td align=\"left\"> Inactive or moderately inactive</td><td align=\"left\">1.00</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> Moderately active</td><td align=\"left\">0.90</td><td align=\"left\">0.83–0.97</td><td align=\"left\">0.004</td></tr><tr><td align=\"left\"> Highly active</td><td align=\"left\">0.81</td><td align=\"left\">0.56–1.19</td><td align=\"left\">0.290</td></tr><tr><td align=\"left\">Diabetes duration, years</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\">HbA<sub>1c</sub>, %</td><td align=\"left\">1.06</td><td align=\"left\">1.03–1.08</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">BMI, kg·m<sup>− 2</sup></td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\">Triglycerides, mmol·l<sup>− 1</sup></td><td align=\"left\">1.00</td><td align=\"left\">1.00-1.01</td><td align=\"left\">0.092</td></tr><tr><td align=\"left\">Total cholesterol, mmol·l<sup>− 1</sup></td><td align=\"left\">0.94</td><td align=\"left\">0.90–0.97</td><td align=\"left\">0.001</td></tr><tr><td align=\"left\">HDL cholesterol, mmol·l<sup>− 1</sup></td><td align=\"left\">0.84</td><td align=\"left\">0.75–0.94</td><td align=\"left\">0.002</td></tr><tr><td align=\"left\">Systolic BP, mmHg</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\">Diastolic BP, mmHg</td><td align=\"left\">0.99</td><td align=\"left\">0.99-1.00</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Anti-hyperglycemic treatment</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Lifestyle</td><td align=\"left\">1.00</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> Non-insulin</td><td align=\"left\">1.31</td><td align=\"left\">1.15–1.49</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Insulin</td><td align=\"left\">1.83</td><td align=\"left\">1.60–2.10</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Lipid-lowering treatment</td><td align=\"left\">0.78</td><td align=\"left\">0.73–0.84</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Anti-hypertensive treatment</td><td align=\"left\">1.18</td><td align=\"left\">1.08–1.29</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">DKD phenotype</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> No DKD</td><td align=\"left\">1.00</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> Albuminuric DKD with preserved eGFR</td><td align=\"left\">1.43</td><td align=\"left\">1.31–1.56</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Nonalbuminuric DKD</td><td align=\"left\">1.51</td><td align=\"left\">1.36–1.67</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\"> Albuminuric DKD with reduced eGFR</td><td align=\"left\">1.89</td><td align=\"left\">1.71–2.09</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">DR grade</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">0.001</td></tr><tr><td align=\"left\"> No DR</td><td align=\"left\">1.00</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> Non-advanced DR</td><td align=\"left\">1.04</td><td align=\"left\">0.95–1.14</td><td align=\"left\">0.419</td></tr><tr><td align=\"left\"> Advanced DR</td><td align=\"left\">1.21</td><td align=\"left\">1.10–1.34</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Any coronary event</td><td align=\"left\">1.26</td><td align=\"left\">1.15–1.37</td><td align=\"left\">&lt; 0.0001</td></tr><tr><td align=\"left\">Any cerebrovascular event</td><td align=\"left\">1.14</td><td align=\"left\">1.03–1.26</td><td align=\"left\">0.009</td></tr><tr><td align=\"left\">Any comorbidity</td><td align=\"left\">1.63</td><td align=\"left\">1.51–1.75</td><td align=\"left\">&lt; 0.0001</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM5\"></supplementary-material>" ]
[ "<table-wrap-foot><p>PA = physical activity; HbA<sub>1c</sub> = hemoglobin A<sub>1c</sub>; BMI = body mass index; BP = blood pressure; eGFR = estimated glomerular filtration rate; DKD = diabetic kidney disease; DR = diabetic retinopathy; = CVD = cardiovascular disease; COPD = chronic obstructive pulmonary disease</p></table-wrap-foot>", "<table-wrap-foot><p>CI = confidence interval</p></table-wrap-foot>", "<table-wrap-foot><p>HR = hazard ratio; CI = confidence interval; PA = physical activity; HbA<sub>1c</sub> = hemoglobin A<sub>1c</sub>; BMI = body mass index; BP = blood pressure; DKD = diabetic kidney disease; DR = diabetic retinopathy</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2107_Fig1_HTML\" id=\"d32e1642\"/>", "<graphic xlink:href=\"12933_2023_2107_Fig2_HTML\" id=\"d32e1672\"/>", "<graphic xlink:href=\"12933_2023_2107_Fig3_HTML\" id=\"d32e1702\"/>" ]
[ "<media xlink:href=\"12933_2023_2107_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>", "<media xlink:href=\"12933_2023_2107_MOESM2_ESM.docx\"><caption><p>Supplementary Material 2</p></caption></media>", "<media xlink:href=\"12933_2023_2107_MOESM3_ESM.docx\"><caption><p>Supplementary Material 3</p></caption></media>", "<media xlink:href=\"12933_2023_2107_MOESM4_ESM.docx\"><caption><p>Supplementary Material 4</p></caption></media>", "<media xlink:href=\"12933_2023_2107_MOESM5_ESM.doc\"><caption><p>Supplementary Material 5</p></caption></media>" ]
[{"label": ["10."], "mixed-citation": ["Stedman M, Robinson A, Dunn G, Meza-Torres B, Gibson JM, Reeves ND et al. Diabetes foot Complications and standardized mortality rate in type 2 Diabetes. Diabetes Obes Metab 2023 Sep 18."]}, {"label": ["17."], "surname": ["Costa", "Cardoso", "Proc\u00f3pio", "Navarro", "Dardik", "de Loiola Cisneros"], "given-names": ["RHR", "NA", "RJ", "TP", "A", "L"], "article-title": ["Diabetic foot Ulcer carries high amputation and mortality rates, particularly in the presence of advanced age, peripheral artery Disease and anemia"], "source": ["Diabetes Metab Syndr"], "year": ["2017"], "volume": ["11"], "issue": ["Suppl 2"], "fpage": ["583"], "lpage": ["S587"]}]
{ "acronym": [ "BMI", "BP", "CI", "COPD", "CVD", "DKD", "DPN", "DR", "eGFR", "HbA1c", "HR", "OR", "PA", "PAD", "RIACE" ], "definition": [ "Body mass index", "Blood pressure", "Confidence interval", "Chronic Obstructive Pulmonary Disease", "Cardiovascular disease", "Diabetic kidney disease", "Diabetic peripheral neuropathy", "Diabetic retinopathy", "Estimated glomerular filtration rate", "Hemoglobin A1c", "Hazard ratio", "Odds ratio", "Physical activity", "Peripheral artery disease", "Renal Insufficiency and cardiovascular events" ] }
46
CC BY
no
2024-01-14 23:43:45
Cardiovasc Diabetol. 2024 Jan 13; 23:34
oa_package/8b/53/PMC10787405.tar.gz
PMC10787406
0
[ "<title>Background</title>", "<p id=\"Par15\">Depression is one of the most common mental disorders in childhood and adolescence [##REF##25649325##1##], with incidences rising up to 7.5% [##REF##25524788##2##]. In the context of the COVID-19 pandemic, recent studies report increased mental health problems in youth, including a heightened prevalence of depressive symptoms and depressive disorder. For example, a recent meta-analysis found an increase of clinically relevant depressive symptoms to 25.2% among children and adolescents [##REF##34369987##3##]. Moreover, a systematic review reported an estimated increase of 27.6% for major depressive disorder among the global population in the context of the COVID-19 pandemic, with a more pronounced increase in younger compared to older age groups [##REF##34634250##4##]. There is further evidence which shows that increases in depression symptoms and clinically relevant depression rates during the COVID-19 pandemic were related to pandemic-related restrictions, with more stringent and invasive pandemic-related restrictions being associated with higher effect estimates [##REF##36587221##5##]. The same pattern was also evident for anxiety symptoms and clinically relevant anxiety rates [##REF##37344892##6##].</p>", "<p id=\"Par16\">Despite the high burden and negative psychosocial and medical consequences of youth depression [##REF##11879160##7##, ##REF##27118666##8##], data from Germany show that only 12.5% of adolescents with clinically relevant depressive symptoms seek help and start treatment in a 12-month period [##UREF##0##9##]. Children and adolescents and their families are confronted with a number of barriers when it comes to seeking help in case of mental problems including long waiting times and limited treatment offers, negative prior experiences, fear of stigmatisation and limited knowledge regarding treatment options [##REF##21192795##10##–##UREF##1##12##]. In the context of depression, limited depression literacy is also seen as a barrier against seeking professional help [##REF##21504872##13##]. Yet, reducing the time between the onset of a depressive disorder and the start of treatment is of great importance, as the longer a depressive disorder is not treated effectively, the higher the risk for chronification with more episodes throughout the course [##REF##16507961##14##, ##REF##24183486##15##].</p>", "<p id=\"Par17\">Parents of youth with a mental disorder play an important role in supporting their children to seek professional help [##UREF##2##16##]. There is evidence that knowledge about mental disorders, symptom severity and treatment in parents of children with a history of depression is associated with more treatment-seeking, improved treatment decision and better treatment quality concerning their children [##UREF##3##17##, ##REF##19485588##18##]. Further research shows that parents’ knowledge about, e.g., their child’s mental disorder influences the parental ability to carry out practices to support their affected offspring [##UREF##4##19##]. Thus, parental knowledge about mental disorders like youth depression is crucial for effective parental support. There is further evidence that parents of adolescents with mental disorders proactively seek sources to increase their knowledge in order to increase their support abilities [##REF##24499095##20##], which underlines their willingness to provide support.</p>", "<p id=\"Par18\">Thus, well-informed parents can substantially contribute to the early detection of mental disorders like depression in their children, to supporting them in seeking help from suitable specialists and to dealing with the challenges over the course of their illness. Yet, a majority of children and adolescents as well as their parents know only little about the symptoms, causes and forms of treatment of depression in childhood and adolescence [##REF##12212529##21##, ##REF##17311685##22##]. In a recent study [##UREF##5##23##], parents were asked to respond to vignettes about children and children with different mental health problems. The results showed less knowledge and more stigma in parents towards depression compared to other frequent mental health conditions like attention-deficit/hyperactivity disorder (ADHD). Another study investigated knowledge on mood disorders and their treatment in parents of children with a diagnosed mood disorder [##UREF##6##24##]. The results showed that parents had some basic knowledge about these topics, yet none had full knowledge, suggesting room for improvement. Together, these findings indicate the need to provide more psychoeducation offers to parents on depression in childhood and adolescence in order to enhance their depression literacy and reduce stigma towards the disorder.</p>", "<p id=\"Par19\">Enhancing parents’ knowledge about depression in childhood and adolescence can be achieved by making such information broadly available, for instance with low-threshold online approaches. Up to now, there are only few broadly accessible evidence-based sources of information about youth depression for children and adolescents as well as their parents. Due to the increasing web usage [##UREF##7##25##–##UREF##9##27##], even more during the COVID-19 pandemic [##UREF##10##28##], digital sources of information are increasingly gaining importance. Digital formats on mental health topics are well accepted by adults of various ages [##REF##25710352##29##, ##UREF##11##30##], yet scientific evaluations on whether the reception of the contents leads to knowledge growth are still scarce.</p>", "<p id=\"Par20\">Research has shown the beneficial effects of public awareness and psychoeducation programs on mental disorders and stigmatization to improve knowledge and awareness of mental disorders among the general population [##REF##22526821##31##, ##REF##19723735##32##]. Moreover, one study evaluated the effects of an psychoeducation manual about depression in youths and reported increased knowledge and high acceptance among a sample of parents of adolescents with a history of depression [##REF##8340297##33##]. There is, however, only little research on the effects of digital formats. Studies show that parents and relatives of adolescents with a history of depression report satisfaction and appreciate the helpfulness of web-based support offers [##REF##16429086##34##, ##REF##24550185##35##]. Previous studies have proven the efficacy of digital psychoeducation content in increasing mental health knowledge in adults and decreasing stigma related to mental disorders [##REF##14742346##36##, ##REF##18289823##37##]. More specifically, there is also evidence for the efficacy of internet-based psychoeducational interventions in increasing depression literacy and decreasing depression stigma in adults (e.g. [##REF##21504872##13##, ##REF##15458995##38##]). An RCT (randomized-controlled trial) study with parents both of healthy adolescents and adolescents with mental health problems showed that parents who took part in a web-based mental health intervention program exhibited increased knowledge about youth mental health topics and enhanced self-efficacy in dealing with these aspects compared to a waitlist control group. The intervention program contained information on the nature, symptoms and treatment of youth depression and anxiety [##REF##18845585##39##]. Digital formats in outpatient treatment of mental disorders gained increasing importance during the COVID-19 pandemic. Studies on the effects of this approach during the pandemic, however, are scarce ([##REF##36587221##5##], but see e.g. [##REF##34904742##40##]).</p>", "<p id=\"Par21\">Taken together, previous findings indicate that web-based formats could be both an effective and low-threshold approach to increase knowledge about mental health and depression in adults. Yet, to our knowledge, there are no studies that investigated whether imparting information about depression in childhood and adolescence via web-based formats leads to an increase in knowledge about the topic in parents. The current study aimed to close this research gap. Besides, previous studies on the effects of web-based approaches did not investigate whether individual factors, and particularly sociodemographic variables, might influence knowledge gain. This, however, is a relevant aspect as it provides insight into the question, which individuals might profit most from such approaches and it thus helps to tailor digital psychoeducational offers.</p>", "<p id=\"Par22\">Building on the aforementioned research, the current study evaluated an innovative evidence-based information portal for parents on depression in childhood and adolescence (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ich-bin-alles.de/eltern\">www.ich-bin-alles.de/eltern</ext-link>). The platform addresses the need for broadly available and easily accessible evidence-based information on depression and was developed with the participation of parents. The aim of the study was to investigate whether parents of adolescents with a history of depression would show increased knowledge about depression in childhood and adolescence after reception of the website and whether this knowledge gain would be stable over the course of 4 weeks. In this context, we also exploratively aimed to investigate whether sociodemographic factors would influence knowledge gain. An additional aim of the study was to assess how participants evaluate the layout and acceptance of the website. Based on previous research in adults [##REF##21504872##13##, ##REF##15458995##38##], we hypothesised that parents of adolescents with a history of depression would show increased knowledge about depression after presentation of the website and that this knowledge gain would be stable over the course of 4 weeks. Moreover, given the participatory approach during the development of the website, we hypothesized a positive evaluation of the portal’s layout and a high acceptance rate.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par23\">To investigate the aforementioned study aims, i.e. (1) knowledge change after reception of contents of the website “ich bin alles”, and (2) acceptance as well as evaluation of the layout in parents of adolescents with a history of depression, a pre-post follow-up design in a convenience sample was employed. This study was preregistered on ClinicalTrials.gov (identifier: NCT05335564) and was approved by the local ethics committee.</p>", "<title>Participants</title>", "<p id=\"Par24\">The sample consisted of <italic>N</italic> = 33 parents (<italic>M</italic><sub>age</sub> = 50.97, <italic>SD</italic><sub><italic>age</italic></sub> = 6.76, 17 females and 16 males) of adolescents (<italic>M</italic><sub>age</sub> = 15.61, <italic>SD</italic><sub><italic>age</italic></sub> = 1.62, age range 12–17 years) with a history of depression, either current or remitted or partially remitted. Information on participant’s sex was received via self-report during recruitment and in the sociodemographic questionnaire (where participants had to fill in “mother” or “father”). The history of depression was assessed via the Kinder-DIPS, a semi-structured diagnostic interview [##UREF##12##41##, ##UREF##13##42##], which was conducted with the participants’ children. The Kinder-DIPS has a good retest and interrater reliability (Cohens Kappa ≥ 0.90) [##UREF##14##43##, ##UREF##15##44##] and good validity (<italic>p</italic> ≤ 0.001 for the difference between target disorder and other diagnoses, indicating discriminant validity) [##UREF##12##41##]. With regard to depression diagnoses, 14 children fulfilled the criteria for a current depressive disorder (42.4%) and 19 (54.5%) were remitted or partially remitted. Participants were required to have sufficient German language skills to understand the instructions, the contents of the website and the questionnaires. A self-designed sociodemographic questionnaire was used to assess participant’s socioeconomic status index (ses-index) according to Lampert, Kroll [##REF##23703479##45##]. The questionnaire contains questions on educational level, professional qualification, and income of the families. The majority of participants had a high socioeconomic status (78.8% high; 18.2% middle; 0% low; 1 missing value). For a summary of participants’ sociodemographic data, see Additional file ##SUPPL##0##1##: Table S1.</p>", "<p id=\"Par25\">Participants were recruited via the Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Hospital of the Ludwig-Maximilians-University (LMU) Munich. Recruitment took place from January 2021 until April 2022. We contacted (1) parents of adolescents with a history of depression who had participated in studies on youth depression at the department in the past. In addition, we (2) recruited parents of adolescents with a history of depression who were currently undergoing treatment or had formerly been treated at the department’s clinic. During the recruitment process, we aimed to reach a balanced sample regarding participants’ sex, i.e. both mothers and fathers were contacted.</p>", "<p id=\"Par26\">Participants were informed in detail about the procedure and aims of the study and gave written consent for their study participation. For the conduction of the Kinder-DIPS, parents of children younger than 18 years gave written consent for their children’s participation. For children aged 18, their personal written consent was sufficient. The participants received money or vouchers (worth 50€) as compensation for their participation.</p>" ]
[ "<title>Results</title>", "<title>Baseline knowledge</title>", "<p id=\"Par40\">Participants’ total baseline knowledge (with <italic>N</italic> = 33) was <italic>M</italic> = 74.02% (<italic>SD</italic> = 11.94%) and ranged from 43 to 92% of correct answers in total. Baseline scores for the different domains were as follows: “prevalence and comorbidities” (<italic>M</italic> = 72.73%, <italic>SD</italic> = 20.12%), “professional diagnostic and treatment” (<italic>M</italic> = 69.70%, <italic>SD</italic> = 32.93%), “symptoms” (<italic>M</italic> = 76.77%, <italic>SD</italic> = 14.40%), “causes” (<italic>M</italic> = 73.11%, <italic>SD</italic> = 11.74%), and “course and degree of severity” (<italic>M</italic> = 77.77%, <italic>SD</italic> = 18.00%).</p>", "<title>Knowledge changes over time</title>", "<p id=\"Par41\">Participants’ total knowledge (with <italic>n</italic> = 31) at post-assessment was <italic>M</italic> = 88.52% (<italic>SD</italic> = 7.00%) and ranged from 68 to 98% correct answers in total. Participants’ total knowledge at follow-up-assessment was <italic>M</italic> = 85.62% (<italic>SD</italic> = 8.37%) and ranged from 57 to 94% of correct answers in total. The repeated-measures ANOVA on changes in knowledge across all domains revealed a significant effect of time, <italic>F</italic>(2, 60) = 25.55, <italic>p</italic> &lt; 0.001, partial η<sup>2</sup> = 0.46. Post-hoc dependent samples <italic>t</italic>-tests revealed a significant increase in knowledge from pre to post (<italic>t</italic>(30) = − 6.55, <italic>p</italic> &lt; 0.001) and from pre to follow-up (<italic>t</italic>(30) = − 4.95, <italic>p</italic> &lt; 0.001). There was no significant change from post to follow-up (<italic>t</italic>(30) = 1.67, <italic>p</italic> = 0.106) (see Fig. ##FIG##0##1##). The repeated-measures ANOVA on changes in knowledge for the five domains revealed a significant effect of time (<italic>F</italic>(2, 60) = 25.55, <italic>p</italic> &lt; 0.001, partial η<sup>2</sup> = 0.46) and domain (<italic>F</italic>(2.69, 80.65) = 3.30, <italic>p</italic> = 0.029, partial η<sup>2</sup> = 0.10). The interaction between time and domain did not reach significance (<italic>F</italic>(4.16, 125.07) = 1.92, <italic>p</italic> = 0.11, partial η<sup>2</sup> = 0.06). The descriptive statistics show a similar pattern of knowledge change across all domains (see Additional file ##SUPPL##0##1##: Fig. S3).</p>", "<title>Prediction of baseline knowledge and of changes in knowledge</title>", "<p id=\"Par42\">The regression analysis with socioeconomic status and sex as predictors and baseline knowledge as the dependent variable showed that the model with both variables did not account for a significant proportion of variance (<italic>F</italic>(2, 29) = 2.69, <italic>p</italic> = 0.085, <italic>R</italic><sup><italic>2</italic></sup> = 0.16). An explorative examination of the variance explained by the single predictors revealed that sex was a significant predictor of baseline knowledge (β = − 0.37; <italic>t</italic>(29) = − 2.08; <italic>p</italic> = 0.042), with mothers exhibiting a higher baseline knowledge score than fathers. By contrast, socioeconomic status did not account for a significant proportion of variance.</p>", "<p id=\"Par43\">The second regression analysis with socioeconomic status, sex and changes in knowledge from pre to post as the dependent variable revealed that the variables did not account for a significant proportion of variance (<italic>F</italic>(2, 29) = 0.23, <italic>p</italic> = 0.794, <italic>R</italic><sup><italic>2</italic></sup> = 0.02). Explorative examination showed that neither of the two variables had a significant effect on changes in participants’ knowledge (see Additional file ##SUPPL##0##1##: Table S3 for an overview of the regression analyses).</p>", "<title>Evaluation of the layout and acceptance of the website</title>", "<p id=\"Par44\">The average value of the VisAwi-S general aesthetic factor was <italic>M</italic> = 5.83 (<italic>SD</italic> = 0.88) and thus exceeded 4.5 as the benchmark for a positive evaluation of the website’s layout. The overall grade given to the website was <italic>M</italic> = 1.76 (<italic>SD</italic> = 0.55), and thus fell in between very good and good. The results for participants’ answers to the evaluation of the website are presented in Table ##TAB##1##2##.</p>", "<p id=\"Par45\">Correlation analyses revealed a significant negative correlation (Spearman’s ρ = -0.48, <italic>p</italic> = 0.005) between participants’ social desirability tendency and the VisAWI-S general aesthetic factor. Thus, against what might be expected, higher levels of social desirability were associated with lower scores in the VisAWI-S. Yet, there were no significant correlations between participants’ social desirability tendencies and the items of the evaluation questionnaire (all <italic>p</italic>s ≥ 0.116).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par46\">The main goal of the study was to investigate whether parents of adolescents with a history of depression show increased depression literacy after the reception of a website about youth depression and whether this increase remains stable at follow-up. Another main aim of the study was to assess the reception of the layout and acceptance of the website in the study sample. We found an increase in overall knowledge from pre to post that remained stable from post to follow-up. Given the non-significant interaction between time and domain, this pattern was evident across domains. The reception of the layout was positive, as were the acceptance ratings for the website. Imparting and increasing knowledge through low-threshold psychoeducational approaches like websites are particularly relevant in times of crisis and increased prevalence rates of depressive symptoms and disorders.</p>", "<p id=\"Par47\">Our findings of a stable increase in knowledge with large effect sizes provide promising support that our digital approach can educate parents of adolescents with a history of depression. Our findings are in line with previous studies on the effects of (online) information formats in increasing knowledge on mental health and depression, and decreasing stigma in adults (e.g. [##REF##21504872##13##, ##REF##17311685##22##, ##REF##22526821##31##, ##REF##8340297##33##, ##REF##14742346##36##–##REF##15458995##38##]).</p>", "<p id=\"Par48\">Despite high baseline knowledge rates, participants’ knowledge gain was significant with a mean of 13.5% from pre to post and 10.6% from pre to follow-up. As a digital information portal is a low-threshold offer that can reach many people, even numerically small changes might be clinically relevant when they result in more treatment seeking and subsequently more beneficial outcomes in adolescents with depression. Yet, it was beyond the scope of the present investigation to assess a transfer of the acquired knowledge into everyday life or the potential benefits on clinical outcomes, which should be addressed in future studies.</p>", "<p id=\"Par49\">With respect to the results of the regression analyses, it first needs to be discussed that sociodemographic variables did not influence the extent of knowledge gain. This suggests that both mothers and fathers from adolescents with a history of depression with different socioeconomic backgrounds seem to profit from our online information portal. Yet, it has to be noted that the majority of our participants had a high socioeconomic status and nones had a low socioeconomic status. Further research with a more diverse sample in terms of sociodemographic status is therefore needed in order to replicate our results and draw more comprehensive conclusions.</p>", "<p id=\"Par50\">Although the regression analysis on the influence of sociodemographic variables on baseline knowledge failed statistical significance, it is worth noting that—on an explorative level—mothers exhibited a higher baseline knowledge than fathers. This goes in line with findings of previous research showing that women exhibit higher mental health literacy (e.g. [##REF##16911755##56##, ##REF##26413429##57##]) and are more informed about mental illnesses than men [##UREF##24##58##]. Another explanation for the higher baseline knowledge of mothers might be that, typically, they are still more involved in their children’s upbringing. Hence, mothers might have gathered more knowledge about their child’s depression, e.g. in the context of its treatment and other contacts to the health care system than fathers (e.g. [##UREF##25##59##]). Taken together, our explorative finding emphasizes the importance of targeting not only mothers but in particular fathers to close knowledge gaps.</p>", "<p id=\"Par51\">The positive evaluation of the layout of the website and our finding of high acceptance based on the evaluation questionnaire fits into previous findings that show a high acceptance of digital information platforms on mental disorders [##REF##25710352##29##, ##UREF##11##30##]. High acceptance rates and e.g. confirmatory responses regarding the tendency to recommend the website to others are essential for online formats to reach as many people as possible and to ensure the dissemination of the contents in the target groups. In this context, it’s worth briefly commenting on the outreach of the final website, which attracts around 1000 daily visitors 2-years post-launch (analysed via the tool Matomo). Together with the promising results regarding the evaluation, this emphasizes the potential of the participative approach taken during the development of our website, with the perspective and feedback of the target groups being strongly considered. Our findings on the relationship between the evaluation results and social desirability clearly speak against the notion that the positive reception of the website was biased by tendencies to respond socially desirable. Indeed, we even found a negative correlation between higher social desirability tendencies and the reception of the website’s layout as assessed with the VisAWI-S.</p>", "<p id=\"Par52\">Web-based ehealth services, like our digital information portal, bear many benefits for their defined target groups. They provide an easily and broadly accessible possibility to get important information on mental health contents, including information on professional services. Since research has shown that, in parents of children and adolescents with a history of depression, higher knowledge regarding mental disorders, symptom severity and treatment is associated with more treatment-seeking, improved treatment decision and better treatment quality concerning their children, low-threshold information offers might contribute to more beneficial outcomes [##UREF##3##17##–##UREF##4##19##]. However, not all adolescents receive the parental support they would need. Thus, adolescents themselves are in need of target-specific, comprehensive information on mental health content. To meet this need, next to the parents’ sub-website of “ich bin alles”, the website contains a sub-website for adolescents, which was evaluated in two independent studies (pre-registered at ClinicalTrials.gov: NCT05300204; NCT05300217).</p>", "<p id=\"Par53\">Our results of increased knowledge and stable knowledge change after the reception of contents of a web-based information portal on youth depression provide an important basis for similar approaches and might stimulate further research on web-based portals, which is still scarce. Furthermore, in light of the promising findings regarding the high acceptance of the portal and the positive evaluation of its layout, the approach chosen could inform the design of other web-based portals on mental health issues. Next to research related implications, the results of our study might also bear implications for policy decisions concerning the relevance of ehealth services in mental health education and campaigns.</p>", "<p id=\"Par54\">As the study was conducted during the COVID-19 pandemic, it might be the case that the restrictions and burdens associated with the crisis have influenced the results on the acceptance and evaluation of the website, in that information offers on mental health contents were perceived as particularly relevant. Yet, also after the end of pandemic-related restrictions, the website attracts a high number of visitors, thus proving support for its acceptance in the naturalistic setting.</p>" ]
[ "<title>Limitations and conclusions</title>", "<p id=\"Par55\">Some limitations of the study need to be considered. The majority of the parents had a high socioeconomic status, which might be attributed to the fact that the sample was drawn from a convenience sample. Therefore, the generalizability of the results should be supported in future studies including a population with a lower socioeconomic status. This is of particular importance, as these families are of greater risk for developing mental health problems (e.g. [##REF##34369987##3##]) and should thus be particularly considered in the context of low-threshold offers. Moreover, the study population was drawn from a convenience sample consisting of parents of adolescents with a history of depression who were currently or had been in treatment at the clinic for child and adolescent psychiatry of the Hospital of the LMU Munich. Therefore, generalizability of the results to other parent groups, including e.g. parents of untreated offspring, should be supported in future studies. In this context, it should be said that we have carried out another study with parents of healthy adolescents (ClinicalTrials.gov: NCT05326178), the results of which will be reported elsewhere.</p>", "<p id=\"Par56\">Furthermore, the study employed a single-armed pre-post-follow-up design, which does not exclude the possibility that factors that are not related to the reception of website contents per se contributed to knowledge change (including e.g. the readministration of the questionnaires or the possibility that participants got information elsewhere). Yet, between pre- and post-assessment, the study was conducted in a highly controlled laboratory setting, where participants were under continuous supervision, thus excluding the possibility of parents getting information elsewhere between these measurement points. This having said, future studies with a randomized-controlled study design are clearly needed to draw more rigorous conclusions on the efficacy of the website.</p>", "<p id=\"Par57\">Despite the a priori power analysis, which indicated that the sample size was sufficiently large to detect the expected effects, a sample of <italic>N</italic> = 33 represents a rather small number. Future studies should thus recruit larger samples to draw even more robust conclusions. Related to the restricted sample size, the present study could only exploratively investigate the possible influence of sociodemographic factors. In order to draw more rigorous conclusions on the influence of sociodemographic factors on knowledge change, larger samples are clearly warranted.</p>", "<p id=\"Par58\">Despite these limitations, this is the first study on knowledge effects and acceptance of a digital information platform on youth depression in a sample of parents of adolescents with a history of depression. Our study provides important information for the design of digital platforms addressing similar topics like “ich bin alles”. Digital offers on mental health are a low-threshold approach to inform parents and increase their knowledge and are thus especially important in times of limited resources or increased need such as the COVID-19 crisis. Moreover, approaches like ours might also decrease stigma. Given the negative consequences of youth depression when untreated (e.g. [##REF##34369987##3##, ##REF##24183486##15##]) as well as the important role of parents in supporting their children (e.g. [##UREF##3##17##, ##REF##19485588##18##]), it is essential to promote information platforms that are broadly available and easily accessible. Future studies should systemically explore whether such approaches also improve early detection and effective treatment of depression in affected youths.</p>" ]
[ "<p id=\"Par1\">Research shows the important role of parents’ mental health literacy in detecting depressive symptoms and supporting their children to seek professional help. Improving mental health literacy in parents has recently gained even greater importance due to the negative impact of the COVID-19 pandemic on children and adolescents’ mental health. The aim of the present experimental pre-post-follow-up study was to examine knowledge change after the reception of contents from an innovative web-based platform (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ich-bin-alles.de/eltern\">www.ich-bin-alles.de/eltern</ext-link>) containing evidence-based information on youth depression and mental health in parents of adolescents with a history of depression. A second aim was to assess evaluation of the layout and the acceptance of the platform. <italic>N</italic> = 33 parents of adolescents with a history of depression (either current or remitted depression) were presented different content domains of the website. Participants’ knowledge about depression was assessed at pre- and post-intervention, and at a four week follow-up. Moreover, parents evaluated the acceptance and the layout of the website. The trial was preregistered at clinicaltrials.gov (NCT05335564). The results showed a significant increase in total knowledge from pre to post, which remained stable over the course of four weeks. Explorative analyses showed that sociodemographic variables did not influence the extent of knowledge gain. Acceptance rates were high and evaluations of the website’s layout were positive. The findings show that the web-based information portal is a promising and appealing means to increase parental knowledge on youth depression. Low-threshold psychoeducational approaches like websites are particularly relevant in times of crisis and increased prevalence rates of depressive symptoms and disorders (ehealth). These results are an important basis for future studies as well as approaches that aim to impart knowledge about mental disorders like youth depression via web-based means. Furthermore, they bear implications for policy decisions concerning mental health education and campaigns.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13034-023-00703-x.</p>", "<title>Keywords</title>", "<p>Open Access funding enabled and organized by Projekt DEAL.</p>" ]
[ "<title>Materials</title>", "<title>Website</title>", "<p id=\"Par27\">The web-based information platform “ich bin alles” (www-ich-bin-alles.de, English translation: “I am everything”) was launched in September 2021 and was developed by the Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy of the LMU Hospital Munich together with the Prof. Otto Beisheim Foundation and media partners. The platform contains evidence-based information on depression and mental health in childhood and adolescence. An overview on the structure and contents of the website can be found in the Additional file ##SUPPL##0##1##: Table S2. The information presented was developed based on extensive literature reviews as well as the S3 evidence- and consensus-based clinical guideline for the treatment of youth depression in Germany (German treatment guidelines with the highest quality level) [##UREF##16##46##]. The final website contains two sub-websites, which were specifically designed for two different target groups: (1) children and adolescents and (2) parents. The contents, language, and layout of the platform were created with the help of interviews with children and adolescents, their parents, as well as experts like child and adolescent psychiatrists and psychotherapists. The texts are written in a target-specific and appealing way and are easy to understand. For a good reading flow, the texts are structured in several sections. The information is illustrated by graphical elements. Moreover, other media formats (like videos and podcasts) are included to illustrate and complement the textual information. A professional design and media agency was involved in the conception, design and technical setup of the website.</p>", "<p id=\"Par28\">Prior to the finalisation of the website, an evaluation website for parents, which was not publicly accessible, was created for scientific purposes. This evaluation website contained five pages of the final website with general information about depression in childhood and adolescence for parents: (1) prevalence and comorbidities; (2) professional diagnostic and treatment; (3) symptoms; (4) causes; (5) course and degree of severity. The evaluation website comprised texts, graphical elements, two videos and one podcast. In one video, for example, a child and adolescent psychiatrist answers questions on symptoms of depression in childhood and adolescence. A screenshot of the evaluation website can be found in Additional file ##SUPPL##0##1##: Fig. S2.</p>", "<title>Assessment of baseline knowledge and knowledge gain</title>", "<p id=\"Par29\">A questionnaire designed by the research team, henceforward described as “self-designed”, was used to assess parents’ knowledge on depression in childhood and adolescence at three measurement points: their knowledge before (pre-assessment; pre) consuming the information of the evaluation website (baseline knowledge) and just afterwards at post-assessment (post) at, as well as at a follow-up testing four weeks after they had consumed the information (follow-up) (see procedure for more details). Pre- and post-assessment took place within one testing session, with the reception of the website laying in between these two time points. The knowledge questionnaire consisted of 26 items in total of which 15 used a multiple choice format (of 4 answer options, 1–4 could be correct) and the remaining 11 used a “correct or incorrect” answer format. The items corresponded to the five sections of the evaluation website (see Table ##TAB##0##1## for an overview and item examples). Correctly answered questions were coded as 1, incorrectly answered questions were coded as 0. Thus, the final total sum score of correctly answered questions ranged from 0 to 26 across all sections (0–4 for prevalence and comorbidities; 0–2 for professional diagnostic and treatment; 0–6 for symptoms; 0–8 for causes; 0–6 for course and degree of severity).</p>", "<title>Acceptance and layout of website, and social desirability</title>", "<p id=\"Par30\">The German short version of the Visual Aesthetics of Websites Inventory (VisAWI; [##UREF##17##47##, ##UREF##18##48##]) was used to assess participants’ evaluation of the website’s design with a focus on visual aesthetics. The VisAWI-S is a reliable (internal consistency: Cronbach’s α = 0.81) and valid questionnaire. The VisAWI-S consists of four items (e.g. “The layout appears to be designed professionally”) with a seven-point Likert scale (ranging from 1 “not agree at all” to 7 “fully agree”). The general aesthetics factor is calculated by calculating the mean value from the four item responses. As a benchmark, an overall rating of 4.5 or higher means that participants experienced the website as overall positive [##REF##25311956##49##, ##UREF##19##50##]. Moreover, a self-designed evaluation questionnaire was applied to assess additional layout aspects and the acceptance of the website (for items, see Table ##TAB##1##2##). These items were assessed using a four-point rating scale (from 0 “not accurate” to 3 “entirely accurate”). Furthermore, participants were asked to give a grade for the website (ranging from 1 “very good” to 6 “insufficient”, based on the grading system used in German schools). Since participants’ tendencies towards social desirability might influence their response behaviour to questions on acceptance and layout, the Social Desirability Scale-17 (SDS-17; 51) was applied. The SDS-17 is a reliable (internal consistency: Cronbach’s α = 0.72–0.75) and valid questionnaire [##UREF##20##51##, ##UREF##21##52##].</p>", "<title>Procedure</title>", "<p id=\"Par31\">Data collection was carried out from January 2021 until May 2022. Due to the COVID-19 pandemic and accompanying restrictions, the study was mostly conducted online via the secure/encrypted medical video tool RED Connect (RED Medical Systems), except for the Kinder-DIPS interviews, which were conducted in person with the affected children of the participants at the Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Hospital of LMU Munich. 31 participants participated digitally (94.0%); two participated in person (6.0%). At the beginning of the testing session, the experimenter presented the knowledge questionnaire for pre-assessment to the participants via screen-sharing. The experimenter asked the participants to provide oral answers to the questions and filled out the answers in the questionnaire. In case of participation in person at the department, participants filled out the questionnaires in paper–pencil format. After pre-assessment, the experimenter instructed the participants to open a new browser tab, type in the Website URL and a username and password. Participants were instructed to share their screen so that the experimenter could control which pages of the website participants were looking at. Thereafter, the experimenter guided the participants through the website and instructed the participants to read the textual contents of the website, and to consume the included videos and podcasts in a concentrated manner until they reached the bottom of the page. Guided by the experimenter, the participants followed a fixed procedure for each of the five website pages: “depression in childhood and adolescence” (4 min., plus a 3:27 min. video); “professional diagnostic and treatment” (3 min.); “prevalence and comorbidities (2 min.); “course and degree of severity” (3 min., plus a 7:00 min. podcast); and “causes of depression in childhood and adolescence” (6 min., plus a 4:05 min. video). In case of a participation in person, participants were seated in front of a laptop at the laboratory to look at the website. The guided instruction and the procedure for consuming the contents of the website were identical with the digital participation.</p>", "<p id=\"Par32\">After reception of the website (post), participants were presented the knowledge questionnaire, the evaluation questionnaire, the VisAWI-S, the SDS-17 and the sociodemographic questionnaire. After a period of four weeks, the follow-up testing took place, at which the participants again were assessed with the knowledge questionnaire. 32 participants attended the follow-up digitally (97.0%), one attended in person again (3.0%). As the experimenter guided the participants through both the website contents as well as the questionnaires, the experimenter was aware of participants’ exposure history in the context of the present study.</p>", "<p id=\"Par33\">Seven participants (21.21%) participated in the study prior to the launch of the final website. The remaining 26 participants (78.79%) participated after the launch. Therefore, at pre-assessment the latter were presented a short questionnaire assessing whether they knew the website and had already consumed the contents; moreover, at follow-up, they were asked whether they had looked at the website between post- and follow-up-assesssments. Only two particitpants indicated that they had visited the launched website briefly once between post and follow-up measurements. Sensitivity analyses showed that the pattern of results remained stable when excluding these two participants. Thus, we decided to keep these participants in the final sample. Furthermore, due to exceeded time periods between post and follow-up measurements, two participants (6 and 8 weeks between post and follow-up) had to be excluded from the analyses on knowledge changes over time, resulting in a sample of <italic>n</italic> = 31 adults for analysing this aspect of the study. However, they were kept in the analyses focusing on acceptance and layout (see next paragraph). For an illustration of the study procedure, see Additional file ##SUPPL##0##1##: Fig. S1.</p>", "<title>Data analysis</title>", "<p id=\"Par34\">Statistical data analysis was carried out using IBM SPSS Statistics 26. For all analyses, the significance level was set to <italic>p</italic> = 0.05 (two-tailed).</p>", "<p id=\"Par35\">To obtain knowledge scores for the three assessment points, we calculated unweighted index values for the items of the knowledge questionnaire for each participant (following [##UREF##22##53##]), separately for every domain as well as across all domains. This procedure is based on the classical test theory assumption of parallel items, which means that all items are equally good indicators for the construct that they measure. We first calculated proportional scores for each domain by dividing the sum score of the domain by the number of questions (i.e. the highest possible score) and multiplied the proportional scores with 100 to receive percentages. For the score across all domains (overall score), we summed up the proportional scores across the domains and divided this by the number of domains, and then multiplied this score with 100 to receive percentages again (see [##REF##23907413##54##] for a similar approach).</p>", "<p id=\"Par36\">To investigate changes in knowledge across domains, we conducted a repeated-measures ANOVA with time (pre/post/follow-up) as a within-subject factor. To investigate changes in knowledge for the five different domains, we conducted repeated-measures ANOVAs with time (pre/post/follow-up) and domain (prevalence and comorbidities/professional diagnostic and treatment/symptoms/causes/course and degree of severity) as within-subject factors. In case of a significant interaction effect between time and domain, we would conduct follow-up repeated-measures ANOVAs with the within-subject factor time (pre/post/follow-up) for each domain (i.e. five ANOVAs). In case of significant effects in the repeated-measures ANOVAs, we would further conduct post-hoc tests comparing the time points based on dependent <italic>t</italic>-tests. For the post-hoc tests, we would apply the Bonferroni-Holm correction for multiple testing and would correct all <italic>p</italic>-values accordingly. For all ANOVAs, we computed the effect size partial eta square (a small effect is defined as η<sup>2</sup> = 0.01, a medium effect as η<sup>2</sup> = 0.06 and a large effect as η<sup>2</sup> = 0.16 [##UREF##23##55##]).</p>", "<p id=\"Par37\">To exploratively investigate whether sociodemographic factors might impact baseline knowledge and knowledge change, we conducted two multiple regressions with socioeconomic status and sex as predictors and (1) baseline knowledge and (2) changes in knowledge from pre to post as criteria (i.e. the difference score between post minus pre).</p>", "<p id=\"Par38\">To investigate participants’ evaluation of the acceptance and the layout of the website (evaluation questionnaire and VisAWI-S), we calculated descriptive statistics (<italic>M</italic>, <italic>SD</italic>). Furthermore, we conducted explorative correlation analyses (Spearman’s ρ) to investigate whether social desirability influenced participants’ answers in the evaluation questionnaire and the VisAWI-S. For these analyses, no correction for multiple comparisons was conducted, which in this case is the more conservative approach regarding the validity of our results (i.e., significant results would speak against and not in favour of the validity of our results). The analysis plan was pre-determined for the main analyses, yet not the explorative analyses.</p>", "<title>Power analysis</title>", "<p id=\"Par39\">We calculated a priori power analysis to determine the necessary sample size to detect the expected effects. This calculation was based on a similar study by Kiropoulos and Griffiths [##REF##21504872##13##], which investigated the effects of an internet-based information intervention in increasing depression literacy and reducing depression stigma and symptoms based on a pre-post-follow-up study by calculating ANOVAs and ANCOVAs. The authors reported large effect size for the knowledge gain from pre to post (Cohen’s <italic>d</italic> = − 1.78). Based on a conservative assumption of a medium effect size in the ANOVAs (<italic>f</italic> = 0.25), an alpha level of 0.05 and power of 0.80, the target sample size is <italic>N</italic> = 30. Thus, our sample of <italic>N</italic> = 31 was sufficiently large to detect the expected effect. The calculations for the sample size were computed with G*Power 3.1.9.2.</p>", "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank all participants and their parents. Furthermore, the authors would like to thank Cosima Klingele for their help with data collection.</p>", "<title>Author contributions</title>", "<p>EG, GS-K, RP, CP and LF contributed to the study conception. RP, LI, SK and CK performed the data collection. LI analysed and interpreted the data under supervision from EG and with support from all authors. The first draft of the manuscript was written by LI under supervision of EG. All authors commented on the manuscript draft. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>Open Access funding enabled and organized by Projekt DEAL. The study was funded by a grant from the foundation “Prof. Otto Beisheim Stiftung” to G.S.-K., E.G., C.P., R.P., and L.F.</p>", "<title>Availability of data and material</title>", "<p>Our data includes sensitive patient information, such as information on comorbidities. Since participants could possibly be identified by making our raw data publicly available, ethical principles of protecting patient confidentiality would be breached. Thus, raw data cannot be made publicly available. We can make additional materials and aggregated data available upon request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par59\">The study was approved by the ethics committee of the Medical Faculty of the LMU Munich and all procedures were in accordance with the latest version of the Declaration of Helsinki. All participants were informed in detail about the procedures and the aims of the study and provided written informed assent.</p>", "<title>Consent for publication</title>", "<p id=\"Par60\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par61\">All authors declare no conflicts of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Knowledge changes over time (M, SE) in %; ***<italic>p</italic> &lt;. 001; <italic>n</italic> = 31</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Overview of items and example items for the different sections in the knowledge questionnaire</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Domain</th><th align=\"left\">Number of items</th><th align=\"left\">Example item</th><th align=\"left\">Answer options</th></tr></thead><tbody><tr><td align=\"left\">Prevalence and comorbidities</td><td align=\"left\">4</td><td align=\"left\">Depression is one of the most common mental disorders in childhood and adolescence</td><td align=\"left\"><bold>a) correct</bold> b) incorrect</td></tr><tr><td align=\"left\">Professional diagnostic and treatment</td><td align=\"left\">2</td><td align=\"left\">Who can diagnose a depressive disorder?</td><td align=\"left\">a) anyone can assess this, if one has dealt with the topic extensively and knows the symptoms b) there are reliable tests in the internet that are helpful to find out whether one has depression or not <bold>c) only specific professionals with appropriate qualifications can assess this</bold> d) close friends and family can best assess this since they know the person best</td></tr><tr><td align=\"left\">Symptoms</td><td align=\"left\">6</td><td align=\"left\">What are possible symptoms of depression?</td><td align=\"left\"><bold>a) sadness b) loss of interest</bold> c) increased talkativeness <bold>d) loss of energy</bold></td></tr><tr><td align=\"left\">Causes</td><td align=\"left\">8</td><td align=\"left\">If one encounters a great amount of burdens and has a genetic risk for depression, one has an increased risk to develop a depression</td><td align=\"left\"><bold>a) correct</bold> b) incorrect</td></tr><tr><td align=\"left\">Course and degree of severity</td><td align=\"left\">6</td><td align=\"left\">How are the different degrees of severity of depression called?</td><td align=\"left\">a) big, small b) low, strong <bold>c) mild, moderate, severe</bold> d) light, heavy</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Results for evaluation questionnaire items (in %)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Items</th><th align=\"left\">Entirely accurate</th><th align=\"left\">Mainly accurate</th><th align=\"left\">Somewhat accurate</th><th align=\"left\">Not accurate</th></tr></thead><tbody><tr><td align=\"left\">I would recommend the website to other parents.</td><td char=\".\" align=\"char\"><bold>90.9</bold></td><td char=\".\" align=\"char\">9.1</td><td char=\".\" align=\"char\">0</td><td char=\".\" align=\"char\">0</td></tr><tr><td align=\"left\">I think the website is well suited for parents.</td><td char=\".\" align=\"char\"><bold>81.8</bold></td><td char=\".\" align=\"char\">12.1</td><td char=\".\" align=\"char\">6.1</td><td char=\".\" align=\"char\">0</td></tr><tr><td align=\"left\">It was fun looking at the website.</td><td char=\".\" align=\"char\"><bold>48.5</bold></td><td char=\".\" align=\"char\">45.5</td><td char=\".\" align=\"char\">3.0</td><td char=\".\" align=\"char\">3.0</td></tr><tr><td align=\"left\">The website is clearly structured.</td><td char=\".\" align=\"char\"><bold>51.5</bold></td><td char=\".\" align=\"char\">42.4</td><td char=\".\" align=\"char\">0</td><td char=\".\" align=\"char\">3.0</td></tr><tr><td align=\"left\">I like the texts.</td><td char=\".\" align=\"char\"><bold>60.6</bold></td><td char=\".\" align=\"char\">39.4</td><td char=\".\" align=\"char\">0</td><td char=\".\" align=\"char\">0</td></tr><tr><td align=\"left\">Overall, I like the pictures on the website.</td><td char=\".\" align=\"char\"><bold>51.5</bold></td><td char=\".\" align=\"char\">30.3</td><td char=\".\" align=\"char\">18.2</td><td char=\".\" align=\"char\">0</td></tr><tr><td align=\"left\">I like the video.*</td><td char=\".\" align=\"char\"><bold>54.6</bold></td><td char=\".\" align=\"char\">37.9</td><td char=\".\" align=\"char\">6.1</td><td char=\".\" align=\"char\">1.5</td></tr><tr><td align=\"left\">I like the podcast.</td><td char=\".\" align=\"char\"><bold>51.5</bold></td><td char=\".\" align=\"char\">39.4</td><td char=\".\" align=\"char\">9.1</td><td char=\".\" align=\"char\">0</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Correct answers are indicated in bold</p></table-wrap-foot>", "<table-wrap-foot><p>Results based on a four-point rating scale (0: not accurate, 1: somewhat accurate; 2: mainly accurate; 3: entirely accurate); %; <italic>N</italic> = 33; *mean values of both videos</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Gerd Schulte-Körne and Ellen Greimel shared senior authorship.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13034_2023_703_Fig1_HTML\" id=\"MO1\"/>" ]
[ "<media xlink:href=\"13034_2023_703_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Table S1. </bold>Sociodemographic Data. <bold>Table S2.</bold> Contents of the final website. <bold>Figure S1. </bold>Study procedure. <bold>Figure S2.</bold> Screenshot of the evaluation website on the contents of prevalences &amp; comorbidities. <bold>Figure S3.</bold> Differences in knowledge changes over time (in %). <bold>Table S3.</bold> Results of the regression analyses; N = 33.</p></caption></media>" ]
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Acceptance of the German e-mental health portal "], "ext-link": ["www.psychenet.de"]}, {"label": ["41."], "surname": ["Margraf", "Cwik", "Pflug", "Schneider"], "given-names": ["J", "JC", "V", "S"], "article-title": ["Structured clinical interviews for mental disorders across the life span: psychometric quality and further developments of the DIPS open access interviews"], "source": ["Z Klin Psychol Psychother"], "year": ["2017"], "volume": ["46"], "issue": ["3"], "fpage": ["176"], "lpage": ["186"]}, {"label": ["42."], "surname": ["Schneider", "Pflug", "In-Albon", "Margraf"], "given-names": ["S", "V", "T", "J"], "source": ["Kinder-DIPS Open Access: Diagnostisches Interview bei psychischen St\u00f6rungen im Kindes- und Jugendalter"], "year": ["2017"], "publisher-loc": ["Bochum"], "publisher-name": ["Forschungs- und Behandlungszentrum f\u00fcr psychische Gesundheit, Ruhr-Universit\u00e4t Bochum"]}, {"label": ["43."], "surname": ["Adornetto", "In-Albon", "Schneider"], "given-names": ["C", "T", "S"], "article-title": ["Diagnostik im Kindes-und Jugendalter anhand strukturierter Interviews: anwendung und Durchf\u00fchrung des Kinder-DIPS"], "source": ["Klinische Diagnostik Eval"], "year": ["2008"], "volume": ["1"], "issue": ["4"], "fpage": ["363"], "lpage": ["377"]}, {"label": ["44."], "surname": ["Neuschwander", "In-Albon", "Adornetto", "Roth", "Schneider"], "given-names": ["M", "T", "C", "B", "S"], "article-title": ["Interrater-Reliabilit\u00e4t des Diagnostischen Interviews bei psychischen St\u00f6rungen im Kindes-und Jugendalter (Kinder-DIPS)"], "source": ["Zeitschrift f\u00fcr Kinder Jugendpsychiatr Psychother"], "year": ["2013"], "volume": ["41"], "issue": ["5"], "fpage": ["319"], "lpage": ["334"]}, {"label": ["46."], "mixed-citation": ["Dolle K, Schulte-K\u00f6rne G. S3-Behandlungsleitlinie zur Behandlung von depressiven St\u00f6rungen bei Kindern und Jugendlichen, Langfassung.: AWMF; 2013. "], "ext-link": ["https://register.awmf.org/assets/guidelines/028-043l_S3_Depressive_St%C3%B6rungen_bei_Kindern_Jugendlichen_2013-07-abgelaufen.pdf"]}, {"label": ["47."], "surname": ["Moshagen", "Thielsch"], "given-names": ["M", "M"], "article-title": ["A short version of the visual aesthetics of websites inventory"], "source": ["Behav Inf Technol"], "year": ["2013"], "volume": ["32"], "issue": ["12"], "fpage": ["1305"], "lpage": ["1311"]}, {"label": ["48."], "surname": ["Moshagen", "Thielsch"], "given-names": ["M", "MT"], "article-title": ["Facets of visual aesthetics"], "source": ["Int J Hum Comput Stud"], "year": ["2010"], "volume": ["68"], "issue": ["10"], "fpage": ["689"], "lpage": ["709"]}, {"label": ["50."], "mixed-citation": ["Thielsch M, Moshagen M. Manual zum VisAWI (Visual Aesthetics of Websites Inventory) und der Kurzversion VisAWI-S (Short Visual Aesthetics of Websites Inventory).2014."]}, {"label": ["51."], "surname": ["St\u00f6ber"], "given-names": ["J"], "article-title": ["The Social Desirability Scale-17 (SDS-17): Convergent validity, discriminant validity, and relationship with age"], "source": ["Eur J Psychol Assess"], "year": ["2001"], "volume": ["17"], "issue": ["3"], "fpage": ["222"]}, {"label": ["52."], "surname": ["St\u00f6ber"], "given-names": ["J"], "article-title": ["Die soziale-erw\u00fcnschtheits-skala-17 (SES-17): entwicklung und erste befunde zu reliabilit\u00e4t und validit\u00e4t [The social desirability scale-17 (SDS-17): development and first findings on reliability and validity]"], "source": ["Diagnostica"], "year": ["1999"], "volume": ["45"], "issue": ["4"], "fpage": ["173"], "lpage": ["177"]}, {"label": ["53."], "surname": ["D\u00f6ring", "Bortz"], "given-names": ["N", "J"], "source": ["Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften"], "year": ["2016"], "publisher-loc": ["Heidelberg"], "publisher-name": ["Springer"]}, {"label": ["55."], "surname": ["Ellis"], "given-names": ["PD"], "source": ["The essential guide to effect sizes: statistical power, meta-analysis, and the interpretation of research results"], "year": ["2010"], "publisher-loc": ["Cambridge"], "publisher-name": ["Cambridge University Press"]}, {"label": ["58."], "surname": ["Holzinger", "Floris", "Schomerus", "Carta", "Angermeyer"], "given-names": ["A", "F", "G", "MG", "MC"], "article-title": ["Gender differences in public beliefs and attitudes about mental disorder in western countries: a systematic review of population studies"], "source": ["Epidemiol Psychiatric Sci"], "year": ["2012"], "volume": ["21"], "issue": ["1"], "fpage": ["73"], "lpage": ["85"]}, {"label": ["59."], "surname": ["Craig", "Mullan"], "given-names": ["L", "K"], "article-title": ["How mothers and fathers share childcare: a cross-national time-use comparison"], "source": ["Am Sociol Rev"], "year": ["2011"], "volume": ["76"], "issue": ["6"], "fpage": ["834"], "lpage": ["861"]}]
{ "acronym": [ "ADHD", "ANOVA", "Follow-up", "Kinder-DIPS", "LMU", "M", "Pre", "Post", "RCT", "SD", "SDS-17", "SE", "SES" ], "definition": [ "Attention-deficit/hyperactivity disorder", "Analysis of variance", "Follow-up assessment", "Diagnostic Interview for Mental Disorders for Children and Adolescents", "Ludwig-Maximilians-University", "Mean", "Pre-assessment", "Post-assessment", "Randomized-controlled trial", "Standard deviation", "The Social Desirability Scale-17", "Standard error", "Socioeconomic status" ] }
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2024-01-14 23:43:45
Child Adolesc Psychiatry Ment Health. 2024 Jan 13; 18:7
oa_package/01/98/PMC10787406.tar.gz
PMC10787407
0
[ "<title>Introduction</title>", "<p id=\"Par2\">Rheumatoid arthritis (RA) is an autoimmune disorder that is characterized by persistent inflammation of the joints and bones, resulting in severe synovitis and osteoporosis [##REF##22150039##1##, ##REF##37641070##2##]. In addition to pain, stiffness, edema, and loss of joint function, RA patients are more likely to develop cancer and cardiovascular disease. Enhancing the intestinal flora may help reduce RA symptoms because studies have revealed that nearly all RA patients have changed intestinal flora [##REF##33202579##3##].</p>", "<p id=\"Par3\">Numerous bacteria that are vital for immunological control, metabolism, illness prevention, and digestion reside in the human gut [##REF##22972295##4##]. When the balance between beneficial bacteria and “harmful bacteria” is disrupted and the “harmful bacteria” become overabundant, this can often lead to the development of diseases. Consequently, restoring the disturbed intestinal flora is an effective approach to treating diseases. Furthermore, the gut is a vital “metabolic organ” of the body, influencing the metabolic processes of endogenous substances such as bile acid metabolism and tryptophan metabolism, as well as playing a key role in the metabolism of exogenous drug substances [##REF##29902437##5##, ##UREF##0##6##]. As our knowledge of the intestinal flora has grown, the potential of the intestinal flora for drug metabolism has become increasingly apparent. The gut is a significant location of medication absorption. The drug remains in the gut after oral administration and interacts with the diverse gut flora. Gut bacteria can metabolize drugs by secreting glycosidases, reductases, and other metabolic enzymes, thus influencing drug absorption and efficacy [##REF##32116054##7##].</p>", "<p id=\"Par4\">Researchers have been paying more and more attention lately to the ability of polysaccharides used in traditional Chinese medicine (TCM) to control the flora in the intestine [##REF##35609509##8##]. Although TCM polysaccharides are difficult for the body to digest, they may still have an impact through interacting with the flora in the intestine. Studies have demonstrated that TCM polysaccharides have a variety of pharmacological effects, including anti-inflammatory [##REF##32114173##9##], antioxidant [##REF##36587222##10##], and immunomodulatory [##REF##21058924##11##]. Some TCM polysaccharides also have the ability to treat disorders by altering the composition of gut flora [##REF##34229020##12##]. Therefore, it is important to consider the pharmacological action of TCM polysaccharides and their regulatory effects on the gut flora.</p>", "<p id=\"Par5\">Wu-tou decoction (WTD) is a TCM recipe composed of Aconiti Radix Preparata, Ephedrae Herba, Glycyrrhiza Radix, Paeoniae Radix Alba, and Astragali Radix. It is a classical Chinese medicine recipe for treating RA. The WTD water extraction was roughly decomposed into small molecule compounds (SM) with low molecular weight and polysaccharides (PS). Many investigations on the effective ingredients and mechanisms of WTD in the treatment of RA had been conducted [##REF##24170633##13##–##REF##26895106##16##]. In our previous study, we examined the components of WTD absorbed in the blood [##REF##31762208##17##, ##UREF##1##18##], and it was found that WTD could be effective in treating RA by modulating the composition of the intestinal flora [##UREF##2##19##]. However, there had been relatively few research on the involvement of polysaccharides in WTD because they cannot be absorbed into the bloodstream. In this study, the 16S rRNA gene sequencing technique was used to investigate the role of PS and SM in the regulation of intestinal flora in AIA rats. After that, the impact of PS intervention on the pharmacokinetic (PK) characteristics of SM was evaluated using UPLC-MS/MS analysis. The function of PS in the TCM formula was clarified by examining the effects of changes in the gut flora composition on the PK properties of SM.</p>" ]
[ "<title>Materials and methods</title>", "<title>Chemicals and reagents</title>", "<p id=\"Par6\">Complete Freund’s adjuvant (CFA) was purchased from Chondrex Inc. (Redmond, WA, USA). Methanol, formic acid, acetonitrile, and isopropanol (chromatographic grade) were purchased from Fisher Scientific (Loughborough, UK). Ultrapure water was prepared using the Milli-Q plus system (Milford, MA, USA). Other chemicals were of analytical grade.</p>", "<p id=\"Par7\">Reference standards of ephedrine, methylephedrine, albiflorin, calycosin-7-glucoside, oxypaeoniflorin, paeoniflorin, liquiritin apiosid, liquiritin, isoliquiritin, liquiritigenin, calycosin, isoliquiritigenin, glycyrrhizic acid, formononetin, glycyrrhetinic acid, reserpine (IS), and naringin (IS) were purchased from the Chinese Authenticating Institute of Material and Biological Products (Beijing, China). Benzoylpaeoniflorin, benzoylaconine, benzoylmesaconine, benzoylhypaconine, neoline, songorine, talatizamine, and fuziline were purchased from Lanyuan Biological technology Co., Ltd. (Shanghai, China). The purities of all references were more than 98%.</p>", "<title>Preparation of WTD, SM, and PS</title>", "<p id=\"Par8\">A total of 1400 g of crude herbs, comprising 200 g Aconiti Radix Preparata (ZCW), 300 g Ephedrae Herba (MH), 300 g Glycyrrhiza Radix (GC), 300 g Paeoniae Radix Alba (BS) and 300 g Astragali Radix (HQ) were immersed in water solvent for 1 h and then extracted twice by refluxing with 14 L and 11.2 L water for 1.5 h, respectively. The two extracts were combined. Subsequently, half of the WTD extract was concentrated to 1.5 g/mL and stored. The other half of the WTD extract was concentrated to 0.5 g/mL, 95% ethanol was added to make the ethanol concentration of the extract 70%, and alcohol precipitation was allowed to stand overnight. After centrifugation, the supernatant (SM) and the precipitated fraction (PS) were separated. The SM was concentrated to 1.5 g/mL of crude drug, while the PS was dissolved in water and concentrated to 1.5 g/mL of crude drug. They were kept separately frozen.</p>", "<title>Animals</title>", "<p id=\"Par9\">The Animal Experiment Protocol listed below was approved by the Institutional Animal Care Committee of Jilin University Research Ethics Committee Guide (20190068) and performed according to Jilin Provincial Laboratory Animal Regulations. 42 male Sprague–Dawley (SD) rats (180–220 g) were purchased from Liaoning Changsheng Biotechnology Co., Ltd (Dalian, China). The animals were raised in an SPF grade, temperature-controlled (25 ± 1 ℃) and humidity-controlled (50% ± 5%) room at a 12 h light–dark cycle. Their food and water were provided to them free of charge. The animals fasted for 12 h before the start of the experiment.</p>", "<title>Drug administration</title>", "<p id=\"Par10\">In the study of intestinal microflora, 30 SD rats were randomly divided into 5 groups (n = 6 for each group), namely the normal control group (NC group), model group (AIA group), WTD group, SM group and PS group, respectively. The model group, the WTD group, the SM group, and the PS group each received 0.1 mL of CFA in the left hind foot, whereas the NC group received 0.1 mL of saline in the same location. The AIA model was successfully established two weeks later. Rats in the WTD group were orally administrated WTD (9.8 g crude drug/kg/day) [##UREF##2##19##, ##REF##24561351##20##], SM group rats received SM (9.8 g crude drug/kg/day), PS group rats were given PS (9.8 g crude drug/kg/day). The drug was given continuously for 30 days. Pathological sections, serum for biochemical component analysis, and colon contents for 16S rRNA sequencing analysis were all taken 1 h following the last treatment.</p>", "<p id=\"Par11\">In the PK study, 12 SD rats were divided into model group (MG group) and model + polysaccharide group (MPS group). Rats in the MPS group were given PS (9.8 g crude drug/kg/day) by oral administration, while rats in the MG group received the same amount of saline. After continuous administration for 21 days, rats in both groups were given SM (39.2 g crude drug/kg/day), and two groups of rats were subjected to a PK study. The aim was to find out the effect of PS on the PK properties of SM components. Whole blood was collected in a 1.5 mL centrifuge tube containing heparin sodium before and 0.083, 0.25, 0.5, 0.75, 1, 2, 4, 6, 8, 12, 24,36 and 48 h after administration.</p>", "<title>16S rRNA gene sequencing</title>", "<p id=\"Par12\">The E.Z.N.A.<sup>®</sup> soil DNA extraction kit (Norcross, GA,) was used for DNA extraction. The V3-V4 variable region was PCR-amplified using primers the quality of the DNA extraction was established, and the composition of the intestinal flora was determined by sequencing using a high-throughput sequencer Miseq. PCoA analysis was used to evaluate the difference in bacteria composition between the NC group, AIA group, WTD group, SM group and PS group. LEfSe analysis was used to determine the dominant flora of the different groups and to highlight the differences in flora.</p>", "<title>Pharmacodynamic analysis</title>", "<p id=\"Par13\">The ELISA kit to detect the levels of TNF-α and IL-6 in rat serum according to the instructions. The ankle joints of the right hind feet of rats were fixed with 10% paraformaldehyde, and histological examination was conducted using hematoxylin–eosin (HE) staining.</p>", "<title>PK study</title>", "<p id=\"Par14\">100 μL plasma was mixed with 10 μL internal standard solution (containing 150 ng/mL reserpine and 200 ng/mL naringin) and 500 μL isopropanol, shaken for 10 min. The supernatant was collected and dried with N<sub>2</sub>, redissolved with 100 μL methanol, and centrifuged again after 10 min centrifugation at 4 °C, 13000 rpm. Then the supernatant was collected for UPLC-MS /MS analysis.</p>", "<title>Instruments and analytical conditions</title>", "<p id=\"Par15\">The Shimadzu UPLC-MS/MS system was used for the PK study. The system consists of high-performance liquid chromatography (LC-30A) and a triple quadrupole mass spectrometer (LCMS-8050) with ESI source. The multiple reaction monitoring (MRM) mode was used both in positive and negative mode. The MS parameters were as follows: flow rate of heating gas 10 L/min, flow rate of drying gas 10 L/min, flow rate of atomizing gas 3 L/min, interfacial temperature 300 ℃, DL temperature 250 ℃. The LabSolution LCMS ver. 5.6 software (Shimadzu, Japan) for data collection and processing.</p>", "<p id=\"Par16\">Separation was performed using a Waters ACQUITY UPLC BEH C<sub>18</sub> column (2.1 mm × 100 mm, 1.7 μm). The mobile phase was 0.1% formic acid water (v/v) (A) and acetonitrile (B). The optimal elution conditions were as follows: in positive ion mode, 0–8 min, 15–30% B; 8–10 min, 30–100% B; 10–12 min, 100% B; 12–14 min, 100–15% B; 14–17 min, 15% B. In negative ion mode, 0–2 min, 15–30% B; 2–7 min, 30–60% B; 7–8 min, 60–100% B; 8–10 min, 100% B; 10–12 min, 100–15% B; 12–15 min, 15% B.</p>", "<title>Statistical analysis</title>", "<p id=\"Par17\">All data were shown as the mean ± SEM. GraphPad Prism version 8.0.1 (GraphPad Software, San Diego, USA) was used for statistical analyses. The significance of multiple groups was assessed using one-way analysis of variance (ANOVA) with Dunnett’s <italic>post hoc</italic> test. When data were not normally distributed, the Kruskal–Wallis H and Mann–Whitney U tests were performed. Significance was defined as <italic>p</italic> &lt; 0.05 using SPSS 16.0 software. Compared with model *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001.</p>" ]
[ "<title>Results and discussion</title>", "<title>Pharmacodynamic evaluation</title>", "<p id=\"Par18\">In order to investigate the overall effect of WTD and different components, the pharmacodynamics of WTD (yield 52.12%/ crude drug), SM (yield 24.79%/ crude drug), and PS (yield 22.55%/ crude drug) were evaluated. Polysaccharide content in WTD, SM, and PS were determined by phenol–sulfuric acid method (Additional file ##SUPPL##0##1##: Table S1.). Their mass spectra were shown in Additional file ##SUPPL##0##1##: Figure S1. The ankle swelling diminished after drug administration (Fig. ##FIG##0##1##A). The levels of TNF-α and IL-6 in rat serum were measured using an ELISA kit, and the anti-inflammatory effects of the different groups were assessed. In addition, the HE staining procedure was used to study the pathology of the right hind foot’s ankle joint. The results showed that the AIA group had considerably greater levels of TNF-α and IL-6 in their serum than the NC group (Fig. ##FIG##0##1##B). The AIA rats' synovial tissue was badly proliferated, accompanied by a massive influx of inflammatory cells (Fig. ##FIG##0##1##C). WTD was able to successfully limit the inflammatory response both inside and outside of the joint, diminish the synovial destruction, and dramatically lower the levels of inflammatory factors in the serum. SM and PS were also able to inhibit the expression of inflammatory factors in the serum and alleviate the pathological changes of the joints induced by RA, though their effects were weaker than WTD.</p>", "<title>Analysis of gut microbiota composition</title>", "<p id=\"Par19\">The 16S rRNA gene sequencing technology was used to examine the microbiota in rats' colon contents. The PCoA results demonstrated that the AIA group's intestinal flora was considerably different from the NC group, and the composition of the intestinal flora changed amongst the experimental groups (Fig. ##FIG##1##2##A). At the phylum level, AIA group had significantly lower abundance values for Bacteroidetes, Actinobacteria, and Tenericutes compared with the NC group. In contrast, Firmicutes abundance values increased. Compared with the AIA group, the relative abundance of Bacteroidetes and Tenericutes increased in the WTD, SM and PS groups, and the general trend was similar to the NC group (Fig. ##FIG##1##2##B). At the genus level, compared to the NC group, the AIA group showed an increase in the abundance values of Unspecified Clostridiaceae and Prevotella, while the abundances of Oscillospira and Bifidobacterium decreased. The relative abundance of Unspecified Clostridiaceae and Prevotella decreased and Oscillospira and Bifidobacterium increased in the administered groups by comparison with the AIA group (Fig. ##FIG##1##2##C). The above results indicate that RA could alter the composition of the intestinal flora in rats and cause disruption. WTD, SM, and PS had distinct restorative effects on the disordered gut bacterial composition.</p>", "<title>Differential microflora analysis</title>", "<p id=\"Par20\">PCoA analysis demonstrated disparities in the composition of the intestinal flora among the experimental groups, thus the LEfSe analysis was utilized to identify the differential flora among these groups. The results of the LEfSe and PCoA analysis revealed a total of 12 key differential flora (Fig. ##FIG##2##3##).</p>", "<p id=\"Par21\">When compared to the NC group, the colonic contents of AIA rats had considerably higher concentrations of Verrucomicrobiae, Akkermansia, Prevotella, Dorea, Turicibacter, Streptococcus, Adlercreutzia, and Unspecified_Clostridiaceae, with Akkermansia showing the greatest increase. Akkermansia is an intestinal mucin-degrading bacterium. Chiang et al. reported that the abundance of Verrucomicrobia and Akkermansia was significantly higher in RA patients compared to healthy individuals [##REF##31652955##21##]. Additionally, some researchers have reported a significant increase in the abundance of Akkermansia in patients with juvenile spondyloarthritis, which was positively correlated with ankle swelling [##REF##29599513##22##]. The elevated abundance of Akkermansia may be the primary cause of the elevated abundance of the Verrucomicrobia phylum. Prevotella abundance was also closely connected with RA, and patients with RA were frequently associated with elevated Prevotella abundance [##REF##31581593##23##, ##REF##36323929##24##]. Some Clostridium species in the Clostridiaceae family can produce toxins and cause bacterial illnesses. Individuals with RA, as well as those with both inflammatory bowel disease and arthropathy, had a higher abundance of Clostridiaceae [##REF##30321331##25##]. Turicibacter is a pro-inflammatory bacterium that boosts the body's inflammatory response. It was also a pathogen found in increased concentrations in the guts of ulcerative colitis mice. Furthermore, Turicibacter abundance was positively correlated with the levels of TNF-α, IL-1β, and IL-6, suggesting that its overproduction may be linked to intestinal inflammation [##REF##35229916##26##]. Streptococcus is a large group of common gram-positive cocci among septicococci, and some pathogenic streptococci can cause a variety of septic inflammatory diseases in humans.</p>", "<p id=\"Par22\">In addition, there was a significant decrease in the abundance of Blautia, Bifidobacterium and Oscillospira in the colonic contents of rats in the model group. The abundance of Oscillospira was shown to be proportional to health and was significantly lower in patients suffering from inflammatory diseases [##REF##26996766##27##]. Bifidobacterium is one of the most frequent probiotics in the human intestine and it is advantageous to human health because it performs a range of key physiological tasks such as biological barrier, nutritional impacts, immunomodulation, and gastrointestinal function enhancement. Blautia is a unique potential probiotic that has been shown in tests to reduce inflammation, promote SCFA synthesis, and maintain intestinal homeostasis in colorectal cancer patients [##REF##34132169##28##]. The findings demonstrated that AIA rats had intestinal bacteria abnormalities, and that WTD, SM, and PS could all regulate the intestinal flora disorders produced by RA to varying degrees.</p>", "<title>Effects of PS on the PK profile of SM.</title>", "<p id=\"Par23\">In our previous work, 74 chemical components were measured [##REF##24274266##29##], and mass spectrometry was applied to the isolated SM and PS. The specific constituents were provided in Additional file ##SUPPL##0##1##: Table S2. The majority of the components in SM were small molecules, whereas the components in PS, which were primarily polysaccharide components, had a minimal SM content. In this study, the focus was to investigate the changes in PK properties of these absorbed components in plasma under PS influence using UPLC-MS/MS analysis, and then to clarify the effect of PS on the absorption of SM. A total of 23 components from WTD were subjected to PK studies. The MRM parameters, standard curves and representative MRM chromatograms of the compounds to be tested were shown in Tables ##TAB##0##1##, ##TAB##1##2##, and Fig. ##FIG##3##4##, respectively.\n</p>", "<p id=\"Par24\">The blood concentration–time curves of the 23 potential pharmacodynamic substances in each group were shown in Fig. ##FIG##4##5##. After the administration of polysaccharide, the songorine concentration–time curve changed significantly in the first 6 h. The C<sub>max</sub> values of benzoylhypaconine, fuziline, oxypaeoniflorin, benzoylpaeoniflorin, formononetin, liquiritin, isoliquiritigenin, and glycyrhizic acid showed significant changes (<italic>p</italic> &lt; 0.05). It shows that PS improves the absorption of active ingredients in AIA rats. Their PK parameters such as T <sub>max</sub>, C <sub>max</sub>, t <sub>1/2</sub>, AUC <sub>0-∞</sub>, and AUC <sub>0-t</sub> were compared and analyzed (Table ##TAB##2##3##). They were calculated from PK Solver 2.0. Compared with the MG Group, after oral PS, the C <sub>max</sub> and AUC <sub>0-∞</sub> of benzoylhypaconine increased, AUC <sub>0-t</sub> and AUC <sub>0-∞</sub> were increased for songorine, paeoniflorin, albiflorin and liquiritin apioside. The C <sub>max</sub> of liquiritin, benzoylpaeoniflorin, isoliquiritigenin and glycyrrhizic acid significantly increased. The C <sub>max</sub>, AUC <sub>0-t</sub>, and AUC <sub>0-∞</sub> of oxypaeoniflora were all significantly higher. The C <sub>max</sub> of fuziline and formononetin reduced, and the AUC <sub>0-t</sub> and AUC <sub>0-∞</sub> of methylephedrine decreased significantly. In summary, the PK characteristics of the components produced from GC and BS were primarily adjusted.</p>", "<p id=\"Par25\">After oral administration, Chinese herbs remain in the intestinal tract and interact with a large number of abundant intestinal flora. The intestinal flora is also referred to as a crucial \"metabolic organ\" of the human body because it affects not only the metabolism of exogenous drug components that can have a big impact on drug absorption but also the metabolism of endogenous substances like bile acids (BAs) and tryptophan. Researchers have been playing a lot of attention lately to how intestinal flora affects drug metabolism, and an increasing number of studies have revealed that intestinal flora is crucial for PK and pharmacodynamics. Intestinal flora can affect the metabolism and absorption of drugs by secreting abundant enzymes such as glycosidases and reductases, which in turn affect the efficacy of the drug. Liquiritin, liquiritigenin, glycyrrhizic acid, liquiritin apioside, paeoniflorin, oxypaeoniflora, and benzoylpaeoniflorin were typical herbal components that could be significantly metabolized by the intestinal flora [##UREF##3##30##, ##REF##30223050##31##]. For example, most of the glycyrrhizic acid would be converted to glycyrrhetinic acid in the intestine by the action of intestinal flora, thus continuing its medicinal effect. Liquiritin could be metabolized to liquiritigenin. Paeoniflorin could also be metabolized to albiflorin, albiflorinaglycone, and deacylate albiflorin [##UREF##4##32##]. SM prototypes also can alleviate inflammation by increasing absorption. Paeoniflorin [##UREF##5##33##], calycosin [##REF##27678042##34##], liquiritin [##REF##30785275##35##], liquiritigenin [##UREF##6##36##], and glycyrrhetinic acid [##REF##35668739##37##], for example, exhibit a wide spectrum of anti-inflammatory and immunomodulatory actions and have been found to be useful in the treatment of RA. These chemical components will continue to be targeted in subsequent studies.</p>", "<p id=\"Par26\">Previous research by our group demonstrated that WTD might improve intestinal flora dysbiosis and relieve the aberrant flora metabolite alterations caused by RA in AIA rats. Spearman correlation analysis revealed a close association between flora metabolites and intestinal flora. As a result, we hypothesized that a portion of the therapeutic impact of WTD on RA could be mediated by intestinal flora via modulation of the inflammatory response and intestinal barrier function. The integrity of the intestinal barrier is also linked to the development of inflammation and drug transfer [##UREF##7##38##].</p>", "<p id=\"Par27\">PS administration may modify the composition of intestinal flora in AIA rats, influencing SM absorption and metabolism. The association between SM absorption and gut flora was investigated by using Spearman correlation analysis. The differential flora impacted by the PS group was strongly linked with SM absorption, as shown in Fig. ##FIG##5##6##, with a total of 67 pairs had significant modifications. The drug absorption of liquiritin apioside, glycyrrhizic acid, oxypaeoniflorin, paeoniflorin, benzoylhypaconine, and songorine were negatively linked with Prevotella_2, meanwhile, whereas it exhibited a positive relationship with Oscillospira. Fuziline and methylephedrine exhibited a negatively correlation with Oscillospira and Bifidobacterium, while they were positively correlated with most of the differential flora. Furthermore, prior research had revealed that the intestinal barrier integrity of AIA rats has changed, and PS may also regulate the disruption of AIA rats' intestinal microbiota, repair the intestinal barrier of sick rats, and so affect SM absorption [##UREF##2##19##]. This could explain why the PK characteristics of the components in GC and BS had changed. Although polysaccharides cannot be absorbed into the bloodstream, they can influence the absorption and metabolism of small molecules by changing the gut bacteria, hence influencing medicinal efficacy. Products of microbiota metabolism can significantly mediate microbiota and host physiological function. Short-chain fatty acids (SCFAs), bile acids (BA), tryptophan metabolites and amino acids were important microbiota-associated metabolites that had immunomodulatory effects and were closely associated with RA disease progression [##REF##27711063##39##]. In our preceding metabolomics studies, kynurenic acid, xanthurenic acid, tyrosine and phenylalanine were potential biomarkers that were associated with RA and WTD treatment. The changes in the content of a series of metabolites such as SCFA, BA, tryptophan metabolites and amino acids were further determined by targeted assays [##REF##31762208##17##]. The results demonstrated that WTD can promote host health by alleviating metabolic disorders, reducing inflammation, modulating immune responses and maintaining intestinal barrier function. PS could affect the PK properties and absorption of pharmacodynamic substances in SM fraction in vivo. Hence, it was more logical to administer WTD as a combination of both PS and SM, which may result in improved pharmacodynamic effects.</p>", "<p id=\"Par28\">It is imperative to recognize a noteworthy constraint: Firstly, the results of the study were not sufficient to demonstrate the role of gut microbiota affected by PS or SM on WTD effect. Secondly, PS from WTD could affect the PK of some SM to a certain extent. However, no correlation was established between PD and these components based on their changes in this study. In future studies, in-depth research should be conducted in these aspects to elucidate the underlying mechanisms of WTD more comprehensively.</p>" ]
[ "<title>Results and discussion</title>", "<title>Pharmacodynamic evaluation</title>", "<p id=\"Par18\">In order to investigate the overall effect of WTD and different components, the pharmacodynamics of WTD (yield 52.12%/ crude drug), SM (yield 24.79%/ crude drug), and PS (yield 22.55%/ crude drug) were evaluated. Polysaccharide content in WTD, SM, and PS were determined by phenol–sulfuric acid method (Additional file ##SUPPL##0##1##: Table S1.). Their mass spectra were shown in Additional file ##SUPPL##0##1##: Figure S1. The ankle swelling diminished after drug administration (Fig. ##FIG##0##1##A). The levels of TNF-α and IL-6 in rat serum were measured using an ELISA kit, and the anti-inflammatory effects of the different groups were assessed. In addition, the HE staining procedure was used to study the pathology of the right hind foot’s ankle joint. The results showed that the AIA group had considerably greater levels of TNF-α and IL-6 in their serum than the NC group (Fig. ##FIG##0##1##B). The AIA rats' synovial tissue was badly proliferated, accompanied by a massive influx of inflammatory cells (Fig. ##FIG##0##1##C). WTD was able to successfully limit the inflammatory response both inside and outside of the joint, diminish the synovial destruction, and dramatically lower the levels of inflammatory factors in the serum. SM and PS were also able to inhibit the expression of inflammatory factors in the serum and alleviate the pathological changes of the joints induced by RA, though their effects were weaker than WTD.</p>", "<title>Analysis of gut microbiota composition</title>", "<p id=\"Par19\">The 16S rRNA gene sequencing technology was used to examine the microbiota in rats' colon contents. The PCoA results demonstrated that the AIA group's intestinal flora was considerably different from the NC group, and the composition of the intestinal flora changed amongst the experimental groups (Fig. ##FIG##1##2##A). At the phylum level, AIA group had significantly lower abundance values for Bacteroidetes, Actinobacteria, and Tenericutes compared with the NC group. In contrast, Firmicutes abundance values increased. Compared with the AIA group, the relative abundance of Bacteroidetes and Tenericutes increased in the WTD, SM and PS groups, and the general trend was similar to the NC group (Fig. ##FIG##1##2##B). At the genus level, compared to the NC group, the AIA group showed an increase in the abundance values of Unspecified Clostridiaceae and Prevotella, while the abundances of Oscillospira and Bifidobacterium decreased. The relative abundance of Unspecified Clostridiaceae and Prevotella decreased and Oscillospira and Bifidobacterium increased in the administered groups by comparison with the AIA group (Fig. ##FIG##1##2##C). The above results indicate that RA could alter the composition of the intestinal flora in rats and cause disruption. WTD, SM, and PS had distinct restorative effects on the disordered gut bacterial composition.</p>", "<title>Differential microflora analysis</title>", "<p id=\"Par20\">PCoA analysis demonstrated disparities in the composition of the intestinal flora among the experimental groups, thus the LEfSe analysis was utilized to identify the differential flora among these groups. The results of the LEfSe and PCoA analysis revealed a total of 12 key differential flora (Fig. ##FIG##2##3##).</p>", "<p id=\"Par21\">When compared to the NC group, the colonic contents of AIA rats had considerably higher concentrations of Verrucomicrobiae, Akkermansia, Prevotella, Dorea, Turicibacter, Streptococcus, Adlercreutzia, and Unspecified_Clostridiaceae, with Akkermansia showing the greatest increase. Akkermansia is an intestinal mucin-degrading bacterium. Chiang et al. reported that the abundance of Verrucomicrobia and Akkermansia was significantly higher in RA patients compared to healthy individuals [##REF##31652955##21##]. Additionally, some researchers have reported a significant increase in the abundance of Akkermansia in patients with juvenile spondyloarthritis, which was positively correlated with ankle swelling [##REF##29599513##22##]. The elevated abundance of Akkermansia may be the primary cause of the elevated abundance of the Verrucomicrobia phylum. Prevotella abundance was also closely connected with RA, and patients with RA were frequently associated with elevated Prevotella abundance [##REF##31581593##23##, ##REF##36323929##24##]. Some Clostridium species in the Clostridiaceae family can produce toxins and cause bacterial illnesses. Individuals with RA, as well as those with both inflammatory bowel disease and arthropathy, had a higher abundance of Clostridiaceae [##REF##30321331##25##]. Turicibacter is a pro-inflammatory bacterium that boosts the body's inflammatory response. It was also a pathogen found in increased concentrations in the guts of ulcerative colitis mice. Furthermore, Turicibacter abundance was positively correlated with the levels of TNF-α, IL-1β, and IL-6, suggesting that its overproduction may be linked to intestinal inflammation [##REF##35229916##26##]. Streptococcus is a large group of common gram-positive cocci among septicococci, and some pathogenic streptococci can cause a variety of septic inflammatory diseases in humans.</p>", "<p id=\"Par22\">In addition, there was a significant decrease in the abundance of Blautia, Bifidobacterium and Oscillospira in the colonic contents of rats in the model group. The abundance of Oscillospira was shown to be proportional to health and was significantly lower in patients suffering from inflammatory diseases [##REF##26996766##27##]. Bifidobacterium is one of the most frequent probiotics in the human intestine and it is advantageous to human health because it performs a range of key physiological tasks such as biological barrier, nutritional impacts, immunomodulation, and gastrointestinal function enhancement. Blautia is a unique potential probiotic that has been shown in tests to reduce inflammation, promote SCFA synthesis, and maintain intestinal homeostasis in colorectal cancer patients [##REF##34132169##28##]. The findings demonstrated that AIA rats had intestinal bacteria abnormalities, and that WTD, SM, and PS could all regulate the intestinal flora disorders produced by RA to varying degrees.</p>", "<title>Effects of PS on the PK profile of SM.</title>", "<p id=\"Par23\">In our previous work, 74 chemical components were measured [##REF##24274266##29##], and mass spectrometry was applied to the isolated SM and PS. The specific constituents were provided in Additional file ##SUPPL##0##1##: Table S2. The majority of the components in SM were small molecules, whereas the components in PS, which were primarily polysaccharide components, had a minimal SM content. In this study, the focus was to investigate the changes in PK properties of these absorbed components in plasma under PS influence using UPLC-MS/MS analysis, and then to clarify the effect of PS on the absorption of SM. A total of 23 components from WTD were subjected to PK studies. The MRM parameters, standard curves and representative MRM chromatograms of the compounds to be tested were shown in Tables ##TAB##0##1##, ##TAB##1##2##, and Fig. ##FIG##3##4##, respectively.\n</p>", "<p id=\"Par24\">The blood concentration–time curves of the 23 potential pharmacodynamic substances in each group were shown in Fig. ##FIG##4##5##. After the administration of polysaccharide, the songorine concentration–time curve changed significantly in the first 6 h. The C<sub>max</sub> values of benzoylhypaconine, fuziline, oxypaeoniflorin, benzoylpaeoniflorin, formononetin, liquiritin, isoliquiritigenin, and glycyrhizic acid showed significant changes (<italic>p</italic> &lt; 0.05). It shows that PS improves the absorption of active ingredients in AIA rats. Their PK parameters such as T <sub>max</sub>, C <sub>max</sub>, t <sub>1/2</sub>, AUC <sub>0-∞</sub>, and AUC <sub>0-t</sub> were compared and analyzed (Table ##TAB##2##3##). They were calculated from PK Solver 2.0. Compared with the MG Group, after oral PS, the C <sub>max</sub> and AUC <sub>0-∞</sub> of benzoylhypaconine increased, AUC <sub>0-t</sub> and AUC <sub>0-∞</sub> were increased for songorine, paeoniflorin, albiflorin and liquiritin apioside. The C <sub>max</sub> of liquiritin, benzoylpaeoniflorin, isoliquiritigenin and glycyrrhizic acid significantly increased. The C <sub>max</sub>, AUC <sub>0-t</sub>, and AUC <sub>0-∞</sub> of oxypaeoniflora were all significantly higher. The C <sub>max</sub> of fuziline and formononetin reduced, and the AUC <sub>0-t</sub> and AUC <sub>0-∞</sub> of methylephedrine decreased significantly. In summary, the PK characteristics of the components produced from GC and BS were primarily adjusted.</p>", "<p id=\"Par25\">After oral administration, Chinese herbs remain in the intestinal tract and interact with a large number of abundant intestinal flora. The intestinal flora is also referred to as a crucial \"metabolic organ\" of the human body because it affects not only the metabolism of exogenous drug components that can have a big impact on drug absorption but also the metabolism of endogenous substances like bile acids (BAs) and tryptophan. Researchers have been playing a lot of attention lately to how intestinal flora affects drug metabolism, and an increasing number of studies have revealed that intestinal flora is crucial for PK and pharmacodynamics. Intestinal flora can affect the metabolism and absorption of drugs by secreting abundant enzymes such as glycosidases and reductases, which in turn affect the efficacy of the drug. Liquiritin, liquiritigenin, glycyrrhizic acid, liquiritin apioside, paeoniflorin, oxypaeoniflora, and benzoylpaeoniflorin were typical herbal components that could be significantly metabolized by the intestinal flora [##UREF##3##30##, ##REF##30223050##31##]. For example, most of the glycyrrhizic acid would be converted to glycyrrhetinic acid in the intestine by the action of intestinal flora, thus continuing its medicinal effect. Liquiritin could be metabolized to liquiritigenin. Paeoniflorin could also be metabolized to albiflorin, albiflorinaglycone, and deacylate albiflorin [##UREF##4##32##]. SM prototypes also can alleviate inflammation by increasing absorption. Paeoniflorin [##UREF##5##33##], calycosin [##REF##27678042##34##], liquiritin [##REF##30785275##35##], liquiritigenin [##UREF##6##36##], and glycyrrhetinic acid [##REF##35668739##37##], for example, exhibit a wide spectrum of anti-inflammatory and immunomodulatory actions and have been found to be useful in the treatment of RA. These chemical components will continue to be targeted in subsequent studies.</p>", "<p id=\"Par26\">Previous research by our group demonstrated that WTD might improve intestinal flora dysbiosis and relieve the aberrant flora metabolite alterations caused by RA in AIA rats. Spearman correlation analysis revealed a close association between flora metabolites and intestinal flora. As a result, we hypothesized that a portion of the therapeutic impact of WTD on RA could be mediated by intestinal flora via modulation of the inflammatory response and intestinal barrier function. The integrity of the intestinal barrier is also linked to the development of inflammation and drug transfer [##UREF##7##38##].</p>", "<p id=\"Par27\">PS administration may modify the composition of intestinal flora in AIA rats, influencing SM absorption and metabolism. The association between SM absorption and gut flora was investigated by using Spearman correlation analysis. The differential flora impacted by the PS group was strongly linked with SM absorption, as shown in Fig. ##FIG##5##6##, with a total of 67 pairs had significant modifications. The drug absorption of liquiritin apioside, glycyrrhizic acid, oxypaeoniflorin, paeoniflorin, benzoylhypaconine, and songorine were negatively linked with Prevotella_2, meanwhile, whereas it exhibited a positive relationship with Oscillospira. Fuziline and methylephedrine exhibited a negatively correlation with Oscillospira and Bifidobacterium, while they were positively correlated with most of the differential flora. Furthermore, prior research had revealed that the intestinal barrier integrity of AIA rats has changed, and PS may also regulate the disruption of AIA rats' intestinal microbiota, repair the intestinal barrier of sick rats, and so affect SM absorption [##UREF##2##19##]. This could explain why the PK characteristics of the components in GC and BS had changed. Although polysaccharides cannot be absorbed into the bloodstream, they can influence the absorption and metabolism of small molecules by changing the gut bacteria, hence influencing medicinal efficacy. Products of microbiota metabolism can significantly mediate microbiota and host physiological function. Short-chain fatty acids (SCFAs), bile acids (BA), tryptophan metabolites and amino acids were important microbiota-associated metabolites that had immunomodulatory effects and were closely associated with RA disease progression [##REF##27711063##39##]. In our preceding metabolomics studies, kynurenic acid, xanthurenic acid, tyrosine and phenylalanine were potential biomarkers that were associated with RA and WTD treatment. The changes in the content of a series of metabolites such as SCFA, BA, tryptophan metabolites and amino acids were further determined by targeted assays [##REF##31762208##17##]. The results demonstrated that WTD can promote host health by alleviating metabolic disorders, reducing inflammation, modulating immune responses and maintaining intestinal barrier function. PS could affect the PK properties and absorption of pharmacodynamic substances in SM fraction in vivo. Hence, it was more logical to administer WTD as a combination of both PS and SM, which may result in improved pharmacodynamic effects.</p>", "<p id=\"Par28\">It is imperative to recognize a noteworthy constraint: Firstly, the results of the study were not sufficient to demonstrate the role of gut microbiota affected by PS or SM on WTD effect. Secondly, PS from WTD could affect the PK of some SM to a certain extent. However, no correlation was established between PD and these components based on their changes in this study. In future studies, in-depth research should be conducted in these aspects to elucidate the underlying mechanisms of WTD more comprehensively.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par29\">Drug metabolism and absorption are significantly influenced by intestinal flora, which has an effect on both drug toxicity and efficacy. In this study, the regulatory effects of WTD, SM, and PS fractions on the intestinal microbiota of AIA rats were clarified using 16S rRNA gene sequencing technology. WTD showed stronger efficiency than SM and PS in reducing RA-induced increased serum inflammatory factors, arthropathy, and intestinal flora problems.</p>", "<p id=\"Par30\">Furthermore, UPLC-MS/MS analysis was used to further evaluate how PS intervention affected the PK profiles of SM. The PK profiles of 13 potential pharmacodynamic substances were altered under the intervention of PS. The absorption of benzoylhypaconine, songorine, paeoniflorin, albiflorin, liquiritin apioside, oxypaeoniflorin, liquiritin, benzoylpaeoniflorin, isoliquiritigenin, and glycyrrhizic acid were increased, while the absorption of fuziline, formononetin, and methylephedrine were decreased. GC and BS were the main sources of the components with changed PK profiles. As a result, PS may modify the composition of the intestinal flora of AIA rats, impacting the metabolism and absorption of SM. This allowed the absorbed SM in circulation to exercise their effects, which may explain why the efficacy of WTD was superior than SM and PS alone. As a result, it has been confirmed that the TCM recipe is more effective when taken as a whole.</p>" ]
[ "<p id=\"Par1\">Wu-tou decoction (WTD), a traditional Chinese medicine prescription, is used to treat rheumatoid arthritis (RA). It works by controlling intestinal flora and its metabolites, which in turn modulates the inflammatory response and intestinal barrier function. Small molecular compounds (SM) and polysaccharides (PS) were the primary constituents of WTD extract. In this work, a model of adjuvant-induced arthritis (AIA) in rats was established and treated with WTD, SM, and PS, respectively. 16S rRNA gene sequencing was used to examine the regulatory impact of the various groups on the disturbance of the gut flora induced by RA. Further, since PS cannot be absorbed into the blood, the influence of PS on the absorption and metabolism of SM was studied by examining their pharmacokinetic (PK) parameters of 23 active components in SM by UPLC-MS/MS. WTD was found to be more effective than PS and SM in alleviating arthritis in AIA rats, which may be related to changes in gut flora. The PK properties of 13 active compounds were altered after PS intervene. Based on the findings, PS may be able to manage the disruption of intestinal microbiota, enhance the intestinal environment of model animals, and hence influence SM absorption and metabolism.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13020-024-00878-1.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Author contributions</title>", "<p>DY: Formal analysis, writing-original draft and validation; XC: Conceptualization, investigation and data curation; MF and DX: Validation and formal analysis; ZL, FZ and YD: Formal analysis and data curation. ZP and HY: Review and editing, supervision and funding acquisition.</p>", "<title>Funding</title>", "<p>This work was supported by the National Natural Science Foundation of China (82274216, 81774009).</p>", "<title>Availability of data and materials</title>", "<p>Data available on request from the authors. The data that support the findings of this study are available from the corresponding author, Zifeng Pi, upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par31\">This article is compliance with ethical standard.</p>", "<title>Consent for publication</title>", "<p id=\"Par32\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par33\">The authors declare that they have no known competing financial interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The levels of ankle swelling (<bold>A</bold>), levels of TNF-α and IL-6 in the serum of rats in each experimental group (<bold>B</bold>) and the pathological sections of the ankle joint of the right hind foot (<bold>C</bold>). Black arrow indicates inflammatory cell infiltration, and yellow arrow indicates bone and cartilage destruction and erosion. Results were expressed as mean ± SEM. <italic>P</italic> value was determined by one-way ANOVA with Dunnett’s<italic> post hoc</italic> test. Compared with model, *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001 (n = 6)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Modulatory effects of WTD, SM and PS on the composition of the intestinal flora. <bold>A</bold> PCoA analysis, <bold>B</bold> Average relative abundance of bacterial taxa at the phylum level, and <bold>C</bold> Relative abundance of bacterial taxa at the genus level</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>LEfSe analysis (<bold>A</bold> normal control (NC) vs model group (AIA), <bold>B</bold> AIA vs WTD group) and relative abundance of differential intestinal flora in each experimental group (<bold>C</bold>). Results were expressed as mean ± SEM. <italic>P</italic> value was determined by one-way ANOVA with Dunnett’s <italic>post hoc</italic> test. Compared with model, *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001 (n = 6)</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Representative MRM chromatograms of blank plasma, blank plasma containing standards and actual samples (0.25 h). Positive spectrum: <bold>A</bold>, <bold>B</bold> and <bold>C</bold>; negative spectrum: <bold>D</bold>, <bold>E</bold> and <bold>F</bold>. Positive spectrum: 1. Ephedrine, 2. Methylephedrine, 3. Songorine, 4. Fuziline, 5. Neoline, 6. Albiflorin, 7. Talatizamine, 8. Calycosin-7-glucoside, 9. Benzoylmesaconine, 10. Benzoylaconine, 11. Benzoylhypaconine, 12. Reserpine. Negative spectrum: 1. Oxypaeoniflora, 2. Paeoniflorin, 3. Liquiritin apioside, 4. Liquiritin, 5. Naringin, 6. Isoliquiritin, 7. Liquiritigenin, 8. Calycosin, 9. Benzoylpaeoniflorin, 10. Isoliquiritigenin, 11. Glycyrrhizic acid, 12. Formononetin, 13. Glycyrrhetinic acid</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Mean blood concentration–time profiles of 23 potential pharmacodynamic substances (MG: model group, MPS: model + polysaccharide group)</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Correlation analysis between gut flora and SM</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>MRM parameters for each compound and internal standard to be tested in the PK study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Compounds</th><th align=\"left\">Ion Mode</th><th align=\"left\">R<sub>t</sub> (min)</th><th align=\"left\">Precursor (m/z)</th><th align=\"left\">Product ion (m/z)</th><th align=\"left\">Q1 (V)</th><th align=\"left\">Collision energy (V)</th><th align=\"left\">Q3 (V)</th></tr></thead><tbody><tr><td align=\"left\">Ephedrine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">1.7</td><td char=\".\" align=\"char\">166.2</td><td char=\".\" align=\"char\">148.2</td><td align=\"left\">14</td><td align=\"left\">15</td><td align=\"left\">15</td></tr><tr><td align=\"left\">Methylephedrine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">1.9</td><td char=\".\" align=\"char\">180.1</td><td char=\".\" align=\"char\">162.2</td><td align=\"left\">11</td><td align=\"left\">15</td><td align=\"left\">30</td></tr><tr><td align=\"left\">Songorine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">1.9</td><td char=\".\" align=\"char\">358.1</td><td char=\".\" align=\"char\">340.1</td><td align=\"left\">20</td><td align=\"left\">30</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Fuziline</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">2.4</td><td char=\".\" align=\"char\">454.2</td><td char=\".\" align=\"char\">436.1</td><td align=\"left\">12</td><td align=\"left\">33</td><td align=\"left\">21</td></tr><tr><td align=\"left\">Neoline</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">2.6</td><td char=\".\" align=\"char\">438.2</td><td char=\".\" align=\"char\">420.2</td><td align=\"left\">10</td><td align=\"left\">30</td><td align=\"left\">21</td></tr><tr><td align=\"left\">Albiflorin</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">3.0</td><td char=\".\" align=\"char\">480.9</td><td char=\".\" align=\"char\">105.2</td><td align=\"left\">23</td><td align=\"left\">25</td><td align=\"left\">21</td></tr><tr><td align=\"left\">Talatizamine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">3.3</td><td char=\".\" align=\"char\">422.3</td><td char=\".\" align=\"char\">390.2</td><td align=\"left\">15</td><td align=\"left\">30</td><td align=\"left\">29</td></tr><tr><td align=\"left\">Calycosin-7-glucoside</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">4.2</td><td char=\".\" align=\"char\">446.9</td><td char=\".\" align=\"char\">285.1</td><td align=\"left\">21</td><td align=\"left\">21</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Benzoylmesaconine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">7.3</td><td char=\".\" align=\"char\">590.1</td><td char=\".\" align=\"char\">105.1</td><td align=\"left\">28</td><td align=\"left\">53</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Benzoylaconine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">8.3</td><td char=\".\" align=\"char\">604.4</td><td char=\".\" align=\"char\">105.0</td><td align=\"left\">22</td><td align=\"left\">54</td><td align=\"left\">19</td></tr><tr><td align=\"left\">Benzoylhypaconine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">8.9</td><td char=\".\" align=\"char\">574.2</td><td char=\".\" align=\"char\">542.2</td><td align=\"left\">20</td><td align=\"left\">36</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Reserpine</td><td align=\"left\"> + </td><td char=\".\" align=\"char\">10.1</td><td char=\".\" align=\"char\">609.3</td><td char=\".\" align=\"char\">195.1</td><td align=\"left\">22</td><td align=\"left\">37</td><td align=\"left\">21</td></tr><tr><td align=\"left\">Oxypaeoniflorin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">1.7</td><td char=\".\" align=\"char\">495.1</td><td char=\".\" align=\"char\">137.2</td><td align=\"left\">23</td><td align=\"left\">30</td><td align=\"left\">12</td></tr><tr><td align=\"left\">Paeoniflorin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">2.6</td><td char=\".\" align=\"char\">479.1</td><td char=\".\" align=\"char\">448.9</td><td align=\"left\">23</td><td align=\"left\">10</td><td align=\"left\">22</td></tr><tr><td align=\"left\">Liquiritin apioside</td><td align=\"left\">−</td><td char=\".\" align=\"char\">2.9</td><td char=\".\" align=\"char\">549.3</td><td char=\".\" align=\"char\">255.2</td><td align=\"left\">24</td><td align=\"left\">32</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Liquiritin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">3.0</td><td char=\".\" align=\"char\">417.2</td><td char=\".\" align=\"char\">255.1</td><td align=\"left\">18</td><td align=\"left\">22</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Naringin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">3.3</td><td char=\".\" align=\"char\">579.3</td><td char=\".\" align=\"char\">271.1</td><td align=\"left\">24</td><td align=\"left\">35</td><td align=\"left\">17</td></tr><tr><td align=\"left\">Isoliquiritin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">3.8</td><td char=\".\" align=\"char\">417.2</td><td char=\".\" align=\"char\">255.1</td><td align=\"left\">18</td><td align=\"left\">19</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Liquiritigenin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">4.3</td><td char=\".\" align=\"char\">255.2</td><td char=\".\" align=\"char\">119.1</td><td align=\"left\">12</td><td align=\"left\">24</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Calycosin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">4.5</td><td char=\".\" align=\"char\">283.1</td><td char=\".\" align=\"char\">211.2</td><td align=\"left\">29</td><td align=\"left\">34</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Benzoylpaeoniflorin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">4.9</td><td char=\".\" align=\"char\">583.1</td><td char=\".\" align=\"char\">431.0</td><td align=\"left\">40</td><td align=\"left\">17</td><td align=\"left\">19</td></tr><tr><td align=\"left\">Isoliquiritigenin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">5.8</td><td char=\".\" align=\"char\">255.3</td><td char=\".\" align=\"char\">119.1</td><td align=\"left\">16</td><td align=\"left\">24</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Glycyrrhizic acid</td><td align=\"left\">−</td><td char=\".\" align=\"char\">5.9</td><td char=\".\" align=\"char\">821.6</td><td char=\".\" align=\"char\">351.0</td><td align=\"left\">20</td><td align=\"left\">40</td><td align=\"left\">11</td></tr><tr><td align=\"left\">Formononetin</td><td align=\"left\">−</td><td char=\".\" align=\"char\">6.0</td><td char=\".\" align=\"char\">267.0</td><td char=\".\" align=\"char\">223.2</td><td align=\"left\">13</td><td align=\"left\">32</td><td align=\"left\">21</td></tr><tr><td align=\"left\">Glycyrrhetinic acid</td><td align=\"left\">−</td><td char=\".\" align=\"char\">9.1</td><td char=\".\" align=\"char\">469.5</td><td char=\".\" align=\"char\">425.4</td><td align=\"left\">12</td><td align=\"left\">40</td><td align=\"left\">20</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Standard curves and linear ranges for each compound to be tested in PK studies</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Analytes</th><th align=\"left\">Calibration curve</th><th align=\"left\">r<sup>2</sup></th><th align=\"left\">Linear range (ng/mL)</th></tr></thead><tbody><tr><td align=\"left\">Ephedrine</td><td char=\".\" align=\"char\">y = 0.8825x + 3.7555</td><td char=\".\" align=\"char\">0.9928</td><td align=\"left\">10–1000</td></tr><tr><td align=\"left\">Methylephedrine</td><td char=\".\" align=\"char\">y = 1.5091x + 0.0095</td><td char=\".\" align=\"char\">0.9945</td><td align=\"left\">0.1–25</td></tr><tr><td align=\"left\">Songorine</td><td char=\".\" align=\"char\">y = 2.1609x-0.0359</td><td char=\".\" align=\"char\">0.9905</td><td align=\"left\">0.1–50</td></tr><tr><td align=\"left\">Fuziline</td><td char=\".\" align=\"char\">y = 1.4974x-0.0152</td><td char=\".\" align=\"char\">0.9915</td><td align=\"left\">0.1–25</td></tr><tr><td align=\"left\">Neoline</td><td char=\".\" align=\"char\">y = 0.4646x-0.0020</td><td char=\".\" align=\"char\">0.9923</td><td align=\"left\">0.1–50</td></tr><tr><td align=\"left\">Albiflorin</td><td char=\".\" align=\"char\">y = 0.1032x + 0.0452</td><td char=\".\" align=\"char\">0.9916</td><td align=\"left\">5–500</td></tr><tr><td align=\"left\">Talatizamine</td><td char=\".\" align=\"char\">y = 1.9382x-0.0038</td><td char=\".\" align=\"char\">0.9928</td><td align=\"left\">0.1–50</td></tr><tr><td align=\"left\">Calycosin-7-glucoside</td><td char=\".\" align=\"char\">y = 0.1515x-0.0034</td><td char=\".\" align=\"char\">0.9936</td><td align=\"left\">0.1–100</td></tr><tr><td align=\"left\">Benzoylmesaconine</td><td char=\".\" align=\"char\">y = 1.0726x-0.0059</td><td char=\".\" align=\"char\">0.9929</td><td align=\"left\">0.1–100</td></tr><tr><td align=\"left\">Benzoylaconine</td><td char=\".\" align=\"char\">y = 0.7982x + 0.0047</td><td char=\".\" align=\"char\">0.9962</td><td align=\"left\">0.05–10</td></tr><tr><td align=\"left\">Benzoylhypaconine</td><td char=\".\" align=\"char\">y = 1.5379x-0.0135</td><td char=\".\" align=\"char\">0.9973</td><td align=\"left\">0.1–10</td></tr><tr><td align=\"left\">Oxypaeoniflorin</td><td char=\".\" align=\"char\">y = 0.9149x-0.0075</td><td char=\".\" align=\"char\">0.9995</td><td align=\"left\">0.5–50</td></tr><tr><td align=\"left\">Paeoniflorin</td><td char=\".\" align=\"char\">y = 0.0324x + 0.0288</td><td char=\".\" align=\"char\">0.9938</td><td align=\"left\">2.5–2500</td></tr><tr><td align=\"left\">Liquiritin apioside</td><td char=\".\" align=\"char\">y = 2.8756x-0.1369</td><td char=\".\" align=\"char\">0.9985</td><td align=\"left\">1–2500</td></tr><tr><td align=\"left\">Liquiritin</td><td char=\".\" align=\"char\">y = 4.1916x + 0.1199</td><td char=\".\" align=\"char\">0.9961</td><td align=\"left\">1–500</td></tr><tr><td align=\"left\">Isoliquiritin</td><td char=\".\" align=\"char\">y = 3.6659x-0.0129</td><td char=\".\" align=\"char\">0.9999</td><td align=\"left\">0.5–50</td></tr><tr><td align=\"left\">Liquiritigenin</td><td char=\".\" align=\"char\">y = 2.9112x + 0.0522</td><td char=\".\" align=\"char\">0.9990</td><td align=\"left\">0.5–100</td></tr><tr><td align=\"left\">Calycosin</td><td char=\".\" align=\"char\">y = 9.7214x-0.0172</td><td char=\".\" align=\"char\">0.9958</td><td align=\"left\">0.1–25</td></tr><tr><td align=\"left\">Benzoylpaeoniflorin</td><td char=\".\" align=\"char\">y = 0.0862x-0.0007</td><td char=\".\" align=\"char\">0.9992</td><td align=\"left\">1–50</td></tr><tr><td align=\"left\">Isoliquiritigenin</td><td char=\".\" align=\"char\">y = 6.5489x-0.0406</td><td char=\".\" align=\"char\">0.9993</td><td align=\"left\">0.5–50</td></tr><tr><td align=\"left\">Glycyrrhizic acid</td><td char=\".\" align=\"char\">y = 0.6790x-0.3716</td><td char=\".\" align=\"char\">0.9982</td><td align=\"left\">100–10000</td></tr><tr><td align=\"left\">Formononetin</td><td char=\".\" align=\"char\">y = 13.0676x + 0.0165</td><td char=\".\" align=\"char\">0.9974</td><td align=\"left\">0.5–50</td></tr><tr><td align=\"left\">Glycyrrhetinic acid</td><td char=\".\" align=\"char\">y = 3.2768x + 0.3358</td><td char=\".\" align=\"char\">0.9948</td><td align=\"left\">100–20000</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>PK parameters of 23 potential pharmacodynamic substances in the MG and MPS groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Component name</th><th align=\"left\">Group</th><th align=\"left\">t <sub>1/2</sub>(h)</th><th align=\"left\">T <sub>max</sub>(h)</th><th align=\"left\">C <sub>max</sub>(ng/mL)</th><th align=\"left\">AUC <sub>0-t</sub>(ng/ml*h)</th><th align=\"left\">AUC <sub>0-∞</sub>(ng/ml*h)</th><th align=\"left\">Source</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Benzoylaconine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">7.430 ± 5.148</td><td char=\".\" align=\"char\">0.125 ± 0.072</td><td char=\".\" align=\"char\">0.548 ± 0.178</td><td char=\".\" align=\"char\">0.764 ± 0.082</td><td char=\".\" align=\"char\">1.015 ± 0.158</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.875 ± 1.842</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">0.720 ± 0.116</td><td char=\".\" align=\"char\">1.064 ± 0.136</td><td char=\".\" align=\"char\">1.202 ± 0.128</td></tr><tr><td align=\"left\" rowspan=\"2\">Benzoylmesaconitine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.530 ± 0.873</td><td char=\".\" align=\"char\">0.139 ± 0.079</td><td char=\".\" align=\"char\">14.305 ± 3.689</td><td char=\".\" align=\"char\">21.413 ± 1.140</td><td char=\".\" align=\"char\">23.447 ± 1.422</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">1.723 ± 0.296</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">15.899 ± 4.818</td><td char=\".\" align=\"char\">25.368 ± 7.147</td><td char=\".\" align=\"char\">25.465 ± 7.145</td></tr><tr><td align=\"left\" rowspan=\"2\">Benzoylhypaconine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.938 ± 0.322</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">0.467 ± 0.108</td><td char=\".\" align=\"char\">1.018 ± 0.049</td><td char=\".\" align=\"char\">1.123 ± 0.062</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">4.742 ± 0.904</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">0.861 ± 0.160*</td><td char=\".\" align=\"char\">1.394 ± 0.255</td><td char=\".\" align=\"char\">1.604 ± 0.229*</td></tr><tr><td align=\"left\" rowspan=\"2\">Talatizamine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">6.242 ± 1.838</td><td char=\".\" align=\"char\">0.417 ± 0.276</td><td char=\".\" align=\"char\">3.376 ± 0.595</td><td char=\".\" align=\"char\">21.996 ± 1.581</td><td char=\".\" align=\"char\">30.766 ± 4.871</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">5.163 ± 1.483</td><td char=\".\" align=\"char\">0.292 ± 0.093</td><td char=\".\" align=\"char\">3.576 ± 0.320</td><td char=\".\" align=\"char\">22.338 ± 1.786</td><td char=\".\" align=\"char\">28.106 ± 2.545</td></tr><tr><td align=\"left\" rowspan=\"2\">Neoline</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.245 ± 0.999</td><td char=\".\" align=\"char\">0.333 ± 0.118</td><td char=\".\" align=\"char\">3.221 ± 1.040</td><td char=\".\" align=\"char\">7.417 ± 0.718</td><td char=\".\" align=\"char\">8.058 ± 0.838</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">2.486 ± 0.349</td><td char=\".\" align=\"char\">0.250 ± 0.001</td><td char=\".\" align=\"char\">3.695 ± 1.005</td><td char=\".\" align=\"char\">7.559 ± 0.880</td><td char=\".\" align=\"char\">7.980 ± 0.757</td></tr><tr><td align=\"left\" rowspan=\"2\">Songorine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">2.638 ± 0.461</td><td char=\".\" align=\"char\">0.667 ± 0.236</td><td char=\".\" align=\"char\">13.961 ± 2.318</td><td char=\".\" align=\"char\">60.186 ± 6.505</td><td char=\".\" align=\"char\">64.576 ± 6.039</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">2.522 ± 0.269</td><td char=\".\" align=\"char\">0.917 ± 0.773</td><td char=\".\" align=\"char\">17.665 ± 1.910</td><td char=\".\" align=\"char\">80.730 ± 5.544*</td><td char=\".\" align=\"char\">84.255 ± 5.364*</td></tr><tr><td align=\"left\" rowspan=\"2\">Fuziline</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.235 ± 0.929</td><td char=\".\" align=\"char\">0.250 ± 0.001</td><td char=\".\" align=\"char\">1.396 ± 0.100</td><td char=\".\" align=\"char\">3.636 ± 0.369</td><td char=\".\" align=\"char\">3.938 ± 0.411</td><td align=\"left\" rowspan=\"2\">ZCW</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.196 ± 0.607</td><td char=\".\" align=\"char\">0.375 ± 0.125</td><td char=\".\" align=\"char\">1.032 ± 0.122*</td><td char=\".\" align=\"char\">3.590 ± 0.513</td><td char=\".\" align=\"char\">3.917 ± 0.539</td></tr><tr><td align=\"left\" rowspan=\"2\">Ephedrine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">1.852 ± 0.273</td><td char=\".\" align=\"char\">0.250 ± 0.001</td><td char=\".\" align=\"char\">673.726 ± 137.169</td><td char=\".\" align=\"char\">1721.094 ± 96.813</td><td char=\".\" align=\"char\">1746.650 ± 93.580</td><td align=\"left\" rowspan=\"2\">MH</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">1.736 ± 0.108</td><td char=\".\" align=\"char\">0.333 ± 0.118</td><td char=\".\" align=\"char\">661.523 ± 149.062</td><td char=\".\" align=\"char\">1559.029 ± 227.025</td><td char=\".\" align=\"char\">1575.759 ± 228.293</td></tr><tr><td align=\"left\" rowspan=\"2\">Methylephedrine</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">4.131 ± 1.363</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">14.012 ± 2.615</td><td char=\".\" align=\"char\">27.900 ± 4.829</td><td char=\".\" align=\"char\">30.265 ± 3.815</td><td align=\"left\" rowspan=\"2\">MH</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">4.331 ± 0.765</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">12.523 ± 3.287</td><td char=\".\" align=\"char\">16.109 ± 2.770*</td><td char=\".\" align=\"char\">18.607 ± 4.409*</td></tr><tr><td align=\"left\" rowspan=\"2\">Albiflorin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">2.488 ± 0.458</td><td char=\".\" align=\"char\">0.250 ± 0.001</td><td char=\".\" align=\"char\">287.831 ± 42.177</td><td char=\".\" align=\"char\">424.990 ± 55.691</td><td char=\".\" align=\"char\">458.506 ± 69.994</td><td align=\"left\" rowspan=\"2\">BS</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">1.669 ± 0.080</td><td char=\".\" align=\"char\">0.139 ± 0.072</td><td char=\".\" align=\"char\">306.851 ± 57.880</td><td char=\".\" align=\"char\">644.268 ± 174.084*</td><td char=\".\" align=\"char\">698.946 ± 175.788*</td></tr><tr><td align=\"left\" rowspan=\"2\">Paeoniflorin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">2.132 ± 0.102</td><td char=\".\" align=\"char\">0.438 ± 0.108</td><td char=\".\" align=\"char\">1924.153 ± 225.157</td><td char=\".\" align=\"char\">2541.326 ± 95.887</td><td char=\".\" align=\"char\">2455.492 ± 223.257</td><td align=\"left\" rowspan=\"2\">BS</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">1.992 ± 0.126</td><td char=\".\" align=\"char\">0.396 ± 0.180</td><td char=\".\" align=\"char\">2063.985 ± 352.472</td><td char=\".\" align=\"char\">2870.390 ± 71.706**</td><td char=\".\" align=\"char\">2904.597 ± 68.691*</td></tr><tr><td align=\"left\" rowspan=\"2\">Oxypaeoniflorin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.408 ± 0.586</td><td char=\".\" align=\"char\">0.437 ± 0.110</td><td char=\".\" align=\"char\">28.569 ± 0.784</td><td char=\".\" align=\"char\">61.034 ± 2.601</td><td char=\".\" align=\"char\">67.007 ± 3.218</td><td align=\"left\" rowspan=\"2\">BS</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.399 ± 0.306</td><td char=\".\" align=\"char\">0.458 ± 0.093</td><td char=\".\" align=\"char\">31.514 ± 0.848*</td><td char=\".\" align=\"char\">70.355 ± 1.558*</td><td char=\".\" align=\"char\">75.327 ± 2.198*</td></tr><tr><td align=\"left\" rowspan=\"2\">Benzoylpaeoniflorin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.588 ± 0.489</td><td char=\".\" align=\"char\">0.139 ± 0.079</td><td char=\".\" align=\"char\">14.781 ± 2.659</td><td char=\".\" align=\"char\">27.904 ± 5.404</td><td char=\".\" align=\"char\">30.566 ± 6.082</td><td align=\"left\" rowspan=\"2\">BS</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">6.957 ± 2.271</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">24.334 ± 3.995*</td><td char=\".\" align=\"char\">31.559 ± 6.741</td><td char=\".\" align=\"char\">37.891 ± 9.822</td></tr><tr><td align=\"left\" rowspan=\"2\">Formononetin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">4.271 ± 0.406</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">7.387 ± 1.162</td><td char=\".\" align=\"char\">15.278 ± 1.823</td><td char=\".\" align=\"char\">17.533 ± 1.685</td><td align=\"left\" rowspan=\"2\">HQ</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.756 ± 0.557</td><td char=\".\" align=\"char\">0.250 ± 0.001</td><td char=\".\" align=\"char\">4.499 ± 0.902*</td><td char=\".\" align=\"char\">12.291 ± 1.983</td><td char=\".\" align=\"char\">13.592 ± 1.930</td></tr><tr><td align=\"left\" rowspan=\"2\">Calycosin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">4.942 ± 0.315</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">8.479 ± 2.434</td><td char=\".\" align=\"char\">12.296 ± 1.063</td><td char=\".\" align=\"char\">14.276 ± 1.185</td><td align=\"left\" rowspan=\"2\">HQ</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.531 ± 0.666</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">6.610 ± 1.443</td><td char=\".\" align=\"char\">12.353 ± 0.972</td><td char=\".\" align=\"char\">13.577 ± 0.642</td></tr><tr><td align=\"left\" rowspan=\"2\">Calycosin-7-glycoside</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">2.342 ± 0.959</td><td char=\".\" align=\"char\">0.110 ± 0.062</td><td char=\".\" align=\"char\">17.607 ± 2.640</td><td char=\".\" align=\"char\">17.473 ± 2.858</td><td char=\".\" align=\"char\">18.097 ± 2.629</td><td align=\"left\" rowspan=\"2\">HQ</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">2.113 ± 0.779</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">15.506 ± 2.308</td><td char=\".\" align=\"char\">15.987 ± 2.778</td><td char=\".\" align=\"char\">16.625 ± 2.476</td></tr><tr><td align=\"left\" rowspan=\"2\">Liquiritin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">2.089 ± 0.132</td><td char=\".\" align=\"char\">0.167 ± 0.083</td><td char=\".\" align=\"char\">125.917 ± 18.484</td><td char=\".\" align=\"char\">300.440 ± 52.811</td><td char=\".\" align=\"char\">306.988 ± 53.933</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.301 ± 0.429</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">190.023 ± 19.153*</td><td char=\".\" align=\"char\">321.663 ± 49.723</td><td char=\".\" align=\"char\">339.781 ± 52.584</td></tr><tr><td align=\"left\" rowspan=\"2\">Isoliquiritin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">5.850 ± 2.022</td><td char=\".\" align=\"char\">0.194 ± 0.079</td><td char=\".\" align=\"char\">13.586 ± 1.061</td><td char=\".\" align=\"char\">23.305 ± 0.956</td><td char=\".\" align=\"char\">30.845 ± 2.926</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">7.608 ± 1.853</td><td char=\".\" align=\"char\">0.111 ± 0.062</td><td char=\".\" align=\"char\">14.210 ± 1.547</td><td char=\".\" align=\"char\">21.893 ± 1.756</td><td char=\".\" align=\"char\">33.055 ± 3.187</td></tr><tr><td align=\"left\" rowspan=\"2\">Liquiritigenin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">1.841 ± 0.242</td><td char=\".\" align=\"char\">0.139 ± 0.079</td><td char=\".\" align=\"char\">25.519 ± 7.560</td><td char=\".\" align=\"char\">48.549 ± 6.497</td><td char=\".\" align=\"char\">49.404 ± 6.315</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">1.448 ± 0.025</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">23.367 ± 4.695</td><td char=\".\" align=\"char\">47.195 ± 4.360</td><td char=\".\" align=\"char\">47.548 ± 4.374</td></tr><tr><td align=\"left\" rowspan=\"2\">Isoliquiritigenin</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">3.117 ± 0.571</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">4.003 ± 0.545</td><td char=\".\" align=\"char\">8.764 ± 1.421</td><td char=\".\" align=\"char\">9.614 ± 1.601</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">3.871 ± 0.889</td><td char=\".\" align=\"char\">0.167 ± 0.083</td><td char=\".\" align=\"char\">5.421 ± 0.422*</td><td char=\".\" align=\"char\">9.467 ± 1.445</td><td char=\".\" align=\"char\">10.514 ± 1.272</td></tr><tr><td align=\"left\" rowspan=\"2\">Glycyrrhizic acid</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">7.605 ± 1.142</td><td char=\".\" align=\"char\">0.500 ± 0.001</td><td char=\".\" align=\"char\">3796.250 ± 303.817</td><td char=\".\" align=\"char\">23,076.672 ± 1971.518</td><td char=\".\" align=\"char\">25,908.272 ± 2650.703</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">7.254 ± 0.086</td><td char=\".\" align=\"char\">0.667 ± 0.236</td><td char=\".\" align=\"char\">5196.097 ± 705.783*</td><td char=\".\" align=\"char\">29,642.523 ± 2974.308</td><td char=\".\" align=\"char\">27,449.610 ± 2279.134</td></tr><tr><td align=\"left\" rowspan=\"2\">Glycyrrhetinic acid</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">10.666 ± 3.723</td><td char=\".\" align=\"char\">2.000 ± 0.001</td><td char=\".\" align=\"char\">7828.313 ± 282.922</td><td char=\".\" align=\"char\">28,800.324 ± 986.106</td><td char=\".\" align=\"char\">32,851.097 ± 2465.278</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">10.750 ± 1.956</td><td char=\".\" align=\"char\">2.000 ± 0.001</td><td char=\".\" align=\"char\">11,572.293 ± 3757.206</td><td char=\".\" align=\"char\">30,512.597 ± 6563.268</td><td char=\".\" align=\"char\">34,507.972 ± 6423.101</td></tr><tr><td align=\"left\" rowspan=\"2\">Liquiritin apioside</td><td align=\"left\">MG</td><td char=\".\" align=\"char\">4.060 ± 0.589</td><td char=\".\" align=\"char\">0.250 ± 0.001</td><td char=\".\" align=\"char\">571.677 ± 49.414</td><td char=\".\" align=\"char\">941.302 ± 42.085</td><td char=\".\" align=\"char\">1053.558 ± 63.193</td><td align=\"left\" rowspan=\"2\">GC</td></tr><tr><td align=\"left\">MPS</td><td char=\".\" align=\"char\">2.969 ± 0.328</td><td char=\".\" align=\"char\">0.083 ± 0.001</td><td char=\".\" align=\"char\">850.691 ± 179.709</td><td char=\".\" align=\"char\">1580.263 ± 242.037*</td><td char=\".\" align=\"char\">1669.308 ± 244.694*</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup><italic>*</italic></sup><italic>p</italic> &lt; <italic>0.05, **p &lt; 0.01, compared with the MG group</italic></p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Di Yang and Xiaoxu Cheng have contributed equally to this paper.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13020_2024_878_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13020_2024_878_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"13020_2024_878_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"13020_2024_878_Fig4_HTML\" id=\"MO4\"/>", "<graphic xlink:href=\"13020_2024_878_Fig5_HTML\" id=\"MO5\"/>", "<graphic xlink:href=\"13020_2024_878_Fig6_HTML\" id=\"MO6\"/>" ]
[ "<media xlink:href=\"13020_2024_878_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Table S1.</bold> WTD extractions yield and Polysaccharide content. <bold>Table S2.</bold> Mass spectral data of compounds in SM and PS. <bold>Figure S1.</bold> Mass spectra of WTD, SM, and PS. (A, C, D were positive spectra for WTD, SM, and PS. B, D, F were negative spectra for WTD, SM, and PS.).</p></caption></media>" ]
[{"label": ["6."], "surname": ["Gong", "Li", "Bo", "Shi", "Li", "Lei"], "given-names": ["X", "X", "A", "RY", "QY", "LJ"], "article-title": ["The interactions between gut microbiota and bioactive ingredients of traditional Chinese medicines: a review"], "source": ["Pharmacol Res"], "year": ["2020"], "volume": ["157"], "issue": ["104824"], "fpage": ["25"]}, {"label": ["18."], "surname": ["Cheng", "Lu", "Fan", "Pi", "Zheng", "Liu"], "given-names": ["X", "E", "M", "Z", "Z", "S"], "article-title": ["A comprehensive strategy to clarify the pharmacodynamic constituents and mechanism of Wu-tou decoction based on the constituents migrating to blood and their in vivo process under pathological state"], "source": ["J Ethnopharmacol"], "year": ["2021"], "volume": ["275"], "issue": ["114172"], "fpage": ["28"]}, {"label": ["19."], "surname": ["Cheng", "Pi", "Zheng", "Liu", "Song", "Liu"], "given-names": ["X", "Z", "Z", "S", "F", "Z"], "article-title": ["Combined 16S rRNA gene sequencing and metabolomics to investigate the protective effects of Wu-tou decoction on rheumatoid arthritis in rats"], "source": ["J Chromatogr B Analyt Technol Biomed Life Sci"], "year": ["2022"], "volume": ["30"], "issue": ["123249"], "fpage": ["12"]}, {"label": ["30."], "surname": ["Hattori", "Shu", "Shimizu", "Hayashi", "Morita", "Kobashi"], "given-names": ["M", "YZ", "M", "T", "N", "K"], "article-title": ["Metabolism of paeoniflorin and related compounds by human intestinal bacteria"], "source": ["Chem Pharm Bull"], "year": ["1985"], "volume": ["33"], "issue": ["9"], "fpage": ["3838"], "lpage": ["3846"], "pub-id": ["10.1248/cpb.33.3838"]}, {"label": ["32."], "surname": ["Ke", "Yang", "Hou", "Wang", "Feng", "Jia"], "given-names": ["ZC", "N", "XF", "AD", "L", "XB"], "article-title": ["Metabolism of paeoniflorin by rat intestinal flora in vitro"], "source": ["Chin J Chin Mater Med"], "year": ["2016"], "volume": ["41"], "fpage": ["3839"], "lpage": ["3845"]}, {"label": ["33."], "surname": ["Zhang", "Wei"], "given-names": ["L", "W"], "article-title": ["Anti-inflammatory and immunoregulatory effects of paeoniflorin and total glucosides of paeony"], "source": ["Pharmacol Therapeut"], "year": ["2020"], "pub-id": ["10.1016/j.pharmthera.2019.107452"]}, {"label": ["36."], "surname": ["Ning", "Ni", "Cao", "Zhang"], "given-names": ["X", "Y", "J", "H"], "article-title": ["Liquiritigenin attenuated collagen-induced arthritis and cardiac complication via inflammation and fibrosis inhibition in mice"], "source": ["Chem Pharm Bull"], "year": ["2023"], "volume": ["71"], "issue": ["4"], "fpage": ["269"], "lpage": ["276"], "pub-id": ["10.1248/cpb.c22-00684"]}, {"label": ["38."], "surname": ["Horowitz", "Chanez-Paredes", "Haest", "Turner"], "given-names": ["A", "SD", "X", "JR"], "article-title": ["Paracellular permeability and tight junction regulation in gut health and disease"], "source": ["Nat Rev Gastro Hepat"], "year": ["2023"], "volume": ["20"], "issue": ["7"], "fpage": ["417"], "lpage": ["432"], "pub-id": ["10.1038/s41575-023-00766-3"]}]
{ "acronym": [], "definition": [] }
39
CC BY
no
2024-01-14 23:43:45
Chin Med. 2024 Jan 13; 19:9
oa_package/27/d2/PMC10787407.tar.gz
PMC10787408
38216875
[ "<title>Background</title>", "<p id=\"Par7\">Human papillomavirus (HPV) is one of the most prevalent sexually transmitted diseases (STDs) worldwide [##REF##30207593##1##]. While most HPV infections are cleared spontaneously with the natural immune response, part of this infection persists, which can lead to malignant disease [##REF##25493236##2##]. Persistent oncogenic HPV infections are responsible for cervical and anal cancers due to structural changes in DNA [##REF##31500479##3##, ##REF##33397387##4##]. Cervical cancer is the fourth most common female cancer in women aged 15 to 44 years worldwide [##REF##36839570##5##]. Globally, more than 95% of cervical cancers and more than 300,000 deaths per year occur due to HPV infection [##REF##33538338##6##, ##UREF##0##7##]. About 341,831 new cervical cancer cases are diagnosed annually in the world and the global mortality rate among women is reported 13.3/100,000 in 2020 [##UREF##1##8##]. Decreasing the incidence of HPV infections and associated carcinogenicity is possible by understanding the factors contributing to the occurrence and persistence of the infection [##UREF##2##9##].</p>", "<p id=\"Par8\">In previous studies, the relationship between HPV and some vitamins including vitamin D has been assessed [##REF##33182663##10##, ##REF##28486774##11##]. It is emphasized that vitamin D, in addition to its essential role in maintaining calcium and phosphorus homeostasis and bone health [##REF##35408981##12##], contains antiviral and immunomodulatory effects, and plays a key role in the modulation of the immunological response in infectious diseases [##REF##35408981##12##, ##REF##28733125##13##]. The maturation of macrophages, function regulation, and proliferation of lymphocytes are attributed to this vitamin [##REF##21896008##14##]. Indeed, sufficient vitamin D levels protect against some infectious diseases, while non-optimal levels of this vitamin are associated with an increased risk of incidence and severity of the disease [##REF##32503801##15##, ##UREF##3##16##]. The effectiveness of vitamin D in the successful treatment of viral hepatitis, respiratory infections, and Herpes virus, is confirmed [##REF##30614127##17##]. These findings are related to the role of vitamin D in strengthening innate and acquired immunity against infection [##REF##26404359##18##].</p>", "<p id=\"Par9\">Although there is progressive evidence suggesting that vitamin D has an important role in the immune system- boosting [##REF##28733125##13##, ##REF##21896008##14##, ##UREF##3##16##, ##REF##19491064##19##], and immune response is thought to have a critical role in preventing and treating HPV infection, no conclusive evidence is available regarding serum levels of vitamin D in patients with HPV infection. Some previous studies reported lower levels of vitamin D in patients with HPV [##REF##26908722##20##–##UREF##4##22##], while some other studies observed inconsistent findings [##REF##25411259##23##, ##UREF##5##24##]. Considering these incompatible reports, the present review aimed to investigate the relationship between cervicovaginal HPV infection and vitamin D serum levels to compile evidence on the topic. Understanding this relationship may ultimately contribute to more effective strategies for preventing HPV-related diseases and improving overall public health.</p>" ]
[ "<title>Methods</title>", "<title>Design</title>", "<p id=\"Par10\">This was a systematic review of the literature. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline was followed [##UREF##6##25##].</p>", "<title>Search strategy</title>", "<p id=\"Par11\">Electronic databases including Web of Science, Embase, Scopus, and PubMed were searched. In order to maximize the search comprehensiveness, general keywords including human papillomavirus, vitamin D, 25-hydroxyvitamin D, cholecalciferol, as well as standardized keywords of Emtree and Mesh including papillomavirus infections, Alphapapillomavirus, Human papillomavirus, vitamin D cholecalciferol, and their combination were used through relevant operators (such as AND, and OR). Furthermore, the references of the assessed papers were reviewed manually. The final keywords were reviewed by the research supervisor. An example of the PubMed search query is shown in Table ##TAB##0##1##.</p>", "<title>Selection criteria</title>", "<p id=\"Par12\">Observational studies (cohort, case‑control, and cross‑sectional) published in English that assessed the relationship between HPV infection and vitamin D status in women included until December 24, 2022. The articles were selected based on the inclusion and exclusion criteria, with no restrictions regarding the start date for article inclusion. Review studies, letters to editors, conference papers, non-English articles, and those with unavailable full texts excluded.</p>", "<title>Study selection process</title>", "<p id=\"Par13\">The title, abstract, and full text of articles were reviewed by two authors independently. In the case of meeting the inclusion criteria, the article was included for the quality assessment and data extraction, and in case of disagreement, the third author was consulted.</p>", "<title>Data extraction</title>", "<p id=\"Par14\">Data extraction was done based on a checklist, which included the first author’s name and year of publication, country, study design, sample size, and participants, as well as the most important findings.</p>", "<title>Quality assessment</title>", "<p id=\"Par15\">Two reviewers independently assessed the quality of the selected articles based on the Newcastle-Ottawa Scale (Newcastle-Ottawa cohort scale version and its modified version for cross-sectional studies) [##UREF##7##26##]. This Scale 3 domains (selection, comparability, and outcome. For case control studies instead of outcome the domain is exposure). The maximum quality score for each type of studies is 9. Studies with a score of 7-9, are considered as high quality, 4-6 as high risk, and 0-3 as very high risk of bias. For cohort studies, a score of 6 or higher is considered as low risk and good quality, and a score of &lt;6 is considered as high risk and low quality [##UREF##8##27##]. Disagreements between the two reviewers were resolved by discussion with the research supervisor. The result of quality assessment of the selected articles is shown in Table ##TAB##1##2##.</p>" ]
[ "<title>Results</title>", "<p id=\"Par16\">In all, 276 citations were identified (Embase=62, Web of Science=48, Scopus=82, PubMed=84). After reviewing the title, duplicate cases were removed (<italic>n</italic>=161). The remaining citations were assessed through the abstract and full text of the papers considering inclusion and exclusion criteria and an additional 108 irrelevant articles were excluded. Eventually, 7 full-text articles satisfied the inclusion criteria. The flow diagram of the review is shown in Fig ##FIG##0##1##.</p>", "<p id=\"Par17\">The first article on the relationship between HPV and vitamin D was published in 2015 [##REF##25411259##23##]. In all studies, vitamin D was assessed by measuring serum 25-hydroxyvitamin D levels [##REF##26908722##20##, ##REF##28471122##21##, ##REF##25411259##23##, ##UREF##5##24##, ##REF##34747902##28##–##REF##32317302##30##]. Furthermore, 4 emerging biomarkers, (1,25(OH)2D; 24,25(OH)2D; free vitamin D; and vitamin D binding protein) were measured in two studies [##REF##33205195##29##, ##REF##32317302##30##]. One study assessed the short-term persistence of high-risk HPV [##REF##33205195##29##], while other studies investigated transient or sporadic detection of high-risk HPV [##REF##26908722##20##, ##REF##28471122##21##, ##REF##25411259##23##, ##UREF##5##24##, ##REF##34747902##28##, ##REF##32317302##30##]. The HPV DNA testing was followed by self-collection cervicovaginal swab specimens [##REF##26908722##20##, ##UREF##5##24##, ##REF##33205195##29##, ##REF##32317302##30##]; cervical sample and colposcopic investigations [##REF##28471122##21##]; Pap smear and HPV test [##REF##25411259##23##, ##REF##34747902##28##]. All studies investigated high-risk HPV patients. However, two studies considered both high-risk and low-risk patients [##REF##26908722##20##, ##UREF##5##24##]. One study was conducted on a sample of women with systemic lupus erythematosus [##REF##25411259##23##].</p>", "<p id=\"Par18\">According to three studies, there was a significant relationship between vitamin D deficiency and cervicovaginal HPV [##REF##26908722##20##, ##REF##28471122##21##, ##REF##34747902##28##], while three studies did not show any relationship [##REF##25411259##23##, ##UREF##5##24##, ##REF##32317302##30##]. One study showed a significant positive association between serum vitamin D measured by multiple biomarkers and short-term high-risk HPV persistence [##REF##33205195##29##]. However, they emphasized that the relationship between vitamin D status, as measured by 5 biomarkers, and short-term persistence of high-risk HPV led to mixed results [##REF##33205195##29##]. Also, a report showed that higher levels of a new biomarker 24,25(OH)2D3 were positively associated with a higher likelihood of high-risk HPV detection (aOR ¼ 1.22; 95% CI, 0.97–1.52) [##REF##32317302##30##], whereas the study of Ozgu et al. (2016) showed that deficiency of Vitamin D metabolites can be a possible reason for HPVDNA persistence and related cervical intraepithelial neoplasia (<italic>P</italic>=0.009) [##REF##28471122##21##]. Table ##TAB##2##3## demonstrates data extracted from the included Studies.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par19\">The relationship between HPV infection and serum vitamin D levels has garnered increasing attention due to its potential significance in the context of public health and cervical cancer prevention. In this systematic review, we aimed to consolidate existing evidence to discern any noteworthy associations. However, after careful evaluation of the available studies, the findings showed no clear-cut evidence to suggest vitamin D is associated with HPV, although a few studies claimed this association [##REF##26908722##20##, ##REF##28471122##21##, ##REF##34747902##28##]. One of the most striking observations from our systematic review is the inconsistency in the reported findings across various studies. While some studies suggested a potential inverse association between serum vitamin D levels and HPV infection [##REF##26908722##20##, ##REF##28471122##21##, ##REF##34747902##28##], others failed to establish a significant link [##REF##25411259##23##, ##UREF##5##24##, ##REF##33205195##29##, ##REF##32317302##30##]. This heterogeneity in results highlights the complex and multifaceted nature of HPV infection and vitamin D metabolism. However, one wonders how to interpret and find an explanation for such observations.</p>", "<p id=\"Par20\">The majority of HPV infections are spontaneously cleared by natural immune responses without leading to cancers, and only a small portion of HPV infections are reported to be persistent, which results in precancerous intraepithelial neoplasia and cancer [##REF##31500479##3##]. Vitamin D is known for its immunomodulatory properties, and a deficiency may theoretically compromise the immune response against viral infections such as HPV [##REF##32967126##33##]. The potential role of vitamin D in protecting and strengthening the immune system is considered in several studies [##REF##28733125##13##, ##REF##21896008##14##, ##UREF##11##34##]. The majority of immune system cells such as macrophages, lymphocytes, and neutrophils, have vitamin D receptors in their nuclei [##REF##36902117##35##]. Vitamin D makes the physical barriers such as the skin, respiratory tract, and genitourinary tract more resistant to bacteria and viruses by upregulating the proteins that promote tight junctions, gap junctions, and adherens junctions [##REF##35406694##36##]. Thus, sufficient vitamin D levels by strengthening the mucous barriers impair HPV penetration into the basal layer; conversely, insufficient vitamin D levels, by increasing vulnerability against HPV penetration and decreasing the host’s ability to clear the virus, lead to higher incidence of HPV infection [##UREF##5##24##, ##REF##36960048##37##]. In keeping and maintaining an intact epidermal barrier in the skin, vaginal mucosa, and genitourinary system vitamin D plays a protective and efficient role [##REF##26824295##38##]. Additionally, vitamin D has demonstrated anti-inflammatory and anti-proliferative properties, which could potentially influence the progression and persistence of HPV infection [##REF##33182663##10##]. Numerous studies have reported the positive role of vitamin D in preventing carcinogenic processes and decreasing the risk of cancer by viral infections, especially DNA viruses such as HPV [##REF##32967126##33##, ##UREF##12##39##–##REF##30399574##41##]. An optimal level of vitamin D might exert beneficial effects in the early phases of cervical cancer by preventing its onset and progression [##REF##37240017##42##]. Nevertheless, according to some studies, vitamin D supplementation does not significantly increase the rate of HPV regression [##REF##36501056##43##, ##UREF##13##44##].</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par23\">The systematic review presented here has thoroughly examined the existing literature on the relationship between cervicovaginal HPV infection and serum vitamin D levels. Despite the initial interest and the potential biological plausibility of such a relationship, the findings showed no firm evidence for any association between HPV infection and serum vitamin D levels. This inconclusiveness underscores the need for further well-designed studies to explore this topic comprehensively.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Human papillomavirus (HPV) is one of the most prevalent sexually transmitted diseases worldwide. The present review was conducted to accumulate evidence on the relationship between cervicovaginal human papillomavirus infection and serum vitamin D status.</p>", "<title>Methods</title>", "<p id=\"Par2\">Electronic databases including Web of Science, Embase, Scopus, and PubMed were searched by different combinations of keywords related to “human papillomavirus” and “vitamin D”, obtained from Mesh and Emtree with AND, and OR operators without any time restriction until December 24, 2022. Selection of articles was based on the inclusion and exclusion criteria. Newcastle-Ottawa Scale was used for quality assessment. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was applied for reporting.</p>", "<title>Results</title>", "<p id=\"Par3\">In total, 276 citations were retrieved. After removing duplicates, and non-related articles, the full texts of 7 articles were reviewed including 11168 participants. Three studies reported that there was a positive relationship between vitamin D deficiency and cervicovaginal human papillomavirus while three studies did not. One study showed a significant positive association between higher vitamin D stores and short-term high-risk human papillomavirus persistence.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The findings showed no firm evidence for any association between serum vitamin D level and cervicovaginal human papillomavirus infection, although the possible association could not be discarded. Further investigations are needed to reach sound evidence.</p>", "<title>Keywords</title>" ]
[ "<title>Excluded evidence</title>", "<p id=\"Par21\">Two studies were not evaluated in the present study according to the inclusion criteria [##UREF##9##31##, ##UREF##10##32##]. One study compared the vitamin D levels in 30 HPV-negative and 68 HPV-positive patients and found no statistically significant difference in vitamin D mean levels between the two groups [##UREF##9##31##]. Similarly, another study compared the vitamin D levels in 94 HPV-negative and 39 HPV-positive patients and no significant difference was observed [##UREF##10##32##]. The source titles that published these studies Apparently, both studies failed to provide sound evidence since not enough sample sizes were studied, and it seems that the power for such a comparison in both studies was very poor.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par22\">This review included all studies that reported the relationship between vitamin D serum levels in various study populations (reproductive ages, suffering from low-risk and high-risk types of HPV, with abnormal Pap smear specimens, and suffering from systemic lupus erythematosus) and not merely one particular group. However, given the diverse study designs and study populations represented in this review, it is difficult to infer causality. Furthermore, variations in measurement techniques for serum vitamin D levels or its metabolite substances may have contributed to the inconsistency in findings. Moreover, the role of population characteristics, including age, gender, geographical location, and baseline health status of the study participants, might influence vitamin D metabolism and immune response to HPV that were not possible to examine in this review. Finally, considering the design of studies under review, one should note that the evidence derived from cohort studies and a case-control study should receive more weight than the evidence derived from cross-sectional studies. Thus, although not sharply, one might argue that the findings were in favor of a positive association rather than no relationship.</p>" ]
[ "<p>The authors would like to extend their gratitude to Shahid Beheshti University of Medical Sciences.</p>", "<title>Authors’ contributions</title>", "<p>S.M.K., H.E.R., M.H., L.A., F.G., and Z.K. collected the data. A.M. was involved in data interpretation, responding to reviewers’ comments, and helped in providing the final draft. H.R. designed and supervised the study, and provided the final draft. All authors reviewed and approved the manuscript.</p>", "<title>Funding</title>", "<p>The authors received no financial support for the research, authorship, and/or publication of this article.</p>", "<title>Availability of data and materials</title>", "<p>All data generated during this study are included in this published article.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par24\">The ethics committee of Shahid Beheshti University of Medical Sciences approved the study (IR.SBMU.PHARMACY.REC.1401.170).</p>", "<title>Consent for publication</title>", "<p id=\"Par25\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par26\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The flow diagram of the review</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>An example of PubMed search query</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\" colspan=\"2\">(\"Alphapapillomavirus\" [mh] OR \"Human papillomavirus 16\" [mh] OR \"Human papillomavirus 31\" [mh] OR \"Human papillomavirus 18\" [mh] OR \"Human papillomavirus 6\" [mh] OR \"Human papillomavirus 11\" [mh] OR \"Papillomavirus Infections\" [mh] OR \"Warts\" [mh] OR Alphapapillomaviruses [tiab] OR HPV Human Papillomavirus [tiab] OR HPV Human Papillomaviruses [tiab] OR Human Papillomavirus [tiab] OR Human Papillomaviruses [tiab] OR HPV 16 [tiab] OR Human papillomavirus type 16 [tiab] OR HPV 31 [tiab] OR Human papillomavirus type 31 [tiab] OR HPV 18 [tiab] OR Human papillomavirus type 18 [tiab] OR HPV 6[tiab] OR Human papillomavirus type 6 [tiab] OR Papillomavirus [tiab] OR HPV 11 [tiab] OR Human papillomavirus type 11 [tiab] OR Papillomavirus Infection [tiab] OR Human Papillomavirus Infection [tiab] OR Human Papillomavirus Infections [tiab] OR HPV Infection [tiab] OR HPV Infections [tiab] OR Wart [tiab]) AND (\"Vitamin D\" [mh] OR \"25-Hydroxyvitamin D 2\" [mh] OR \"Calcifediol 25-hydroxyvitamin D\" [mh] OR \"Cholecalciferol\" [mh] OR \"Hydroxycholecalciferols\" [mh] OR \"Calcitriol\" [mh] OR 25 Hydroxyvitamin D 2 [tiab] OR 25 Hydroxyergocalciferol [tiab] OR 25 Hydroxyvitamin D2 [tiab] OR Ercalcidiol [tiab] OR 25 Hydroxycalciferol [tiab] OR 25 Hydroxyvitamin D 3 [tiab] OR 25 Hydroxycholecalciferol Monohydrate [tiab] OR 25 Hydroxyvitamin D3 [tiab] OR Calcidiol [tiab] OR 25 Hydroxycholecalciferol [tiab] OR Calcifediol Anhydrous [tiab] OR Dedrogyl [tiab] OR Hidroferol [tiab] OR Calderol [tiab] OR 25-hydroxyergocalciferol [tiab] OR Calciol [tiab] OR Vitamin D 3 [tiab] OR Vitamin D3 [tiab] OR Cholecalciferols [tiab] OR Hydroxyvitamins D [tiab] OR Hydroxycholecalciferol [tiab] OR Bocatriol [tiab] OR Calcijex [tiab] OR Calcitriol KyraMed [tiab] OR Calcitriol Nefro [tiab] OR Decostriol [tiab])</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Quality assessment of included studies using the Newcastle-Ottawa Scale*</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\" colspan=\"10\"><bold>Assessment of the quality of cohort studies</bold></td></tr><tr><td align=\"left\" colspan=\"5\"><bold>Selection (max 4 scores)</bold></td><td align=\"left\"><bold>Comparability (max 2 scores)</bold></td><td align=\"left\" colspan=\"3\"><bold>Outcome (max 3 scores)</bold></td><td align=\"left\" rowspan=\"2\"><bold>Total score**</bold></td></tr><tr><td align=\"left\"><bold>Author/ Year/ Reference</bold></td><td align=\"left\"><bold>Representativeness of the exposed cohort</bold></td><td align=\"left\"><bold>Selection of the non-exposed cohort</bold></td><td align=\"left\"><bold>Ascertainment of exposure</bold></td><td align=\"left\"><bold>Demonstration that outcome of interest was not present at start of study</bold></td><td align=\"left\"><bold>Comparability of cohorts on the basis of the design or analysis</bold></td><td align=\"left\"><bold>Assessment of outcome</bold></td><td align=\"left\"><bold>Was follow-up long enough for outcomes to occur</bold></td><td align=\"left\"><bold>Adequacy of follow up of cohorts</bold></td></tr><tr><td align=\"left\">Chu et al. (2021) [##REF##34747902##28##]</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">9</td></tr><tr><td align=\"left\">El-Zein et al. (2021) [##UREF##5##24##]</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">9</td></tr><tr><td align=\"left\">Troja et al. (2021) [##REF##33205195##29##]</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">9</td></tr><tr><td align=\"left\" colspan=\"10\"><bold>Assessment of the quality of cross-sectional studies</bold></td></tr><tr><td align=\"left\" colspan=\"5\"><bold>Selection (max 5 scores)</bold></td><td align=\"left\"><bold>Comparability (max 1 score)</bold></td><td align=\"left\" colspan=\"3\"><bold>Outcome (max 3 scores)</bold></td><td align=\"left\"/></tr><tr><td align=\"left\"><bold>Author/ Year/ Reference</bold></td><td align=\"left\"><bold>Representativeness of the sample</bold></td><td align=\"left\"><bold>Sample size</bold></td><td align=\"left\"><bold>Non-response rate</bold></td><td align=\"left\"><bold>Ascertainment of the measure</bold></td><td align=\"left\"><bold>Potential confounders were investigated based on the study design or subgroup analysis</bold></td><td align=\"left\"><bold>Assessment of the outcome</bold></td><td align=\"left\"><bold>Statistical test</bold></td><td align=\"left\"><bold>-</bold></td><td align=\"left\"><bold>Total score</bold></td></tr><tr><td align=\"left\">Shim et al. (2016) [##REF##26908722##20##]</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">7</td></tr><tr><td align=\"left\">Garcia-Carrasco et al. (2015) [##REF##25411259##23##]</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">**</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">7</td></tr><tr><td align=\"left\">Troja et al. (2020) [##REF##32317302##30##]</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Mertoğlu et al. (2017) [##UREF##9##31##]</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">2</td></tr><tr><td align=\"left\">Çakir et al. (2022) [##UREF##10##32##]</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">2</td></tr><tr><td align=\"left\" colspan=\"10\"><bold>Assessment of the quality of case-control studies</bold></td></tr><tr><td align=\"left\" colspan=\"5\"><bold>Selection (max 4 scores)</bold></td><td align=\"left\"><bold>Comparability (max 2 scores)</bold></td><td align=\"left\" colspan=\"3\"><bold>Exposure (max 3 scores)</bold></td><td align=\"left\"/></tr><tr><td align=\"left\"><bold>Author/ Year/ Reference</bold></td><td align=\"left\"><bold>Adequate case definition</bold></td><td align=\"left\"><bold>Representativeness of the cases</bold></td><td align=\"left\"><bold>Selection of controls</bold></td><td align=\"left\"><bold>Definition of controls</bold></td><td align=\"left\"><bold>Basis of the design or analysis</bold></td><td align=\"left\"><bold>Ascertainment of exposure</bold></td><td align=\"left\"><bold>Same method of ascertainment for cases and controls</bold></td><td align=\"left\"><bold>Non-Response rate</bold></td><td align=\"left\"><bold>Total score</bold></td></tr><tr><td align=\"left\">Ozgu et al. (2016) [##REF##28471122##21##]</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">**</td><td align=\"left\">-</td><td align=\"left\">*</td><td align=\"left\">*</td><td align=\"left\">8</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Data extracted from the included studies</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"><bold>Author (Year)/Ref.</bold></th><th align=\"left\"><bold>Country</bold></th><th align=\"left\"><bold>Design</bold></th><th align=\"left\"><bold>Sample size/Participants</bold></th><th align=\"left\"><bold>Findings</bold></th></tr></thead><tbody><tr><td align=\"left\">Garcia-Carrasco et al. (2015) [##REF##25411259##23##]</td><td align=\"left\">Mexico</td><td align=\"left\">Cross-sectional</td><td align=\"left\">67 / patients with systemic lupus erythematous</td><td align=\"left\">No significant relationship was found between vitamin D deficiency and cervical HPV (<italic>P</italic>=0.7).</td></tr><tr><td align=\"left\">Shim et al. (2016) [##REF##26908722##20##]</td><td align=\"left\">USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">2351 / 20-59 years</td><td align=\"left\">Cervicovaginal HPV prevalence was associated with less-than-optimal levels of serum vitamin D (aOR, 1.14; 95% CI, 1.02– 1.27).</td></tr><tr><td align=\"left\">Ozgu et al. (2016) [##REF##28471122##21##]</td><td align=\"left\">Turkey</td><td align=\"left\">Case-control</td><td align=\"left\">85 / 20-65 years/ 23 cases: positive HPVDNA testing and abnormal PAP smear result / 62 controls: negative HPV DNA testing and cervical biopsy results</td><td align=\"left\">Deficiency of Vitamin D and its metabolites can be a possible reason for HPVDNA persistence and related cervical intraepithelial neoplasia (<italic>P</italic>=0.009).</td></tr><tr><td align=\"left\">Troja et al. (2020) [##REF##32317302##30##]</td><td align=\"left\">USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">404 / 30–50 years</td><td align=\"left\">Serum vitamin D levels were not associated with hrHPV prevalence. However higher levels of a subtype [24,25(OH)2D3] was positively associated with the higher likelihood of hrHPV detection (aOR ¼ 1.22; 95% CI, 0.97–1.52). No significant associations were observed for other biomarkers.</td></tr><tr><td align=\"left\">El-Zein et al. (2021) [##UREF##5##24##]</td><td align=\"left\">Canada</td><td align=\"left\">Cohort</td><td align=\"left\">490 / 18-24-years</td><td align=\"left\">No evidence of an association between low vitamin D levels and increased HPV prevalence, acquisition, or clearance.</td></tr><tr><td align=\"left\">Troja et al. (2021) [##REF##33205195##29##]</td><td align=\"left\">USA</td><td align=\"left\">Longitudinal cohort</td><td align=\"left\">72/ 30–50 years</td><td align=\"left\">Significant positive association between higher systemic vitamin D stores and short-term hrHPV persistence.</td></tr><tr><td align=\"left\">Chu et al. (2021) [##REF##34747902##28##]</td><td align=\"left\">Taiwan</td><td align=\"left\">Data were derived from the ongoing prospective cohort of health examinations</td><td align=\"left\">7699/ women over 20 years</td><td align=\"left\">Vitamin D deficiency was associated with the hrHPV infection of the cervix (<italic>P</italic> &lt; 0.05).</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><sup>*</sup> The last two studies in cross-sectional section are not included in the review</p><p><sup>**</sup> Each asterisk is equivalent to one score. The maximum score is 9. Studies with a score of 7-9, are considered as high quality, 4-6 as high risk, and 0-3 as very high risk of bias. For cohort studies, a score of 6 or higher is considered as low risk and good quality, and a score of &lt;6 is considered as high risk and low quality</p></table-wrap-foot>", "<table-wrap-foot><p><italic>aOR</italic> Adjusted odds ratiom <italic>CI</italic> Confidence interval, <italic>hrHPV</italic> High-risk HPV</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12879_2024_9006_Fig1_HTML\" id=\"MO1\"/>" ]
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[{"label": ["7."], "mixed-citation": ["Stelzle D, Tanaka LF, Lee KK, et al. Estimates of the global burden of cervical cancer associated with HIV. Lancet Glob Health 2020; published online Nov 16. S2214-109X(20)30459-9"]}, {"label": ["8."], "surname": ["Momenimovahed", "Mazidimoradi", "Maroofi", "Allahqoli", "Salehiniya", "Alkatout"], "given-names": ["Z", "A", "P", "L", "H", "I"], "article-title": ["Global, regional and national burden, incidence, and mortality of cervical cancer"], "source": ["Cancer Rep"], "year": ["2023"], "volume": ["6"], "issue": ["3"], "fpage": ["e1756"], "pub-id": ["10.1002/cnr2.1756"]}, {"label": ["9."], "surname": ["Kombe Kombe", "Li", "Zahid", "Mengist", "Bounda", "Zhou", "Jin"], "given-names": ["AJ", "B", "A", "HM", "GA", "Y", "T"], "article-title": ["Epidemiology and burden of human papillomavirus and related diseases, molecular pathogenesis, and vaccine evaluation"], "source": ["Front Public Health"], "year": ["2021"], "volume": ["20"], "issue": ["8"], "fpage": ["552028"], "pub-id": ["10.3389/fpubh.2020.552028"]}, {"label": ["16."], "mixed-citation": ["Wang H, Chen W, Li D, Yin X, Zhang X, Olsen N, Zheng SG. Vitamin D and chronic diseases. Aging Dis. 2017; 8(3):346-353. 10.14336/AD.2016.1021. PMID: 28580189."]}, {"label": ["22."], "surname": ["El Mongy", "Hilal", "Badr", "Alraawi"], "given-names": ["NN", "RF", "AM", "SA"], "article-title": ["Serum vitamin D level in patients with viral warts"], "source": ["J Egypt Women's Dermatologic Soc"], "year": ["2018"], "volume": ["15"], "issue": ["3"], "fpage": ["133"], "lpage": ["8"], "pub-id": ["10.1097/01.EWX.0000544897.93500.a8"]}, {"label": ["24."], "mixed-citation": ["El-Zein M, Khosrow-Khavar F, Burchell AN, Tellier PP, Eintracht S, McNamara E, Coutl\u00e9e F, Franco EL; HITCH study group. Association of serum 25-hydroxyvitamin D with prevalence, incidence, and clearance of vaginal HPV infection in young women. J Infect Dis. 2021; 224(3):492-502. 10.1093/infdis/jiaa758."]}, {"label": ["25."], "mixed-citation": ["Page M J, McKenzie J E, Bossuyt P M, Boutron I, Hoffmann T C, Mulrow C D et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews BMJ 2021; 372 :n71. 10.1136/bmj.n71."]}, {"label": ["26."], "surname": ["Lo", "Mertz", "Loeb"], "given-names": ["CK", "D", "M"], "article-title": ["Newcastle-Ottawa Scale: comparing reviewers' to authors' assessments"], "source": ["BMC Med Res Methodol"], "year": ["2014"], "volume": ["1"], "issue": ["14"], "fpage": ["45"], "pub-id": ["10.1186/1471-2288-14-45"]}, {"label": ["27."], "mixed-citation": ["Wells GA, Shea B, O\u2019Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. Available from: URL: "], "ext-link": ["http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm"]}, {"label": ["31."], "surname": ["Merto\u011flu", "Nayk\u0131", "Nayk\u0131", "G\u00fcnay"], "given-names": ["C", "\u00dc", "C", "M"], "article-title": ["The relationship between vitamin D And human papilloma virus infection"], "source": ["J Clin Anal Med"], "year": ["2017"], "volume": ["8"], "issue": ["6"], "fpage": ["538"], "lpage": ["40"], "pub-id": ["10.4328/JCAM.5400"]}, {"label": ["32."], "mixed-citation": ["\u00c7akir AT, \u00d6zten MA. Serum vitamin D levels in high-risk HPV infected patients, is there any relation? J Clin Med Kaz. 2022; 19(3):35-39. 10.23950/jcmk/12113."]}, {"label": ["34."], "surname": ["Beard", "Bearden", "Striker"], "given-names": ["JA", "A", "R"], "article-title": ["Vitamin D and the anti-viral state"], "source": ["J Investig Med"], "year": ["2011"], "volume": ["50"], "issue": ["3"], "fpage": ["194"], "lpage": ["200"]}, {"label": ["39."], "surname": ["Fleet", "DeSmet", "Johnson", "Li"], "given-names": ["JC", "M", "R", "Y"], "article-title": ["Vitamin D and Cancer: A review of molecular mechanisms"], "source": ["Biochem J"], "year": ["2011"], "volume": ["441"], "issue": ["1"], "fpage": ["61"], "pub-id": ["10.1042/BJ20110744"]}, {"label": ["44."], "surname": ["Koc", "Kurt", "Ilgen", "Timur", "Uslu"], "given-names": ["S", "S", "O", "H", "T"], "article-title": ["The effect of vitamin D on the regression of human papilloma virus infection and metabolic parameters: a retrospective study"], "source": ["Eur J Gynaecol Oncol"], "year": ["2021"], "volume": ["42"], "issue": ["2"], "fpage": ["340"], "lpage": ["345"], "pub-id": ["10.31083/j.ejgo.2021.02.2246)"]}]
{ "acronym": [ "HPV", "STD" ], "definition": [ "Human papillomavirus", "Sexually transmitted disease" ] }
44
CC BY
no
2024-01-14 23:43:45
BMC Infect Dis. 2024 Jan 13; 24:80
oa_package/65/99/PMC10787408.tar.gz
PMC10787409
38216968
[ "<title>Background</title>", "<p id=\"Par18\">The rotator cuff is composed of the subscapularis, supraspinatus, infraspinatus, and teres minor tendons. This structure connects the scapula to the humeral head and maintains dynamic stability of the glenohumeral joint through a concave compression mechanism. It is also an essential component in maintaining the equilibrium of couples in the shoulder joint [##UREF##0##1##]. Rotator cuff tears (RCTs) can cause pain and limitation of shoulder motion, with the supraspinatus tendon being the most commonly affected site. A recent study found that RCTs account for approximately 50%–85% of shoulder disorders treated by clinicians, and the morbidity increases with age [##REF##32007452##2##].</p>", "<p id=\"Par19\">The rotator cuff tendinopathy has been classically summarized as extrinsic, intrinsic, or a combination of both. Intrinsic mechanisms, such as the mechanical properties, age-related degeneration, and vascularity of the rotator cuff, along with extrinsic mechanisms such as internal and external impingement caused by alterations in scapular and glenohumeral kinematics, appear to be significant contributors to RCTs [##UREF##1##3##]. Tears most commonly occur in and around the critical zone of the supraspinatus tendon, which lies in the region between the bony insertion of the tendon and the nearest musculotendinous junction [##REF##14560548##4##]. This anatomic factor combined with multiple internal and external mechanisms contributes to this result, such as the morphology of supraspinatus [##UREF##2##5##], subacromial impingement [##UREF##3##6##], and the presence of “critical zone” [##REF##17866481##7##, ##REF##18647848##8##]. The high incidence of supraspinatus tear gives its segmentation a higher priority and considerable clinical significance for the diagnosis of RCTs.</p>", "<p id=\"Par20\">In clinical practice, shoulder magnetic resonance imaging (MRI) plays a crucial role in diagnosing RCTs, assessing the extent of tears, and formulating surgical plans. MRI offers advantages such as non-invasiveness, non-ionizing, anatomical reproducibility, and excellent tissue contrast, making it a common modality for the clinical diagnosis of RCTs and preoperative preparation [##REF##11832041##9##].</p>", "<p id=\"Par21\">Currently, computer-aided diagnosis (CAD) techniques have been widely applied in medical image analysis, significantly enhancing diagnostic accuracy and efficiency. With the advent of the artificial intelligence (AI) revolution, AI-enabled health care has become a hot research field. Targeting the issues of low efficiency in the interpretation of massive MRI images and subjective differences in human interpretation, this paper proposes deep learning (DL) methods and builds an innovative DL model based on existing research findings. It was developed to automatically segment and extract regions of interest, aiming to alleviate the workload of clinical doctors.</p>", "<p id=\"Par22\">The supraspinatus is the most common site of RCTs, and its tears along with atrophy can reflect the severity of damage. Therefore, the supraspinatus is chosen as the segmentation target, and an improved DL model that can accurately extract the supraspinatus in the coronal plane was proposed in this paper. Compared to the more extensively studied sagittal plane, the coronal plane is a vertical plane perpendicular to the body. It is commonly used to observe the anterior–posterior thickness and morphology of the supraspinatus muscle in the shoulder. The coronal plane is particularly useful in assessing tears or changes in the anterior–posterior thickness of the supraspinatus muscle. Therefore, compared to segmentation based on the sagittal plane, extracting the supraspinatus muscle based on the coronal plane can improve the efficiency of diagnosing and treating RCTs. It has a significant impact on clinical decision-making and the formulation of surgical plans. This innovation holds certain practical significance in the field of intelligent recognition and interpretation of medical images.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par23\">Shoulder MRI has relatively simple semantics and fixed structures. Both high-level and low-level semantic information are equally important, and there is a high demand for timeliness in medical diagnosis. Therefore, image segmentation algorithms are commonly used in research to improve segmentation results and accuracy while reducing manual intervention and segmentation time. Considering these characteristics, this paper chooses the LinkNet [##UREF##4##10##] model as the base framework. LinkNet has demonstrated good performance in achieving accurate segmentation results. It utilizes a combination of encoder and decoder structure to capture local and global context information, which is crucial for accurately segmenting the supraspinatus muscle and distinguishing it from surrounding tissues. LinkNet strikes a balance between accuracy and efficiency based on a lightweight network structure. It computes efficiently while still maintaining competitive segmentation performance. This is especially valuable in clinical settings for real-time or near real-time MRI image analysis. The LinkNet shows robustness in handling image quality and noise variations. The model’s structure helps mitigate the impact of noise and artifacts, resulting in more reliable segmentation results, showing. This robustness is essential for accurate segmentation of the supraspinatus muscle. And LinkNet can be pre-trained on large datasets, such as medical image repositories, to enhance model generalization and improve segmentation performance. Considering these factors, the LinkNet model is a suitable choice for accurate and efficient supraspinatus muscle segmentation in MRI images. However, the MRI images of the supraspinatus encompass intricate details and local features, accurate segmentation is challenging, and the selection and improvement of any segmentation model depends on the specific requirements of the task. This paper constructs an attention-dense atrous spatial pyramid pooling UNet (A-DAsppUnet) network for the segmentation of the supraspinatus in shoulder MRI. As shown in Fig. ##FIG##0##1##, the proposed model involves an encoder ResNet34 [##UREF##5##11##], a channel attention module, and dense atrous spatial pyramid pooling (DenseASPP), which connects the encoder and decoder network. The encoder can extract deep semantic feature information, while the channel attention incorporates skip connections to enhance feature representation during encoding and decoding. Drawing from the structural experience of the D-LinkNet model [##UREF##6##12##], DenseASPP is beneficial to capture multi-context information, intensive feature extraction, and parameter sharing and improves the accuracy of semantic segmentation. It is widely used in object segmentation [##UREF##7##13##] and scene semantic recognition [##UREF##8##14##, ##UREF##9##15##]. The aforementioned structures were integrated into the model and had been innovatively applied to muscle tissue segmentation in medical MRI images. The proposed model demonstrates the ability to resist noise and image quality interference, enabling efficient and accurate segmentation of the supraspinatus and surrounding tissues.</p>", "<p id=\"Par24\">As shown in the diagram, the selected sequences were downloaded and exported as TIFF files and saved across three RGB image channels, which were adjusted to 8-bit 512 × 512 × 3-pixel portable network graphics (PNG) files using Photoshop to match the standardized network input. Compared with the original grayscale image, which only contains brightness information, RGB image helps to separate the supraspinatus muscle from the surrounding tissue. Due to the inclusion of three information channels, RGB images facilitate the differentiation of certain muscle diseases or conditions that may result in color variations in muscle tissue. Moreover, the richness of contextual information in RGB images enhances their visualization effect, making them more intuitive and suitable for specific algorithms. The ResNet34 model utilizes multiple down-sampling steps to extract the desired target features. At the end of the encoding process, the image dimensions are reduced to a size of 16 × 16 with 512 channels. Subsequently, the feature map is passed into the DenseASPP module. This step is beneficial for expanding the receptive field without compromising the resolution of the feature map. Additionally, it ensures the preservation of abundant spatial information. In the decoding stage, the feature map size is restored through transposed convolution for up-sampling. The model utilizes skip connections and channel attention modules to fuse and complement the feature information, enhancing both the integrity of the feature information and the exchange of channel features. This approach significantly improves the network's capability to extract target regions in complex MRI images, ensuring high accuracy and robustness in feature extraction.</p>", "<title>Channel attention module</title>", "<p id=\"Par25\">In medical image segmentation, extracting structural features of target regions is often challenging. Additionally, the performance and stability of medical image segmentation models are often compromised due to the lack of high-quality manually labeled datasets and class imbalance among the samples. Attention mechanisms have demonstrated their effectiveness in enhancing a model's ability to focus on important features [##UREF##10##16##]. In this paper, a channel attention mechanism is introduced to adjust the importance of each channel in the feature maps after encoding and down-sampling. This mechanism dynamically adjusts the network's attention to different features, thereby effectively enhancing feature extraction and utilization. It helps alleviate class imbalance issues, reduce noise, and eliminate redundant information. As a result, it improves the robustness of the model and enhances segmentation accuracy [##UREF##11##17##]. Figure ##FIG##1##2## illustrates the structure of the channel attention module.</p>", "<title>Dense atrous spatial pyramid pooling</title>", "<p id=\"Par26\">In the middle part of the model, the DenseASPP structure based on the dense convolutional network (DenseNet) [##UREF##13##19##] model is used to connect the encoding and decoding networks. Figure ##FIG##2##3## shows the structure of DenseASPP, it utilizes multiple branches of different void convolution kernels to extract multi-scale features from the input data. In medical image segmentation research, accurate segmentation of the target region is a crucial performance metric. The DenseASPP module expands the receptive field and adapts to multi-scale input images by utilizing dilated convolutions and pyramid pooling within a dense block structure. In Fig. ##FIG##2##3##, d represents the dilation rate of dilated convolutions. This module enhances the semantic expressive power of features and exhibits outstanding performance in image segmentation tasks.</p>" ]
[ "<title>Experimental results and analysis</title>", "<p id=\"Par35\">To ensure fair and objective analysis of the experimental results, all experiments in this paper were conducted using the same dataset and experimental environment. Table ##TAB##0##1## displays the quantitative statistical results of the five models on the experiment's test set for supraspinatus tendon extraction. The evaluation of model performance is conducted using three assessment metrics: Pre, IoU, and Dice coefficient.</p>", "<p id=\"Par36\">According to the table, the mentioned models are capable of extracting the supraspinatus tendon to some extent, with differences in terms of completeness, continuity, and accuracy of the extraction. The proposed method in this paper achieved Pre, IoU, and Dice coefficients of 99.20%, 83.38%, and 90.94%, respectively. The comparison clearly indicates that this method has a significant advantage and performs in terms of extracting the supraspinatus tendon. Compared to the four comparative models, the proposed method exhibited improvements in the evaluation metrics. The “Pre” metric showed an enhancement of approximately 0.4%–1%, the “IoU” metric witnessed an improvement of 7.5%–18.3%, and the \"Dice coefficient\" experienced an increase of approximately 4.7%–12.1%. These improvements were significant across all indicators. Among the comparative models, DenseNet performed the best, followed by UNet and SegNet, while FCN had the worst effect and had a large gap with the proposed algorithm in IoU and Dice indicators in this paper.</p>", "<p id=\"Par37\">Based on the data in the table and the equation above, it can be observed that the improvement in the Pre metric is not significant. The reason is that the target pixel constitutes a relatively small proportion of the total number of pixels, and reducing false-positive pixels does not lead to a significant increase in accuracy. According to the IoU indicator and its calculation formula, a higher IoU value signifies a larger proportion of accurately classified supraspinatus pixels relative to the total number of correctly classified pixels, with fewer incorrectly predicted pixels. In the supraspinatus segmentation task, the significant improvement in the IoU measure indicates that the proposed model achieves the highest accuracy in supraspinatus segmentation. In addition, with a Dice coefficient of 90.94%, it can be inferred that the performance of the model proposed in this paper is superior.</p>", "<p id=\"Par38\">To fully validate the above conclusions, this paper conducted a visual analysis of the supraspinatus segmentation results. Figure ##FIG##4##5## illustrates a visual comparison between the results obtained using the proposed method and those obtained using the comparative model on the test set images. Four representative images are provided in the figure for comparison. As shown in the figure, the segmentation results obtained using the proposed method exhibit the best performance in terms of completeness and capturing fine details. Specifically, the extracted supraspinatus is delineated clearly from structures such as the humeral tuberosity, scapular spine, and inferior glenohumeral capsule. The segmentation results exhibit well-preserved details, and there is a high level of accuracy in aligning the upper and lower boundaries of the segmented region with the ground truth labels. In contrast, in the results obtained using the comparative model, the boundaries of the supraspinatus extraction are blurred near the side of the scapular spine in images (1) and (3). Image (1) shows poor overall segmentation performance, with a significant portion of supraspinatus pixels left unsegmented. Image (3) exhibits numerous erroneous segmentations. On the other hand, in images (2) and (4), the proposed method accurately delineated the edges of the supraspinatus, particularly at the tendon junction with the humeral head and the superior border of the deltoid muscle.</p>", "<p id=\"Par39\">In the comparison model, DenseNet performs well in extracting the target and achieves reasonably accurate segmentation. However, it fails to capture fine details, especially in capturing the blurry boundaries with the deltoid muscle, resulting in insufficient accuracy. The UNet model lacks completeness in target extraction. For example, in image (1), there is information missing in the proximal part of the supraspinatus, and the extracted region is smaller than the actual boundaries defined by the labels. For the SegNet and FCN models, their segmentation results exhibit more false positives and false negatives, as shown in images (1) and (3).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par45\">With the advancement of medical imaging technology, the quantity and complexity of medical imaging data are continuously increasing. In most cases, even with access to shoulder MRI, nonorthopedic surgeons may find it challenging to identify and diagnose RCTs. In this case, the application of CAD techniques provides support for ensuring high efficiency and accuracy in clinical diagnosis.</p>", "<p id=\"Par46\">Ledley et al. [##REF##13668531##20##] pioneered the field of CAD by building a mathematical model for lung cancer diagnosis. With the emergence of artificial intelligence, CAD has evolved into a DL approach, which has shown great potential and widespread application in image processing and computer vision. DL models have revolutionized the field of medical image analysis by leveraging their ability to extract complex patterns and features from images. Through training on extensive datasets, these models can learn to identify subtle abnormalities, assist in disease diagnosis, and provide valuable insights for clinical work.</p>", "<p id=\"Par47\">DL methods have made significant contributions to medical imaging research, with representative works including brain tumor segmentation [##UREF##14##21##], lung nodule detection [##REF##26441412##22##], and case image segmentation [##UREF##15##23##]. In the field of musculoskeletal imaging, accurate imaging diagnosis is crucial, which has spurred the vigorous development of DL techniques. Research in this domain encompasses various areas, such as knee cartilage injury [##REF##29584598##24##], meniscus and ligament tears [##UREF##16##25##, ##REF##30481176##26##], spinal canal stenosis [##REF##28168339##27##], bone age detection, and osteoporosis diagnosis [##REF##29095675##28##], all of which have achieved fruitful results. In this context, the focus is on shoulder MRI, where the mature technologies primarily concentrate on the segmentation of bony tissues. However, the extraction of imaging features related to musculoskeletal tissue, as well as research on their role in assisting diagnosis, is still under development. Research on robust and accurate algorithms for the segmentation and analysis of these soft tissues in shoulder MRI holds great potential for improving diagnostic accuracy and facilitating treatment planning in orthopedics.</p>", "<p id=\"Par48\">Indeed, DL research based on shoulder MRI has made significant progress. Kim et al. [##REF##34341475##29##] developed a FCN model for the segmentation of the supraspinatus and supraspinatus fossa in the sagittal plane of MRI, which visualizes the degree of supraspinatus atrophy and fatty infiltration. Medina et al. [##REF##32621063##30##] utilized an improved UNet convolutional neural network (CNN) architecture to accurately segment the supraspinatus, infraspinatus, and subscapularis in sagittal plane MRI. Ro et al. [##UREF##17##31##] employed a CNN-based approach to segment the supraspinatus and supraspinatus fossa. They analyzed the occupation rate of the supraspinatus and utilized an improved Otsu thresholding technique to quantify the extent of fatty infiltration in the supraspinatus. These studies, focusing on sagittal plane of shoulder MRI, enable physicians to accurately assess the degree of supraspinatus atrophy and fatty infiltration and predict the effectiveness of rotator cuff repair surgery.</p>", "<p id=\"Par49\">However, RCTs are primarily categorized as tendinopathy. Only knowing the atrophy and fatty infiltration of the supraspinatus has limited clinical significance. Therefore, the current trend is to study the tendons themselves. Yao et al. [##REF##35190850##32##] employed a three-stage pipeline consisting of ResNet, UNet, and CNN to perform screening, segmentation, and binary classification (tear or no tear) of supraspinatus images. Hess et al. [##REF##37238157##33##] utilized nnUNet to segment both the bony structures (humerus and scapula) and the rotator cuff on a shoulder MR T1-weighted sequence. Lin et al. [##UREF##18##34##] used four parallel 3D ResNet50 convolutional neural network architectures to detect and classify RCTs based on tear types.</p>", "<p id=\"Par50\">This paper focuses on the supraspinatus and constructs an A-DAsppUnet model, attempting to segment the supraspinatus in the same MRI sequence. Compared with the results of other segmentation models, the proposed model has better segmentation accuracy and performance. It validated the feasibility of using DL methods for segmenting the rotator cuff, and the results provide a reference for clinical treatment and surgical planning in this paper.</p>", "<p id=\"Par51\">However, it is important to acknowledge the limitations of the study. Although the data volume was increased through data augmentation, the experimental data in this study are still not abundant, the prediction results may have minor errors in displaying subtle tears. The training set images only outline the contour of the supraspinatus, so the model prediction results cannot reflect internal injuries and tendon quality. Full-thickness tears mean continuous interruptions of the rotator cuff, leading to significant errors in the segmentation of the tendon stump. Additionally, the boundaries between the supraspinatus and adjacent muscles, such as the trapezius, appear unsatisfactory due to the similarity in pixel grayscale values on MRI. Furthermore, it excluded cases affected by other shoulder diseases, limiting the clinical utility of this model. Addressing the aforementioned issue and expanding the dataset to encompass a broader range of cases would enhance the model's generalization capability.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par52\">In this study, it aimed to investigate the effectiveness of DL models for the extraction of the supraspinatus from shoulder MRI. An improved DL network model was designed, and extensive experiments were carried out on self-constructed supraspinatus dataset.</p>", "<p id=\"Par53\">The experimental results demonstrated that the proposed improved DL model has excellent performance in extracting the supraspinatus the coronal plane of shoulder MRI. The model achieved a high segmentation accuracy with Dice coefficient, precision, and IoU of 0.91, 0.99, and 0.83, respectively. These results indicate that the DL method is capable of accurately segmenting the supraspinatus in shoulder MRI.</p>", "<p id=\"Par54\">Furthermore, the analysis revealed several advantages of the model. The proposed model demonstrates robustness to variations in the position and shape of the supraspinatus. It exhibits resistance to noise interference and achieves high-quality and complete extraction. Compared to traditional image processing techniques, the model outperforms them and shows greater potential in clinical research and applications.</p>", "<p id=\"Par55\">DL-based image segmentation has several advantages compared to the detection and classification of RCTs. Image segmentation offers more detailed information and supports quantitative analysis. It accurately delineates structures or abnormalities at the pixel level, enabling precise localization and providing rich anatomical and pathological details. Therefore, DL-based image segmentation is better suited for handling complex scenarios and personalized medical interventions.</p>", "<p id=\"Par56\">In summary, the research demonstrates the effectiveness of DL models in extracting the supraspinatus from the coronal plane of shoulder MRI. This validates the experimental value and practical significance of DL methods in assisting medical decision-making. Future studies can make breakthroughs by continuously exploring attention mechanisms and multi-scale structures, such as dilated convolutions, and utilizing high-quality data from multiple centers, fully harnessing the potential of DL methods in musculoskeletal imaging.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">With potential of deep learning in musculoskeletal image interpretation being explored, this paper focuses on the common site of rotator cuff tears, the supraspinatus. It aims to propose and validate a deep learning model to automatically extract the supraspinatus, verifying its superiority through comparison with several classical image segmentation models.</p>", "<title>Method</title>", "<p id=\"Par2\">Imaging data were retrospectively collected from 60 patients who underwent inpatient treatment for rotator cuff tears at a hospital between March 2021 and May 2023. A dataset of the supraspinatus from MRI was constructed after collecting, filtering, and manually annotating at the pixel level. This paper proposes a novel A-DAsppUnet network that can automatically extract the supraspinatus after training and optimization. The analysis of model performance is based on three evaluation metrics: precision, intersection over union, and Dice coefficient.</p>", "<title>Results</title>", "<p id=\"Par3\">The experimental results demonstrate that the precision, intersection over union, and Dice coefficients of the proposed model are 99.20%, 83.38%, and 90.94%, respectively. Furthermore, the proposed model exhibited significant advantages over the compared models.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The designed model in this paper accurately extracts the supraspinatus from MRI, and the extraction results are complete and continuous with clear boundaries. The feasibility of using deep learning methods for musculoskeletal extraction and assisting in clinical decision-making was verified. This research holds practical significance and application value in the field of utilizing artificial intelligence for assisting medical decision-making.</p>", "<title>Keywords</title>" ]
[ "<title>Experiment and analysis</title>", "<title>Experimental data and comparative models</title>", "<title>Experimental data</title>", "<p id=\"Par27\">This paper was approved by the Ethics Committee of Jiangsu Province Hospital with Integration of Chinese and Western Medicine, and the approval number is 2023-LWKYZ-033. Personal informed consent was waived for this retrospective study. It retrospectively collected data from 60 patients who underwent inpatient treatment for RCTs at the hospital between March 2021 and May 2023. Patients with other shoulder conditions, such as fractures, dislocations, and calcific tendinitis, were excluded from the study.</p>", "<p id=\"Par28\">Examinations were acquired with a 1.5 T MR scanner (General Electric, SIGNA CREATOR). Conventional two-dimensional MR images were obtained from the proton density (PD) fat-suppressed sequence in the oblique coronal plane. The acquisition parameters are as follows: TR = 2278 + ms, TE = 12.6–84.2 ms, FOV = 20 cm, NEX = 2, bandwidth = 31.25 Hz/pixel, slice thickness = 4 mm, and spacing: 0.5 mm.</p>", "<p id=\"Par29\">Due to the physiological differences between individuals and the diverse location of tears, the author selected images capable of displaying the supraspinatus clearly from acquired images, about 3–5 images per sequence. After the selection process, a total of 200 MRI images were chosen for further analysis. The 60 subjects were randomly divided into a training set, a validation set, and a test set, ensuring that images from the same subject in the training dataset were not used in the validation or evaluation processes in this paper. To fully train the model in this paper, the experimental data were expanded threefold using data augmentation techniques, including image rotation, horizontal flipping, and vertical flipping. These techniques aim to enhance the robustness and generalization capability of the model, thereby improving the accuracy of target extraction during model training.</p>", "<p id=\"Par30\">The images were in RGB format with a size of 512 × 512 pixels. The supraspinatus was manually annotated by tracing its contour on the images. The proximal end of the annotation started at the scapular spine, while the distal end ended at the greater tuberosity of the humerus. The superior boundary was defined by the acromion, shoulder joint capsule, and trapezius, while the inferior boundary was determined by the scapular spine, the upper aspect of the humeral head, and the supraglenoid tubercle. These annotations output corresponding labels for the supraspinatus tendon. The data were annotated by three graduate students and physicians specialized in musculoskeletal imaging. The annotations underwent verification by experienced physicians to ensure accuracy and reliability. The original images and extended data are shown in Fig. ##FIG##3##4##.</p>", "<title>Comparative models</title>", "<p id=\"Par31\">To assess the feasibility and high accuracy of the proposed model for segmenting the supraspinatus tendon in MRI images, several classic image segmentation algorithms, including fully convolution network (FCN), UNet, semantic segmentation network (SegNet), and DenseNet, were selected for comparative experiments on the dataset employed in this paper. These models were chosen to evaluate the accuracy and performance of the proposed method against established approaches.</p>", "<title>Experimental environment and evaluation metrics</title>", "<title>Experimental environment</title>", "<p id=\"Par32\">The experiments were conducted using the Python 3.7 programming language and the PyTorch 1.8.1 deep learning framework. All experiments were performed on a computer equipped with an AMD Ryzen 7 3700X CPU and an NVIDIA GeForce RTX 2700 graphics card with 8 GB of VRAM. For model training, the binary cross-entropy loss function (BCELoss) was used, along with the Adam optimizer to update the network parameters. The batch size was set to 2, and the learning rate was set to 0.0001. The models were trained for 30 epochs.</p>", "<title>Evaluation metrics</title>", "<p id=\"Par33\">Image segmentation is evaluated using metrics such as precision (Pre), <italic>F</italic>1 score, and intersection over union (IoU). However, in medical image segmentation, the Dice coefficient is often used to assess model performance. Therefore, this paper uses Pre, the Dice coefficient, and IoU as the evaluation metrics to measure model performance and the accuracy of supraspinatus tendon segmentation. The formulas for these evaluation metrics are as follows:</p>", "<p id=\"Par34\">In the equations, TP represents the number of pixels correctly predicted as supraspinatus tendon, FP represents the number of pixels incorrectly predicted as supraspinatus tendon, TN represents the number of pixels correctly predicted as background, and FN represents the number of pixels incorrectly predicted as background.</p>", "<title>Robustness analysis through ablation experiments</title>", "<p id=\"Par40\">To thoroughly validate the effectiveness of the proposed innovative model, it conducted ablation experiments to investigate the impact of the deep encoding network, channel attention, and dense spatial pyramid pooling modules on the performance of the proposed model. The experimental setup is described as follows:</p>", "<p id=\"Par41\">LinkNet18 was selected as the baseline model in this paper. Scheme 1: ResNet34 is selected as the model encoder network. Scheme 2: Add the channel attention mechanism at the jump junction of the Scheme 1 model. Scheme 3: DenseASPP in the middle of the Scheme 1 model to connect the encoder and decoder networks. The models of the ablation experiment are shown in Table ##TAB##1##2##.</p>", "<p id=\"Par42\">The ablation experiments were carried out in the same environment as the experimental dataset. The extraction results of the supraspinatus from the images of the test set by each ablation model are shown in Table ##TAB##2##3##.</p>", "<p id=\"Par43\">Figure ##FIG##5##6## shows the extraction results of the supraspinatus in the test set images of each ablation model. According to the comprehensive table and Fig. ##FIG##5##6##, the Pre, IoU, and Dice indexes of Scheme 1 increased by 2.68%, 2.25%, and 1.47%, respectively, and the extraction integrity of the supraspinatus was improved by the model. For example, the extraction results of images (2) and (3) are complete, continuous, and clear. In Scheme 2, the channel attention mechanism is added on the basis of Scheme 1, and the IoU and Dice coefficients are increased by 0.94% and 0.61%, respectively. The channel attention mechanism enhances the fusion of important features in the jump connection, thereby improving the accuracy of supraspinatus edge extraction.</p>", "<p id=\"Par44\">In Scheme 3, the DenseASPP module is used as the middle part of connection coding–decoding, and the model performance indexes Pre, IoU, and Dice are increased by 1.21%, 4.45%, and 2.88%, respectively. The DenseASPP module extends the receptive field of the down-sampled feature maps obtained from the encoder without reducing their resolution. It preserves rich feature information and effectively helps the model recognize and extract target regions after up-sampling in the decoder. This module achieved the best results in terms of the integrity, accuracy, and clarity of supraspinatus edge extraction.</p>" ]
[ "<title>Acknowledgements</title>", "<p>Thanks to the physicians and masters who contributed to the development of our dataset.</p>", "<title>Author contributions</title>", "<p>PW and YL are the first authors of the paper. Wang is responsible for the medical content of the paper, and Liu is responsible for the experiments related to the paper. They wrote this article together. Mr. ZZ provides professional guidance and is the corresponding author in this paper.</p>", "<title>Funding</title>", "<p>This work was supported by 2022 Jiangsu Graduate Practice Innovation Plan (SJCX22-0836).</p>", "<title>Availability of data and materials</title>", "<p>The data and code that support the findings of this study are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par57\">This paper was approved by the Ethics Committee of Jiangsu Province Hospital with Integration of Chinese and Western Medicine. The approval number is 2023-LWKYZ-033. Personal informed consent was waived for this retrospective study.</p>", "<title>Consent for publication</title>", "<p id=\"Par58\">Written informed consent for publication was obtained from all participants.</p>", "<title>Competing interests</title>", "<p id=\"Par59\">The authors declare that they have no conflict of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Improved model architecture diagram based on LinkNet</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Channel attention diagram [##UREF##12##18##]</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>DenseASPP structure diagram [##UREF##9##15##]</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>The original data and data expansion. <bold>a</bold> Original images and labels. <bold>b</bold> Rotate the image and label. <bold>c</bold> Flip horizontal images and labels</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Visualization of extraction results. <bold>a</bold> Images. <bold>b</bold> Labels. <bold>c</bold> A-DAsppUnet. <bold>d</bold> DenseNet. <bold>e</bold> UNet. <bold>f</bold> SegNet. <bold>g</bold> FCN</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Visualization of ablation model extraction results. <bold>a</bold> Images. <bold>b</bold> Labels. <bold>c</bold> A-DAsppUnet. <bold>d</bold> Baseline. <bold>e</bold> Scheme 1. <bold>f</bold> Scheme 2. <bold>g</bold> Scheme 3</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Extraction result statistics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Model</th><th align=\"left\">Pre (%)</th><th align=\"left\">IoU (%)</th><th align=\"left\">Dice (%)</th></tr></thead><tbody><tr><td align=\"left\">FCN</td><td char=\".\" align=\"char\">98.28</td><td char=\".\" align=\"char\">65.07</td><td char=\".\" align=\"char\">78.84</td></tr><tr><td align=\"left\">SegNet</td><td char=\".\" align=\"char\">98.53</td><td char=\".\" align=\"char\">70.59</td><td char=\".\" align=\"char\">82.76</td></tr><tr><td align=\"left\">UNet</td><td char=\".\" align=\"char\">98.74</td><td char=\".\" align=\"char\">73.61</td><td char=\".\" align=\"char\">84.80</td></tr><tr><td align=\"left\">DenseNet</td><td char=\".\" align=\"char\">98.79</td><td char=\".\" align=\"char\">75.86</td><td char=\".\" align=\"char\">86.27</td></tr><tr><td align=\"left\">A-DAsppUnet</td><td char=\".\" align=\"char\"><bold>99.20</bold></td><td char=\".\" align=\"char\"><bold>83.38</bold></td><td char=\".\" align=\"char\"><bold>90.94</bold></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Ablation experimental model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Model</th><th align=\"left\">ResNet34</th><th align=\"left\">Channel attention</th><th align=\"left\">DenseASPP</th></tr></thead><tbody><tr><td align=\"left\">Baseline</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Scheme 1</td><td align=\"left\">√</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Scheme 2</td><td align=\"left\">√</td><td align=\"left\">√</td><td align=\"left\"/></tr><tr><td align=\"left\">Scheme 3</td><td align=\"left\">√</td><td align=\"left\"/><td align=\"left\">√</td></tr><tr><td align=\"left\">A-DAsppUnet</td><td align=\"left\">√</td><td align=\"left\">√</td><td align=\"left\">√</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Extraction results of ablation experiments</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Model</th><th align=\"left\">Pre (%)</th><th align=\"left\">IoU (%)</th><th align=\"left\">Dice (%)</th></tr></thead><tbody><tr><td align=\"left\">Baseline</td><td char=\".\" align=\"char\">89.03</td><td char=\".\" align=\"char\">73.66</td><td char=\".\" align=\"char\">84.83</td></tr><tr><td align=\"left\">Scheme 1</td><td char=\".\" align=\"char\">91.71</td><td char=\".\" align=\"char\">75.91</td><td char=\".\" align=\"char\">86.3</td></tr><tr><td align=\"left\">Scheme 2</td><td char=\".\" align=\"char\">89.01</td><td char=\".\" align=\"char\">76.85</td><td char=\".\" align=\"char\">86.91</td></tr><tr><td align=\"left\">Scheme 3</td><td char=\".\" align=\"char\">90.24</td><td char=\".\" align=\"char\">78.11</td><td char=\".\" align=\"char\">87.71</td></tr><tr><td align=\"left\">A-DAsppUnet</td><td char=\".\" align=\"char\"><bold>92.77</bold></td><td char=\".\" align=\"char\"><bold>83.38</bold></td><td char=\".\" align=\"char\"><bold>90.94</bold></td></tr></tbody></table></table-wrap>" ]
[ "<disp-formula id=\"Equ1\"><label>1</label><alternatives><tex-math id=\"M1\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{Precision}} = \\frac{{{\\text{TP}}}}{{{\\text{TP}} + {\\text{FP}}}} \\times 100\\%$$\\end{document}</tex-math><mml:math id=\"M2\" display=\"block\"><mml:mrow><mml:mtext>Precision</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mtext>TP</mml:mtext><mml:mrow><mml:mtext>TP</mml:mtext><mml:mo>+</mml:mo><mml:mtext>FP</mml:mtext></mml:mrow></mml:mfrac><mml:mo>×</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math></alternatives></disp-formula>", "<disp-formula id=\"Equ2\"><label>2</label><alternatives><tex-math id=\"M3\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{IoU}} = \\frac{{{\\text{TP}}}}{{{\\text{TP}} + {\\text{FP}} + {\\text{FN}}}} \\times 100\\%$$\\end{document}</tex-math><mml:math id=\"M4\" display=\"block\"><mml:mrow><mml:mtext>IoU</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mtext>TP</mml:mtext><mml:mrow><mml:mtext>TP</mml:mtext><mml:mo>+</mml:mo><mml:mtext>FP</mml:mtext><mml:mo>+</mml:mo><mml:mtext>FN</mml:mtext></mml:mrow></mml:mfrac><mml:mo>×</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math></alternatives></disp-formula>", "<disp-formula id=\"Equ3\"><label>3</label><alternatives><tex-math id=\"M5\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{Dice}} = \\frac{{2{\\text{TP}}}}{{\\left( {{\\text{TP}} + {\\text{FP}}} \\right) + \\left( {{\\text{TP}} + {\\text{FN}}} \\right)}} \\times 100\\%$$\\end{document}</tex-math><mml:math id=\"M6\" display=\"block\"><mml:mrow><mml:mtext>Dice</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>2</mml:mn><mml:mtext>TP</mml:mtext></mml:mrow><mml:mrow><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mtext>TP</mml:mtext><mml:mo>+</mml:mo><mml:mtext>FP</mml:mtext></mml:mrow></mml:mfenced><mml:mo>+</mml:mo><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mtext>TP</mml:mtext><mml:mo>+</mml:mo><mml:mtext>FN</mml:mtext></mml:mrow></mml:mfenced></mml:mrow></mml:mfrac><mml:mo>×</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math></alternatives></disp-formula>" ]
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[ "<table-wrap-foot><p>Bold values indicate the performance of the proposed method over the comparison method</p></table-wrap-foot>", "<table-wrap-foot><p>Bold values indicate the performance of the proposed method over the comparison method</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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{ "acronym": [ "RCTs", "CAD", "DL", "A-DAsppUnet", "DASPP", "DenseNet", "PD", "FCN", "SegNet", "BCELoss", "Pre", "IoU", "CNN" ], "definition": [ "Otator cuff tears", "Computer-aided diagnosis", "Deep learning", "Attention-dense atrous spatial pyramid pooling UNet", "Dense atrous spatial pyramid pooling", "Dense convolutional network", "Proton density", "Fully convolution network", "Semantic segmentation network", "Binary cross-entropy loss function", "Precision", "Intersection over union", "Convolutional neural network" ] }
34
CC BY
no
2024-01-14 23:43:45
J Orthop Surg Res. 2024 Jan 13; 19:60
oa_package/71/7f/PMC10787409.tar.gz
PMC10787410
38216885
[ "<title>Background</title>", "<p id=\"Par5\">\nEsophageal cancer is one of the leading causes of cancer-related deaths worldwide, with relatively low survival rate [##REF##33538338##1##], and esophageal squamous cell carcinoma (ESCC) is the main pathological type in China [##REF##23629646##2##]. Definitive chemoradiotherapy (dCRT) is the standard of care for inoperable patients with ESCC, which has a comparable survival and quality of life to surgical resection for favorable responders [##REF##22887465##3##, ##UREF##0##4##]. However, the therapeutic response is affected by tumor oxygenation. Since hypoxia plays an important role in tumor angiogenesis and metastasis, it can increase resistance to chemoradiotherapy [##UREF##1##5##]. It has been confirmed that the hypoxic part of tumor is insensitive to chemoradiotherapy, which is correlated with poor prognosis [##REF##20581454##6##]. Therefore, early monitoring of the status of tumor oxygenation is crucial to evaluate the treatment response and prognosis of ESCC treated with dCRT.</p>", "<p id=\"Par6\">The traditional imaging methods, such as barium esophagography and computed tomography (CT), for evaluating the therapeutic response of ESCC are based on the tumor morphological changes after treatment, and do not evaluate tumor oxygenation. Although positron emission tomography (PET) can be used for hypoxia imaging to evaluate the treatment response to chemoradiotherapy in patients [##UREF##2##7##], high cost and radiation exposure limit its widespread application.</p>", "<p id=\"Par7\">Blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) has been used as a noninvasive tool for assessing the tissue oxygen metabolism [##REF##25423146##8##, ##REF##35366813##9##]. Since deoxyhemoglobin shortens T2* relaxation time, R2* (= 1/T2* relaxation time) can reflect the relative content of deoxyhemoglobin in tissue and is regarded as a quantitative parameter of signal attenuation in BOLD images. Currently, R2* value has been widely utilized in assessing cerebrovascular reactivity [##REF##33687287##10##], muscle activation [##REF##31956534##11##, ##REF##34628310##12##], renal function [##REF##28777704##13##, ##REF##34583652##14##], blood perfusion and histopathological status of tumors [##REF##31582044##15##–##REF##34109120##18##]. Especially, BOLD MRI has been demonstrated to be effective in evaluating the treatment response and prognosis to chemoradiotherapy in various tumors, such as prostate [##REF##19190629##19##], cervical [##REF##24763631##20##, ##REF##31016443##21##] and breast cancer [##REF##20858850##22##]. A preliminary study has reported that blood oxygenation T2* value is a useful quantitative indicator for differentiating preoperative stage of ESCC [##REF##24763631##20##]. However, to the best of our knowledge, BOLD MRI has not been used for assessing the therapeutic response to dCRT and prognosis in ESCC. Tumor hypoxia is an independent prognostic factor, which is significantly associated with increased resistance to treatment and decreased cancer-free survival [##REF##20581454##6##]. Given that BOLD MRI can assess the tissue oxygenation status, we hypothesized that the R2* value may be a hypoxia imaging predictor for response and prognosis of ESCC treated with dCRT.</p>", "<p id=\"Par8\">Therefore, this study aimed to investigate the value of BOLD MRI in early evaluation of the treatment response and prognosis for dCRT in ESCC patients.</p>" ]
[ "<title>Methods</title>", "<title>Patients</title>", "<p id=\"Par9\">This retrospective study was approved by our institutional review board (IRB, 2022-521-03) and followed the ethical standards of the World Medical Association (Declaration of Helsinki). The informed consent was waived for patients. The data of patients with ESCC who underwent BOLD MRI examination and completed dCRT between March 2016 and Aug 2017 were collected. The inclusion criteria were as follows: (1) diagnosis of esophageal cancer confirmed by endoscopic biopsy; (2) no local or systematic treatment before MRI scan. The exclusion criteria were as follows: (1) insufficient MRI data (<italic>n</italic> = 1); (2) poor MR image quality due to artifacts caused by the pulsation of large vessels (<italic>n</italic> = 2); and (3) Lost to follow-up (<italic>n</italic> = 2). A total of 33 consecutive patients were initially enrolled. Finally, 28 patients (23 men and five women; mean age, 64.25 ± 7.65 years; range, 45–80 years) formed the study cohort (Fig. ##FIG##0##1##). The flowchart of study design is shown in Fig. ##FIG##1##2##.</p>", "<p id=\"Par10\">\n\n</p>", "<p id=\"Par11\">\n\n</p>", "<title>MRI examination</title>", "<p id=\"Par12\">All patients underwent MRI examinations pre-dCRT (within five days before dCRT) and post-dCRT (2–3 weeks after the start of dCRT) on a 3.0T MR scanner (Ingenia 3.0 T; Philips Medical Systems, Best, the Netherlands), with a 32-channel dStream Torso coil. Patients were trained in breath-holding before MRI examination and instructed to avoid swallowing during the scan.</p>", "<p id=\"Par13\">Axial BOLD MR images were obtained using the respiratory-triggered multiple fast field echo (mFFE) sequence. The scan parameters were as follows: repetition time (TR), 100 ms; range of echo time (TE), 4–40 ms; flip angle, 27°; slice thickness, 5 mm; interslice gap, 1.5 mm. field of view (FOV), 400 × 400 mm; slices, 12. The corresponding T2* mappings were automatically generated. Axial T2-weighted (T2W) images were collected as high-resolution structural maps using a respiratory-triggered turbo spin-echo sequence (TR, 1000 msec; TE, 80 msec; matrix, 260 × 228; section thickness, 5 mm; gap, 0.5 mm; field of view (FOV), 390 × 390 mm; slices, 32).</p>", "<title>Image analysis</title>", "<p id=\"Par14\">All MR images were transmitted into the workstation (Extended MR WorkSpace 2.6.3.5; Philips Medical Systems) and were reviewed together by two radiologists (X.X., X.X.) with eight and 11 years of experience in MRI, respectively, who were blinded to clinicopathological information of the patients.</p>", "<p id=\"Par15\">The location of esophageal cancer was identified on T2-weighted (T2W) images. Esophageal cancer usually presents as a thickening of the esophageal wall or a mass lesion. On T2W images, normal esophageal mucosa appeared isointense, submucosa showed hyperintense and muscularis propria showed iso to hypointense [##REF##28670162##23##]. The tumor appeared slightly hypointense compared with mucosa and muscularis propria, but hyperintense compared with submucosa.</p>", "<p id=\"Par16\">The BOLD MR images were loaded into SPIN software (Magnetic Resonance Innovations Inc., Detroit, Michigan), and the corresponding color-coded R2* maps and T2* mapping of the lesion was automatically generated. After referring to corresponding T2W images, three oval region of interests (ROIs) were drawn by the two radiologists at the largest tumor area slice on BOLD MR images and were simultaneously copied to T2* mapping images. The three ROIs covered the solid part of the tumor as much as possible to avoid macroscopically visible necrosis or cystic degeneration and adjacent tissues (Fig. ##FIG##2##3##). If the lesion had majorly shrunken after dCRT, the ROIs were placed at the same region of pre-treated tumor after referring to the previous MR images [##REF##27489868##24##]. The average value of three ROIs were calculated as the final data. Based on the ROI, the T2* value of the lesion was acquired. Furthermore, the R2* value of the lesion was calculated as follows: R2* = 1/T2*. The changes of R2* values (∆R2* and ∆%R2*) were also calculated. For instance, ∆R2* = post-R2*- pre-R2*, and ∆%R2* = ∆R2* / pre-R2* × 100%, where pre-R2* and post-R2* were R2* values before and 2–3 weeks after dCRT, respectively.</p>", "<p id=\"Par17\">\n\n</p>", "<title>Treatment options</title>", "<p id=\"Par18\">All patients were treated with dCRT. The prescription dose of intensity-modulated radiation therapy (IMRT) was 60–66 Gy in 30–33 fractions (2 Gy for each fraction). The prescribed concurrent chemotherapy was performed with weekly regimen of paclitaxel liposome (50 mg/m<sup>2</sup>) and nedaplatin (25 mg/m<sup>2</sup>) for 4–6 weeks.</p>", "<title>Response evaluation and follow-up</title>", "<p id=\"Par19\">Objective response to treatment was assessed one month after the end of dCRT according to the Response Evaluation Criteria in Solid Tumors (RECIST), including complete response (CR), partial response (PR), progressive disease (PD) and stable disease (SD). All patients were followed-up at 1, 3, and 6 months, and then every 6 months after treatment until death. The time from the date of dCRT initiation to death due to any cause was recorded as overall survival (OS). The follow-up was completed on March 25, 2022.</p>", "<title>Statistical analysis</title>", "<p id=\"Par20\">The Shapiro-Wilk test was used to check the normality assumption for all parameters. According to the results of Shapiro-Wilk test (Supplemental Table ##SUPPL##0##1##), the variations of R2<sup>*</sup> at pre- and post-dCRT were observed by Wilcoxon test. Independent samples t-test (normality) or Mann-Whitney U test (non-normality) was used to compare differences of parameters between the CR and non-CR groups. Clinical characteristics of different groups were compared using Fisher’s exact tests. The diagnostic performance of the parameters in predicting treatment response was tested with receiver operating characteristic (ROC) curve analysis. The 3-year OS of variables were compared by Kaplan Meier curve and log rank test. Variables with <italic>P</italic> &lt; 0.05 in the univariate analysis were finally included in the multivariable analysis and a stepwise backward method was used in Cox proportional hazards regression analysis. Statistical analyses were performed with SPSS (v.22.0 for Microsoft Windows x64, SPSS, Chicago, IL). ROC analysis was performed using MedCalc Statistical Software version 19 (MedCalc Software bvba, Ostend, Belgium; <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.medcalc.org\">https://www.medcalc.org</ext-link>; 2019). A two-tailed P value &lt; 0.05 was considered as statistically significant.</p>" ]
[ "<title>Results</title>", "<title>Patient characteristics</title>", "<p id=\"Par21\">Among 28 patients with ESCC, the cases with CR, PR, PD and SD were 17 (60.71%), eight (28.57%), one (3.57%) and two (7.14%), respectively. PR, PD and SD patients were classified as the non-CR group. The median follow-up time was 61.1 (2–71) months. Moreover, 13 (46.43%) patients died of ESCC, one (3.57%) died of respiratory failure caused by radioactive pneumonia and 14 (50.00%) patients survived. The baseline characteristics of all patients are listed in Table ##TAB##0##1##. There was no significant difference in the baseline characteristics between the CR and non-CR groups (all <italic>P</italic> &gt; 0.05).</p>", "<p id=\"Par22\">\n\n</p>", "<title>Comparison of R2* values at pre-dCRT and post-dCRT</title>", "<p id=\"Par23\">In the CR group, the R2* values were significantly increased from 38.20 ± 10.26 s<sup>− 1</sup> to 48.89 ± 8.19 s<sup>− 1</sup> (<italic>P</italic> = 0.003) after 2–3 weeks of dCRT (Fig. ##FIG##3##4##). In contrast, the R2* values were decreased by 37.66 ± 8.12 s<sup>− 1</sup> from 40.61 ± 10.18 s<sup>− 1</sup> in the non-CR group (<italic>P</italic> = 0.286).</p>", "<p id=\"Par24\">\n\n</p>", "<title>Differences of R2* values between the CR and non-CR groups</title>", "<p id=\"Par25\">Table ##TAB##1##2## shows the differences of R2* values between the CR and non-CR groups before and after dCRT. The post-R2*, ∆R2* and ∆%R2* values in the CR group were significantly higher than those in the non-CR group (<italic>P</italic> = 0.002, 0.003, and 0.006, respectively). While there was no significant difference in pre-R2* between the CR and non-CR groups (<italic>P</italic> = 0.264).</p>", "<p id=\"Par26\">\n\n</p>", "<title>Prediction of early tumor response</title>", "<p id=\"Par27\">Table ##TAB##2##3## shows the diagnostic performance of R2* values in differentiating CR from non-CR patients. After 2–3 weeks of dCRT, the post-R2*, ∆R2, and ∆%R2* showed good prediction of tumor response with an area under the curve (AUC) of 0.829, 0.813, and 0.813, respectively (Fig. ##FIG##4##5##).</p>", "<p id=\"Par28\">\n\n</p>", "<p id=\"Par29\">\n\n</p>", "<title>Survival analysis</title>", "<p id=\"Par30\">The overall 1-year, 2-year, and 3-year survival rates after dCRT were 75.00%, 60.71%, and 53.57%, respectively. We used X-tile to obtain the optimal thresholds of the R2*-related parameters [##UREF##3##25##]. According to the optimal thresholds, R2*-related parameters were divided into two groups (Table ##TAB##3##4##). The 3-year OS rate of patients with ∆R2* &gt;-7.54 s<sup>− 1</sup> were significantly longer than those with ∆R2* ≤ -7.54 s<sup>− 1</sup> (72.37% vs. 0.00%; hazard ratio, HR = 0.196; 95% confidence interval, 95% CI = 0.047–0.807; <italic>P</italic> = 0.024), based on multivariate analysis (Fig. ##FIG##5##6##). The ESCC patients with a CR were associated with better survival prognosis of dCRT (HR = 0.238, 95% CI = 0.059–0.963; <italic>P</italic> = 0.044).</p>", "<p id=\"Par31\">\n\n</p>", "<p id=\"Par32\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par33\">Hypoxia plays a vital role in tumor microenvironment by allowing development and maintenance of cancer cells [##UREF##4##26##]. Hypoxia is a major hindrance for effective anti-cancer therapy and the main reason for failure of most anti-cancer drugs and radiotherapy. Therefore, early monitoring of hypoxic status in tumors can predict the efficacy during treatment, which can help with timely adjustment of treatment plans to avoid extra chemoradiotherapy toxicity and economic burden. BOLD MRI can non-invasively evaluate tissue oxygenation metabolism, and R2* quantification reflects the changes of deoxyhemoglobin content. This study found that the post-R2* and change of R2* values in the CR group were significantly higher than those in the non-CR group, and ∆R2* was an independent prognostic factor of ESCC after dCRT. These findings suggested that BOLD MRI might be useful in evaluating early tumor response and forecasting the prognosis of patients with ESCC who underwent dCRT, and monitoring the changes of tumor oxygenation during treatment.</p>", "<p id=\"Par34\">We found that the R2* values significantly increased after dCRT in CR patients, which might be explained by the increase of local deoxyhemoglobin content due to the reduction of neovascularization in the tumor after treatment, as well as the decrease of vascular permeability and blood flow [##REF##24763631##20##]. A study on dynamic contrast-enhanced MRI also revealed that the K<sup>trans</sup> and K<sup>ep</sup> values, which reflected the tumor microcirculation perfusion and vessel permeability, decreased significantly after chemoradiotherapy in patients with ESCC [##UREF##5##27##]. Increase in R2* value was also found after chemoradiotherapy in cervical cancer [##REF##24763631##20##] and breast cancer [##REF##20858850##22##]. However, in this study, there was no significant difference in the R2* value of non-CR patients before and after treatment. The results suggested that the tumor was hypoxic after treatment, and patients with increased R2* values might be more sensitive to dCRT.</p>", "<p id=\"Par35\">Previous studies had reported that R2* values might have the potential as an imaging biomarker for predicting breast cancer response to treatment [##REF##25581675##28##]. This study showed that the R2* values were significantly higher in the CR group than in the non-CR group after 2–3 weeks of dCRT. Patients in the CR group were more likely to exhibit tumor shrinkage and fibrosis after dCRT, which may lead to local tumor hypoxia with higher R2* value. This means that early change in R2* values might indicate short-term outcomes for ESCC. Therefore, the post-R2* differences in this study were clinically relevant. The findings showed that higher R2*-related parameter values in the early stage after dCRT showed good response. Once post-R2* and change in R2* values were known, it might be able to screen out patients with CR as early as possible after dCRT (2-3weeks after treatment), which might help to provide reference value for selecting appropriate consolidation treatment for patients achieving non-CR.</p>", "<p id=\"Par36\">Oxygenation of tumors before treatment is important for disease control [##REF##25581675##28##], and pretreatment R2* value was a significant independent predictor of progression and survival in patients [##REF##31016443##21##]. In this study, patients with high pre-R2* had significantly worse survival than those with low pre-R2* (3-year OS rate, 0.00% vs. 76.19%; <italic>P</italic> = 0.002) in the univariate analysis, but it was not an independent predictor in the multivariate analysis. Moreover, a high change of R2* value (∆R2*) was an independent prognostic factor of ESCC after dCRT. However, the small sample size and lack of confounder (age, gender, location, and clinical staging) control made the final statistical significance of our results challenging. Therefore, ∆R2* might be unstable in evaluating prognosis. In addition, early treatment response had an impact on the prognosis of esophageal cancer patients. It might be explained by the fact that non-CR patients with residual tumor were more susceptible to recurrence and metastasis, resulting in a lower survival rate. ∆R2* and treatment response might be helpful in assessing prognosis, but needed to be validated with a large sample size.</p>", "<p id=\"Par37\">In interpreting our findings, several limitations must be taken into account. This study had several limitations. First, the main limitation of this study was the relatively small sample size, which might not be able to strongly support definitive statements about the diagnostic efficacy of our findings. In clinical practice, BOLD MRI was not mandatory for the patients with ESCC, and our inclusion criteria were strict, which resulting in a small sample size of eligible cases. The primary aim of this study was to preliminarily attempt to find an effective non-invasive evaluation biomarker for dCRT, hoping to provide a feasibility foundation for further research by expanding the sample size. Second, there was a lack of control for important confounders in survival analysis. Due to the small sample size in this study, it was not possible to include too many parameters in the multivariate analysis. Nevertheless, in univariate analysis, the important confounders (age, gender, location, and clinical stage) were balanced among the different groups without significant statistical differences. If controlling for multiple hypothesis tests, some of our findings might not meet statistically significant. Hence, the findings might have limited utility for prognosis. Lastly, besides oxygenation, R2* value is also affected by blood volume, blood flow, hemoglobin, etc. Therefore, future studies will be conducted by expanding the sample size, controlling for important confounders, and exploring the mechanism of R2* value reflecting hypoxia to confirm the findings.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par38\">This preliminary study demonstrated that the R2* value might be a useful hypoxia non-invasive biomarkerfor assessing response and prognosis of ESCC treated with dCRT. BOLD MRI might be used as a potential tool for evaluating tumor oxygenation metabolism, which is routinely applied in clinical practice and beneficial to clinical decision-making. A large sample size was needed for further follow-up studies to confirm the findings.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">To find a useful hypoxia non-invasive biomarker for evaluating early treatment response and prognosis to definitive chemoradiotherapy (dCRT) in patients with esophageal squamous cell carcinoma (ESCC), using blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI).</p>", "<title>Methods</title>", "<p id=\"Par2\">The R2* values were obtained pre- and 2–3 weeks post-dCRT in 28 patients with ESCC using BOLD MRI. Independent samples t-test (normality) or Mann-Whitney U test (non-normality) was used to compare the differences of R2*-related parameters between the complete response (CR) and the non-CR groups. Diagnostic performance of parameters in predicting response was tested with receiver operating characteristic (ROC) curve analysis. The 3-year overall survival (OS) was evaluated using Kaplan Meier curve, log rank test, and Cox proportional hazards regression analysis.</p>", "<title>Results</title>", "<p id=\"Par3\">The post-R2*, ∆R2*, and ∆%R2* in the CR group were significantly higher than those in the non-CR group (<italic>P</italic> = 0.002, 0.003, and 0.006, respectively). The R2*-related parameters showed good prediction of tumor response, with AUC ranging from 0.813 to 0.829. The 3-year OS rate in patients with ∆R2* &gt;-7.54 s<sup>− 1</sup> or CR were significantly longer than those with ∆R2* ≤ -7.54 s<sup>− 1</sup> (72.37% vs. 0.00%; Hazard ratio, HR = 0.196; 95% confidence interval, 95% CI = 0.047–0.807; <italic>P</italic> = 0.024) or non-CR (76.47% vs. 29.27%; HR = 0.238, 95% CI = 0.059–0.963; <italic>P</italic> = 0.044).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The preliminary results demonstrated that the R2* value might be a useful hypoxia non-invasive biomarker for assessing response and prognosis of ESCC treated with dCRT. BOLD MRI might be used as a potential tool for evaluating tumor oxygenation metabolism, which is routinely applied in clinical practice and beneficial to clinical decision-making. A large sample size was needed for further follow-up studies to confirm the findings.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12880-024-01193-9.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>YZ, XW and WR collected relevant data, SL and WR analyzed and interpreted the patient data regarding the parametric features. HZ and HZ wrote the main manuscript and prepared Figs. ##FIG##0##1##, ##FIG##1##2##, ##FIG##2##3##, ##FIG##3##4##, ##FIG##4##5## and ##FIG##5##6##. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>Nanjing Drum Tower Hospital New Technology Development Fund (No. XJSFZJJ202035), Bethune Young and Middle-aged Physician Scientific Research Ability Training Project (No. BQE-TY-SSPC(7)-N-01), and Special Fund for Clinical Scientific Research of Wu Jieping Medical Foundation (No. 320.6750.2021-01-36).</p>", "<title>Data availability</title>", "<p>Data and material in the study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Competing interests</title>", "<p id=\"Par39\">The authors declare no competing interests.</p>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par40\">This study was approved by the institutional review board of Nanjing Drum Tower Hospital, and informed consent was waived for patients in this retrospective study.</p>", "<title>Consent for publication</title>", "<p id=\"Par41\">Not applicable.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The flowchart of the patients enrolled in this study. CR, complete response; PR, partial response; PD, progressive disease; SD, stable disease</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The flowchart of study design. (<bold>a</bold>) Clinical characteristics and BOLD images of patients with ESCC who were treated with definitive chemoradiotherapy were collected. (<bold>b</bold>) Clinical characteristics and R2* value-related parameters were extracted. (<bold>c</bold>) Statistical analysis. (<bold>d</bold>) Diagnostic performance for predicting response and prognosis were obtained by ROC curve analysis, Cox proportional hazards regression analysis, Kaplan Meier curve and log rank test, respectively. BOLD, blood oxygenation level-dependent; MR, magnetic resonance; ROC, receiver operating characteristic</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>A 62-year-old man with ESCC received definitive chemoradiotherapy (dCRT) and achieved CR. Before dCRT, axial T2W and BOLD images showed a mass lesion at the upper thoracic esophagus (white arrow). On the corresponding color-coded R2* maps, blue-green represents low-medium R2* values, reflecting low-medium concentration of deoxyhemoglobin. Three oval regions of interest of the lesion were drawn, with a mean value of 30.58 s<sup>-1</sup>. Approximately 2–3 weeks after dCRT, T2W, BOLD, and corresponding color-coded R2* maps showed that the mass had shrunken (white arrow). Red represents high R2* values, reflecting high concentration of deoxyhemoglobin. The R2* value of the lesion increased to 56.79 s<sup>-1</sup></p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Box-whisker plots of R2* values in ESCC at pre- and post-dCRT in the CR group. The horizontal line through each box represents the median value and the box represents data of 95% confidence intervals. Graph shows that R2* values of esophageal cancer had significantly increased at 2–3 weeks post-dCRT in the CR group (<italic>P</italic> = 0.003)</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>ROC curves of R2* values in early identification of CR from non-CR in ESCC. The post-R2* (2–3 weeks post-dCRT), ∆R2*, ∆%R2* and the fitting parameter (pre-R2* combined with post-R2*) values showed good prediction performance, yielding an AUC of 0.829, 0.813, and 0.813 (<bold>A</bold>∆<bold>C</bold>), respectively</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Kaplan–Meier survival curves of overall survival (OS) in patients. Kaplan–Meier survival curves showing 3-year OS for patients with a ∆R2* value ≤ -7.54 s<sup>-1</sup> compared to those with a ∆R2* value &gt; -7.54 s<sup>-1</sup> (<bold>A</bold>), and patients with a CR compared to those with a non-CR (<bold>B</bold>). Both P values obtained by log rank test were &lt; 0.001</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Clinical characteristics of patients</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Characteristics</th><th align=\"left\">All Patients</th><th align=\"left\">non-CR</th><th align=\"left\">CR</th><th align=\"left\" rowspan=\"2\">\n<italic>P</italic>\n</th></tr><tr><th align=\"left\">(<italic>n</italic> = 28)</th><th align=\"left\">(<italic>n</italic> = 11)</th><th align=\"left\">(<italic>n</italic> = 17)</th></tr></thead><tbody><tr><td align=\"left\">\n<bold>Age at diagnosis (years)</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">1.000</td></tr><tr><td align=\"left\">≤ 60</td><td char=\".\" align=\"char\">9 (32.14%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td char=\".\" align=\"char\">6 (21.43%)</td><td align=\"left\"/></tr><tr><td align=\"left\">&gt; 60</td><td char=\".\" align=\"char\">19 (67.86%)</td><td char=\".\" align=\"char\">8 (28.57%)</td><td char=\".\" align=\"char\">11 (39.29%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Gender</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">1.000</td></tr><tr><td align=\"left\">Male</td><td char=\".\" align=\"char\">5 (17.86%)</td><td char=\".\" align=\"char\">2 (7.14%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Female</td><td char=\".\" align=\"char\">23 (82.14%)</td><td char=\".\" align=\"char\">9 (32.14%)</td><td char=\".\" align=\"char\">14 (50.00%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Location</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.062</td></tr><tr><td align=\"left\">Cervical</td><td char=\".\" align=\"char\">7 (25.00%)</td><td char=\".\" align=\"char\">1 (3.57%)</td><td char=\".\" align=\"char\">6 (21.43%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Upper</td><td char=\".\" align=\"char\">11 (39.29%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td char=\".\" align=\"char\">8 (28.57%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Middle</td><td char=\".\" align=\"char\">10 (35.71%)</td><td char=\".\" align=\"char\">7 (25.00%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Clinical stage</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.424</td></tr><tr><td align=\"left\">II</td><td char=\".\" align=\"char\">10 (35.71%)</td><td char=\".\" align=\"char\">5 (17.86%)</td><td char=\".\" align=\"char\">5 (17.86%)</td><td align=\"left\"/></tr><tr><td align=\"left\">III</td><td char=\".\" align=\"char\">12 (42.86%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td char=\".\" align=\"char\">9 (32.14%)</td><td align=\"left\"/></tr><tr><td align=\"left\">IVA</td><td char=\".\" align=\"char\">6 (21.43%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td char=\".\" align=\"char\">3 (10.71%)</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Differences in the R2* values between the CR and the non-CR groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Parameters</th><th align=\"left\">Non-CR</th><th align=\"left\">CR</th><th align=\"left\">\n<italic>P</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Pre-R2* (s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">38.61 (13.52)</td><td char=\".\" align=\"char\">34.75 (8.98)</td><td char=\".\" align=\"char\">0.264</td></tr><tr><td align=\"left\">Post-R2* (s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">37.66 ± 8.12</td><td char=\".\" align=\"char\">48.99 ± 8.82</td><td char=\".\" align=\"char\">0.002</td></tr><tr><td align=\"left\">∆R2*(s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">-2.95 ± 9.59</td><td char=\".\" align=\"char\">10.78 ± 11.44</td><td char=\".\" align=\"char\">0.003</td></tr><tr><td align=\"left\">∆%R2*</td><td char=\".\" align=\"char\">-2.85 ± 29.21</td><td char=\".\" align=\"char\">33.87 ± 33.00</td><td char=\".\" align=\"char\">0.006</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Diagnostic performance of R2* values in differentiating CR from non-CR in patients with ESCC</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Parameters</th><th align=\"left\">Cutoff</th><th align=\"left\">Sensitivity</th><th align=\"left\">Specificity</th><th align=\"left\">Accuracy</th><th align=\"left\">AUC</th></tr></thead><tbody><tr><td align=\"left\">Pre-R2* (s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">≤ 36.60</td><td char=\".\" align=\"char\">64.71%</td><td char=\".\" align=\"char\">72.73%</td><td char=\".\" align=\"char\">67.86%</td><td char=\".\" align=\"char\">0.631</td></tr><tr><td align=\"left\">Post-R2* (s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">&gt; 39.71</td><td char=\".\" align=\"char\">88.24%</td><td char=\".\" align=\"char\">81.82%</td><td char=\".\" align=\"char\">85.72%</td><td char=\".\" align=\"char\">0.829</td></tr><tr><td align=\"left\">∆R2*(s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">&gt; 2.76</td><td char=\".\" align=\"char\">76.47%</td><td char=\".\" align=\"char\">81.82%</td><td char=\".\" align=\"char\">78.57%</td><td char=\".\" align=\"char\">0.813</td></tr><tr><td align=\"left\">∆%R2*</td><td char=\".\" align=\"char\">&gt; 7.85</td><td char=\".\" align=\"char\">76.47%</td><td char=\".\" align=\"char\">81.82%</td><td char=\".\" align=\"char\">78.57%</td><td char=\".\" align=\"char\">0.813</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Univariate and multivariate analyses for 3-year overall survival</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variables</th><th align=\"left\" colspan=\"3\">Univariate analysis</th><th align=\"left\" colspan=\"3\">Multivariate analysis</th></tr><tr><th align=\"left\">HR</th><th align=\"left\">95% CI</th><th align=\"left\">P</th><th align=\"left\">HR</th><th align=\"left\">95% CI</th><th align=\"left\">\n<italic>P</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Age (&gt; 60 year)</td><td char=\".\" align=\"char\">1.452</td><td char=\".\" align=\"char\">0.436–4.832</td><td char=\".\" align=\"char\">0.543</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Gender (man)</td><td char=\".\" align=\"char\">0.287</td><td char=\".\" align=\"char\">0.072–1.142</td><td char=\".\" align=\"char\">0.091</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"><sup>§</sup>Location</td><td char=\".\" align=\"char\">0.971</td><td char=\".\" align=\"char\">0.290–3.250</td><td char=\".\" align=\"char\">0.962</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"><sup>§</sup>Clinical stage</td><td char=\".\" align=\"char\">1.270</td><td char=\".\" align=\"char\">0.390–4.132</td><td char=\".\" align=\"char\">0.691</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Pre-R2*(&gt; 42.18 s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">9.175</td><td char=\".\" align=\"char\">2.284–36.862</td><td char=\".\" align=\"char\">0.002</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Post-R2* (&gt; 35.16 s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">0.092</td><td char=\".\" align=\"char\">0.018–0.483</td><td char=\".\" align=\"char\">0.005</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">∆R2* (&gt;-7.54 s<sup>− 1</sup>)</td><td char=\".\" align=\"char\">0.018</td><td char=\".\" align=\"char\">0.003–0.112</td><td char=\".\" align=\"char\">&lt; 0.001</td><td char=\".\" align=\"char\">0.196</td><td char=\".\" align=\"char\">0.047–0.807</td><td char=\".\" align=\"char\">0.024</td></tr><tr><td align=\"left\">∆%R2* (&gt;-12.77)</td><td char=\".\" align=\"char\">0.018</td><td char=\".\" align=\"char\">0.003–0.112</td><td char=\".\" align=\"char\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Response (CR)</td><td char=\".\" align=\"char\">0.078</td><td char=\".\" align=\"char\">0.020–0.308</td><td char=\".\" align=\"char\">&lt; 0.0011</td><td char=\".\" align=\"char\">0.238</td><td char=\".\" align=\"char\">0.059–0.963</td><td char=\".\" align=\"char\">0.044</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>Note</italic>: Data are presented as median (range) or n (%). Location and clinical stage before treatment were according to the American Joint Committee on Cancer (8th edition). CR = complete response</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Note</italic>: Data are presented as mean ± standard deviation (normality) or median (interquartile range) (non-normality). CR = complete response. P values with independent samples t-test (normality) or Mann-Whitney U test (non-normality)</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Note</italic>: CR = complete response; AUC = area under the curve</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Note</italic>: §, Location, Cervical + Upper vs. Middle; Clinical stage, II vs. III + IVA; HR, Hazard ratio; 95% CI, 95% confidence interval</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Huanhuan Zheng and Hailong Zhang contributed equally to this manuscript.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12880_2024_1193_Fig1_HTML\" id=\"d32e344\"/>", "<graphic xlink:href=\"12880_2024_1193_Fig2_HTML\" id=\"d32e367\"/>", "<graphic xlink:href=\"12880_2024_1193_Fig3_HTML\" id=\"d32e404\"/>", "<graphic xlink:href=\"12880_2024_1193_Fig4_HTML\" id=\"d32e684\"/>", "<graphic xlink:href=\"12880_2024_1193_Fig5_HTML\" id=\"d32e898\"/>", "<graphic xlink:href=\"12880_2024_1193_Fig6_HTML\" id=\"d32e1117\"/>" ]
[ "<media xlink:href=\"12880_2024_1193_MOESM1_ESM.docx\"><caption><p><bold>Supplementary Material 1: Supplemental Table 1.</bold> Comparison of P values of R2*-related parameters between non-CR and CR patients with Shapiro-Wilk test for normality assumption</p></caption></media>" ]
[{"label": ["4."], "surname": ["Bedenne", "Michel", "Bouch\u00e9", "Milan", "Mariette", "Conroy", "Pezet", "Roullet", "Seitz", "Herr"], "given-names": ["L", "P", "O", "C", "C", "T", "D", "B", "JF", "JP"], "article-title": ["Chemoradiation followed by surgery compared with chemoradiation alone in squamous cancer of the esophagus: FFCD 9102"], "source": ["J Clin Oncology: Official J Am Soc Clin Oncol"], "year": ["2007"], "volume": ["25"], "issue": ["10"], "fpage": ["1160"], "lpage": ["8"], "pub-id": ["10.1200/JCO.2005.04.7118"]}, {"label": ["5."], "surname": ["Muz", "de la Puente", "Azab", "Azab"], "given-names": ["B", "P", "F", "AK"], "article-title": ["The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy"], "source": ["Hypoxia (Auckland NZ)"], "year": ["2015"], "volume": ["3"], "fpage": ["83"], "lpage": ["92"]}, {"label": ["7."], "surname": ["Yue", "Yang", "Cabrera", "Sun", "Zhao", "Xie", "Zheng", "Ma", "Fu", "Yu"], "given-names": ["J", "Y", "AR", "X", "S", "P", "J", "L", "Z", "J"], "article-title": ["Measuring tumor hypoxia with "], "sup": ["18"], "source": ["Dis Esophagus: Official J Int Soc Dis Esophagus"], "year": ["2012"], "volume": ["25"], "issue": ["1"], "fpage": ["54"], "lpage": ["61"], "pub-id": ["10.1111/j.1442-2050.2011.01209.x"]}, {"label": ["25."], "surname": ["Camp", "Dolled-Filhart", "Rimm"], "given-names": ["RL", "M", "DL"], "article-title": ["X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization"], "source": ["Clin cancer Research: Official J Am Association Cancer Res"], "year": ["2004"], "volume": ["10"], "issue": ["21"], "fpage": ["7252"], "lpage": ["9"], "pub-id": ["10.1158/1078-0432.CCR-04-0713"]}, {"label": ["26."], "surname": ["Al Tameemi", "Dale", "Al-Jumaily", "Forsyth"], "given-names": ["W", "TP", "RMK", "NR"], "article-title": ["Hypoxia-modified Cancer Cell Metabolism"], "source": ["Front cell Dev Biology"], "year": ["2019"], "volume": ["7"], "fpage": ["4"], "pub-id": ["10.3389/fcell.2019.00004"]}, {"label": ["27."], "mixed-citation": ["Sun NN, Liu C, Ge XL, Wang J. Dynamic contrast-enhanced MRI for advanced esophageal cancer response assessment after concurrent chemoradiotherapy. Diagnostic and interventional radiology (Ankara, Turkey) 2018, 24(4):195\u2013202."]}]
{ "acronym": [ "ESCC", "dCRT", "MRI", "BOLD", "T2W", "TR", "TE", "FOV", "mFFE", "ROIs", "IMRT", "RECIST", "CR", "PR", "PD", "SD", "OS", "ROC", "AUC", "HR", "95%CI" ], "definition": [ "Esophageal squamous cell carcinomas", "Definitive chemoradiotherapy", "Magnetic resonance imaging", "Blood oxygenation level-dependent", "T2-weighted", "Repetition time", "Echo time", "Field of view", "Multiple fast field echo", " Region of interests", "Intensity-modulated radiation therapy", "Response Evaluation Criteria in Solid Tumors", "Complete response", "Partial response", "Progressive disease", "Stable disease", "Overall survival", "Receiver operating characteristic", "Area under the curve", "Hazard ratio", "95% confidence interval" ] }
28
CC BY
no
2024-01-14 23:43:45
BMC Med Imaging. 2024 Jan 12; 24:18
oa_package/e2/c1/PMC10787410.tar.gz
PMC10787411
0
[ "<title>Background</title>", "<p id=\"Par37\">Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination and neurodegeneration [##REF##25887774##1##]. In addition to physical limitations, 43–65% of people with MS (PwMS) develop cognitive symptoms that may severely affect daily life functioning and consequently health-related quality of life [##REF##27512050##2##–##REF##30169585##4##]. The most commonly and earliest affected cognitive domains are information processing speed, verbal memory, and visuospatial memory [##REF##29343470##3##, ##REF##33951975##5##].</p>", "<p id=\"Par38\">The impact of cognitive impairment on daily life functioning can be significant, especially since most PwMS are relatively young at disease onset [##REF##29343470##3##]. As such, cognitive impairment is one of the main reasons for unemployment in MS [##REF##23842211##6##, ##REF##26346789##7##]. About 43% of PwMS become unemployed within three years of diagnosis due to fatigue and physical impairment, but also cognitive impairment [##REF##26083386##8##–##UREF##0##10##]. This early unemployment has a large impact on PwMS, their families, and on society in general [##UREF##1##11##]. However, by the time PwMS with self-perceived cognitive problems approach health care professionals, their cognitive deficits are often already advanced and potentially more difficult to treat, suggesting that early intervention might be promising [##REF##28639482##12##, ##REF##10625273##13##].</p>", "<p id=\"Par39\">The need for early intervention is emphasized by a recent study showing that successful response to cognitive rehabilitation depends on the status of the brain’s functional network before the intervention [##UREF##2##14##]. PwMS with a functional connectivity that is more like that of healthy controls were able to benefit from a cognitive rehabilitation program (i.e., these participants significantly improved on neuropsychological tests and had better self-perceived cognitive functioning). However, those PwMS with a less efficient brain network at baseline (indicative of more MS-related pathology) were non-responsive, suggesting the existence of a small window of opportunity for intervention early in the development of the disease [##UREF##2##14##]. Additionally, other studies show that less MS-related brain damage (e.g., higher grey matter volume) are linked to better cognitive rehabilitation outcomes [##REF##31254960##15##–##REF##37528618##17##]. Therefore, it is crucial to identify PwMS at the earliest stages of cognitive impairment to allow for intervention when it is most effective to improve cognitive functioning.</p>", "<p id=\"Par40\">Recent international recommendations for measuring and monitoring cognitive functioning in PwMS propose a baseline cognitive screening and annual follow-up [##REF##30303036##18##]. However, in contrast to these recommendations, neuropsychological testing is not part of standard MS-care in current clinical practice in the Netherlands (and several other countries) [##UREF##3##19##]. Consequently, a good reference assessment of baseline cognitive performance is often lacking, hampering the detection of the first subtle changes in cognition. Detecting these early changes is particularly difficult when PwMS already experience difficulties in daily life functioning but still perform (above) average on neuropsychological assessments [##REF##29343470##3##]. The main reason for not following the international recommendations is the lack of time and specialized personnel to assess cognitive functioning [##UREF##3##19##]. As digital assessment tools may lower the threshold for systematic assessment of cognitive functioning in PwMS, we recently developed a self-explanatory, time-efficient digital screening tool, the Multiple Screener<sup>©</sup> [##REF##31760365##20##].</p>", "<p id=\"Par41\">The Multiple Screener<sup>©</sup> consists of an adjusted version of the validated and recommended BICAMS (Brief International Cognitive Assessment for MS) paper-and-pencil assessment [##REF##22190573##21##] and takes 15 min to complete. It assesses the most frequently impaired cognitive domains in MS: information processing speed via the Symbol Digit Modalities Test (SDMT [##UREF##4##22##]), verbal learning and memory via the Dutch version of California Verbal Learning Test Second Edition (CVLT-II [##UREF##5##23##–##UREF##6##25##]), and visuospatial learning and memory via the Spatial Recall Test (SPART [##UREF##7##26##]) [##REF##31760365##20##]. In addition, the Multiple Screener<sup>©</sup> also includes questionnaires on depression and anxiety [##REF##6880820##27##], fatigue [##REF##15008502##28##] and self-perceived cognitive symptoms [##REF##12617275##29##], taking into account psychological factors when screening for cognitive deficits in MS. The main advantages of the Multiple Screener<sup>©</sup> are that it does not require specialized personnel for administration (i.e., PwMS can perform the tests on their own), has automated scoring, and is time-efficient. The Multiple Screener<sup>©</sup> has been tested in 236 healthy controls and normative data are available [##REF##31760365##20##]. In healthy controls, the correlations between the Multiple Screener<sup>©</sup> and the paper-and-pencil versions of the neuropsychological tests have been shown to be good to excellent [##REF##31760365##20##]. However, a next essential step before the Multiple Screener<sup>©</sup> can be used in clinical practice is to investigate its diagnostic accuracy especially in identifying PwMS with mild cognitive impairment according to a reference standard (the Minimal Assessment of Cognitive Function in Multiple Sclerosis, MACFIMS [##REF##16981607##30##]), allowing for timely identification.</p>", "<title>Objectives</title>", "<p id=\"Par42\">As part of a larger research project (i.e., the <italic>Don’t be late! study,</italic> see Table ##TAB##0##1##) the primary objective of this study is to determine diagnostic accuracy of the Multiple Screener<sup>©</sup> in a representative Dutch sample of PwMS. Specifically, we aim to determine how well the Multiple Screener<sup>©</sup> can differentiate between PwMS with no cognitive impairment, mild cognitive impairment, and cognitive impairment according to the reference-standard (MACFIMS [##REF##16981607##30##]). In a second step we aim to confirm the observed diagnostic accuracy of the Multiple Screener<sup>©</sup> in differentiating between PwMS with no cognitive impairment, mild cognitive impairment, and cognitive impairment in an independent subset of PwMS. When reporting on the diagnostic accuracy of the Multiple Screener<sup>©</sup>, the Standards for Reporting Diagnostic Accuracy guidelines from the Equator-Network (STARD 15, [##REF##26511519##31##]) will be followed.\n</p>", "<p id=\"Par43\">The study has the following secondary objectives:<list list-type=\"order\"><list-item><p id=\"Par44\">To determine the test–retest reliability of the Multiple Screener<sup>©</sup>;</p></list-item><list-item><p id=\"Par45\">To determine how cognitive, psychological, work-related, and health-related quality of life outcomes are related.</p></list-item></list></p>" ]
[ "<title>Methods</title>", "<title>Design and setting</title>", "<p id=\"Par46\">The present study is a cross-sectional multicentre study in which a representative sample of 750 PwMS will be included. In the 12 participating Dutch hospitals, demographical and medical information will be collected, and cognitive functioning of PwMS will be assessed with both the reference standard (MACFIMS) and the Multiple Screener<sup>©</sup>. In line with international validation guidelines [##REF##22799620##32##], the assessment of the Multiple Screener<sup>©</sup> will be repeated within 3 weeks after the hospital visit in a small subset of participants (<italic>N</italic> = 30) in order to determine test–retest reliability. Finally, all participants will fill in several online questionnaires at home.</p>", "<title>Participants</title>", "<title>Recruitment and consent</title>", "<p id=\"Par47\">We aim to recruit a representative sample of PwMS in the Netherlands that visit the neurologist in light of their MS. We will include PwMS with a variety in MS types (relapsing remitting, secondary progressive (85% of the population) and primary progressive (15%)), disease duration and age. All participating hospitals are asked to provide a patient information letter for a set period of time to all PwMS that visit the outpatient clinic, independent of cognitive status, employment status, disease status and meeting the in- and exclusion criteria. Contact details of PwMS that give permission to be approached about participation are shared with the researchers from the Amsterdam UMC, Vrije Universiteit Amsterdam. After at least one week, they contact the potential participant to provide additional information if requested (or refer to an independent physician) and to ask whether they would like to participate in the study. When PwMS decide to participate, the researcher will screen the subjects for eligibility via telephone (see below for inclusion and exclusion criteria) such that an unnecessary hospital visit will be avoided when a subject is not eligible. In case of a positive screening outcome, a visit for the assessment will be scheduled at which written informed consent will be obtained.</p>", "<title>Inclusion criteria</title>", "<p id=\"Par48\">To be eligible to participate in this study, people must fulfil the following criteria: a confirmed MS diagnosis according to the McDonald 2017 criteria [##REF##29275977##33##], age between 18 and 67 years, no changes in disease modifying therapy within the last 3 months, and no relapse or steroid treatment six weeks prior to the study visit.</p>", "<title>Exclusion criteria</title>", "<p id=\"Par49\">Participants will be excluded from participation in this study if they have other neurological or psychiatric comorbidities that can potentially influence cognitive functioning, a current or history of drug or alcohol abuse, have insufficient vison or hearing, or are unable to speak or read Dutch<bold>.</bold> The reasons for excluding participants from the current study will be documented.</p>", "<title>Ethical approval</title>", "<p id=\"Par50\">The study will be conducted according to the principles of the Declaration of Helsinki (2013) and in accordance with the Dutch Medical Research Involving Human Subjects Act (WMO). The Medical Ethical Committee (METC) of the Amsterdam UMC, Vrije Universiteit Amsterdam has approved this study (METC 2021.0707) on 4 May 2022.</p>", "<title>Measures and procedures</title>", "<title>Demographic and clinical characteristics</title>", "<p id=\"Par51\">During the assessment at the participating hospitals, information on demographical and clinical characteristics will be collected from participants and their medical file. The following characteristics will be collected: age in years, sex, educational level (Dutch Verhage scale), work status, date of diagnosis, MS subtype, MS severity assessed with the telephone version of the Expanded Disability Status Scale (EDSS) [##REF##6685237##34##], medication usage, medical history, and comorbidities.</p>", "<title>Neuropsychological assessment</title>", "<p id=\"Par52\">Participants will undergo an extensive neuropsychological assessment (120–150 min) at the location of the participating site. The assessment consists of the Multiple Screener<sup>©</sup>, the MACFIMS test battery [##REF##16981607##30##], a social cognition test, performance validity tests and an assessment of awareness of cognitive functioning. Parallel versions will be used for the tests that are overlapping between the MACFIMS and Multiple Screener<sup>©</sup> and the order of administration will be counterbalanced to minimize learning effects and influence of fatigue.</p>", "<title>Multiple Screener<sup>©</sup></title>", "<p id=\"Par53\">The Multiple Screener<sup>©</sup> is a digital tool aiming to assess cognitive functioning in PwMS. It is a digital, self-explanatory version of the validated and recommended BICAMS [##REF##22190573##21##] and takes 15 min to complete. It includes the following three tests:<list list-type=\"bullet\"><list-item><p id=\"Par54\">Digital version of the CVLT-II [##UREF##5##23##–##UREF##6##25##]: Verbal learning and memory. The ability to learn 16 auditory presented semantically related words is examined over five trials. After each trial participants are asked to type the remembered words (direct recall). The total number of the correctly remembered words is calculated.</p></list-item><list-item><p id=\"Par55\">Digital version of the SDMT [##UREF##4##22##]: Processing speed and working memory. Nine pairs of digits and symbols are visually presented. Participants are asked to type the numbers associated with the paired symbols as fast as possible. The total number of correct answers within 90 s is calculated.</p></list-item><list-item><p id=\"Par56\">Digital version of the SPART [##UREF##7##26##]: Visuospatial memory. A 6 × 6 grid with 10 black checkers is displayed three times for ten seconds. After each time, an empty grid is displayed with ten black checkers next to it. Participants must swipe the black checkers to the correct places in the empty grid to match what they observed. The total number of correctly placed checkers is calculated. See Fig. ##FIG##0##1## for an illustration of the SDMT and the SPART.</p></list-item></list></p>", "<p>The software of the Multiple Screener<sup>©</sup> is produced by the manufacturer Sherpa B.V. In accordance with the legislation of the Medical Device Directive, the software is qualified as a medical device, classified in risk class I (low risk), reported to FARMATEC-CIBG-VWS, and CE-certified by the manufacturer.</p>", "<p>A subset of participants (<italic>n</italic> = 30) will be invited to return to the hospital within 3 weeks after the initial assessment to complete The Multiple Screener<sup>©</sup> for a second time to determine the test–retest reliability.</p>", "<title>MACFIMS</title>", "<p id=\"Par59\">The MACFIMS is an internationally renowned and well-validated, 90-min, paper-and-pencil test battery that is commonly used to determine cognitive impairment in MS. It consists of tests for verbal and visuospatial learning and memory and information processing speed (cf. the Multiple Screener<sup>©</sup>) and in addition tests for language and working memory, visuospatial orientation, and executive functioning [##REF##16981607##30##]. The tests and corresponding cognitive domain(s) are summarized in Table ##TAB##1##2##.\n</p>", "<title>Performance validity</title>", "<p id=\"Par60\">The Amsterdam Short Term Memory Test (ASTM) [##REF##9071640##39##] will be used to assess performance validity in all participants. In case the ASTM indicates underperformance (cut-off of ≤ 84; [##UREF##11##40##]) the Rey 15-item Test (higher specificity compared to the ASTM) [##UREF##12##41##] will additionally be performed.</p>", "<title>Social cognition</title>", "<p id=\"Par61\">Social cognition and in particular affective theory of mind (i.e., the ability to recognise the thought or feelings of others) will be measured with the revised version of the Reading the Mind in the Eyes Test [##UREF##13##42##].</p>", "<title>Awareness of cognitive functioning</title>", "<p id=\"Par62\">Finally, to assess (online) awareness of global cognitive functioning, a subset of the participants (<italic>N</italic> = 200) will be asked to estimate their own performance immediately before and after completion of the MACFIMS battery. More specifically, they will be asked to estimate what percentile score they believe that they would receive for the overall test battery if compared with a randomly selected demographically matched peer group. A normal distribution including brief explanations of percentiles scores (inspired by Rothlind et al. [##REF##28034850##43##]) will serve as a visual aid for participants.</p>", "<title>Questionnaires</title>", "<p id=\"Par63\">To reduce the burden on the day in the hospital, participants will fill out several online questionnaires at home (for an overview of the questionnaires see Table ##TAB##2##3##). Participants will be asked to complete the questionnaires within one week after the hospital visit to ensure that the collected data most closely resembles the status of the participant during the hospital visit. The researcher will send reminders if the questionnaires have not been returned.\n</p>", "<title>Outcomes</title>", "<title>Primary outcome</title>", "<p id=\"Par64\">The primary outcome measures for the first study objective are sensitivity, specificity, negative and positive predictive value, and the receiver-operating characteristic of the Multiple Screener<sup>©</sup>.</p>", "<title>Secondary outcomes</title>", "<p id=\"Par65\">A secondary outcome measure is the test–retest reliability (i.e., intraclass correlation coefficients) of the Multiple Screener<sup>©</sup>. Additionally, secondary outcome measures include the relationships between cognitive functioning (as measured with the Multiple Screener<sup>©</sup> and the MACFIMS test battery [##REF##16981607##30##]) with the following measures (the hypothesized directions of these relationships are summarized in Table ##TAB##3##4##):<list list-type=\"order\"><list-item><p id=\"Par66\"><italic>Psychological measures:</italic> self-perceived cognitive functioning [##REF##12617275##29##], awareness of cognitive functioning [##REF##28034850##43##], physical and psychological impact of MS [##REF##11335698##45##], mood [##REF##6880820##27##], fatigue [##REF##15008502##28##], personality traits [##UREF##15##50##, ##REF##16768595##52##], stressful life events [##REF##2399824##53##], resilience [##REF##16602815##48##] and mastery [##UREF##14##49##]</p></list-item><list-item><p id=\"Par67\"><italic>Patient-reported health-related quality of life</italic> [##REF##17277259##44##]</p></list-item><list-item><p id=\"Par68\"><italic>Work-related measures:</italic> MS-related work difficulties [##REF##23786346##55##], work productivity and activity impairment [##REF##10146874##54##], negative work events and work accommodations [##UREF##17##57##]</p></list-item><list-item><p id=\"Par69\"><italic>Health and lifestyle measures:</italic> Physical exercise, smoking, alcohol, diet, sleep, BMI, household composition, and social activities.</p></list-item></list></p>", "<title>Power calculation</title>", "<p id=\"Par70\">Because the Multiple Screener<sup>©</sup> is aimed at assessing cognitive decline, especially sensitivity to detect (mild) cognitive impairment should be high, while a relatively lower degree of specificity can be tolerated. Based on accuracy values from the paper–pencil version of the Multiple Screener<sup>©</sup> (BICAMS) in MS and comparable cognitive screening instruments frequently used in people with Parkinson’s disease, we aim for sensitivity values of at least 0.80 and specificity values of at least 0.70 [##UREF##18##58##, ##REF##23034066##59##]. As reported by Amato et al. [##REF##11594918##60##] we expect that approximately 50% of PwMS at the outpatient clinics will classify as having no cognitive impairment (i.e., cognitively preserved; CP), 30% will classify as having mild cognitive impairment (MCI), and 20% will classify as having overt cognitive impairment (CI). Based on these prevalence estimations, a minimum sample size of 100 will be required to detect sensitivity values of at least 0.80 with a power of 80% and alpha threshold of 0.05 [##REF##27891446##61##]. In total 198 participants will be required to detect specificity values of at least 0.70 with identical power and significance level. However, a sample size of 300 is recommended to reliably evaluate accuracy values of screening tools [##REF##27891446##61##]. As such, for our primary objective we aim to include 300 PwMS. Moreover, we aim to confirm the accuracy of the Multiple Screener<sup>©</sup> in an independent sample of at least 150 PwMS (i.e., another subset of our sample).</p>", "<p id=\"Par71\">This study is part of a larger research project and a subset of participants from the current study (i.e., participants with mild cognitive impairment) will be selected for the intervention study of the second work package (see Table ##TAB##0##1##). Therefore, the overall required sample size (<italic>N</italic> = 750) is based on the power calculation for the intervention study. For additional information, the reader is referred to Aarts et al. [##UREF##19##62##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par72\">Data will be analysed using R Studio software (at least version 4.2.1; [##UREF##20##63##]) and IBM SPSS Statistics (at least version 28 [##UREF##21##64##]). In case of non-normality, data will be presented as median and inter-quartile range and transformed for further analyses if appropriate or non-parametric tests will be applied. Participants with missing data and outliers will be excluded for that particular analysis. A <italic>p</italic>-value of 0.05 will be considered as statistically significant for all analyses.</p>", "<title>Primary study parameters</title>", "<p id=\"Par73\">For our primary objective we will determine sensitivity, specificity, positive and negative predictive values of the Multiple Screener<sup>©</sup> as compared to the MACFIMS. Based on previous definitions for cognitive impairment among PwMS [##REF##28179464##65##], participants will be divided into three subgroups depending on their severity of cognitive impairment. Participants scoring at least 2 standard deviations (SDs) below the mean normative values on at least 2 out of 6 cognitive domains assessed with MACFIMS will be classified as having CI. Participants who score 1 to 1.99 SDs below the mean normative values on at least 1 cognitive domain and/or at least 2 SDs below the mean normative values on 1 cognitive domain (not fulfilling the CI criteria) will be classified as having MCI. The remaining participants will be defined as CP [##REF##28179464##65##]. For the Multiple Screener, participants scoring at least 2 SDs below the mean normative values on at least 1 of the 3 tests will be classified as CI. Participants scoring 1 to 1.99 SDs below the mean normative values on at least 1 of the 3 tests will be classified as MCI. The remaining participants will be defined as CP. Overall, regression-based norms adjusted for age, sex, and education will be used for individual cognitive tests before determining cognitive status.</p>", "<p id=\"Par74\">Participants' cognitive status will be determined via the MACFIMS and will be investigated in relation to the scores detected with Multiple Screener<sup>©</sup>. All accuracy values will be calculated separately for the detection of MCI and CI (one against all approach for multiclass classification) and will be presented as percentages. Additionally, receiver-operating characteristic (ROC) analyses will be performed to determine overall accuracy and optimal cut-off scores of the Multiple Screener<sup>©</sup> for detecting MCI and CI in people with MS. Once we have determined accuracy values and optimal cut-off scores in 300 participants, we will test these in another subset of at least 150 participants to confirm their correctness.</p>", "<p id=\"Par75\">The Multiple Screener<sup>©</sup> will be considered a sufficiently adequate screening instrument for the detection of (M)CI if its overall sensitivity values are at least 0.80 and specificity values at least 0.70. However, if one of the individual tests does not meet these criteria, we will determine accuracy values of the two other tests over and above that of all three tests combined.</p>", "<title>Secondary study parameters</title>", "<title>Test–retest reliability</title>", "<p id=\"Par76\">Test–retest reliability of the Multiple Screener<sup>©</sup> will be determined by calculating intraclass correlation coefficients (ICCs) for absolute agreement, using a two-way mixed model. Based on the 95% confidence interval of the ICC estimate, values will be considered to reflect poor reliability (&lt; 0.5), moderate (0.5 -0.75), good (0.75–0.9), and excellent (&gt; 0.90) [##REF##27330520##66##]. The coefficients will be calculated separately for the SDMT, CVLT-II, and the SPART.</p>", "<title>Relationships between cognition and psychological, work-related, and patient-reported health-related quality of life measures</title>", "<p id=\"Par77\">Cross-sectional associations between cognition and psychological, work-related, and health-related quality of life measures will be analysed using Pearson’s or Point-Biserial correlations and linear regression analyses (including stepwise procedures) in both subsets and the overall sample. Correlations coefficients of less than 0.3, between 0.3 and 0.7, and greater than 0.7 will be considered weak, moderate, and strong, respectively [##UREF##22##67##]. An overview of the hypothesized correlations can be found in Table ##TAB##3##4##.</p>", "<p id=\"Par78\">Additionally, logistic regression analyses will be used to identify the predictive value of demographical and disease characteristics (such as sex, MS subtype, medication, comorbidities) on cognitive functioning. Additionally, differences between groups (CP, MCI and CI) in demographic and clinical characteristics and other outcome measurements (e.g., psychological, work-related and health-related quality of life measures) will be analysed using independent samples t-tests, Mann–Whitney U tests and Pearson’s chi-square tests. For particular analyses, confounding variables (such as age, sex, education, EDSS score, disease duration, mood, fatigue etc.) will be inserted. Bonferroni corrections will be applied to correct for multiple comparisons within each objective.</p>", "<title>Safety reporting</title>", "<p id=\"Par79\">We will not collect information on (serious) adverse events due to the observational and non-interventional nature of this study.</p>", "<title>Study status</title>", "<p id=\"Par80\">The first participant was included on 19 July 2022. Currently 216 participants have been enrolled in the study (December 2023).</p>" ]
[]
[ "<title>Discussion</title>", "<p id=\"Par81\">Cognitive impairment is common in PwMS and can severely affect health-related quality of life. In order to intervene timely, a baseline assessment and frequent monitoring of cognitive functioning seems crucial. However, in the Netherlands, neuropsychological assessment is not (yet) integrated into standard care due to the time-consuming nature of cognitive testing and limited availability of trained personnel [##UREF##3##19##]. The current study will validate a digital screening tool with the primary objective to enable early identification of cognitive decline in PwMS. The validation of the Multiple Screener<sup>©</sup> within a representative sample of PwMS that visit a neurologist, will lay the foundation for implementing a cognitive screening tool for annual testing in clinical practice in the near future. This study will further help raise awareness among health care professionals about cognitive impairment in MS and its significance within the broader scheme of priorities in MS-care. The fact that 12 hospitals in the Netherlands are interested in participating in the study further emphasizes the need for such screening methods. In addition, this study will also contribute to the development of practical guidelines for Dutch professionals regarding the screening and subsequent monitoring of cognitive decline in MS.</p>", "<p id=\"Par82\">Moreover, with the present study we are collecting one of the largest datasets on cognition and its determinants in PwMS which will provide us with a wealth of data that can be used to answer multiple relevant related research questions. Specifically, it will enhance our understanding of the relationship between cognition and relevant confounders, ranging from cognitive self-awareness to fatigue and mood problems.</p>", "<p id=\"Par83\">To conclude, the validation of the Multiple Screener<sup>©</sup> will facilitate early identification of cognitive impairment in PwMS; ultimately enabling better management of cognitive symptoms in this population. Additionally, the study's comprehensive dataset will allow new insights into factors related to cognition in PwMS, thus informing future research and clinical practices. Finally, timely identification of cognitive impairment is a crucial step for initiating early interventions, an important aspect that will be explored in subsequent phases of the larger <italic>Don't be late!</italic> study.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Cognitive impairment occurs in up to 65% of people with multiple sclerosis (PwMS), negatively affecting daily functioning and health-related quality of life. In general, neuropsychological testing is not part of standard MS-care due to insufficient time and trained personnel. Consequently, a baseline assessment of cognitive functioning is often lacking, hampering early identification of cognitive decline and change within a person over time. To assess cognitive functioning in PwMS in a time-efficient manner, a BICAMS-based self-explanatory digital screening tool called the Multiple Screener<sup>©</sup>, has recently been developed. The aim of the current study is to validate the Multiple Screener<sup>©</sup> in a representative sample of PwMS in the Netherlands. Additionally, we aim to investigate how cognitive functioning is related to psychological factors, and both work and societal participation.</p>", "<title>Methods</title>", "<p id=\"Par2\">In this cross-sectional multicentre study, 750 PwMS (aged 18–67 years) are included. To obtain a representative sample, PwMS are recruited via 12 hospitals across the Netherlands. They undergo assessment with the Minimal Assessment of Cognitive Functioning in MS (MACFIMS; reference-standard) and the Multiple Screener<sup>©</sup>. Sensitivity, specificity, and predictive values for identifying (mild) cognitive impairment are determined in a subset of 300 participants. In a second step, the identified cut-off values are tested in an independent subset of at least 150 PwMS. Moreover, test–retest reliability for the Multiple Screener<sup>©</sup> is determined in 30 PwMS. Information on psychological and work-related factors is assessed with questionnaires.</p>", "<title>Discussion</title>", "<p id=\"Par3\">Validating the Multiple Screener<sup>©</sup> in PwMS and investigating cognition and its determinants will further facilitate early identification and adequate monitoring of cognitive decline in PwMS.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Members of the <italic>Don’t be late!</italic> consortium are:</p>", "<p>• Participating sites</p>", "<p> – Casper E.P. van Munster, Amphia Ziekenhuis, Breda, The Netherlands.</p>", "<p> – Renske G. Wieberdink, MS Centrum Stedendriehoek, Gelre, The Netherlands.</p>", "<p> – Jolijn J. Kragt, Reinier de Graaf Ziekenhuis, Delft, The Netherlands.</p>", "<p> – Judith Schouten, Rijnstate, Arnhem, The Netherlands.</p>", "<p> – Erwin L.J. Hoogervorst, St. Antonius Ziekenhuis, Nieuwegein, The Netherlands.</p>", "<p> – Paul A.D. Bouma, Tergooi Ziekenhuizen, Hilversum, The Netherlands.</p>", "<p> – Floris G.C.M. De Kleermaeker, Viecuri Medisch Centrum, Venlo, The Netherlands.</p>", "<p> – Meike Holleman, Jeroen Bosch Ziekenhuis, ’s-Hertogenbosch, The Netherlands.</p>", "<p> – Sofie Geurts, Canisius Wilhelmina Ziekenhuis, Nijmegen, The Netherlands.</p>", "<p> – Christaan de Brabander, Admiraal de Ruyter Ziekenhuis, Vlissingen, The Netherlands.</p>", "<p> – Nynke F. Kalkers, OLVG, Amsterdam, The Netherlands.</p>", "<p>• Bram A.J. den Teuling, Pim van Oirschot, Sonja Cloosterman, Sherpa B.V., Nijmegen, The Netherlands.</p>", "<p>• Jos Vermeer, Personal Fitness Nederland (PFN) B.V., Eindhoven, The Netherlands.</p>", "<p>• Chris C. Schouten, Dutch MS Society, Den Donder, The Netherlands.</p>", "<p>• Gerard J. Stege, Merck B.V., Schiphol-Rijk, The Netherlands.</p>", "<p>• Thijs van‘t Hullenaar, Sanofi B.V., Genzyme Europe, Amsterdam, The Netherlands.</p>", "<p>We would like to thank all members of the consortium for their contribution to the project.</p>", "<title>Authors’ contributions</title>", "<p>PW: Conceptualisation, Methodology, Investigation, Writing – original draft, Visualisation, Project Administration. BdJ: Conceptualisation, Methodology, Writing – Review &amp; Editing, Supervision. BU: Conceptualisation, Methodology, Supervision. SS: Conceptualisation, Investigation, Project Administration. JA: Conceptualisation, Investigation, Project Administration. AR: Investigation, Project Administration. PO: Conceptualisation, Methodology, Software, Writing – Review &amp; Editing. VG: Conceptualisation, Writing – Review &amp; Editing, Supervision. FS: Conceptualisation, Supervision. KH: Conceptualisation, Writing – Review &amp; Editing, Supervision. MR: Conceptualisation, Writing – Review &amp; Editing, Supervision. MS: Conceptualisation, Supervision. GW: Conceptualisation, Writing – Review &amp; Editing, Supervision. SV: Conceptualisation, Project Administration. ES: Conceptualisation. MK: Conceptualisation, Methodology, Writing – Review &amp; Editing, Supervision. HH: Conceptualisation, Methodology, Writing – Review &amp; Editing, Supervision, Funding Acquisition. All authors read and approved the final manuscript.</p>", "<title>Authors’ information</title>", "<p id=\"Par84\">See above.</p>", "<title>Funding</title>", "<p>This study is peer-reviewed and funded by the Dutch Research Council (NWO) as part of the Dutch National Research Agenda (NWA), file number NWA.1292.19.064. The funder does not have role in the design of the study and collection, analysis, and interpretation of the data and in writing the manuscript.</p>", "<title>Availability of data and materials</title>", "<p>Not applicable.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par85\">The Medical Ethical Committee of the Amsterdam UMC, Vrije Universiteit Amsterdam has reviewed and approved this study (METC 2021.0707, protocol version 2, 4 May 2022). Any future substantial changes to the study protocol will undergo review and approval by the METC. Written informed consent is obtained from all participants upon enrolment in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par86\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par87\">Pauline T. Waskowiak has no competing interests regarding publication.</p>", "<p id=\"Par88\">Brigit A. de Jong has no competing interests regarding publication.</p>", "<p id=\"Par89\">Bernard M.J. Uitdehaag has received research support and/or consultancy fees from Biogen Idec, Genzyme, Merck Serono, Novartis, Roche, Teva and Immunic Therapeutics.</p>", "<p id=\"Par90\">Shalina R.D. Saddal has no competing interests regarding publication.</p>", "<p id=\"Par91\">Jip Aarts has no competing interests regarding publication.</p>", "<p id=\"Par92\">Aïda A.M. Roovers has no competing interests regarding publication.</p>", "<p id=\"Par93\">Pim van Oirschot is employed by Sherpa BV.</p>", "<p id=\"Par94\">Vincent de Groot has no competing interests regarding publication.</p>", "<p id=\"Par95\">Frederieke G. Schaafsma has no competing interests regarding publication.</p>", "<p id=\"Par96\">Karin van der Hiele has no competing interests regarding publication.</p>", "<p id=\"Par97\">Marit F.L. Ruitenberg has no competing interests regarding publication.</p>", "<p id=\"Par98\">Menno M. Schoonheim serves on the editorial board of Neurology, Multiple Sclerosis Journal and Frontiers in Neurology, receives research support from the Dutch MS Research Foundation, Eurostars-EUREKA, ARSEP, Amsterdam Neuroscience, MAGNIMS and ZonMW (Vidi grant, project number 09150172010056) and has served as a consultant for or received research support from Atara Biotherapeutics, Biogen, Celgene/Bristol Meyers Squibb, EIP, Sanofi, MedDay and Merck.</p>", "<p id=\"Par99\">Guy A.M. Widdershoven has no competing interests regarding publication.</p>", "<p id=\"Par100\">Sabina van der Veen has no competing interests regarding publication.</p>", "<p id=\"Par101\">Esther C.F. Schippers has no competing interests regarding publication.</p>", "<p id=\"Par102\">Martin Klein has no competing interests regarding publication.</p>", "<p id=\"Par103\">Hanneke E. Hulst is an editor of the Multiple Sclerosis Journal controversies sections, receives research support from the Dutch MS Research Foundation and the Dutch Research Council. She has served as a consultant for or received research support from Atara Biotherapeutics, Biogen, Novartis, Celgene/Bristol Meyers Squibb, Sanofi Genzyme, MedDay and Merck BV.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The digital version of the Digit Modalities Test (SDMT) (left) and the Spatial Recall Test (SPART) (right) in the Multiple Screener<sup>©</sup> application. The Dutch version of the California Verbal Learning Test–second edition (CVLT-II) is not depicted as this test has an auditory format</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Don’t be late study!</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\" colspan=\"2\">The <italic>Don’t be late!</italic> study consists of three work packages (WPs) with the overarching goal to postpone cognitive decline and prevent early unemployment in PwMS. While WP1 focuses on early identification of cognitive impairment, WP2 will investigate the effectiveness of two personalized preventative interventions on health-related quality of life in PwMS. A selection of participants that are included in WP1 (i.e., participants with mild cognitive impairment [who are therefore expected to still benefit from the interventions] and working for at least 12 h a week), will be invited to partake in WP2. Finally, WP3 aims to foster the implementation of these interventions according to patients needs and by including relevant stakeholders</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Minimal assessment of cognitive functioning in MS test battery</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Test</th><th align=\"left\">Cognitive domain(s)</th></tr></thead><tbody><tr><td align=\"left\">Dutch Version of the California Verbal Learning Test, Second Edition (CVLT-II) [##UREF##5##23##–##UREF##6##25##]</td><td align=\"left\">Verbal learning and memory</td></tr><tr><td align=\"left\">Brief Visuospatial Memory Test-Revised (BVMT-R) [##UREF##8##35##]</td><td align=\"left\">Visuospatial learning and memory</td></tr><tr><td align=\"left\">Symbol Digit Modalities Test (SDMT) [##UREF##4##22##]</td><td align=\"left\">Information processing speed</td></tr><tr><td align=\"left\">Paced Auditory Serial Addition Test (PASAT) [##REF##866038##36##]</td><td align=\"left\">Information processing speed</td></tr><tr><td align=\"left\">Controlled Oral Word Association Test (COWAT) [##UREF##9##37##]</td><td align=\"left\">Language and working memory</td></tr><tr><td align=\"left\">Judgment of Line Orientation Test (JLO) [##UREF##9##37##]</td><td align=\"left\">Visuospatial orientation</td></tr><tr><td align=\"left\">Delis-Kaplan Executive Function System sorting test (D-KEFS) [##UREF##10##38##]</td><td align=\"left\">Executive functioning</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Questionnaires on MS-related and psychological factors, work and societal participation</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Domain</th><th align=\"left\">Measure(s)</th></tr></thead><tbody><tr><td align=\"left\">Health-related quality of life</td><td align=\"left\">MOS 36-Item Short Form (SF-36) [##REF##17277259##44##]</td></tr><tr><td align=\"left\">Physical and psychological impact of MS</td><td align=\"left\">Multiple Sclerosis Impact Scale (MSIS-29) [##REF##11335698##45##]</td></tr><tr><td align=\"left\">Self-perceived cognitive functioning</td><td align=\"left\">Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNQ) [##REF##12617275##29##]</td></tr><tr><td align=\"left\">Anxiety and depression</td><td align=\"left\">Hospital Anxiety and Depression Scale (HADS) [##REF##6880820##27##]</td></tr><tr><td align=\"left\">Fatigue</td><td align=\"left\">Modified Fatigue Impact Scale (MFIS) [##REF##15008502##28##]</td></tr><tr><td align=\"left\">Sleep</td><td align=\"left\">Athens Insomnia Scale (AIS) [##REF##11033374##46##, ##REF##12932801##47##]</td></tr><tr><td align=\"left\">Resilience</td><td align=\"left\">Connor Davidson Resilience Scale (CD-RISC 25) [##REF##16602815##48##]</td></tr><tr><td align=\"left\">Mastery</td><td align=\"left\">Pearlin Mastery Scale (PMS) [##UREF##14##49##]</td></tr><tr><td align=\"left\">Personality</td><td align=\"left\">NEO Five-Factor Inventory (NEO-FFI) [##UREF##15##50##–##REF##16768595##52##]</td></tr><tr><td align=\"left\">Stressful life events</td><td align=\"left\">List of Threatening Events Questionnaire (LTE) [##REF##2399824##53##]</td></tr><tr><td align=\"left\">Work functioning &amp; work productivity</td><td align=\"left\">Work Productivity and Activity Impairment Questionnaire (WPAI) [##REF##10146874##54##]; Multiple Sclerosis Work Difficulties Questionnaire (MSWDQ-23) [##REF##23786346##55##, ##UREF##16##56##]; Buffalo Vocational Monitoring Survey (BVMS NL-version) [##UREF##17##57##]</td></tr><tr><td align=\"left\">Lifestyle and social participation</td><td align=\"left\">In-house developed Lifestyle Factors Questionnaire: assessing health-related lifestyle factors (e.g., smoking, drinking, weight, and height to calculate BMI, exercise, diet,), social activities and information regarding the living situation of participants</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Hypothesized direction of correlations between cognitive scores with health-related quality of life, psychological, and work-related, health and lifestyle measures</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Measure</th><th align=\"left\">Hypothesized direction</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\"><bold>Health-related quality of life</bold></td></tr><tr><td align=\"left\"> SF-36 [##REF##17277259##44##]</td><td align=\"center\"> + </td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Psychological measures</bold></td></tr><tr><td align=\"left\"> MSIS-29 [##REF##11335698##45##]</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> MSNQ [##REF##12617275##29##]</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> HADS [##REF##6880820##27##]</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> MFIS [##REF##15008502##28##]</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> AIS [##REF##11033374##46##, ##REF##12932801##47##]</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> CD-RISC 25 [##REF##16602815##48##]</td><td align=\"center\"> + </td></tr><tr><td align=\"left\"> PMS [##UREF##14##49##]</td><td align=\"center\">NA</td></tr><tr><td align=\"left\"> NEO-FFI [##UREF##15##50##–##REF##16768595##52##]</td><td align=\"center\">NA</td></tr><tr><td align=\"left\"> LTE [##REF##2399824##53##]</td><td align=\"center\">NA</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Work-related measures</bold></td></tr><tr><td align=\"left\"> WPAI [##REF##10146874##54##]</td><td align=\"center\">NA</td></tr><tr><td align=\"left\"> MSWDQ-23 [##REF##23786346##55##, ##UREF##16##56##]</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> BVMS NL-version [##UREF##17##57##]</td><td align=\"center\">NA</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Health and lifestyle measures</bold></td></tr><tr><td align=\"left\"> Physical exercise</td><td align=\"center\"> + </td></tr><tr><td align=\"left\"> Smoking</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> Alcohol use</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> Diet</td><td align=\"center\">NA</td></tr><tr><td align=\"left\"> Sleep</td><td align=\"center\"> + </td></tr><tr><td align=\"left\"> BMI</td><td align=\"center\">-</td></tr><tr><td align=\"left\"> Social activities</td><td align=\"center\"> + </td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>MS</italic> Multiple Sclerosis, <italic>BMI</italic> Body Mass Index</p></table-wrap-foot>", "<table-wrap-foot><p><italic>NA</italic> Not Applicable, as no hypothesis can be formulated beforehand</p><p><italic>Abbreviations</italic>: <italic>MSIS-29</italic> Multiple Sclerosis Impact Scale, <italic>MSNQ</italic> Multiple Sclerosis Neuropsychological Screening Questionnaire, <italic>HADS</italic> Hospital Anxiety and Depression Scale (HADS), <italic>MFIS</italic> Modified Fatigue Impact Scale, <italic>AIS</italic> Athens Insomnia Scale, <italic>CD-RISC</italic> Connor Davidson Resilience Scale, <italic>PMS</italic> Pearlin Mastery Scale, <italic>NEO-FFI</italic> NEO Five-Factor Inventor, <italic>LTE</italic> List of Threatening Events Questionnaire, <italic>WPAI</italic> Work Productivity and Activity Impairment Questionnaire, <italic>MSWDQ-23</italic> Multiple Sclerosis Work Difficulties Questionnaire, <italic>BVMS NL-version</italic> Buffalo Vocational Monitoring Survey, <italic>BMI</italic> Body Mass Index</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12883_2023_3495_Fig1_HTML\" id=\"MO1\"/>" ]
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[{"label": ["10."], "mixed-citation": ["Global MS Employment Report 2016. 2016, MS International Federation: msif.org."]}, {"label": ["11."], "surname": ["Uitdehaag"], "given-names": ["B"], "article-title": ["New insights into the burden and costs of multiple sclerosis in Europe: results for the Netherlands"], "source": ["Multiple Sclerosis J"], "year": ["2017"], "volume": ["23"], "issue": ["2_suppl"], "fpage": ["117"], "lpage": ["129"], "pub-id": ["10.1177/1352458517708663"]}, {"label": ["14."], "mixed-citation": ["Prouskas SE, et al. A randomized trial predicting response to cognitive rehabilitation in multiple sclerosis: Is there a window of opportunity? Mult Scler. 2022:13524585221103134."]}, {"label": ["19."], "mixed-citation": ["Klein OA, das Nair R, Ablewhite J, Drummond A. Assessment and management of cognitive problems in people with multiple sclerosis: a National Survey of Clinical Practice. Int J Clin Pract. 2018:e13300."]}, {"label": ["22."], "mixed-citation": ["Smith A. Symbol digit modalities test. 1973: Western Psychological Services Los Angeles."]}, {"label": ["23."], "surname": ["Delis"], "given-names": ["D"], "article-title": ["Neuropsychological assessment of learning and memory"], "source": ["Cortex"], "year": ["1989"], "volume": ["10"], "issue": ["3"], "fpage": ["308"], "lpage": ["317"]}, {"label": ["25."], "surname": ["Mulder", "Dekker", "Dekker"], "given-names": ["JL", "R", "PH"], "source": ["Verbale Leer en Geheugen Test"], "year": ["1996"], "publisher-loc": ["Lisse"], "publisher-name": ["Swets & Zeitlinger"]}, {"label": ["26."], "mixed-citation": ["Rao SM. Cognitive Function Study Group, N. A Manual for the Brief Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis., N.M.S. Society, Editor. 1990: New York."]}, {"label": ["35."], "surname": ["Benedict"], "given-names": ["RH"], "article-title": ["Revision of the Brief visuospatial memory test: studies of normal performance, reliability, and validity"], "source": ["Psychol Assess"], "year": ["1996"], "volume": ["8"], "issue": ["2"], "fpage": ["145"], "pub-id": ["10.1037/1040-3590.8.2.145"]}, {"label": ["37."], "surname": ["Benton", "Sivan", "Hamsher", "Varney", "Spreen"], "given-names": ["AL", "AB", "K", "NR", "O"], "source": ["Contributions to Neuropsychological Assessment"], "year": ["1994"], "edition": ["2"], "publisher-loc": ["New York"], "publisher-name": ["Oxford University Press"]}, {"label": ["38."], "surname": ["Delis", "Kaplan", "Kramer"], "given-names": ["DC", "E", "JH"], "source": ["Delis-Kaplan executive function system"], "year": ["2001"]}, {"label": ["40."], "mixed-citation": ["Nauta IM et al. Performance validity in outpatients with multiple sclerosis and cognitive complaints. Mult Scler. 2021:13524585211025780."]}, {"label": ["41."], "mixed-citation": ["Lee GP, Loring DW, Martin RC. Rey\u2019s 15-item visual memory test for the detection of malingering: normative observations on patients with neurological disorders. Psychol Assess. 1992;4(1):43\u20136."]}, {"label": ["42."], "surname": ["Baron-Cohen"], "given-names": ["S"], "article-title": ["The \u201cReading the Mind in the Eyes\u201d Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism"], "source": ["J Child Psychol Psychiatry Allied Disciplines"], "year": ["2001"], "volume": ["42"], "issue": ["2"], "fpage": ["241"], "lpage": ["251"], "pub-id": ["10.1111/1469-7610.00715"]}, {"label": ["49."], "mixed-citation": ["Pearlin LI, Schooler C. The structure of coping. J Health Soc Behav. 1978:2\u201321."]}, {"label": ["50."], "mixed-citation": ["Costa Jr PT, McCrae RR. 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{ "acronym": [ "AIS", "ASMT", "BICAMS", "BVMS NL version", "BVMT-R", "CD-RISC 25", "CI", "COWAT", "CP", "CVLT", "D-KEFS", "EDSS", "HADS", "ICCs", "JLO", "LTE", "MACFIMS", "MCI", "METC", "MFIS", "MS", "MSIS-29", "MSNQ", "MSWDQ-23", "NEO-FFI", "PMS", "PwMS", "ROC", "SDMT", "SF-36", "SPART", "WMO", "WPAI" ], "definition": [ "Athens Insomnia Scale", "Amsterdam Short Term Memory Test", "Brief International Cognitive Assessment for MS", "Buffalo Vocational Monitoring Survey", "Brief visuospatial memory test-revised", "Connor Davidson Resilience Scale", "Cognitively impaired", "Controlled oral word association test", "Cognitively preserved", "California verbal learning test", "Delis-Kaplan Executive Function System sorting test", "Expanded disability status scale", "Hospital anxiety and depression scale", "Intraclass correlation coefficients", "Judgment of line orientation test", "List of Threatening Events Questionnaire", "Minimal Assessment of Cognitive Function in Multiple Sclerosis", "Mild cognitive impairment", "Medical Ethics Committee", "Modified Fatigue Impact Scale", "Multiple Sclerosis", "Multiple Sclerosis Impact Scale", "Multiple Sclerosis Neuropsychological Questionnaire", "Multiple Sclerosis Work Difficulties Questionnaire", "NEO Five-Factor Inventory", "Pearlin Mastery Scale", "People with Multiple Sclerosis", "Receiver-operating characteristic", "Symbol digit modalities test", "36-Item Short Form", "Spatial Recall Test", "Medical Research Involving Human Subjects Act", "Work Productivity and Activity Impairment Questionnaire" ] }
67
CC BY
no
2024-01-14 23:43:45
BMC Neurol. 2024 Jan 13; 24:26
oa_package/e7/b7/PMC10787411.tar.gz
PMC10787412
0
[ "<title>Background</title>", "<p id=\"Par11\">It is well documented that university students show high levels of mental distress, which is even more pronounced among health sciences students. Health sciences are often considered to be academically, psychologically, and emotionally challenging [##REF##31638442##1##–##REF##31592689##4##]. In our previous study conducted in 2016, we found that 60.2% of medical and health sciences students showed increased levels of depression [##REF##31117829##5##]. Most research on the topic of student mental health was done on medical students. It is considered that the frequencies of mental health issues in other health sciences students are comparable to that of medical students. We have also previously shown that the levels of depressive symptoms among nursing students were comparable to those of medical students, albeit the difference was statistically significant (64.8% vs 57.3%) [##REF##31117829##5##]. In the literature, the prevalence of depressive symptoms in university students varies between 8.6% and 71% [##REF##31638442##1##, ##REF##27923076##3##, ##REF##31117837##6##–##UREF##1##8##].</p>", "<p id=\"Par12\">Anxiety disorders are the most common psychiatric conditions in university students [##REF##25142250##9##]. Medical students report symptoms of anxiety with a global prevalence rate of 33.8%, ranging between 7.7% and 65.5%, showing that a third of medical students exhibit problems with anxiety, which is much more prevalent than in the general population where it is estimated at 3–25%, depending on the instrument and study protocol [##REF##31370266##10##, ##REF##32805704##11##]. The prevalence of anxiety in medical students is not significantly different from that of other university students [##REF##31370266##10##]. Our previous study among medical and health sciences students found high anxiety levels in 54.5% of the students, with no significant differences between medical and nursing students [##REF##31117829##5##].</p>", "<p id=\"Par13\">The prevalence of mental health issues in the population of health sciences students is alarming. These issues may lead to more severe psychiatric conditions, poor academic performance, use of harmful substances, stress-related academic dishonesty, and reduced empathy which is vital for healthcare workers [##UREF##1##8##]. Symptoms of anxiety and depression are known detrimental factors of well-being. </p>", "<p id=\"Par14\">Subjective happiness is one of the measures of a person’s well-being [##REF##23578272##12##]. It can serve as an indicator of a person’s ability to cope with difficulties one can face. A positive outlook on life can help healthcare workers in their relationships with patients. Individuals with higher levels of happiness are shown to live longer; exhibiting happy feelings while at the workplace can make employees more productive, which is particularly important for persons working in the medical field [##UREF##2##13##].</p>", "<p id=\"Par15\">Since our study from 2016, several changes occurred that might have led to additional increases in the levels of mental distress. Most significantly, the COVID-19 pandemic was shown to be a significant factor leading to mental health issues in the student population. Studies from 2020 have shown a higher prevalence of moderate and severe self-reported depressive and anxious symptoms in the general public and in the student populations caused by the COVID-19 pandemic [##REF##32364039##14##]. A meta-analysis of the prevalence of mental health problems in the population of nursing students during the COVID-19 pandemic showed a prevalence of depression at 52%, fear at 41%, anxiety at 32%, and stress at 30% [##REF##34653783##15##].</p>", "<p id=\"Par16\">The aim of this multi-centric study was to assess the levels of depression, anxiety and subjective happiness among health sciences students in Croatia.</p>" ]
[ "<title>Methods</title>", "<title>Study design</title>", "<p id=\"Par17\">This was a multi-centric cross-sectional study.</p>", "<title>Reporting</title>", "<p id=\"Par18\">The study is reported in line with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) [##REF##15471760##16##].</p>", "<title>Participants</title>", "<p id=\"Par19\">The study included health sciences students from 10 higher education institutions in Croatia providing health sciences studies. The following institutions participated in the study: Catholic University of Croatia, Juraj Dobrila University of Pula, Libertas International University, University of Applied Health Sciences, Polytechnic of Bjelovar, University North, University of Dubrovnik, University of Rijeka, University of Split, and University of Zadar. All health sciences students were eligible, including nursing, dental hygiene, physiotherapy, medical laboratory diagnostics, midwifery, radiological technology, occupational therapy, and sanitary engineering.</p>", "<p id=\"Par20\">Students were asked via their official school email addresses to complete the survey hosted on SurveyMonkey. Participation was voluntary, and no incentives were offered to the students. First, information about the study was sent in a separate document with a link to the survey. The survey invitation with information about the study can be found in Supplementary file ##SUPPL##0##1##. Before starting the survey, participants were asked to confirm that they were giving their consent to participate in the study. Two reminders were sent, spaced one week apart, after the first email invitation. The first invitation was sent on March 6, 2023, followed by the first reminder on March 18, 2023, and the second reminder on March 20, 2023. The survey was closed on April 23, 2023. Direct identifiers of the participants were not collected.</p>", "<title>Ethics</title>", "<p id=\"Par21\">The study protocol was approved by the Ethics Committees of all participating institutions. All participants gave their written informed consent in the online interface before starting the online survey. All methods were carried out in accordance with relevant guidelines and regulations.</p>", "<title>Survey</title>", "<p id=\"Par22\">The students were given an online self-administered anonymous survey in Croatian language. The full text of the survey in the English language can be found in Supplementary file ##SUPPL##1##2##. The survey consisted of two parts. The first part included 14 questions about the participants’ sociodemographic characteristics: age, sex, university, type of study, whether they are studying full-time or part-time, school year, whether they are employed, whether they live in a rural or urban setting, the number of habitants in their place of residence, the financial status of their family and the monthly income of their family, their self-reported grade point average (GPA), whether they participated in a scientific project, and whether they failed a year in university. The second part of the survey included validated scales for determining the levels of depression, anxiety, and subjective happiness.</p>", "<p id=\"Par23\">The Patient Health Questionnaire (PHQ-9) is a validated psychological instrument that has shown good specificity and sensitivity for detecting depressive disorders [##REF##20633738##17##]. It consists of nine items that are answered on a Likert scale and correspond to one of the DSM-IV Diagnostic Criterion for symptoms of major depressive disorder [##REF##15183601##18##–##REF##23664569##21##]. The total score ranges from 0 to 27. Cut-off points were suggested at 5, 10, 15 and 20, corresponding to mild, moderate, moderately severe and severe levels of depressive symptoms [##REF##20633738##17##]. When determining the prevalence of depressive symptoms, we used the cut-off point of 5, thus encompassing all participants with at least mild depression.</p>", "<p id=\"Par24\">The Generalized Anxiety Disorder – 7 (GAD-7) is a validated 7-item self-report psychological instrument developed to diagnose generalized anxiety disorder. It has shown good sensitivity and specificity as a screening tool for panic disorder, social anxiety and PTSD [##REF##20633738##17##]. Its seven items are answered on a Likert scale [##REF##21339006##22##, ##REF##17213178##23##]. The total score ranges from 0 to 21, with proposed cut-off points set at ≥ 5, ≥ 10, and ≥ 15 representing mild, moderate, and severe anxiety symptom levels, respectively [##REF##18388841##24##]. When determining the prevalence of anxiety symptoms, we used the cut-off point of 5, thus encompassing all participants with at least mild anxiety.</p>", "<p id=\"Par25\">The Subjective Happiness Scale (SHS) is a survey consisting of 4 items, and it aims to assess the respondents’ subjective happiness. Respondents are asked to characterize themselves using total ratings and ratings relative to others and to assess to what extent the characterizations of happy and unhappy individuals describe them personally. Each item is scored on a 7-point Likert scale. The possible score range is 4 to 28, with higher scores indicating a higher level of subjective happiness [##UREF##3##25##].</p>", "<p id=\"Par26\">We used official Croatian versions of the PHQ-9 and GAD-7 since all the participants spoke Croatian. We used the Croatian translation of the Subjective Happiness Scale that our team prepared previously and used in a similar study [##REF##31117829##5##]. Items were not randomized or alternated, nor was adaptive questioning applied. All the items were shown on a single page. The participants could correct their answers before sending the completed survey. Unique site visitors were not counted. The authors tested the online survey on desktop and mobile phones to ensure technical functionality before the data collection. We did not use any methods to prevent duplicate entries potentially. No surveys were submitted with an atypical timestamp.</p>", "<title>Statistical analysis</title>", "<p id=\"Par27\">All surveys were included in the study, regardless of their completeness. We reported the completion rate as the number of surveys filled out and submitted divided by the number of surveys started by respondents. The distribution normality of scalar variables was tested by Kolmogorov–Smirnov and Shapiro-Wilks tests. Non-parametrical tests were used due to the non-normal distribution of all scalar variables. Numerical data were presented as medians and interquartile ranges (IQR), or as means and standard deviations. Categorical variables were presented by relative and absolute frequencies. Mann–Whitney U-test was used to assess the differences between the two groups. Cronbach’s Alpha was used to assess the internal consistency of the psychological instruments. The chi-square test was used to assess the differences in ratios between independent samples, and Spearman’s ρ was used to assess correlations among variables. The effect of multiple variables was assessed by a Stepwise Multiple Linear Regression Analysis. Data analysis was performed using an IBM SPSS Statistics version 16.0 for Windows. <italic>P</italic>-values less than 0.05 were considered statistically significant.</p>", "<title>Raw data</title>", "<p id=\"Par28\">Raw data collected within the study, without indirect identifiers of the participants, are published on Open Science Framework (link: <ext-link ext-link-type=\"uri\" xlink:href=\"https://osf.io/ms2u4/\">https://osf.io/ms2u4/</ext-link>).</p>" ]
[ "<title>Results</title>", "<title>Participants’ characteristics</title>", "<p id=\"Par29\">Of the 7460 invited students, 2137 students participated in the study (29% response rate). The completion rate of the survey was 97%. Response rates across institutions ranged from 16 to 65%. Response rates per institutions and number of students in different study courses accross specialty per institution are available in Supplementary file ##SUPPL##2##3##. One week after the first invitation, the response rate was 14% (<italic>N</italic> = 1022); one week after the first reminder, the response rate was 23% (<italic>N</italic> = 1679), finally reaching 29% after the second reminder by the time the survey was closed for further responses.</p>", "<p id=\"Par30\">The sociodemographic characteristics of the participants are presented in Table ##TAB##0##1##. The majority of participants (86.3%) were women. The participants’ median age was 22 years (IQR 20–26). Most participants studied nursing. More than half were employed full-time. Most were employed in healthcare, lived in an urban area and had a monthly income of 1001–2000 €. Few students had ever failed a study year. Less than 20% participated in a scientific project (Table ##TAB##0##1##).\n</p>", "<title>Levels of depression, anxiety and subjective happiness among health sciences students</title>", "<p id=\"Par31\">All scalar variables showed a deviation from normal distribution as tested by the Kolmogorov–Smirnov test. Cronbach’s Alpha test showed satisfactory internal consistency of the instruments used in the study, with PHQ-9 having an alpha of 0.905, GAD-7 of 0.905 and SHS of 0.807. Suicidal or auto-destructive ideations were present in 414 (19.4%) of students.</p>", "<p id=\"Par32\">The median scores were as follows: PHQ-9 8 (4–13), GAD-7 7 (4–12), SHS 19 (15.25–22), and GPA 4 (4–4). There were no significant differences in GPA between the sexes (<italic>p</italic> = 0.064).</p>", "<p id=\"Par33\">Differences in PHQ-9, GAD-7 and SHS scores are presented in Table ##TAB##1##2##. Significant differences in the levels of depression were found based on sex (<italic>p</italic> &lt; 0.001), whether the students worked part-time or full-time (<italic>p</italic> = 0.007), year of study (<italic>p</italic> &lt; 0.001), employment (<italic>p</italic> &lt; 0.001), self-assessed financial status (<italic>p</italic> &lt; 0.001), average monthly income (<italic>p</italic> &lt; 0.001), failing a year in college (<italic>p</italic> &lt; 0.001). Significant differences in the anxiety levels were found based on sex (<italic>p</italic> &lt; 0.001), year of study (<italic>p</italic> &lt; 0.001), employment (<italic>p</italic> &lt; 0.001), self-assessed financial status (<italic>p</italic> &lt; 0.001), average monthly income (<italic>p</italic> = 0.010), failing a year in college (<italic>p</italic> = 0.005). Significant differences in the subjective happiness scores were found based on whether the students worked part-time or full-time (<italic>p</italic> = 0.019), year of study (<italic>p</italic> &lt; 0.001), employment (<italic>p</italic> &lt; 0.001), self-assessed financial status (<italic>p</italic> &lt; 0.001), average monthly income (<italic>p</italic> &lt; 0.001), failing a year in college (<italic>p</italic> &lt; 0.001).\n</p>", "<p id=\"Par34\">There was a strong positive correlation between depression and anxiety (rho = 0.826, <italic>p</italic> &lt; 0.001), and those variables had a strong negative correlation with subjective happiness (depression: rho = -0.600, <italic>p</italic> &lt; 0.001; anxiety, rho = -0.556, <italic>p</italic> &lt; 0.001). Age negatively correlated with depression (-0.145, <italic>p</italic> &lt; 0.001) and anxiety (rho = -0.091, <italic>p</italic> &lt; 0.001) and positively with subjective happiness (rho = 0.083, <italic>p</italic> &lt; 0.001).</p>", "<p id=\"Par35\">Since the scores of the PHQ-9 and GAD-7 surveys can be divided into categories based on predefined cut points, the frequencies of those categories are presented in Table ##TAB##2##3##. Men had higher frequencies of low and mild anxiety, while women had higher frequencies of moderate and severe anxiety (<italic>p</italic> &lt; 0.001). Men had higher frequencies of low depressive symptoms, while women had higher frequencies of mild, moderate, moderately severe and severe depressive symptoms (<italic>p</italic> = 0.003).\n</p>", "<p id=\"Par36\">Stepwise Multiple Linear Regression Analysis determined how different variables affected the PHQ-9, GAD-7 and SHS scores. Variables that were offered to the models were as follows: gender, age, type of study, GPA, year of study, full-time or part-time student, employees yes/no, residence, self-assessed financial status, average monthly income, failing a year in college yes/no, previous research project yes/no.</p>", "<p id=\"Par37\">All variables offered to the models for PHQ-9, GAD-7 and SHS were included in the final models. Gender, monthly income and failing a year were the most significant predictors for all the tested variables.</p>", "<p id=\"Par38\">The model for PHQ-9 explained 8.4% of the variance, determined as an adjusted R squared (R<sup>2</sup>) with a standard error of 6.28. The ANOVA test results suggest satisfactory explanatory power, F = 16.17, df = 12, <italic>p</italic> &lt; 0.001 (Table ##TAB##3##4##).\n</p>", "<p id=\"Par39\">The model for GAD-7 explained 5.8% of the variance, determined as an adjusted R squared (R<sup>2</sup>) with a standard error of 5.24. The ANOVA test results suggest satisfactory explanatory power, F = 10.82, df = 12, <italic>p</italic> &lt; 0.001 (Table ##TAB##3##4##).</p>", "<p id=\"Par40\">The model for SHS explained 6.8% of the variance, determined as an adjusted R squared (R<sup>2</sup>) with a standard error of 4.7. The ANOVA test results suggest satisfactory explanatory power, F = 12.46, df = 12, <italic>p</italic> &lt; 0.001 (Table ##TAB##3##4##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par41\">Our analysis of the levels of depression, anxiety and subjective happiness in students of health sciences students in Croatia showed concerning results. There were 41.4% of students that exhibited at least mild depressive symptoms, with 8% of students exhibiting moderately severe symptoms, and 1.8% severe depressive symptoms. Mild anxiety was found in 36.8%, moderate anxiety in 23.9% and severe anxiety in 15.8% of students.</p>", "<p id=\"Par42\">Women students had significantly higher levels of depression and anxiety than their men peers. Suicidal or auto-destructive ideations were present in 19.4% of students. Students in earlier years of the study showed higher levels of anxiety, depression and lower levels of subjective happiness. Students with lower self-assessed financial status had higher levels of anxiety and depression. Students that failed an academic year had higher levels of depression but lower levels of anxiety.</p>", "<p id=\"Par43\">In our previous study conducted in 2016, we assessed the same variables in medical and nursing students [##REF##31117829##5##]. We found that the anxiety levels in the current study were markedly higher than in our previous study. Among nursing students, we previously found that 55.7% exhibited at least mild anxiety levels, compared to 76.4% in this study. On the contrary, the levels of depression were lower in the current research; 57.3% of students exhibited at least mild depressive symptoms in our previous research, compared to the current 41.4% [##REF##31117829##5##]. However, the results are not completely comparable since, in the current study, we included other health science university studies and multiple institutions from different parts of Croatia. Thus, the sample was more diverse in the current study.</p>", "<p id=\"Par44\">Pursuing higher education can feel overwhelming for many students, marking a period of first independence from their parents, often accompanied by financial burdens, dealing with long study hours and pressure from family members [##UREF##4##26##]. Indeed, we found that low self-assessed financial status was associated with higher levels of depression and anxiety in our study. Kumar et al. found that higher financial status was associated with higher levels of happiness in nursing students [##REF##36419689##27##].</p>", "<p id=\"Par45\">Many students have to work part-time or full-time to ease the financial burden of university life, with the share of students working reaching up to 85% in certain countries [##UREF##5##28##, ##UREF##6##29##]. It has been shown that working students have more prevalent physical and mental problems due to the increased workload, sleep deprivation and lack of social contact with loved ones [##UREF##6##29##]. In our study, students that worked showed higher levels of depression and anxiety and lower levels of subjective happiness compared to students that did not work. When comparing these variables based on the type of employment, it can be seen that between the groups of students working in the medical field, outside the medical field, and those who are unemployed, students working in the medical field showed the lowest levels of depression and anxiety, and those who were employed outside the medical field, the highest. These results may imply that having a job in the medical field may give the students a sense of stability and competence, which may lead to better mental health.</p>", "<p id=\"Par46\">Higher levels of depression and anxiety in students of lower years of study might be associated with balancing new duties, but the curriculum obligations must also be taken into account in future research. Bachelor studies are often considered to be more difficult than Master’s studies in Croatia, and the analysis of whether this is a factor in students’ levels of depression and anxiety should be expanded upon in the future since several studies found that school was the main stressor for students [##UREF##1##8##, ##UREF##7##30##]. Medical and health sciences are often considered more demanding than other types of studies due to difficult courses but also because of the clinical work, which is often emotionally and physically demanding. Medical students have shown higher levels of depression and burnout than other university types of studies, and most research on the topic of mental health of university students was done on this population. Studies have shown that medical students often exhibit symptoms of burnout, with prevalence as high as 70—95% [##UREF##1##8##, ##REF##31774379##31##–##REF##29656675##33##]. The prevalence of depression in this population is 10–15% higher than in the general population [##UREF##7##30##].</p>", "<p id=\"Par47\">In our study, we found that students that failed a year in college had higher levels of depression and anxiety. However, it is difficult to suggest, based on our data, the direction in which these variables are associated, i.e., whether the initially decreased mental health leads to problems with studying or whether the stress related to school responsibilities leads to decreased mental health. The most plausible answer is that there is an interplay between the variables that eventually form a vicious circle.</p>", "<p id=\"Par48\">Even though the levels of depression are higher in medical students than in other health sciences students, the results are comparable, and there are no significant differences in anxiety levels between medical students and other health science students [##REF##31117829##5##, ##REF##31370266##10##]. A study in Turkey found that nursing students had a borderline to high prevalence of mental health problems compared to other university types of studies and the general population [##REF##30769177##34##]. Other studies found that nursing and public health students were less likely to have mental health problems than other university majors [##UREF##8##35##]. In the current study, we found a prevalence of at least mild depressive symptoms of 41.4%, which is similar to previous studies [##REF##31638442##1##, ##REF##27923076##3##, ##REF##31117829##5##–##UREF##1##8##, ##UREF##9##36##].</p>", "<p id=\"Par49\">Research has shown that 6–26% of students are diagnosed with a mental health issue [##REF##31638442##1##, ##UREF##0##7##, ##UREF##1##8##, ##UREF##7##30##]. Studies have shown that anxiety is more prevalent than depression, which is in line with our results [##UREF##7##30##]. Women students are usually more affected [##REF##32987932##37##–##REF##28876408##40##], even though a recent meta-analysis found no gender-related differences in anxiety in the medical student population [##REF##31370266##10##]. In our research, we also found significantly higher levels of anxiety in women students. It is important to note that most mental health problems occur in early adulthood, with the onset of 75% of mental health problems occurring by the age of 25, which coincides with the age of pursuing higher education [##REF##29768071##2##]. Still, only a third of them seek treatment [##UREF##1##8##, ##UREF##11##41##]. This shows that the stigma of mental health issues still exists, even among health sciences students [##UREF##12##42##]. Stigma is considered the most important obstacle to seeking professional help [##REF##29768071##2##].</p>", "<p id=\"Par50\">It has been shown that untreated mental health issues may progress into more complex psychiatric disorders, school dropout, addiction, and other auto-destructive behaviors [##REF##31324561##43##]. However, things might be changing as more students seek help at a rate exceeding enrolment increases [##REF##31324561##43##]. Not requesting help may lead to other negative outcomes, such as school dropout, suicidal ideation and burnout [##UREF##11##41##]. It is known that medical professionals have high rates of suicide [##UREF##4##26##, ##REF##32186412##32##]. Medical students show rates of suicidal ideations of 7.4 -24.2%, which are higher than those in the general university student population which are at a rate of 6.7% [##REF##27923076##3##, ##REF##25142250##9##, ##UREF##11##41##, ##REF##31324561##43##]. Even though we did not ask our participants about their suicidal ideations, we asked them about their self-destructive and suicidal ideations (Item 9 from the PHQ-9 scale: “<italic>Thoughts that you would be better off dead, or of hurting yourself</italic>”), and we found a rate of 19.4% which is comparable to prior results about suicidal ideations.</p>", "<p id=\"Par51\">Studies on nursing students showed that during the COVID-19 pandemic, they showed higher levels of anxiety or depression [##REF##34653783##15##, ##UREF##9##36##, ##REF##34202384##38##, ##UREF##13##44##–##UREF##14##47##]. Previous research has also shown that in pandemic outbreaks, nurses are more likely to experience worse mental health than doctors, which might be related to the increased time nurses spend in contact with patients when compared to physicians [##UREF##13##44##]. The COVID-19 pandemic has put a unique strain on students. In Croatia, following the onset of the COVID-19 pandemic, students were abruptly switched to online-only education, and not all students had a positive attitude towards that switch [##REF##33167960##48##].</p>", "<p id=\"Par52\">Meda et al. conducted a study on Italian students and reported higher levels of depression during the COVID-19 pandemic, with those students who previously showed no problems with mental health having a more pronounced increase in their levels of depression [##REF##33360865##49##]. However, the same research has shown that after the lockdown, the prevalence of psychiatric issues returned to levels before the lockdown [##REF##33360865##49##].</p>", "<p id=\"Par53\">Our study was conducted during March–April 2023 when most measures against COVID-19 were abolished, except in the clinical setting. Our results are in line with those of Meda et al., as the levels of depression and anxiety are comparable to those of similar research done before the COVID-19 pandemic [##REF##31117829##5##, ##REF##33360865##49##].</p>", "<p id=\"Par54\">Studies have shown that higher mental well-being is positively associated with empathy [##REF##28876408##40##]. Empathy is one of the most important traits for workers in healthcare. In this study, we assessed subjective happiness as a measure of well-being [##REF##23578272##12##]. Previous studies have shown that nursing students show higher levels of subjective happiness when compared to medical students [##REF##31117829##5##]. It is known that happier individuals tend to live longer, are more productive at the workforce and contribute to making society a better place through socially cooperative roles such as voluntary work [##UREF##2##13##]. Previous, albeit limited, research has shown low-to-moderate happiness levels in the nursing student population [##REF##36419689##27##].</p>", "<p id=\"Par55\">High levels of mental health problems in the population of students of health sciences present a reason for concern as it may damage professional performance, decrease empathy, ethical conduct and professionalism, and it may lead to personal consequences such as substance abuse, broken relationships, and suicidal ideation [##REF##31638442##1##, ##REF##21715992##50##].</p>", "<title>Limitations of the study</title>", "<p id=\"Par56\">Our study has several limitations. It was an online survey that guaranteed confidentiality and the students were free to decide whether they wished to participate. Due to our response rate (29%), it is possible that the students who exhibit mental problems were overrepresented and more motivated to participate in the study due to self-selection bias [##UREF##15##51##]. Since we used the cut-off points for mild anxiety and depression, the prevalence we found could represent an overestimation. Our study may provide a baseline for monitoring students’ mental health in the future. Even though we aimed to use a limited set of instruments to have a better completion rate, a broader set of instruments would give us a better picture of the possible underlying causes of the problems, and a qualitative study of these findings would be beneficial. Variables that would be useful to assess in future research are the levels of burnout, empathy, stress and personality and whether the students are diagnosed with a mental condition and are seeking professional help. Due to the nature of the study, our findings do not represent the official diagnoses of participants. Also, we would like to emphasize that even though there were more women among participants, this is representative of the demographics of health sciences students.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par57\">This study shows that health science students exhibit high levels of depression and anxiety at rates exceeding those in the general population reported in other studies. Since the well-being of medical professionals is essential for their professional work, adequate care must be given to these individuals to prevent further progression of mental illness.</p>", "<p id=\"Par58\">Our results may help educational institutions to put greater effort into the battle against mental health stigma, foster acceptance of mental health issues and encourage students to seek help when needed. Adequate mental health services are needed at universities to promote timely diagnosis and treatment of mental health problems.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Previous studies have shown that symptoms of depression and anxiety were highly prevalent among health sciences students. This may lead to other professional and personal difficulties and a decrease in individuals’ well-being. This study aimed to analyze levels of depression, anxiety and subjective happiness among health sciences students in Croatia.</p>", "<title>Methods</title>", "<p id=\"Par2\">We conducted a cross-sectional study in 10 higher education institutions in Croatia during March 2023. Eligible participants were health sciences students. Participants filled out an online survey consisting of sociodemographic questions and validated scales for determining the levels of depression (9-question Patient Health Questionnaire, PHQ-9), anxiety (General Anxiety Disorder 7-item scale, GAD-7), and happiness (Subjective Happiness Scale, SHS).</p>", "<title>Results</title>", "<p id=\"Par3\">Of 7460 invited students, 2137 students participated in the study (29% response rate). There were 41.4% of students that exhibited at least mild depressive symptoms, with 8% of students exhibiting moderately severe symptoms and 1.8% severe depressive symptoms. Mild anxiety was found in 36.8%, moderate anxiety in 23.9% and severe anxiety in 15.8% of students. The median SHS score was 19 (15.25–22).</p>", "<p id=\"Par4\">Women students had significantly higher levels of depression (<italic>p</italic> &lt; 0.001) and anxiety (<italic>p</italic> &lt; 0.001) than their men peers. Students in earlier study years showed higher levels of depression, anxiety and lower levels of subjective happiness compared to those in later study years. Students with lower self-assessed financial status had higher levels of depression (<italic>p</italic> &lt; 0.001) and anxiety (<italic>p</italic> &lt; 0.001). Students that failed an academic year had higher levels of depression (<italic>p</italic> &lt; 0.001), but lower levels of anxiety (<italic>p</italic> = 0.005).</p>", "<title>Conclusion</title>", "<p id=\"Par5\">In this study, we have shown that health sciences students exhibit high levels of depression and anxiety, at rates exceeding those in the general population reported in other studies. Our results may help educational institutions to put greater effort into the battle against mental health stigma, foster acceptance of mental health issues and encourage students to seek help when needed. Adequate mental health services are needed at universities to promote timely diagnosis and treatment of mental health problems.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12888-024-05498-5.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We are grateful to students who participated in the study.</p>", "<title>Authors’ contributions</title>", "<p>Study design: JMi, LP Data collection, analysis, and interpretation: JMi, NS, DM, SZ, MČ, KI, MM, JMe, ZP, MN, SČ, AR, LP Writing of the manuscript and revising the manuscript for intellectual content: JMi, NS, DM, SZ, MČ, KI, MM, JMe, ZP, MN, SČ, AR, LP Final approval of the manuscript: JMi, NS, DM, SZ, MČ, KI, MM, JMe, ZP, MN, SČ, AR, LP.</p>", "<title>Funding</title>", "<p>No extramural funding.</p>", "<title>Availability of data and materials</title>", "<p>Raw data collected and analyzed within this study are published on Open Science Framework (link: <ext-link ext-link-type=\"uri\" xlink:href=\"https://osf.io/ms2u4/\">https://osf.io/ms2u4/</ext-link>), except for the indirect identifiers of the participants.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par59\">The study protocol was approved by the Ethics Committees of all institutions participating in the study. All participants gave their written informed consent in the online interface prior to starting the online survey. All methods were carried out in accordance with relevant guidelines and regulations.</p>", "<title>Consent for publication</title>", "<p id=\"Par60\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par61\">The authors declare no competing interests.</p>" ]
[]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Sociodemographic characteristics of the tested population (<italic>N</italic> = 2137)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"/><th align=\"left\"><italic>n</italic> ( %)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Sex</td><td align=\"left\">Men</td><td align=\"left\">237 (12.8)</td></tr><tr><td align=\"left\">Women</td><td align=\"left\">1845 (86.3)</td></tr><tr><td align=\"left\">Decline to answer</td><td align=\"left\">19 (0.9)</td></tr><tr><td align=\"left\" rowspan=\"10\">Institution of study</td><td align=\"left\">Catholic University of Croatia</td><td align=\"left\">187 (8.7)</td></tr><tr><td align=\"left\">Libertas International University</td><td align=\"left\">130 (6.1)</td></tr><tr><td align=\"left\">Juraj Dobrila University of Pula</td><td align=\"left\">193 (9.0)</td></tr><tr><td align=\"left\">University North</td><td align=\"left\">194 (9.1)</td></tr><tr><td align=\"left\">University of Applied Health Sciences</td><td align=\"left\">542 (25.4)</td></tr><tr><td align=\"left\">University of Dubrovnik</td><td align=\"left\">47 (2.2)</td></tr><tr><td align=\"left\">University of Rijeka</td><td align=\"left\">291 (13.6)</td></tr><tr><td align=\"left\">University of Split</td><td align=\"left\">260 (12.2)</td></tr><tr><td align=\"left\">University of Zadar</td><td align=\"left\">153 (7.2)</td></tr><tr><td align=\"left\">Polytechnic of Bjelovar</td><td align=\"left\">140 (6.5)</td></tr><tr><td align=\"left\" rowspan=\"10\">Type of study</td><td align=\"left\">Nursing</td><td align=\"left\">1479 (69.2)</td></tr><tr><td align=\"left\">Clinical nutritionism</td><td align=\"left\">3 (0.1)</td></tr><tr><td align=\"left\">Dental hygiene</td><td align=\"left\">1 (0.0)</td></tr><tr><td align=\"left\">Physiotherapy</td><td align=\"left\">332 (15.5)</td></tr><tr><td align=\"left\">Medical laboratory diagnostics</td><td align=\"left\">74 (3.5)</td></tr><tr><td align=\"left\">Midwifery</td><td align=\"left\">44 (2.1)</td></tr><tr><td align=\"left\">Radiological technology</td><td align=\"left\">101 (4.7)</td></tr><tr><td align=\"left\">Occupational therapy</td><td align=\"left\">33 (1.5)</td></tr><tr><td align=\"left\">Sanitary engineering</td><td align=\"left\">68 (3.2)</td></tr><tr><td align=\"left\">Did not specify</td><td align=\"left\">3 (0.1)</td></tr><tr><td align=\"left\" rowspan=\"2\">Full-time or part-time student</td><td align=\"left\">Full-time</td><td align=\"left\">1123 (52.5)</td></tr><tr><td align=\"left\">Part-time</td><td align=\"left\">1014 (47.4)</td></tr><tr><td align=\"left\" rowspan=\"5\">Year of study</td><td align=\"left\">1</td><td align=\"left\">198 (9.3)</td></tr><tr><td align=\"left\">2</td><td align=\"left\">527 (24.6)</td></tr><tr><td align=\"left\">3</td><td align=\"left\">203 (9.5)</td></tr><tr><td align=\"left\">4</td><td align=\"left\">594 (27.8)</td></tr><tr><td align=\"left\">5</td><td align=\"left\">615 (28.8)</td></tr><tr><td align=\"left\" rowspan=\"3\">Employment</td><td align=\"left\">Employed in the medical field</td><td align=\"left\">821 (38.4)</td></tr><tr><td align=\"left\">Employed outside the medical field</td><td align=\"left\">424 (19.8)</td></tr><tr><td align=\"left\">Unemployed</td><td align=\"left\">892 (41.7)</td></tr><tr><td align=\"left\" rowspan=\"2\">Residence</td><td align=\"left\">Urban</td><td align=\"left\">1451 (67.9)</td></tr><tr><td align=\"left\">Rural</td><td align=\"left\">686 (32.1)</td></tr><tr><td align=\"left\" rowspan=\"5\">Size of residence</td><td align=\"left\"> &lt; 10000</td><td align=\"left\">879 (41.1)</td></tr><tr><td align=\"left\">10001–50000</td><td align=\"left\">545 (25.5)</td></tr><tr><td align=\"left\">50001–100000</td><td align=\"left\">226 (10.6)</td></tr><tr><td align=\"left\">100001–200000</td><td align=\"left\">136 (6.4)</td></tr><tr><td align=\"left\"> &gt; 200000</td><td align=\"left\">351 (16.4)</td></tr><tr><td align=\"left\" rowspan=\"5\">Self-assessed financial status</td><td align=\"left\">1 – very low</td><td align=\"left\">16 (0.7)</td></tr><tr><td align=\"left\">2</td><td align=\"left\">105 (4.9)</td></tr><tr><td align=\"left\">3</td><td align=\"left\">1007 (47.1)</td></tr><tr><td align=\"left\">4</td><td align=\"left\">826 (38.7)</td></tr><tr><td align=\"left\">5—excellent</td><td align=\"left\">183 (8.6)</td></tr><tr><td align=\"left\" rowspan=\"4\">Average monthly income</td><td align=\"left\"> &lt; 1000 €</td><td align=\"left\">193 (9.0)</td></tr><tr><td align=\"left\">1001–2000 €</td><td align=\"left\">905 (42.3)</td></tr><tr><td align=\"left\">2001–3000 €</td><td align=\"left\">636 (29.7)</td></tr><tr><td align=\"left\"> &gt; 3000 €</td><td align=\"left\">403 (18.8)</td></tr><tr><td align=\"left\" rowspan=\"2\">Failing a year in college</td><td align=\"left\">Yes</td><td align=\"left\">156 (7.3)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">1981 (92.7)</td></tr><tr><td align=\"left\" rowspan=\"2\">Doing a scientific project</td><td align=\"left\">Yes</td><td align=\"left\">404 (18.9)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">1733 (81.1)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Medians and interquartile ranges (IQR) of the scores of the PHQ-9 (The patient health questionnaire-9), GAD-7 (Generalized Anxiety Disorder-7), and Subjective Happiness Scale (SHS) scales depending on the different variables and the difference between those groups. For small groups, the 75th percentile, or both the 25th and the 75th percentile could not be calculated (<italic>N</italic> = 2138 participants)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"2\">PHQ-9</th><th align=\"left\" colspan=\"2\">GAD-7</th><th align=\"left\" colspan=\"2\">SSH</th></tr><tr><th align=\"left\">median (IQR)</th><th align=\"left\"><italic>p</italic></th><th align=\"left\">median (IQR)</th><th align=\"left\"><italic>p</italic></th><th align=\"left\">median (IQR)</th><th align=\"left\"><italic>p</italic></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Sex</td><td align=\"left\">Men</td><td align=\"left\">3 (7–10.5)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">3 (6–9)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">20 (16–23)</td><td align=\"left\">0.069</td></tr><tr><td align=\"left\">Women</td><td align=\"left\">8 (4–14)</td><td align=\"left\"/><td align=\"left\">8 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"9\">Type of study</td><td align=\"left\">Nursing</td><td align=\"left\">8 (4–13)</td><td align=\"left\">0.222</td><td align=\"left\">7 (4–12)</td><td align=\"left\">0.072</td><td align=\"left\">19 (16–22)</td><td align=\"left\">0.156</td></tr><tr><td align=\"left\">Clinical nutritionism</td><td align=\"left\">12 (1)</td><td align=\"left\"/><td align=\"left\">8 (5)</td><td align=\"left\"/><td align=\"left\">14 (13)</td><td align=\"left\"/></tr><tr><td align=\"left\">Dental hygiene</td><td align=\"left\">18</td><td align=\"left\"/><td align=\"left\">14</td><td align=\"left\"/><td align=\"left\">25</td><td align=\"left\"/></tr><tr><td align=\"left\">Physiotherapy</td><td align=\"left\">7.5 (3.25–13)</td><td align=\"left\"/><td align=\"left\">7 (3–11)</td><td align=\"left\"/><td align=\"left\">19 (15–23)</td><td align=\"left\"/></tr><tr><td align=\"left\">Medical laboratory diagnostics</td><td align=\"left\">9 (5–15.25)</td><td align=\"left\"/><td align=\"left\">10 (4.75–14.25)</td><td align=\"left\"/><td align=\"left\">17 (15–21)</td><td align=\"left\"/></tr><tr><td align=\"left\">Midwifery</td><td align=\"left\">9.5 (4.25–12.75)</td><td align=\"left\"/><td align=\"left\">10 (5–14.75)</td><td align=\"left\"/><td align=\"left\">19 (16.75–24)</td><td align=\"left\"/></tr><tr><td align=\"left\">Radiological technology</td><td align=\"left\">8 (3.5–14)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">18 (14–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">Occupational therapy</td><td align=\"left\">8 (6–13)</td><td align=\"left\"/><td align=\"left\">8 (3.5–12.5)</td><td align=\"left\"/><td align=\"left\">20 (15.25–24)</td><td align=\"left\"/></tr><tr><td align=\"left\">Sanitary engineering</td><td align=\"left\">9 (6–15)</td><td align=\"left\"/><td align=\"left\">8.5 (5–12)</td><td align=\"left\"/><td align=\"left\">17 (14–21)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"2\">Full-time or part-time student</td><td align=\"left\">Full-time</td><td align=\"left\">8 (4–14)</td><td align=\"left\">0.007</td><td align=\"left\">8 (4–13)</td><td align=\"left\">0.061</td><td align=\"left\">19 (15–22)</td><td align=\"left\">0.019</td></tr><tr><td align=\"left\">Part-time</td><td align=\"left\">8 (4–13)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (16–22)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"5\">Year of study</td><td align=\"left\">1</td><td align=\"left\">9 (5–14)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">8 (4–12)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">14 (12–23)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">2</td><td align=\"left\">9 (4–14)</td><td align=\"left\"/><td align=\"left\">8 (4–13)</td><td align=\"left\"/><td align=\"left\">19 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">3</td><td align=\"left\">8 (4–14)</td><td align=\"left\"/><td align=\"left\">9 (5–13)</td><td align=\"left\"/><td align=\"left\">18 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">4</td><td align=\"left\">6 (3–11)</td><td align=\"left\"/><td align=\"left\">6 (3–10)</td><td align=\"left\"/><td align=\"left\">20 (17–24)</td><td align=\"left\"/></tr><tr><td align=\"left\">5</td><td align=\"left\">6 (3–11)</td><td align=\"left\"/><td align=\"left\">6 (4–9)</td><td align=\"left\"/><td align=\"left\">20 (17–23)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"3\">Employment</td><td align=\"left\">In the medical field</td><td align=\"left\">7 (4–12)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">7 (4–11)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">20 (17–22)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">Outside the medical field</td><td align=\"left\">9 (5–16)</td><td align=\"left\"/><td align=\"left\">8.5 (5–13)</td><td align=\"left\"/><td align=\"left\">18 (14–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">Unemployed</td><td align=\"left\">8 (4–14)</td><td align=\"left\"/><td align=\"left\">8 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"2\">Residence</td><td align=\"left\">Urban</td><td align=\"left\">8 (4–13)</td><td align=\"left\">0.888</td><td align=\"left\">7 (4–12)</td><td align=\"left\">0.793</td><td align=\"left\">19 (16–22)</td><td align=\"left\">0.083</td></tr><tr><td align=\"left\">Rural</td><td align=\"left\">8 (4–14)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"5\">Size of residence</td><td align=\"left\"> &lt; 10000</td><td align=\"left\">8 (4–14)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">10001–50000</td><td align=\"left\">9 (4–13)</td><td align=\"left\">0.650</td><td align=\"left\">8 (4–12)</td><td align=\"left\">0.628</td><td align=\"left\">19 (16–22)</td><td align=\"left\">0.178</td></tr><tr><td align=\"left\">50001–100000</td><td align=\"left\">8 (4–13)</td><td align=\"left\"/><td align=\"left\">7 (4–11.25)</td><td align=\"left\"/><td align=\"left\">19 (16–23)</td><td align=\"left\"/></tr><tr><td align=\"left\">100001–200000</td><td align=\"left\">7 (3–13.75)</td><td align=\"left\"/><td align=\"left\">7 (3–12)</td><td align=\"left\"/><td align=\"left\">19 (15–22.25)</td><td align=\"left\"/></tr><tr><td align=\"left\"> &gt; 200000</td><td align=\"left\">8 (4–13)</td><td align=\"left\"/><td align=\"left\">8 (4–13)</td><td align=\"left\"/><td align=\"left\">20 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"5\">Self-assessed financial status</td><td align=\"left\">1</td><td align=\"left\">15 (4.25–23.75)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">8.5 (3–14.75)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">15.5 (13.75–22.25)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">2</td><td align=\"left\">12 (6–18.75)</td><td align=\"left\"/><td align=\"left\">11 (6–15)</td><td align=\"left\"/><td align=\"left\">16.5 (13–20)</td><td align=\"left\"/></tr><tr><td align=\"left\">3</td><td align=\"left\">9 (5–14)</td><td align=\"left\"/><td align=\"left\">8 (5–12)</td><td align=\"left\"/><td align=\"left\">18 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">4</td><td align=\"left\">7 (3–13)</td><td align=\"left\"/><td align=\"left\">7 (4–11.25)</td><td align=\"left\"/><td align=\"left\">20 (16–23)</td><td align=\"left\"/></tr><tr><td align=\"left\">5</td><td align=\"left\">6 (3–11)</td><td align=\"left\"/><td align=\"left\">6 (3–12)</td><td align=\"left\"/><td align=\"left\">21 (17–24)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"4\">Average monthly income</td><td align=\"left\"> &lt; 1000€</td><td align=\"left\">9 (6–16)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">9 (5–14)</td><td align=\"left\">0.010</td><td align=\"left\">18 (15–22)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">1001–2000€</td><td align=\"left\">9 (4–14)</td><td align=\"left\"/><td align=\"left\">8 (5–12)</td><td align=\"left\"/><td align=\"left\">18 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">2001–3000€</td><td align=\"left\">7 (4–13)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (16–23)</td><td align=\"left\"/></tr><tr><td align=\"left\"> &gt; 3000€</td><td align=\"left\">7 (3–13)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">20 (17–23)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"2\">Failing a year in college</td><td align=\"left\">Yes</td><td align=\"left\">11 (5–16)</td><td align=\"left\"/><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">17 (14–21)</td><td align=\"left\"/></tr><tr><td align=\"left\">No</td><td align=\"left\">8 (4–13)</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">9.5 (5–14)</td><td align=\"left\">0.005</td><td align=\"left\">19 (16–22)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\" rowspan=\"2\">Doing a scientific project</td><td align=\"left\">Yes</td><td align=\"left\">8 (4–14)</td><td align=\"left\"/><td align=\"left\">8 (5–13)</td><td align=\"left\">0.105</td><td align=\"left\">19 (15–22)</td><td align=\"left\"/></tr><tr><td align=\"left\">No</td><td align=\"left\">8 (4–13)</td><td align=\"left\">0.184</td><td align=\"left\">7 (4–12)</td><td align=\"left\"/><td align=\"left\">19 (16–22)</td><td align=\"left\">0.783</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>The frequencies and percentages of the categories of depressive and anxiety symptoms according to the GAD-7 (Generalized Anxiety Disorder-7) and PHQ-9 (The patient health questionnaire-9) scales and the sex-related differences (<italic>N</italic> = 2138)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"2\"/><th align=\"left\" colspan=\"3\">n (%)</th><th align=\"left\"><italic>P</italic> (Chi square)</th></tr><tr><th align=\"left\"><bold>Men</bold></th><th align=\"left\"><bold>Women</bold></th><th align=\"left\"><bold>Total</bold></th><th align=\"left\"> &lt; 0.001</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"4\">GAD-7</td><td align=\"left\">Low anxiety</td><td align=\"left\">81 (32.5)</td><td align=\"left\">398 (22.4)</td><td align=\"left\">484 (23.6)</td><td align=\"left\"/></tr><tr><td align=\"left\">Mild anxiety</td><td align=\"left\">103 (41.4)</td><td align=\"left\">646 (36.3)</td><td align=\"left\">752 (36.8)</td><td align=\"left\"/></tr><tr><td align=\"left\">Moderate anxiety</td><td align=\"left\">41 (16.5)</td><td align=\"left\">445 (25.0)</td><td align=\"left\">488 (23.9)</td><td align=\"left\"/></tr><tr><td align=\"left\">Severe anxiety</td><td align=\"left\">24 (9.6)</td><td align=\"left\">291 (16.3)</td><td align=\"left\">324 (15.8)</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"5\">PHQ-9</td><td align=\"left\">Low levels of depressive symptoms</td><td align=\"left\">189 (69.2)</td><td align=\"left\">1056 (57.2)</td><td align=\"left\">1253 (58.6)</td><td align=\"left\">0.003</td></tr><tr><td align=\"left\">Mild depressive symptoms</td><td align=\"left\">42 (15.4)</td><td align=\"left\">383 (20.8)</td><td align=\"left\">427 (20.0)</td><td align=\"left\"/></tr><tr><td align=\"left\">Moderate depressive symptoms</td><td align=\"left\">26 (9.5)</td><td align=\"left\">216 (11.7)</td><td align=\"left\">246 (11.5)</td><td align=\"left\"/></tr><tr><td align=\"left\">Moderately severe depressive symptoms</td><td align=\"left\">15 (5.5)</td><td align=\"left\">152 (8.2)</td><td align=\"left\">172 (8.0)</td><td align=\"left\"/></tr><tr><td align=\"left\">Severe depressive symptoms</td><td align=\"left\">1 (0.4)</td><td align=\"left\">38 (2.1)</td><td align=\"left\">39 (1.8)</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>The unstandardized coefficient betas of the variables included in the stepwise multiple linear regression analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"2\"><bold>PHQ-9</bold></th><th align=\"left\" colspan=\"2\"><bold>GAD-7</bold></th><th align=\"left\" colspan=\"2\"><bold>SHS</bold></th></tr><tr><th align=\"left\">Beta</th><th align=\"left\">Standard Error</th><th align=\"left\">Beta</th><th align=\"left\">Standard Error</th><th align=\"left\">Beta</th><th align=\"left\">Standard Error</th></tr></thead><tbody><tr><td align=\"left\">Gender</td><td align=\"left\">2.042<sup>***</sup></td><td align=\"left\">0.411</td><td align=\"left\">2.065<sup>***</sup></td><td align=\"left\">0.343</td><td align=\"left\">-0.613<sup>*</sup></td><td align=\"left\">0.310</td></tr><tr><td align=\"left\">Age</td><td align=\"left\">-0.138<sup>***</sup></td><td align=\"left\">0.025</td><td align=\"left\">-0.092<sup>***</sup></td><td align=\"left\">0.021</td><td align=\"left\">0.067<sup>***</sup></td><td align=\"left\">0.019</td></tr><tr><td align=\"left\">Type of study</td><td align=\"left\">0.051</td><td align=\"left\">0.065</td><td align=\"left\">-,023</td><td align=\"left\">0.055</td><td align=\"left\">-0.069</td><td align=\"left\">0.049</td></tr><tr><td align=\"left\">GPA</td><td align=\"left\">-0.889<sup>**</sup></td><td align=\"left\">0.286</td><td align=\"left\">-0.491<sup>*</sup></td><td align=\"left\">0.239</td><td align=\"left\">0.556<sup>*</sup></td><td align=\"left\">0.217</td></tr><tr><td align=\"left\">Year of study</td><td align=\"left\">-0.347<sup>**</sup></td><td align=\"left\">0.130</td><td align=\"left\">-0.246<sup>*</sup></td><td align=\"left\">0.108</td><td align=\"left\">-0.113</td><td align=\"left\">0.099</td></tr><tr><td align=\"left\">Full-time or part-time student</td><td align=\"left\">-0.288</td><td align=\"left\">0.379</td><td align=\"left\">-0.277</td><td align=\"left\">0.316</td><td align=\"left\">0.248</td><td align=\"left\">0.286</td></tr><tr><td align=\"left\">Employed</td><td align=\"left\">-0.176</td><td align=\"left\">0.224</td><td align=\"left\">-0.072</td><td align=\"left\">0.187</td><td align=\"left\">-0.288</td><td align=\"left\">0.170</td></tr><tr><td align=\"left\">Residence</td><td align=\"left\">-0.332</td><td align=\"left\">0.296</td><td align=\"left\">-0.149</td><td align=\"left\">0.248</td><td align=\"left\">-0.178</td><td align=\"left\">0.224</td></tr><tr><td align=\"left\">Financial status</td><td align=\"left\">-0.079</td><td align=\"left\">0.174</td><td align=\"left\">-0.027</td><td align=\"left\">0.145</td><td align=\"left\">0.214</td><td align=\"left\">0.131</td></tr><tr><td align=\"left\">Monthly income</td><td align=\"left\">-1.452<sup>***</sup></td><td align=\"left\">0.207</td><td align=\"left\">-0.887<sup>***</sup></td><td align=\"left\">0.173</td><td align=\"left\">1.177<sup>***</sup></td><td align=\"left\">0.157</td></tr><tr><td align=\"left\">Failing a year in college</td><td align=\"left\">2.041<sup>***</sup></td><td align=\"left\">0.536</td><td align=\"left\">1.189<sup>**</sup></td><td align=\"left\">0.448</td><td align=\"left\">-1.200<sup>**</sup></td><td align=\"left\">0.405</td></tr><tr><td align=\"left\">Previous research project</td><td align=\"left\">0.834<sup>*</sup></td><td align=\"left\">0.356</td><td align=\"left\">0.776<sup>**</sup></td><td align=\"left\">0.297</td><td align=\"left\">-0.040</td><td align=\"left\">0.270</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Note: 19 participants declined to specify their gender and were excluded from the analysis. Due to missing data in certain items of the GAD-7, the scores could not be calculated for 90 participants</p></table-wrap-foot>", "<table-wrap-foot><p><sup>*</sup><italic>p</italic> &lt; 0.05</p><p><sup>**</sup><italic>p</italic> &lt; 0.01</p><p><sup>***</sup><italic>p</italic> &lt; 0.001</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12888_2024_5498_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Supplementary file 1.</bold> Invitation and information for participants.</p></caption></media>", "<media xlink:href=\"12888_2024_5498_MOESM2_ESM.docx\"><caption><p><bold>Additional file 2: Supplementary file 2.</bold> Survey used in the research.</p></caption></media>", "<media xlink:href=\"12888_2024_5498_MOESM3_ESM.docx\"><caption><p><bold>Additional file 3: Supplementary file 3.</bold> Response rates per institutions and number of students in different study courses accross specialty per institution.</p></caption></media>" ]
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{ "acronym": [ "PHQ-9", "GAD-7", "SHS", "GPA", "IQR" ], "definition": [ "Patient Health Questionnaire 9", "General Anxiety Disorder 7", "Subjective Happiness Scale", "Grade point average", "Inter-quartile range" ] }
51
CC BY
no
2024-01-14 23:43:45
BMC Psychiatry. 2024 Jan 13; 24:50
oa_package/9e/29/PMC10787412.tar.gz
PMC10787413
38216923
[ "<title>Background</title>", "<p id=\"Par7\">Malaria affects millions of lives yearly, severely impacting tropical and subtropical regions [##UREF##0##1##]. Despite being largely preventable, in 2021 alone, an estimated 247 million people were infected with malaria across 85 countries, resulting in over 600,000 deaths [##UREF##1##2##]. In the ongoing global struggle against malaria, a promising development has emerged. The World Health Organization (WHO) recently endorsed the R21/Matrix-M<sup>™</sup> Malaria Vaccine for preventing malaria across vulnerable age groups. This endorsement followed guidance from the Strategic Advisory Group of Experts on Immunization (SAGE) and the Malaria Policy Advisory Group (MPAG) [##UREF##2##3##]. Developed through a partnership between the University of Oxford and the Serum Institute of India, a major supplier of vaccines to Africa, together with Novavax, a large biotechnology company which supplied the adjuvant, the R21/Matrix-M vaccine builds on the partial success of the RTS,S/AS01 malaria vaccine demonstrated in clinical trials. It represents a significant advancement in providing enhanced protection against malaria [##UREF##3##4##].</p>", "<p id=\"Par8\">Notably, phase 3 clinical trials have shown the R21/Matrix-M 12-month Vaccine Efficacy (VE) to be 75% in locations characterized by seasonal variations, while it registered at 68% in standard locations [##UREF##0##1##]. The VE against multiple clinical malaria episodes exhibited a comparable pattern, with rates of 75% at the seasonal sites and 67% at the standard sites, marking a substantial step forward in the battle against this disease [##UREF##0##1##]. Designed to be low-dose, cost-effective, and readily accessible, this vaccine holds immense potential for malaria-endemic countries in tropical regions. It has also received approval for use in children under 3 years old, who are at the highest risk of malaria-related fatalities [##REF##33964223##5##, ##REF##32236404##6##]. This perspective paper aims to analyse the R21/Matrix-M Malaria Vaccine, its development process, its potential impact on global malaria eradication efforts, and the challenges and opportunities it presents.</p>" ]
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[ "<title>Conclusion</title>", "<p id=\"Par17\">The endorsement by the WHO of the R21/Matrix-M malaria vaccine represents a significant step towards global malaria eradication. Its remarkable efficacy and ongoing scale-up efforts hold immense promise. However, it is essential to recognize that vaccines are not a standalone solution, but a critical addition to existing interventions. A multifaceted approach that combines vaccination with other proven measures will be key to successfully combating malaria and achieving long-term eradication.</p>" ]
[ "<p id=\"Par1\">Malaria affects millions of lives annually, particularly in tropical and subtropical regions. Despite being largely preventable, 2021 witnessed 247 million infections and over 600,000 deaths across 85 countries. In the ongoing battle against malaria, a promising development has emerged with the endorsement by the World Health Organization (WHO) of the R21/Matrix-M<sup>™</sup> Malaria Vaccine. Developed through a collaboration between the University of Oxford and Novavax, this vaccine has demonstrated remarkable efficacy, reaching 77% effectiveness in Phase 2 clinical trials. It is designed to be low-dose, cost-effective, and accessible, with approval for use in children under three years old. This perspective paper critically examines the R21/Matrix-M malaria vaccine, its development, potential impact on global malaria eradication efforts, and the challenges and opportunities it presents.</p>", "<title>Keywords</title>" ]
[ "<title>The breakthrough vaccine</title>", "<p id=\"Par9\">Studies have shown that the R21/Matrix-M vaccine exhibits remarkable efficacy and safety in Phase II trials, including among children who received a booster dose of R21/Matrix-M 1 year after completing a primary three-dose regimen [##UREF##4##7##]. Initially focused on inducing high-level T-cell responses against pre-erythrocytic liver-stage malaria antigens, the vaccine's scope has recently expanded to include the induction of high-level antibodies against the sporozoite stage of the life cycle [##UREF##0##1##]. A distinguishing feature of this vaccine is the inclusion of Novavax’s Matrix-M, a saponin-based adjuvant known for enhancing immune responses, resulting in greater effectiveness and durability. Matrix-M stimulates the recruitment of antigen-presenting cells at the injection site and improves antigen presentation in local lymph nodes. This technology has previously proven successful in Novavax's COVID-19 vaccine and plays a critical role in developing other vaccines in the pipeline [##REF##32236404##6##]. Notably, the R21/Matrix-M vaccine boasts higher efficacy than previous malaria vaccines, offering up to 77% protection against the malaria parasite in clinical trials. It is among the most promising candidates for an effective malaria vaccine [##UREF##2##3##, ##UREF##5##8##].</p>", "<p id=\"Par10\">In October 2021, the WHO recommended the RTS, S/AS01 malaria vaccine for preventing <italic>P. falciparum</italic> malaria in regions with moderate to high transmission, particularly among children, but this vaccine provides only partial immunity against malaria in children [##REF##33964223##5##]. What sets the R21/Matrix-M vaccine apart is its efficacy among children, who are often the most vulnerable to malaria [##UREF##4##7##]. This enhances its potential to have a broad and enduring impact on malaria control [##REF##27355532##9##]. However, there is an observed decline in VE among older children [##UREF##0##1##]. Vaccine-induced antibodies targeting the conserved central NANP repeat sequence of the circumsporozoite protein exhibited a robust correlation with VE. The 5–17-month age group demonstrated significantly higher antibody titers than 18–36-month-olds (p &lt; 0.0001). Specifically, when comparing the two age groups, VE was significantly higher in the younger age group (78%) than in the older age group (70%). This was observed in both seasonal and standard sites: in the seasonal sites, efficacy in the younger age group was 79% and at standard sites, 75%. Importantly, the difference in VE between the two age groups was statistically significant (p &lt; 0.05), emphasizing the importance of developing malaria vaccines with high efficacy across all age groups. Further studies are warranted to explore the factors contributing to the decline in VE in older children.</p>", "<p id=\"Par11\">Furthermore, despite the encouraging results observed in the published clinical trials, it is important to acknowledge concerns regarding VE in both seasonal and standard sites. While the recently released Phase III results did not identify significant differences in VE between seasonal and standard sites, a discernible trend toward higher efficacy in seasonal sites was noted [##UREF##0##1##]. Specifically, over 12 months, VE for the time leading up to the initial clinical malaria episode was 75% in the seasonal sites and 68% in the standard sites [##UREF##0##1##]. Similarly, VE against multiple clinical malaria episodes exhibited comparable figures: 75% in the seasonal sites and 67% in the standard sites. A parallel decline in efficacy over the initial year of follow-up was observed at both seasonal and standard sites. Notably, at the seasonal sites, the introduction of a booster dose demonstrated sustained efficacy for up to 18 months: VE was 74% for the time to the first clinical malaria episode and 72% against multiple clinical malaria episodes. This suggests a potential role for timing and consideration that the VE dynamics might differ if R21 were implemented non-seasonally as part of routine childhood vaccination programmes.</p>", "<p id=\"Par12\">It is also important to note that the original RTS,S trial did not include chemoprevention in its design, setting it apart from the recent R21 Phase III trial [##REF##25913272##10##]. While the authors of the R21 trial adjusted for the confounding factor of chemoprevention and found no discernible impact on protective associations, a lingering debate questions whether such adjustments truly replicate the conditions of an efficacy trial where chemoprevention was absent [##UREF##0##1##]. This is crucial in interpreting the malaria vaccine trial outcomes.</p>", "<p id=\"Par13\">Nonetheless, this innovation represents a significant leap towards reducing the mortality and morbidity caused by this disease. It may pave the way for the global eradication of this preventable yet devastating illness. According to the WHO, the R21 vaccine has been proven safe in clinical trials [##UREF##2##3##], and like other new vaccines, safety monitoring will continue.</p>", "<title>Future directions and prospects</title>", "<p id=\"Par14\">The future of malaria control hinges on recognizing that malaria is a complex and multi-dimensional problem [##UREF##6##11##]. While the R21/Matrix-M<sup>™</sup> Malaria Vaccine is a promising tool, it cannot work in isolation. Malaria control should encompass a range of interventions, including vector control, prompt diagnosis and treatment, community education, and infrastructure development. Moreover, as malaria is endemic in diverse settings, the approach must be adaptable and context-specific. What works in one region may not be suitable for another. Integrating these various strategies in a coordinated manner at the local, national, and international levels is essential. Therefore, tailoring malaria interventions, including vaccine deployment, based on local data and context is imperative. Local factors such as mosquito species, climate, and healthcare infrastructure can significantly influence the effectiveness of interventions. Robust research and data collection efforts are essential to inform decision-making. Furthermore, community engagement is vital. Local communities must be involved in the design and implementation of control measures. This enhances the effectiveness of interventions and fosters community ownership and sustainability.</p>", "<p id=\"Par15\">The inclusion of vaccines in comprehensive malaria control plans signifies a paradigm shift. Historically, malaria control primarily relied on vector control and treatment [##UREF##7##12##]. The introduction of vaccines represents a significant advancement. These vaccines serve as a means to protect individuals and as tools to reduce overall malaria transmission in endemic areas. Integration also requires robust surveillance systems to monitor vaccine impact and malaria prevalence. This data-driven approach ensures that vaccines are deployed strategically, targeting high-transmission areas with the most significant impact.</p>", "<p id=\"Par16\">High-burden regions, especially in sub-Saharan Africa, demand particular attention [##UREF##0##1##]. These areas experience the greatest malaria burden, including the highest mortality rates among children under five. Deploying vaccines like the R21/Matrix-M<sup>™</sup> in these regions can substantially reduce malaria-related morbidity and mortality. Equity in vaccine distribution is essential to ensure that vulnerable populations in high-burden regions have access to the same level of protection as those in lower-burden areas. Efficient distribution and administration are essential to ensure vaccines reach the intended recipients. Timely deployment and proper cold chain management are critical to maintain vaccine efficacy. Minimizing wastage is cost-effective and ensures that vaccines are used to their full potential. Furthermore, equitable access to vaccines is essential to prevent disparities in coverage. This requires addressing logistical challenges, infrastructure gaps, and supply chain issues.</p>" ]
[ "<title>Acknowledgements</title>", "<p>None</p>", "<title>Author contributions</title>", "<p>NA conceptualised the study; All authors were involved in the literature review; GO and NA extracted the data from the reviews studies; All authors wrote the final and first drafts. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>No funding was received for this study.</p>", "<title>Availability of data and materials</title>", "<p>Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par18\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par19\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par20\">The authors declare that they have no competing interests.</p>" ]
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[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["1."], "surname": ["Datoo", "Dicko", "Tinto", "Ou\u00e9draogo", "Hamaluba", "Olotu"], "given-names": ["MS", "A", "H", "JB", "M", "A"], "article-title": ["A Phase III randomised controlled trial evaluating the malaria vaccine candidate R21/Matrix-M\u2122 in African children"], "source": ["Lancet"], "year": ["2024"], "pub-id": ["10.2139/ssrn.4584076"]}, {"label": ["2."], "collab": ["WHO"], "source": ["World Malaria Report 2022"], "year": ["2022"], "publisher-loc": ["Geneva"], "publisher-name": ["World Health Organization"]}, {"label": ["3."], "mixed-citation": ["World Health Organization. WHO recommends R21/Matrix-M vaccine for malaria prevention in updated advice on immunization. 2023. "], "ext-link": ["https://www.who.int/news/item/02-10-2023-who-recommends-r21-matrix-m-vaccine-for-malaria-prevention-in-updated-advice-on-immunization"]}, {"label": ["4."], "mixed-citation": ["Oxford University. Malaria vaccine proves highly effective in a groundbreaking clinical trial. 2021. "], "ext-link": ["https://www.ox.ac.uk/news/2021-04-23-malaria-vaccine-proves-highly-effective-groundbreaking-clinical-trial"]}, {"label": ["7."], "mixed-citation": ["University of Oxford. R21/Matrix-M malaria vaccine developed by the University of Oxford receives regulatory approval. 2023. "], "ext-link": ["https://www.ox.ac.uk/news/2023-04-13-r21matrix-m-malaria-vaccine-developed-university-oxford-receives-regulatory"]}, {"label": ["8."], "mixed-citation": ["Malaria Vaccine Implementation Program (MVIP). Malaria vaccine implementation program (MVIP). "], "ext-link": ["https://www.malariavaccine.org/"]}, {"label": ["11."], "mixed-citation": ["University of Oxford, News and Events. Oxford R21/Matrix-M\u2122 malaria vaccine receives WHO recommendation for use paving the way for global roll-out. 2023 "], "ext-link": ["https://www.ox.ac.uk/news/2023-10-02-oxford-r21matrix-m-malaria-vaccine-receives-who-recommendation-use-paving-way-global"]}, {"label": ["12."], "mixed-citation": ["UN News. WHO approves second malaria vaccine for children. New York: United Nations. 2023. "], "ext-link": ["https://news.un.org/en/story/2023/10/1141787"]}]
{ "acronym": [ "VE", "WHO", "RTS,S/AS01", "COVID-19", "R21/Matrix-M" ], "definition": [ "Vaccine Efficacy", "World Health Organization", "Malaria vaccine abbreviation", "Coronavirus Disease 2019", "Malaria vaccine abbreviation" ] }
12
CC BY
no
2024-01-14 23:43:45
Malar J. 2024 Jan 12; 23:16
oa_package/ae/49/PMC10787413.tar.gz
PMC10787414
38216870
[ "<title>Background</title>", "<p id=\"Par6\">In Germany, 1.8 million people live with dementia [##UREF##0##1##] and one third of them live in a long-term care facility [##UREF##1##2##]. Worldwide, around 57.4 million people are affected, and this number will increase 152.8 million in 2050 [##UREF##2##3##]. Dementia is a clinical syndrome, characterised by cognitive, neuropsychiatric, and functional symptoms. Psychological and psychiatric changes finally lead to restrictions in daily life [##UREF##3##4##]. The care of people living with dementia is challenging for all people involved, i.e. the person living with dementia, their family members and health professionals, due to frequently occuring changed behaviour like aggression, agitation, sleep disturbances, wandering and restlessness [##REF##25731881##5##].</p>", "<p id=\"Par7\">In order to meet the complex care needs of people living with dementia, it is necessary to provide care based on patients’ individual needs [##REF##29361064##6##]. Person-centredness is considered as best practice for people living with dementia and essential for high-quality long-term care for older people [##REF##18339351##7##]. Person-centred care (PCC) was developed by Tom Kitwood, based on Roger’s social-psychological theory of personhood [##UREF##4##8##]. It is based on an established therapeutically relationship between the respective person and the health professional and means respect for the person, the individual’s right to self-determination, mutual respect and understanding [##UREF##5##9##]. To provide PCC, a supportive care environment is needed. This includes, for example, creating a PCC culture, implementing PCC educational programs for staff or designing health care facilities promoting PCC [##UREF##6##10##]. For this reason, some organisational conditions are necessary, e.g., PCC skills training for health professionals and creating a person-centred culture and environment. It is essential, that the organisation (e.g., the nursing home) creates conditions to enable person-centredness [##UREF##7##11##]. It becomes clear, that the implementation of PCC is very complex and this change process is time consuming [##UREF##6##10##]. In recent years, PCC has become a key indicator of quality in health care. In the course of this, numerous measurement instruments have been developed that capture person-centredness or related constructs [##UREF##8##12##].</p>", "<p id=\"Par8\">An early developed, theoretically based and in research frequently used instrument is the Person-centred Climate Questionnaire (PCQ) [##REF##18702777##13##–##REF##31664918##15##]. The PCQ was developed based on a theoretical concept regarding supportive care settings [##REF##16324058##16##], literature and a content validity analysis [##REF##18702777##13##]. The original Swedish 14-item version for patients (PCQ-P) was developed and later on supplemented by another version for health care staff (PCQ-S) and family members (PCQ-F). Person-centred care concerns the patient, family and staff, why different scales are needed to address the different perspectives and to assess to what extent family members or health care staff perceive the care environment as person-centred.</p>", "<p id=\"Par9\">The items of these versions are identical, they are answered using a six-point scale (1 = No, I disagree completely to 6 = Yes, I agree completely). Different versions only differ in their perspective. The instrument items operationalise the following subscales: a climate of safety (five items), a climate of everydayness (five items) and a climate of community (four items). All items are sum scored and scores can range from 14 (a climate not very person-centred) to 84 (a climate very person-centred) [##REF##19793235##17##]. After the PCQ-S was translated into English [##REF##20465729##18##], numerous further translations and psychometric evaluation studies were carried out for the Norwegian PCQ-S [##REF##22380607##19##], the Chinese PCQ-S [##REF##28851797##20##], and the Slovenian PCQ-S [##REF##28393416##21##]. A German version of the instrument is not available so far. Therefore, we translated all three versions of the questionnaire into German language within the project “MoNoPol-Sleep - Multi-modal, non-pharmacological intervention to avoid sleep disturbances in people living in nursing home with dementia” [##REF##33430785##22##] and piloted. We report the translation of the English language PCQ and the evaluation of the item distribution, internal consistency and structural validity of the translated German version based on staff ratings (PCQ-G-S) in a nursing home context.</p>" ]
[ "<title>Methods</title>", "<title>Study design</title>", "<p id=\"Par10\">A cross-sectional study was conducted to determine the item distribution, internal consistency and structural validity of the PCQ-G-S. The investigation of the structural validity was based on an exploratory factor analysis (principal component analysis). This methodical approach was based on the COSMIN standards for test theory studies [##REF##33267819##23##]. The Ethical Committee of the German Society of Nursing Science approved the study protocol for all study centres (no. 20–016).</p>", "<title>Setting and population</title>", "<p id=\"Par11\">Participants were nurses and nursing assistants of the nursing homes enrolled in the MoNoPol-Sleep study (trial registration: ISRCTN36015309) during baseline assessment. Nursing homes were recruited by three regions in Germany (Lübeck: Northern Germany; Halle (Saale): Eastern Germany; Witten: Western Germany). Each region recruited eight nursing homes, first using already existing contacts. Additionally, nursing homes were recruited by means of nursing home registers, information folders, announcements in relevant nursing journals in Germany and the study website (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.monopol-sleep.de\">www.monopol-sleep.de</ext-link>). Nursing homes were contacted via phone or email and verbally informed about the aim and content of the study. Nursing homes with at least 50 residents were eligible for inclusion. Nurses and nursing assistants were included if they were working at least three night shifts in the last three months and were contracted for at least part-time (half-a-day). Inclusion criteria and recruitment have been described in detail elsewhere [##REF##33430785##22##].</p>", "<title>Questionnaire translation</title>", "<p id=\"Par12\">All three versions of the PCQ have been translated into German language (PCQ-G) based on four of the five steps recommended for cross-cultural adaption of measures [##REF##11124735##24##] in the preparatory phase of the MoNoPol-sleep study [##REF##33430785##22##]. Each step was documented in a comprehensible manner. The first stage was the forward translation, performing two independent translations from English to German by two different persons. Both translators were native German speakers with excellent English language skills. Next to the translation, it was possible to enter comments on difficulties in wording or other uncertainties. The second stage contained the synthesis of the translations. Translation results were discussed, inconsistencies were reviewed, and a final translation was agreed. Stage three comprised the back translation. The final version from stage two was back translated by two persons independently. The back-translators had English as mother tongue and excellent skills in German language. Both have been involved with translation issues in research before. Also, in this stage it was possible to enter comments on difficulties in wording or other uncertainties. In stage four an expert committee meeting was carried out. All four translators and the coordinator of the translation process (first author of this paper) were involved in this meeting. During the meeting, all versions of the questionnaire were reviewed, and discrepancies discussed until a consensus was reached. This stage was for validity checking to make sure that the translated version of the questionnaire was reflecting the same item content as the original version. After the fourth stage, the whole documentation of the translation process was sent to the author of the original PCQ, and we received permission for the accuracy of the translation. The final version of the PCQ-G is displayed in Table ##SUPPL##0##S1##. In a final step, based on the available knowledge from the literature and the translation process, a user manual for the German language PCQ was created that is freely available to potential users [##UREF##10##25##]. We did not perform a pretest as a fifth step as recommended by Beaton et al. (2000) [##REF##11124735##24##]. This was due to the restrictive protective measures for nursing homes and the enormous burden of nurses caused by the COVID-19 pandemic, which made it difficult to access nurses for a pretest at the time of the measurement translation.</p>", "<title>Data collection procedures</title>", "<p id=\"Par13\">The PCQ-G staff version (PCQ-G-S) was part of a 7-page questionnaire measuring nurses’ attitudes regarding the implementation of change processes, person-centredness in care and inter-professional cooperation, as part of the process evaluation in the MoNoPol-Sleep study [##REF##33430785##22##]. Beside the PCQ-G-S, the questionnaire consisted demographic variables. The questionnaire was handed out by the supervising nurse. Participating nurses and nursing assistants received information about the aim and content of the study at the first page of the questionnaire. Furthermore, they received information that informed consent was provided by filling in the questionnaire. Questionnaires were returned by postal mail or personally collected by one researcher in the nursing home. In general, the application of the PCQ-G-S was based on the recommendations by the authors of the original instrument as documented in the German user manual [##UREF##10##25##].</p>", "<title>Data analysis</title>", "<p id=\"Par14\">Descriptive statistics were calculated for demographic characteristics and item distribution of the PCQ-G-S items. For the item distribution, the cut-off values were set at &lt; 0.8 and &gt; 3.2, based on the recommendations of Bortz &amp; Döring (2006) [##UREF##11##26##].</p>", "<p id=\"Par15\">In a second step, an explorative factor analysis was performed based on a principal component analysis (PCA). Reasons for conducting the exploratory factor analysis were: no previous knowledge of the factor structure of the PCQ-G S version and the limited sample of nurses available in the Monopol-Sleep study. In addition, the chosen procedure also corresponds to the procedures for the first psychometric evaluation in other countries ( [##REF##22380607##19##–##REF##28393416##21##].</p>", "<p id=\"Par16\">The prerequisites for conducting a PCA were tested [##UREF##12##27##]: Measure of sample adequacy was performed with the Kaiser-Meyer-Olkin (KMO) criterion. The KMO should be ≥ 0.5. Additionally, the Bartlett’s test for sphericity was conducted. The common significance level of &lt; 0.05 was used for verification of a non-existent item correlation assumed before conducted the component analysis [##UREF##12##27##]. After, the factor analysis was performed, based on a PCA using an orthogonal rotational procedure (varimax). The factor extraction followed the criteria: (1) eigenvalues &gt; 1 for a factor (Kaiser-Guttman criterion), and (2) scree plot. Missing values were pairwise excluded. The internal consistency of the scale was evaluated by calculating Cronbach’s α coefficients [##UREF##13##28##]. Data were entered into SPSS v. 22 [##UREF##14##29##]. Plausibility checks were carried out during data entry. To ensure data quality, all data were checked by a second person.</p>" ]
[ "<title>Results</title>", "<title>Characteristics of the sample</title>", "<p id=\"Par17\">A total sample of 120 nurses was included in data analysis. The mean age of participants was 40.7 (SD 11.7), with an average working experience in the care of people living with dementia of 14.6 years (SD 10.1). Participants’ demographic characteristics are displayed in Table ##TAB##0##1##.</p>", "<p id=\"Par18\">\n\n</p>", "<title>Item distribution</title>", "<p id=\"Par19\">The descriptive investigation of the PCQ-G-S showed a balanced distribution (Table ##TAB##1##2##). The response option “yes, I agree” was used most often whereas the response option “no, I disagree completely” was used least frequently. Distributions of the other response options also varied. Based on the mean values, five items (item 4, item 11, item 12, item 13, item 14) showed a ceiling effect (&gt; 0.8). Missing value analyses demonstrated very low percentages of missing values in general. Only item 3, 5 and 9 of the PCQ-G-S showed a percentage of missing values of 1.7% and items 2, 4, 7 and 11 a percentage of missing values of 0.8%. The reason for this was nurses’ and nursing assistants’ denial to rate.</p>", "<p id=\"Par20\">\n\n</p>", "<title>Structural validity</title>", "<p id=\"Par21\">PCA was used to evaluate scale dimensionality and structural validity since Bartlett’s test of sphericity yielded X<sup>2</sup> = 1048,911, was significant (P &lt; 0.01) and Kaiser-Meyer-Olkin was satisfactory (0.863). This indicates the appropriateness of the factor analysis of the data. Kaiser’s eigenvalue &gt; 1 criterion was used to decide on the number of components to extract and a component loading cut-off of 0.5 was used to conclude if an item loaded on a specific component. Based on a first exploratory PCA, three factors with a Kaiser’s eigenvalue &gt; 1 were determined. The scree plot illustrates the result (see Fig. ##FIG##0##1##). Thus, the analysis resulted in a 3-component solution, where all 14 items could be assigned with 68.6% of the total variance. The results of the analysis including factor loads of each item are presented in Table ##TAB##2##3##.</p>", "<p id=\"Par22\">\n\n</p>", "<p id=\"Par23\">\n\n</p>", "<title>Internal consistency</title>", "<p id=\"Par24\">The reliability analysis using Cronbach’s alpha coefficient of the 14-item PCQ-G-S showed a strong internal consistency based on Cronbach’s alpha scores for each of the three subscales: “a climate of safety”: alpha = 0.845, “a climate of everydayness”: alpha = 0.877 and “a climate of community”: alpha = 0.867 (Table ##TAB##2##3##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par25\">The investigation of the item distribution of the PCQ-G-S demonstrated a balanced distribution of the six response options. Nine out of 14 items showed an acceptable item difficulty, but five items (item 4, 11, 12, 13, 14) showed a ceiling effect (&gt; 0.8). However, it should not be generally indicated to cancel these items of the PCQ-G-S. Instead, it must be considered that this is an exploratory study and further evaluation of the scale validity are needed including a larger sample. Since the item distribution has not yet been examined in other studies, no comparison of the results is possible. Further research is justified needed here, because the identified ceiling effects affect all items of the subscale climate of community and 36% of all PCQ-G-S items.</p>", "<p id=\"Par26\">The results for structural validity show that the original factor structure of the PCQ-G is robust. Similar to the original Swedish version [##REF##18702777##13##], the 14 items of the PCQ-G-S could be assigned to the three subscales a climate of safety, a climate of everydayness, and a climate of community. The same instrument structure was found for the Swedish (Edvardsson et al., 2009), Norwegian [##REF##22380607##19##], Slovenian [##REF##28393416##21##], and Chinese [##REF##28851797##20##] versions. Thus, Cai et al. (2017) found a stable three-factor solution explaining 73.3% of the total variance for the Chinese version (“a climate of safety”: 0.58 to 0.84; “a climate of everydayness”: 0.68 to 0.82”; “a climate of community”: 0.64 to 0.66), Bergland et al. (2012) reported the three-factor solution that explained nearly 68% of the variance in the data for the Norwegian version (“a climate of safety”: 0.55 to 0.84; “a climate of everydayness”: 0.49 to 0.83”; “a climate of community”: 0.62 to 0.80) and Vrbnjak et al. (2017) found a three-factor solution that explained 71.22% of the variance in the data of the Slovenian version (“a climate of safety”: 0.59 to 0.87; “a climate of everydayness”: 0.77 to 0.84”; “a climate of community”: 0.54 to 0.86). The analysis of the original Swedish version resulted in a three-factor solution explaining 60.0% of the total variance (“a climate of safety”: 0.64 to 0.79; “a climate of everydayness”: 0.57 to 0.78, “a climate of community”: 0.58–0.82) [##REF##19793235##17##]. Therefore, scale dimensionality could be seen as confirmed.</p>", "<p id=\"Par27\">Psychometric evaluation of the English PCQ-S resulted in a four-component rotated solution (a climate of safety, a climate of everydayness, a climate of community and a climate of comprehensibility) explaining 71,8% of the total variance [##REF##20465729##18##]. The fourth subscale “a climate of comprehensibility” included four items, relating to the extent staff provided understandable information to patients, patients felt safe, staff were easy to talk to and where patients also had others to talk about their experiences [##REF##20465729##18##]. In the original version, these four items belonged to the subscales a climate of safety and climate of community [##REF##19793235##17##]. Edvardsson et al. (2010) explained the deviation from the original version with three subscales by the fact that the study evaluating the original Swedish version included a sample working on an elective surgery ward with a short length of stay. Because of limited possibility for interactions between staff and patients, the sample in this study may felt prioritising that patients understand implemented medical procedures instead of focusing on proving PCC [##REF##20465729##18##].</p>", "<p id=\"Par28\">Based on a Rasch analysis of the English PCQ-S, residual correlations greater than 0.29 than the mean correlation in the matrix were found. This indicated some evidence of local dependence between two items (item 13 “a place where it is easy for patients to talk to staff”; item 14 “a place where patients have someone to talk”) of subscale three. Since removing or combining item 13 and 14 caused other difficulties, according to Wilberforce et al. (2019) the two items were kept.</p>", "<p id=\"Par29\">The 14-item PCQ-G-S consists of three subscales. It showed strong internal consistency for each of the three subscales a climate of safety (alpha = 0.845), a climate of everydayness (alpha = 0.877), and a climate of community (alpha = 0.867). These results are in line with the results of previous psychometric evaluations. Also, the Swedish [##REF##19793235##17##], English [##REF##20465729##18##], Norwegian [##REF##22380607##19##], Slovenian [##REF##28393416##21##] and Chinese [##REF##28851797##20##] version of the PCQ-S showed internal consistency scores of at least 0.77 for each subscale. Sample sizes in previous studies were comparable to our study. Only in the study of Cai et al. (2017) included more participants (n = 1237).</p>", "<p id=\"Par30\">Although further evaluations in other settings and with lager sample sizes are necessary, e.g. studies evaluation reliability, the PCG-G already contribute to gain a deeper understanding of the extent of person-centred care provided in German-language countries. Additionally, the psychometric properties of the family and patient version should be tested. After that, it would be possible to identify similarities and differences about person-centredness is perceived through patients, families, and staff.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par31\">A major strength of this study is that additionally to the German version of the PCQ, a user manual for the questionnaire (PCQ-G) was developed which is now available online. Thus, an internationally proven questionnaire for the assessment of person-centredness is available for research and practice in the German-speaking countries. Moreover, this is the first study evaluating the psychometric properties of the staff version of the PCQ-G.</p>", "<p id=\"Par32\">This study has some limitations. First, only the staff version of the PCQ-G was evaluated. This means that an evaluation of the patient and family versions is pending and recommended. Second, given the relatively small number of nurses and nursing assistants included in the study, results must be interpreted with caution and have to be proven in a larger study with a confirmatory approach for the PCQ-G-S. Third, the PCQ-G-S was only applied in nursing homes participating in the MoNoPol-Sleep study [##REF##33430785##22##]. Further psychometric validation in different settings is needed to ensure generalisability and to help for further comparisons in different contexts. Fourth, we were unable to perform a pretest of the translated PCG-G-S as recommend by Beaton et al. (2000) [##REF##11124735##24##], because of the restrictions and enormous burden in nursing homes during the COVID-19 pandemic. However, it is crucial to state that no relevant uncertainties regarding the understanding of the items arose in the translation process. Consequently, the decision not to pretest was pragmatic and appropriate considering the context. Moreover, the development of cut-off scores for interpretation purposes is a future goal for the PCQ-G versions.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par33\">The aim of this study was the translation and examination of first psychometric properties of the PCQ-G-S in a nursing home context. The results of this study indicate first evidence for the internal consistency and structural validity for the use of the PCQ-G-S to assess the degree of person-centeredness. Based on these results the questionnaire should be used in further studies to measure person-centredness in nursing homes. Therefore, the item distribution, reliability and especially the construct validity of the PCQ-G-S should be further investigated.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Person-centredness is considered as best practice for people living with dementia. A frequently used instrument to assess person-centredness of a care environment is the Person-centred Climate Questionnaire (PCQ). The questionnaire comprises of 14 items with the three subscales a climate of safety, a climate of everydayness and a climate of community.</p>", "<title>Aim</title>", "<p id=\"Par2\">The aim of the study is to describe the translation process of the English language Person-centred Climate Questionnaire (Staff version, Patient version, Family version) into German language (PCQ-G) and to evaluate the first psychometric properties of the German language Person-centred Climate Questionnaire– Staff version (PCQ-G-S).</p>", "<title>Methods</title>", "<p id=\"Par3\">We conducted a cross-sectional study. The three versions of the 14-item English PCQ were translated into German language (PCQ-G) based on the recommendations for cross-cultural adaption of measures. Item distribution, internal consistency and structural validity of the questionnaire were assessed among nursing home staff (PCQ-G-S). Item distribution was calculated using descriptive statistics. Structural validity was tested using principal component analysis (PCA), and internal consistency was assessed for the resulting subscales using Cronbach’s alpha. Data collection took place from May to September 2021.</p>", "<title>Results</title>", "<p id=\"Par4\">A total sample of 120 nurses was included in the data analysis. Nine out of 14 items of the PCQ-G-S demonstrated acceptable item difficulty, while five times showed a ceiling effect. The PCA analysis demonstrated a strong structural validity for a three-factor solution explaining 68.6% of the total variance. The three subscales demonstrated a good internal consistency with Cronbach’s alpha scores of 0.8 for each of the subscales.</p>", "<title>Conclusion</title>", "<p id=\"Par5\">The analysis of the 14-item German version (PCQ-G-S) showed first evidence for a strong internal consistency and structural validity for evaluating staff perceptions of the person-centredness in German nursing homes. Based on this, further investigations for scale validity of the PCQ-G versions should be carried out.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12877-023-04528-3.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We would like to thank all staff nurses, nursing assistants and nursing home managers who participated in the study.</p>", "<title>Author contributions</title>", "<p>Study Concept and Design: DW, RM, AB, JD, NB, TK, GM, MH, SK, MND. Data Analysis and Interpretation: DW, RM, AB, JD, NB, TK, GM, MH, SK, MND. Drafting the Manuscript: DW, RM, AB, JD, NB, TK, GM, MH, SK, MND.</p>", "<title>Funding</title>", "<p>This study was funded by the German Federal Ministry of Education and Research (BMBF grants 01GL1802A-C).</p>", "<title>Data Availability</title>", "<p>Data is available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par35\">Ethical approval was received from the ethics committee of the German Society of Nursing Science (no. 20–016). This study was performed in accordance with the relevant regulations and guidelines. All participants provided informed consent.</p>", "<title>Consent of publication</title>", "<p id=\"Par36\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par34\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Principal component analysis – scree plot (Total N = 120)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Characteristics of nurses and nursing assistants (Total N = 120)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"2\">Nurses and nursing assistants</th><th align=\"left\"/></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\">Age, years, mean (SD)</td><td align=\"left\">40.7 (± 11.7)</td></tr><tr><td align=\"left\" colspan=\"2\">Contract hours, number (%)</td><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"> Full time</td><td align=\"left\">46 (50.5)</td></tr><tr><td align=\"left\"/><td align=\"left\"> Part time</td><td align=\"left\">45 (49.5)</td></tr><tr><td align=\"left\" colspan=\"2\">Years working in elderly care, mean (SD)</td><td align=\"left\">14.6 (± 10.1)</td></tr><tr><td align=\"left\" colspan=\"2\">Healthcare training, number (%)</td><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"> Elderly care</td><td align=\"left\">57 (50)</td></tr><tr><td align=\"left\"/><td align=\"left\"> Health care nursing</td><td align=\"left\">20 (17.5)</td></tr><tr><td align=\"left\"/><td align=\"left\"> Paediatric nursing</td><td align=\"left\">2 (1.8)</td></tr><tr><td align=\"left\"/><td align=\"left\"> Other*</td><td align=\"left\">35 (30.7)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Item distribution per item and total score – German version of the PCQ-G-S (N = 120)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"3\">Subscales and Items</th><th align=\"left\" colspan=\"6\">Response options</th><th align=\"left\"/><th align=\"left\"/><th align=\"left\"/></tr><tr><th align=\"left\" colspan=\"3\">A climate of safety</th><th align=\"left\">No, I disagree completely</th><th align=\"left\">No, I disagree</th><th align=\"left\">No, I partly disagree</th><th align=\"left\">Yes, I partly agree</th><th align=\"left\">Yes, I agree</th><th align=\"left\">Yes, I agree completely</th><th align=\"left\">Missing values</th><th align=\"left\">Item difficulty</th><th align=\"left\">Mean</th></tr></thead><tbody><tr><td align=\"left\"/><td align=\"left\">1.</td><td align=\"left\">A place where I feel welcome</td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">6</td><td align=\"left\">25</td><td align=\"left\">58</td><td align=\"left\">29</td><td align=\"left\">0 (0)</td><td align=\"left\">0.77</td><td align=\"left\">4.9 (0.9)</td></tr><tr><td align=\"left\"/><td align=\"left\">2.</td><td align=\"left\">A place where I feel acknowledged as a person</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">9</td><td align=\"left\">22</td><td align=\"left\">52</td><td align=\"left\">35</td><td align=\"left\">1 (0.8)</td><td align=\"left\">0.78</td><td align=\"left\">4.9 (0.9)</td></tr><tr><td align=\"left\"/><td align=\"left\">3.</td><td align=\"left\">A place where I feel I can be myself</td><td align=\"left\">1</td><td align=\"left\">7</td><td align=\"left\">8</td><td align=\"left\">28</td><td align=\"left\">44</td><td align=\"left\">30</td><td align=\"left\">2 (1.7)</td><td align=\"left\">0.72</td><td align=\"left\">4.7 (1.2)</td></tr><tr><td align=\"left\"/><td align=\"left\">4.</td><td align=\"left\">A place where the patients are in safe hands<sup>a</sup></td><td align=\"left\">0</td><td align=\"left\">5</td><td align=\"left\">2</td><td align=\"left\">23</td><td align=\"left\">44</td><td align=\"left\">45</td><td align=\"left\">1 (0.8)</td><td align=\"left\">\n<bold>0.88</bold>\n</td><td align=\"left\">5.0 (1.0)</td></tr><tr><td align=\"left\"/><td align=\"left\">5.</td><td align=\"left\">A place where the staff use a language that the patients can understand</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">9</td><td align=\"left\">26</td><td align=\"left\">43</td><td align=\"left\">39</td><td align=\"left\">2 (1.7)</td><td align=\"left\">0.77</td><td align=\"left\">4.9 (1.0)</td></tr><tr><td align=\"left\" colspan=\"3\">\n<bold>A climate of everydayness</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\">6.</td><td align=\"left\">A place which feels homely even though it is in an institution</td><td align=\"left\">1</td><td align=\"left\">8</td><td align=\"left\">11</td><td align=\"left\">37</td><td align=\"left\">41</td><td align=\"left\">22</td><td align=\"left\">0 (0)</td><td align=\"left\">0.69</td><td align=\"left\">4.5 (1.1)</td></tr><tr><td align=\"left\"/><td align=\"left\">7.</td><td align=\"left\">A place where there is something nice to look at</td><td align=\"left\">2</td><td align=\"left\">4</td><td align=\"left\">18</td><td align=\"left\">42</td><td align=\"left\">42</td><td align=\"left\">11</td><td align=\"left\">1 (0.8)</td><td align=\"left\">0.64</td><td align=\"left\">4.3 (1.0)</td></tr><tr><td align=\"left\"/><td align=\"left\">8.</td><td align=\"left\">A place where it is quiet and peaceful</td><td align=\"left\">0</td><td align=\"left\">6</td><td align=\"left\">19</td><td align=\"left\">29</td><td align=\"left\">53</td><td align=\"left\">13</td><td align=\"left\">0 (0)</td><td align=\"left\">0.68</td><td align=\"left\">4.4 (1.0)</td></tr><tr><td align=\"left\"/><td align=\"left\">9.</td><td align=\"left\">A place where it is possible to get unpleasant thoughts out of your head</td><td align=\"left\">3</td><td align=\"left\">11</td><td align=\"left\">23</td><td align=\"left\">36</td><td align=\"left\">33</td><td align=\"left\">12</td><td align=\"left\">2 (1.7)</td><td align=\"left\">0.60</td><td align=\"left\">4.0 (1.2)</td></tr><tr><td align=\"left\"/><td align=\"left\">10.</td><td align=\"left\">A place which is neat and clean</td><td align=\"left\">2</td><td align=\"left\">4</td><td align=\"left\">17</td><td align=\"left\">27</td><td align=\"left\">45</td><td align=\"left\">25</td><td align=\"left\">0 (0)</td><td align=\"left\">0.71</td><td align=\"left\">4.5 (1.2)</td></tr><tr><td align=\"left\" colspan=\"3\">\n<bold>A climate of community</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\">11.</td><td align=\"left\">A place where it is easy for the patients to keep in contact with their loved ones<sup>a</sup></td><td align=\"left\">0</td><td align=\"left\">2</td><td align=\"left\">4</td><td align=\"left\">25</td><td align=\"left\">40</td><td align=\"left\">48</td><td align=\"left\">1 (0.8)</td><td align=\"left\">\n<bold>0.81</bold>\n</td><td align=\"left\">5.1 (0.9)</td></tr><tr><td align=\"left\"/><td align=\"left\">12.</td><td align=\"left\">A place where it is easy for the patients to receive visitors<sup>a</sup></td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">1</td><td align=\"left\">17</td><td align=\"left\">47</td><td align=\"left\">52</td><td align=\"left\">0 (0)</td><td align=\"left\">\n<bold>0.81</bold>\n</td><td align=\"left\">5.2 (0.9)</td></tr><tr><td align=\"left\"/><td align=\"left\">13.</td><td align=\"left\">A place where it is easy for the patients to talk to the staff<sup>a</sup></td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">6</td><td align=\"left\">15</td><td align=\"left\">37</td><td align=\"left\">62</td><td align=\"left\">0 (0)</td><td align=\"left\">\n<bold>0.84</bold>\n</td><td align=\"left\">5.3 (0.9)</td></tr><tr><td align=\"left\"/><td align=\"left\">14.</td><td align=\"left\">A place where the patients have someone to talk to if they so wish<sup>a</sup></td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">6</td><td align=\"left\">18</td><td align=\"left\">42</td><td align=\"left\">51</td><td align=\"left\">0 (0)</td><td align=\"left\">\n<bold>0.82</bold>\n</td><td align=\"left\">5.1 (1.0)</td></tr><tr><td align=\"left\" colspan=\"3\">\n<bold>Total Score</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">66.6 (10.4)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Structural validity results of the PCQ-G-S based on the total sample (N = 120)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">No.</th><th align=\"left\">PCQ-G Staff version</th><th align=\"left\">Factor 1<break/> A climate of safety</th><th align=\"left\">Factor 2<break/> A climate of everydayness</th><th align=\"left\">Factor 3<break/> A climate of community</th></tr></thead><tbody><tr><td align=\"left\">1.</td><td align=\"left\">A place where I feel welcome</td><td align=\"left\">0.804</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">2.</td><td align=\"left\">A place where I feel acknowledged as a person</td><td align=\"left\">0.793</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">3.</td><td align=\"left\">A place where I feel I can be myself</td><td align=\"left\">0.810</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">4.</td><td align=\"left\">A place where the patients are in safe hands</td><td align=\"left\">0.502</td><td align=\"left\"/><td align=\"left\">(0.473)</td></tr><tr><td align=\"left\">5.</td><td align=\"left\">A place where the staff use a language that the patients can understand</td><td align=\"left\">0.521</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">6.</td><td align=\"left\">A place which feels homely even though it is in an institution</td><td align=\"left\">(0.470)</td><td align=\"left\">0.498</td><td align=\"left\"/></tr><tr><td align=\"left\">7.</td><td align=\"left\">A place where there is something nice to look at</td><td align=\"left\"/><td align=\"left\">0.715</td><td align=\"left\"/></tr><tr><td align=\"left\">8.</td><td align=\"left\">A place where it is quiet and peaceful</td><td align=\"left\"/><td align=\"left\">0.707</td><td align=\"left\"/></tr><tr><td align=\"left\">9.</td><td align=\"left\">A place where it is possible to get unpleasant thoughts out of your head</td><td align=\"left\">(0.426)</td><td align=\"left\">0.725</td><td align=\"left\"/></tr><tr><td align=\"left\">10.</td><td align=\"left\">A place which is neat and clean</td><td align=\"left\"/><td align=\"left\">0.805</td><td align=\"left\"/></tr><tr><td align=\"left\">11.</td><td align=\"left\">A place where it is easy for the patients to keep in contact with their loved ones</td><td align=\"left\"/><td align=\"left\">(0.472)</td><td align=\"left\">0.673</td></tr><tr><td align=\"left\">12.</td><td align=\"left\">A place where it is easy for the patients to receive visitors</td><td align=\"left\"/><td align=\"left\">(0.409)</td><td align=\"left\">0.779</td></tr><tr><td align=\"left\">13.</td><td align=\"left\">A place where it is easy for the patients to talk to the staff</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.748</td></tr><tr><td align=\"left\">14.</td><td align=\"left\">A place where the patients have someone to talk to if they so wish</td><td align=\"left\">0.442</td><td align=\"left\"/><td align=\"left\">0.788</td></tr><tr><td align=\"left\"/><td align=\"left\">\n<bold>Cumulative explained variance (%)</bold>\n</td><td align=\"left\">51,60</td><td align=\"left\">61,07</td><td align=\"left\">68,88</td></tr><tr><td align=\"left\"/><td align=\"left\">\n<bold>Cronbach’s alpha</bold>\n</td><td align=\"left\">0,845</td><td align=\"left\">0,877</td><td align=\"left\">0,867</td></tr><tr><td align=\"left\"/><td align=\"left\">\n<bold>Kaiser-Meyer-Olkin (KMO) criterion</bold>\n</td><td align=\"left\">0,863</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"><p>\n<bold>Bartlett’s test</bold>\n</p><p>\n<bold>of sphericity</bold>\n</p></td><td align=\"left\">P &lt; 0,005</td><td align=\"left\"/><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Missing values were pairwise excluded</p><p>* e.g. nursing assistant</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup> Item difficulty: Items with floor effects (&lt; 0.2) or ceiling effects (&gt; 0.8) in boldt. Data are the mean (SD) or number (%). Missing values were pairwise excluded</p></table-wrap-foot>", "<table-wrap-foot><p>Only factor loadings &gt; 0.40 are presented; factor loadings in parentheses imply that a specific item loads to more than one factor and that the factor loading to the other factor is higher</p><p>Missing values were pairwise excluded</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12877_2023_4528_Fig1_HTML\" id=\"d32e1029\"/>" ]
[ "<media xlink:href=\"12877_2023_4528_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>" ]
[{"label": ["1."], "mixed-citation": ["DAlzG. "], "italic": ["Informationsblatt 1. Die H\u00e4ufigkeit von Demenzerkrankungen"], "ext-link": ["https://www.deutsche-alzheimer.de/fileadmin/Alz/pdf/factsheets/infoblatt1_haeufigkeit_demenzerkrankungen_dalzg.pdf"]}, {"label": ["2."], "mixed-citation": ["DAlzG. "], "italic": ["Zahlen zu H\u00e4ufigkeit, Pflegebedarf und Versorgung Demenzkranker in Deutschland"], "ext-link": ["https://www.pflegeversicherung-direkt.de/_Resources/Persistent/5cd8c700bdeb89e0795b2480b1a9d99c8c1523c1/Daten-Zahlen_2016-10-von-DALZG.pdf"]}, {"label": ["3."], "mixed-citation": ["GBD. 2019 Dementia Forecasting Collaborators, "], "italic": ["Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019"]}, {"label": ["4."], "surname": ["Gale", "Acar", "Daffner"], "given-names": ["SA", "D", "KR"], "source": ["Dement Am J Med"], "year": ["2018"], "volume": ["131"], "issue": ["10"], "fpage": ["1161"], "lpage": ["9"], "pub-id": ["10.1016/j.amjmed.2018.01.022"]}, {"label": ["8."], "surname": ["Kitwood"], "given-names": ["T"], "source": ["Dementia reconsidered: the person comes first"], "year": ["1997"], "publisher-loc": ["Berkshire, UK"], "publisher-name": ["Open University Press"]}, {"label": ["9."], "surname": ["McCormack", "McCance"], "given-names": ["B", "TV"], "source": ["Person-centred practice in nursing and Healthcare: theory and practice"], "year": ["2017"], "publisher-loc": ["London"], "publisher-name": ["Wiley-Blackwell"]}, {"label": ["10."], "mixed-citation": ["Santana MJ et al. "], "italic": ["How to practice person-centred care: A conceptual framework"]}, {"label": ["11."], "mixed-citation": ["Dichter MN et al. "], "italic": ["Organizational interventions for promoting person-centred care for people with dementia (Protocol)"]}, {"label": ["12."], "surname": ["DeSilva"], "given-names": ["D"], "source": ["Helping measure person-centred care: a review of evidence about commonly used approaches and tools used to help measure person-centred care"], "year": ["2014"], "publisher-loc": ["London"], "publisher-name": ["The Health Foundation"]}, {"label": ["14."], "mixed-citation": ["Xu L et al. "], "italic": ["Person-centered climate, Garden Greenery and Well-being among nursing home residents: a cross-sectional study"]}, {"label": ["25."], "mixed-citation": ["Wilfling D et al. "], "italic": ["Person-Centered Climate Questionnaire \u2013 German version (PCQ-G). Benutzerhandbuch f\u00fcr die deutschsprachige Version"]}, {"label": ["26."], "mixed-citation": ["Bortz J, D\u00f6ring N. "], "italic": ["Forschungsmethoden und Evaluation: f\u00fcr Human- und Sozialwissenschaftler"]}, {"label": ["27."], "mixed-citation": ["Field A, Miles J, Field Z. "], "italic": ["Discovering Statistics Using R"]}, {"label": ["28."], "surname": ["Polit"], "given-names": ["DF"], "source": ["Statistics and Data Analysis for Nursing Research"], "year": ["2014"], "publisher-loc": ["Upper Saddle River, NJ"], "publisher-name": ["Prentice Hall"]}, {"label": ["29."], "collab": ["IBM"], "source": ["IBM SPSS statistics for windows"], "year": ["2013"], "publisher-loc": ["Armonk"], "publisher-name": ["IBM Corp"]}]
{ "acronym": [], "definition": [] }
29
CC BY
no
2024-01-14 23:43:45
BMC Geriatr. 2024 Jan 12; 24:57
oa_package/f0/f2/PMC10787414.tar.gz
PMC10787415
0
[ "<title>Background</title>", "<p id=\"Par22\">Infertility is a worldwide health concern, affecting approximately 168 million people of reproductive age, globally [##UREF##0##1##]. Infertility is defined as the inability to consume a child after 12 or more months of unprotected intercourse [##UREF##0##1##]. Involuntary childlessness can be considered a life crisis with a great impact on physical, social, emotional, and psychological aspects of life [##UREF##0##1##–##REF##34109898##4##]. Social stigma, domestic violence, divorce, decrease in self-esteem, stress, anxiety, and depression are amongst the adverse psychosocial effect of infertility [##UREF##0##1##, ##REF##34109898##4##–##UREF##1##6##]. Even though fertility treatments have evolved during the past decades, these procedures often cause patients physical and or mental distress [##REF##26979745##2##, ##REF##25631310##5##, ##REF##31249819##7##]. The emotional tension experienced by infertile women may lead to changes in endocrine system regulation and probably result in adverse pregnancy outcomes [##REF##25631310##5##, ##UREF##1##6##, ##UREF##2##8##].</p>", "<p id=\"Par23\">A pandemic occurs when a disease spread worldwide, passing international borders and infecting a large number of people [##REF##21734771##9##]. Pandemics and the measures that are taken to control or suppress them such as patient isolation, social distancing, and quarantine can increase mental distress and perceived risk of disease, which leads to psychological consequences including stress, anxiety, depression, delirium, and even post-traumatic stress disorder [##UREF##3##10##].</p>", "<p id=\"Par24\">In December 2019, cases of infection with the new coronavirus were reported in Wuhan, China [##UREF##4##11##]. Soon after, the virus was spread across the world, and in May 2020 it was declared a pandemic by World Health Organization [##REF##32191675##12##, ##UREF##5##13##]. The majority of people infected with this virus through droplet transmission have mild to moderate symptoms, but in some cases, the severity of symptoms may lead to death [##UREF##5##13##]. Until now 767,984,989 people were infected by the virus and more than 6.9 million people lost their lives [##UREF##6##14##]. In addition to physical effects, coronavirus can affect the psychological well-being of individuals [##UREF##4##11##, ##REF##32799105##15##]. People reported fear of infection and/or death, depression, anger, violence, anxiety, and insecurity as the result of the coronavirus pandemic [##UREF##4##11##, ##UREF##7##16##, ##REF##32485289##17##].</p>", "<p id=\"Par25\">In order to disconnect the transmission chain and decrease the pressure on the health system, governments adopted strategies including social distancing, quarantine practices, and postponing non-urgent medical treatments [##REF##32466995##18##–##UREF##8##20##]. Even though access to fertility treatments is considered a reproductive right [##UREF##0##1##], due to the coronavirus pandemic and its unknown effect on fertility and pregnancy most fertility treatments were postponed [##REF##32466995##18##, ##REF##32404170##19##]. The European Society of Human Reproduction and Embryology (ESRHE) and the American Society for Reproductive Medicine (ASRM), also recommended the suspension of new ART cycles [##UREF##9##21##, ##UREF##10##22##]. For infertile couples, especially those with poor prognoses, \"time\" is a crucial element, and the treatment suspension can harm their mental health [##REF##32404170##19##, ##REF##32553464##23##–##UREF##11##25##].</p>", "<p id=\"Par26\">The results of systematic reviews indicate that treatment suspension or postponement has a negative effect on patients' mental health. In a systematic review on the mental health and treatment impacts of covid-19 on neurocognitive disorders, an increase in mental health disorders in patients whose treatments were suspended due to the coronavirus pandemic was reported [##UREF##12##26##]. Similarly, another systematic review reported a negative relationship between mental health and treatment suspension in cancer patients [##UREF##13##27##].</p>", "<p id=\"Par27\">As it was mentioned, both infertility and the coronavirus pandemic have negative mental outcomes, so that if the impact of treatment suspension is added, the severity of adverse mental health effects on infertile patients would be increased. Although different studies have been conducted regarding the relationship between treatment suspension due to the coronavirus pandemic and the mental health of infertile patients; to the best of our knowledge, no systematic review has been conducted in this relation. It is noteworthy that two systematic reviews have been published with respect to fertility treatment during the Covid-19 pandemic. One systematic review examined the challenges of oncofertility and fertility preservation treatment and the importance of telemedicine during the Covid-19 pandemic [##REF##37585870##28##]. Another systematic review was conducted on the psychological impact of the Covid-19 pandemic on fertility care, and its finding suggested that the covid-19 pandemic causes negative psychological impacts on fertility care [##UREF##14##29##]; but because of the heterogeneity of studies, the researchers were not able to perform a meta-analysis. In their review, patients were also heterogeneous, with some studies conducted on patients receiving treatment, and some on patients whose treatment was halted or postponed.</p>", "<p id=\"Par28\">Based on the studies conducted prior to the Covid-19 pandemic [##REF##26979745##2##, ##UREF##15##30##, ##UREF##16##31##], it is clear that infertile patients suffer from psychological disorders resulted from their infertility. Also, as it was mentioned, systematic reviews on patients other than those who undergo fertility care, suggest that suspension or postponement of treatment has a negative effect on patients' mental health [##UREF##12##26##, ##UREF##13##27##]. Therefore, it seems that infertile patients who face treatment suspension or postponement can be at higher risk for mental disorders. Consequently, the mental health status of an infertile patient, who is undergoing fertility treatment might be different from those who experienced treatment postponement. This difference can affect their quality of life and satisfaction with treatment. Therefore, it was decided to conduct a systematic review in this regard. On the other hand, since meta-analyses help with improvement in precision by summarizing and synthesizing of quantitative data from independent yet comparable studies included in a systematic review [##UREF##17##32##–##REF##10789670##35##], it will be easier and more practical for the audiences to grasp the results of different studies by viewing the results of meta-analysis. In order to reach a precise, clear and summarized result from the findings of the reviewed studies, this systematic review and meta-analysis was conducted to assess the mental health of infertile patients facing treatment suspension due to the Covid-19 pandemic.</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par29\">To do this study, MOOSE Guidelines for Meta-Analyses and Systematic Reviews of Observational Studies was followed [##REF##10789670##35##]. The protocol is registered in PROSPERO (International prospective register of systematic reviews) under the code of CRD42023399725. Also, the study was approved by the Local Research Ethics Committee, Mashhad University of Medical Sciences, Mashhad, Iran (Code of ethics: IR.MUMS.NURSE.REC.1401.056).</p>", "<title>Search strategy and data sources</title>", "<p id=\"Par30\">Two researchers (EI, AY), independently, searched PubMed, Web of Science, Scopus, PsycINFO, Embase, and Cochrane library databases using keywords including coronavirus, covid-19, sars-cov-2, infertility, assisted reproductive technique, psychological distress, stress, anxiety, depression, psychological status, psychological problems/issues, mental health, suspension, and postponement with no time limit until 31 December 2022 (see Additional File ##SUPPL##0##1##). Search results of each database was imported to a library created by Endnote reference management software version 9. The software was also used to manage the studies, including identification and removal of duplicated studies, and screening of the titles and abstracts. References of articles which met the inclusion criteria were also searched manually. Since all the relevant articles found by manual search were already included in the study, no records were added by manual search.</p>", "<p id=\"Par31\">Using appropriate keywords, the search of different databases was conducted. At first, duplicate articles were removed. In the next step, the titles and abstracts of the remaining articles were carefully reviewed and the irrelevant articles were excluded. Then the full text of the remaining articles was sought, and articles without access to the full text were excluded. It must be noted that before the exclusion of articles with no access to the full text (n = 1), the corresponding author was reached and she provided us with the full text. Finally, the full text of the remaining articles was reviewed, and those articles that met our inclusion criteria were reviewed in the data extraction process. Two researchers (EI, AY), independently, assessed inclusion and exclusion criteria for each study.</p>", "<title>Inclusion criteria</title>", "<p id=\"Par32\">\n<list list-type=\"bullet\"><list-item><p id=\"Par33\">Observational studies including cross-sectional, case–control, or cohort studies regarding the mental health of infertile patients facing treatment suspension,</p></list-item><list-item><p id=\"Par34\">Studies published in the English language</p></list-item><list-item><p id=\"Par35\">PECO was as follows:<list list-type=\"bullet\"><list-item><p id=\"Par36\">Participants: Infertile patients seeking treatment</p></list-item><list-item><p id=\"Par37\">Exposure: Treatment suspension due to the Covid-19 pandemic</p></list-item><list-item><p id=\"Par38\">Comparator: None</p></list-item><list-item><p id=\"Par39\">Outcomes: Mental health of infertile patients including anxiety, depression, and stress.</p></list-item></list></p></list-item></list></p>", "<title>Exclusion criteria</title>", "<p id=\"Par40\">\n<list list-type=\"bullet\"><list-item><p id=\"Par41\">No access to the full text of the articles</p></list-item><list-item><p id=\"Par42\">Secondary research including systematic reviews, narrative reviews, scoping and rapid reviews as well as other types of articles including qualitative research reports, commentaries and letters to the editor</p></list-item><list-item><p id=\"Par43\">Theses or conference abstracts as well as guidelines</p></list-item><list-item><p id=\"Par44\">Observational studies which did not follow PECO criteria such as studies on infertile couples with ongoing treatment or infertile couples experiencing pregnancy during the Covid-19 pandemic, or studies which assessed outcomes other than those specified in PECO.</p></list-item><list-item><p id=\"Par45\">Languages other than English</p></list-item></list></p>", "<title>Quality assessment</title>", "<p id=\"Par46\">The Newcastle–Ottawa Scale (NOS) was used for the quality assessment of the studies. The scale is consisted of three sections including selection, comparability, and outcome (exposure in case–control studies). The maximum score for the scale is nine stars, and for each sections including selection, comparability, and outcome respectively is four, two, and three stars [##REF##29121640##36##, ##REF##26391008##37##] (see Additional File ##SUPPL##1##2##). The NOS has no established threshold of quality for the studies based on their scores (stars), but previous studies considered scores of 7 or above as high, 5 and 6 as moderate, and 4 and below as low quality [##REF##29121640##36##, ##REF##31138670##38##–##REF##33719081##41##]. Two researchers (EI, EMG), independently, assessed the quality of studies. They shared their results with each other and in cases of inconsistency; the third and senior researcher (RLR) assessed and scored the study. The result of the quality assessment is shown in Additional File ##SUPPL##2##3##. All the assessed studies were of high or moderate quality.</p>", "<title>Data extraction</title>", "<p id=\"Par47\">Full texts of 21 included studies were reviewed and data were extracted by two researchers (EI, MM) working together, and any disagreement was clarified by the third researcher (RLR). Data were extracted based on the pre-prepared checklist including the first author's name, publishing year, country of origin, study design, sample size, mean age of patients, mean infertility duration, data collection tools, outcomes including the prevalence of anxiety, depression, and stress, as well as the total score of quality assessment (See Additional File ##SUPPL##3##4##).</p>", "<title>Data analysis</title>", "<p id=\"Par48\">Data analysis was conducted based on the extracted data from the included studies. Extracted data were first tabulated from all 21 studies (See Additional File 4). The pooled prevalence (pooled event rate) of anxiety, depression, and stress was estimated using the random-effects method (DerSimonian and Laird method) [##REF##3802833##42##, ##UREF##20##43##]. The random-effects meta-analysis approach assumes that the different studies are estimating different, yet related, effects and the effects being estimated in the different studies follow some distribution and allows us to address heterogeneity that cannot be explained by other factors [##UREF##17##32##]. Considering that variables measured using pooled incidence or prevalence can vary between population characteristics, it has been recommended that meta-analyses are performed using the random-effects model [##REF##34544368##33##, ##REF##18286464##44##].</p>", "<p id=\"Par49\">Only studies that reported either the prevalence or number of affected patients by anxiety, depression, and stress were included in the meta-analysis. Since most studies reported the prevalence of patients who wished to resume treatment, the pooled prevalence was also estimated for this variable. Heterogeneity between studies was assessed by the I-squared statistical index. An I<sup>2</sup> index greater than 75 indicates high heterogeneity [##REF##12111919##45##]. Meta-regression and subgroup analysis were used to confirm the sources of heterogeneity. For meta-regression, mean age and sample size were used as moderators. It must be noted that variation in tools/instruments used to assess mental health status such as anxiety, depression, and stress in primary studies was a common limitation faced in the meta-analysis. Based on the previous meta-analyses on mental health outcomes [##REF##37059978##46##–##REF##32513264##51##], the research team decided to carry out the meta-analysis, and due to the expected variation in tools used to measure anxiety, depression, and stress; subgroup analysis was also done based on the tools for each mental health issue. It must be noted that based on the availability of data in reviewed studies, it was not possible to perform meta-regression or subgroup analysis on moderators such as causes or severity of infertility or attitudes toward infertility based on the region of studies. For publication bias, an Egger test was performed. Meta-analysis was conducted by two researchers (EI, AT) working together. Comprehensive Meta-Analysis Software Version 2 was used to estimate the pooled prevalence and 95% CI and prediction interval by random effects models. A p-value less than 0.05 was considered significant.</p>" ]
[ "<title>Results</title>", "<title>Search results</title>", "<p id=\"Par50\">In total 681 studies were identified by searching the databases. After the removal of duplicates, 269 studies were screened for inclusion criteria and 242 studies were excluded. 27 retrieved full-text were assessed for eligibility. It must be noted that one full text was obtained after contacting the corresponding author. Of these, six studies (four qualitative studies and two short communications) did not meet the inclusion criteria, so 21 studies with 5901 participants were included in this systematic review [##UREF##11##25##, ##UREF##21##52##–##UREF##30##71##]. Also, 16 studies were included in the meta-analysis [##UREF##21##52##–##REF##33558171##58##, ##UREF##24##60##, ##UREF##25##61##, ##UREF##26##63##–##REF##34180612##66##, ##REF##33545410##68##, ##REF##34669157##70##, ##UREF##30##71##]. The process of study selection is seen in Fig. ##FIG##0##1##.</p>", "<title>Study characteristics</title>", "<p id=\"Par51\">There was diversity in the region of the studies. Seven studies were from Europe (France [##REF##34638007##56##], Italy [##UREF##21##52##, ##REF##33545410##68##, ##UREF##30##71##], Portugal [##UREF##11##25##], Serbia [##UREF##23##59##], and Spain [##UREF##28##65##]); four were from Asia (China [##UREF##29##67##, ##REF##34669157##70##] and India [##REF##35045244##54##, ##UREF##22##55##]); four studies were from the Middle East (Iran [##UREF##24##60##], Israel [##UREF##26##63##], and Turkey [##UREF##25##61##, ##UREF##27##64##]) and six studies were conducted in Canada and/or USA [##REF##32946479##53##, ##REF##33400078##57##, ##REF##33558171##58##, ##REF##33910567##62##, ##REF##34180612##66##, ##REF##35270268##69##]. Except for the study of Dong et al. (2021) and Rasekh Jahromi et al. (2022), which were case–control studies [##UREF##24##60##, ##REF##34669157##70##], all of the studies had cross-sectional designs. All the participants (n: 5901) were infertile patients seeking treatment during the covid-19 pandemic and their treatment plans were either halted or postponed; the majority of whom were females (90 Percent, n: 5306); and 8.5 percent (n: 504) of the participants were male. Also, 91 participants (1.5 percent) did not mention their gender (Table ##TAB##0##1##).\n</p>", "<p id=\"Par52\">Due to the social distancing practice, except for two studies [##UREF##22##55##, ##REF##34669157##70##], all of the studies were conducted as online surveys [##UREF##11##25##, ##UREF##21##52##–##REF##35045244##54##, ##REF##34638007##56##–##REF##35270268##69##, ##UREF##30##71##]. Also, eight studies used Google forms [##UREF##21##52##, ##REF##33558171##58##, ##UREF##24##60##, ##UREF##25##61##, ##UREF##26##63##, ##UREF##28##65##, ##REF##33545410##68##, ##REF##35270268##69##], two used REDCap [##REF##33910567##62##, ##REF##34180612##66##], and two used the SurveyMonkey.com platform [##REF##33400078##57##, ##UREF##30##71##]. Others did not specify the online measures [##UREF##11##25##, ##REF##32946479##53##–##REF##34638007##56##, ##UREF##23##59##, ##UREF##27##64##, ##UREF##29##67##, ##REF##34669157##70##]. In terms of data collection tools, except for two studies that used self-structured questionnaires [##UREF##22##55##, ##REF##33545410##68##], 19 studies used validated instruments [##UREF##11##25##, ##UREF##21##52##–##REF##35045244##54##, ##REF##34638007##56##, ##REF##33558171##58##–##UREF##29##67##, ##REF##35270268##69##–##UREF##30##71##]. Regarding using specific tools for Covid-19, only two studies used covid-19 related questionnaires, including the Fear of Covid-19 Scale (FCV-19S) and the Covid-19 Anxiety Score [##UREF##26##63##, ##UREF##27##64##] (Table ##TAB##0##1##).</p>", "<p id=\"Par53\">Using the Newcastle–Ottawa scale, seven studies were considered of high quality [##UREF##21##52##, ##REF##33400078##57##, ##UREF##24##60##, ##UREF##28##65##, ##UREF##29##67##, ##REF##35270268##69##, ##UREF##30##71##], and 14 studies were of moderate quality [##UREF##11##25##, ##REF##32946479##53##–##REF##34638007##56##, ##REF##33558171##58##, ##UREF##23##59##, ##UREF##25##61##–##UREF##27##64##, ##REF##34180612##66##, ##REF##33545410##68##, ##REF##34669157##70##] and In regards to quality assessment of cross-sectional studies, all articles (<italic>n</italic> = 19) [##UREF##11##25##, ##UREF##21##52##–##UREF##23##59##, ##UREF##25##61##–##REF##35270268##69##, ##UREF##30##71##] achieved maximum score (three stars) in outcome section. While 74% of articles (<italic>n</italic> = 14) [##UREF##21##52##–##REF##35045244##54##, ##REF##34638007##56##–##REF##33558171##58##, ##REF##33910567##62##, ##UREF##26##63##, ##UREF##28##65##–##REF##35270268##69##, ##UREF##30##71##] achieved maximum score in comparability section and only 10.5% (<italic>n</italic> = 2) [##UREF##21##52##, ##REF##35270268##69##] received maximum score in selection section. As for case–control studies (<italic>n</italic> = 2) [##UREF##24##60##, ##REF##34669157##70##], only one study achieved maximum score in Comparability and Exposure section (two and three stars respectively) [##UREF##24##60##], and both [##UREF##24##60##, ##REF##34669157##70##] achieved three out of four in selection section. (see Additional File ##SUPPL##2##3##).</p>", "<p id=\"Par54\">Based on the findings of this review, the rate of anxiety in infertile women whose treatment was suspended or postponed due to the Covid-19 pandemic ranged from 11 to 72 percent. Also, the prevalence of depression varied from 14 to 77 and the prevalence of stress ranged from 38.9 to 64 percent, which is discussed in more detail. Also, it is important to note that, since the majority of the studies under review did not include male patients in their analysis, meta-analysis could not be performed on male anxiety, depression, and stress due to lack of data.</p>", "<title>Anxiety</title>", "<p id=\"Par55\">Anxiety was the outcome, which was measured in 15 studies [##UREF##11##25##, ##UREF##21##52##, ##REF##35045244##54##–##REF##33558171##58##, ##REF##33910567##62##, ##UREF##27##64##–##REF##33545410##68##, ##REF##34669157##70##, ##UREF##30##71##]. Different tools including General Anxiety Disorder (GAD-7), State-Trait Anxiety Inventory (STAI, STAI-5, and STAI-6), Hospital Anxiety and Depression Scale (HADS), Mental Health Inventory (MHI-5), and the Depression, Anxiety, and Stress Scale-21 Items (DASS-21) were used in order to measure infertile patients' anxiety. Although Galhardo et al. (2021) found no significant differences regarding anxiety scores between infertile patients with treatment suspension during the coronavirus pandemic and an infertility reference sample [##UREF##11##25##], Lablanche et al. (2022) reported that the rate of anxiety was much higher than those expected in the infertile population [##REF##34638007##56##]. Two studies reported an increase in anxiety rate in patients who were in confinement [##UREF##28##65##, ##UREF##29##67##]. Fear of covid-19 infection and exposure to covid-19 related news were reported to have a negative effect on patients' anxiousness [##UREF##21##52##, ##REF##35045244##54##]. Being female [##UREF##21##52##, ##UREF##30##71##], having previous IVF cycles [##UREF##21##52##, ##UREF##29##67##], and older age [##UREF##21##52##, ##REF##35045244##54##, ##UREF##27##64##] were also found to increase the anxiety score.</p>", "<title>The pooled prevalence of anxiety in infertile women</title>", "<p id=\"Par56\">Out of the 15 studies mentioned above, twelve studies reported either the number or percentage of women affected with anxiety during the treatment suspension period. The prevalence of anxiety varied from study to study and it was reported from a low percent of 11 to a high percent of 72. The estimated pooled prevalence was 48.4% (95% CI, 34.8–62.3) (Fig. ##FIG##1##2##). The I<sup>2</sup> index was 98.01, which indicated high heterogeneity. Meta-regression was conducted and the sample size was considered as the source of heterogeneity (<italic>p</italic> &lt; 0.001). Publication bias was not observed (Egger test <italic>p</italic>-value: 0.30).</p>", "<title>Subgroup analysis of the prevalence of anxiety</title>", "<p id=\"Par57\">The highest pooled prevalence estimate was calculated across the two studies using the STAI (40, 51), which was 72.1% (95% CI, 68.7–75.4). The lowest estimate was calculated for the three studies using the GAD-7 (32, 39, 45), which was 51.3% (95% CI 48.2–54.4). The heterogeneity was not significant between subgroups (<italic>P</italic> = 0.64) (Table ##TAB##1##2##).\n</p>", "<title>Depression</title>", "<p id=\"Par58\">Depression was measured in 10 studies [##UREF##11##25##, ##UREF##21##52##, ##REF##32946479##53##, ##UREF##22##55##, ##REF##33400078##57##, ##UREF##24##60##, ##UREF##25##61##, ##UREF##28##65##, ##REF##34180612##66##, ##REF##34669157##70##]. Different tools including Patient Health Questionnaire (PHQ-8 and PHQ-9), Beck's Depression Inventory (BDI), Hospital Anxiety and Depression Scale (HADS), Mental Health Inventory (MHI-5), and the Depression, Anxiety, and Stress Scale-21 Items (DASS-21) were used in order to measure infertile patients' depression. Although Galhardo et al. (2021) found no significant differences regarding depression scores between infertile patients with treatment suspension during the coronavirus pandemic and an infertility reference sample [##UREF##11##25##], Dillard et al. (2022) reported that depressive symptoms were greater during the pandemic [##REF##35270268##69##] and Biviá-Roig et al. (2021) reported an increase in depression score in patients who were in confinement [##UREF##28##65##]. Also, Rasekh Jahromi et al. (2022) reported that infertile women whose treatment was delayed were more depressed than those who were not under treatment[##UREF##24##60##]. It was reported that women were more depressed than men [##UREF##21##52##, ##UREF##30##71##]. Rasekh Jahromi et al. (2022) and Sahin et al. (2021) both reported a positive correlation between depression and hopelessness [##UREF##24##60##, ##UREF##25##61##]; in contrast to Sahin et al. (2021) who found that women with secondary infertility had higher mean depression score [##UREF##25##61##], Rasekh Jahromi et al. (2022) reported that women with primary infertility were more depressed [##UREF##24##60##].</p>", "<title>The pooled prevalence of depression in infertile women</title>", "<p id=\"Par59\">Out of the 10 studies, nine reported either the number or percentage of women affected with depression during the treatment suspension period. The prevalence of depression varied from study to study and it was reported from a low rate of 14 to a high rate of 77 percent. The estimated pooled prevalence was 42% (95% CI, 26.7–59.4) (Fig. ##FIG##2##3##). The I<sup>2</sup> index was 97.70, which indicated high heterogeneity. Meta-regression was conducted and sample size and mean age were considered as the source of heterogeneity (<italic>p</italic> &lt; 0.001). Publication bias was not observed (Egger test <italic>p</italic>-value: 0.09).</p>", "<title>Subgroup analysis of the prevalence of depression</title>", "<p id=\"Par60\">To assess depression, PHQ-9 (32,39,41) with a pooled prevalence of 37.4 (95% CI, 23.8–53.3) was used by three studies. Also, BDI (48, 49) and HADS (34,35) respectively with a pooled prevalence of 62.9 (95% CI, 43.2–79) and 28.2 (95% CI, 14.8–47.2) were used by two studies. Furthermore, PHQ-8 (45) and researcher-made tool (43) each were used in one study. The subgroup analysis suggested evidence of differential prevalence estimates between tools used to assess depression (<italic>P</italic> = 0.001) (Table ##TAB##2##3##).\n</p>", "<title>Stress</title>", "<p id=\"Par61\">Eleven studies reported stress in infertile patients whose treatments were either suspended or postponed [##UREF##11##25##, ##REF##35045244##54##, ##REF##34638007##56##–##UREF##23##59##, ##REF##33910567##62##, ##UREF##26##63##, ##REF##35270268##69##–##UREF##30##71##]. Perceived stress scale (PSS-10, PSS-4), Impact of Event Scale-Revised (IES-R), and Depression, Anxiety, and Stress Scale-21 Items (DASS-21) were used to assess stress. Dillard et al. (2022) and Galhardo et al. (2021) reported the mean score of the perceived stress scale-10 in their studies as 19.9 and 20.9 respectively [##UREF##11##25##, ##REF##35270268##69##]. Three studies reported the prevalence of stress [##REF##34638007##56##, ##REF##33400078##57##, ##UREF##26##63##]. Higher levels of stress were observed in patients whose treatments were suspended or postponed due to the covid-19 pandemic [##REF##35270268##69##, ##REF##34669157##70##]. Even though two studies reported no significant relationship between demographic characteristics of the patients and stress [##REF##33558171##58##, ##REF##35270268##69##], others reported that age [##REF##34638007##56##, ##REF##33400078##57##, ##UREF##26##63##], duration of infertility [##REF##35045244##54##, ##REF##33400078##57##], anxiety levels of the patients [##REF##34638007##56##, ##REF##33558171##58##, ##REF##33910567##62##], support system [##REF##35045244##54##, ##UREF##23##59##], and coping strategies [##REF##33400078##57##, ##UREF##23##59##] are associated with a higher level of stress.</p>", "<title>The pooled prevalence of stress in infertile women</title>", "<p id=\"Par62\">Out of the 11 studies, three reported either the number or percentage of women affected with stress during the treatment suspension period. The prevalence of stress varied from study to study and it was reported from a low rate of 50 to a high rate of 64 percent. The estimated pooled prevalence was 55% (95% CI, 45.4–65) (Fig. ##FIG##3##4##). The I<sup>2</sup> index was 90.99, which indicated high heterogeneity. Publication bias was not observed (Egger test p-value: 0.25). Subgroup analyses and meta-regression were not undertaken because of the small number of studies (n:3) [##UREF##31##72##].</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par64\">The results of this review showed that treatment suspension due to the coronavirus pandemic increased the prevalence of anxiety, depression, and stress in female patients. Based on the findings, the rate of anxiety in infertile women whose treatment was suspended or postponed due to the Covid-19 pandemic ranged from 11 to 72 percent. This wide range may be due to variations in tools and cut-off points that were used to measure infertile women's anxiety. A systematic review on the mental health of the general population during the coronavirus pandemic; reported anxiety rates of 6.33%. This finding in comparison to ours, suggests that infertile patients who faced treatment suspension during the covid-19 pandemic had higher rates of anxiety [##REF##32799105##15##]. We estimated a pooled prevalence of 48.4% for anxiety in infertile women facing treatment suspension or postponement, which is higher than the previously reported 36.17% pooled prevalence of anxiety in female infertile patients before the Covid-19 pandemic in 2020 [##UREF##15##30##]. In accordance with our findings, one study reported that the anxiety rate in infertile women with treatment suspension during the Covid-19 pandemic was much higher than those expected in the infertile population (40). Another study reported a higher level of anxiety in women facing delay in treatment than those who accessed ART treatment during the coronavirus pandemic [##REF##34669157##70##]. The higher prevalence of anxiety can be justified by the increase in anxiety due to both the Covid-19 pandemic and treatment suspension. Although subgroup analysis suggested no significant difference between tools, the HADS scale (anxiety subscale) showed a lower prevalence compared to GAD-7, MHI-5, and STAI. Similarly, another meta-analysis on the prevalence of anxiety in covid-19 patients reported a higher prevalence of anxiety when GAD-7 was used compared to HADS [##REF##33009668##73##]. This can be due to different cut-off points between tools.</p>", "<p id=\"Par65\">In terms of depression, the prevalence varied from 14 to 77 in infertile women whose treatments were either suspended or postponed during the covid-19 pandemic, based on our findings. A systematic review on the mental health of the general population during the coronavirus pandemic reported 14.6 to 48.3 percent of depression [##REF##32799105##15##]. The pooled prevalence of depression before the Covid-19 pandemic was reported at 44.32% in infertile women in low and middle-income countries and 28.03% in high-income countries [##UREF##16##31##]. In this review, a pooled prevalence of 42% was estimated with majority of the included studies conducted in high-income countries. Comparing our findings to that of the meta-analyses by Kiani et al. (2021) [##UREF##16##31##], and Xiong et al. (2020) [##REF##32799105##15##]; we observed an increase in depression rate of infertile women whose treatment was suspended or postponed during the Covid-19 pandemic in comparison to both infertile women before the pandemic and the general population during the pandemic. In line with our results, Rasekh Jahromi et al. (2022) also found that during the Coronavirus pandemic the rate of depression were higher in infertile women with treatment suspension than those who were not under treatment [##UREF##24##60##], however due to the small body of evidence, these findings must be interpreted cautiously. Based on the subgroup analysis, the HADS scale (depression subscale), in comparison to BDI, PHQ-8, and PHQ-9 reported a lower depression prevalence. Similar results were reported in other studies [##UREF##16##31##, ##REF##33009668##73##]. This difference in prevalence can be explained by the difference in cut-off points of the tools used to measure depression. Also, variations in sample size in different studies must be considered.</p>", "<p id=\"Par66\">A systematic review on the general population during Covid-19 reported the prevalence of stress as 29.6 percent [##UREF##4##11##]. In our review, the pooled prevalence of stress was 55 percent. Which is higher than those of the general population at the same time. Also, some studies reported a higher level of stress in patients whose treatments were suspended or postponed due to the covid-19 pandemic [##REF##35270268##69##, ##REF##34669157##70##]. Studies reported infertility treatment as a priority for infertile patients and as the top stressor despite an ongoing pandemic [##REF##32946479##53##, ##REF##32600945##74##]. Most of the patients were worried about both the short-term and long-term impact of the treatment suspension on their chances of getting pregnant [##UREF##23##59##, ##UREF##27##64##, ##REF##34180612##66##, ##REF##33545410##68##, ##REF##35270268##69##, ##UREF##32##75##]. In one study a positive relationship was reported between mental distress and the time spent on the coronavirus-related news in infertile patients facing treatment postponement [##UREF##21##52##]. This positive relationship was also observed in the general population [##REF##32799105##15##].</p>", "<p id=\"Par67\">Based on our findings mental health of patients facing infertility treatment delay, because of the Covid-19 pandemic, was negatively affected. This result is compatible with other studies that stated confinement and treatment suspension have negative effects on the mental health of infertile women [##REF##32946479##53##, ##UREF##28##65##, ##UREF##29##67##, ##REF##34669157##70##]. Three studies reported higher levels of mental health distribution in those patients living in the confinement areas [##UREF##28##65##, ##UREF##29##67##, ##REF##35096733##76##]; the strict rules and higher exposure to coronaviruses-related news in the confinement areas can be the cause of these findings. As time is considered an important factor in infertility treatment planning, delays, and suspensions were presumed to be a threat to the treatment process [##UREF##23##59##, ##REF##34180612##66##, ##REF##35270268##69##, ##UREF##32##75##]. Many infertile patients felt that treatment suspensions were unfair and made them angry [##UREF##22##55##, ##REF##33558171##58##, ##UREF##27##64##]. Closure of fertility treatment centers also decreased the quality of life of patients [##REF##32946479##53##, ##UREF##28##65##, ##REF##33545410##68##]; this is aligned with the findings of a systematic review on the general population [##REF##32951475##77##]. Delay or suspension of treatment due to the coronavirus pandemic was found to be related to increased levels of mental health problems in other patients too. A systematic review reported an increase in mental disorders in patients with neurocognitive disorders whose treatments were suspended [##UREF##12##26##]. A negative relationship between mental health and treatment suspension in cancer patients was also reported in another systematic review [##UREF##13##27##]. Maintaining social relationships, receiving support, keeping fit, and having a daily routine could help infertile patients to cope with this situation better [##REF##32761248##24##, ##REF##33910567##62##, ##UREF##26##63##].</p>", "<p id=\"Par68\">Based on our results 64.4% percent of infertile patients wished to resume their treatment despite the ongoing Covid-19 pandemic. Reports of one study showed that only 6% of infertile patients agreed with delaying their treatment [##REF##32600945##74##]. A cross-sectional study also reported that only 28% of infertile patients were concerned about maternal–fetal transmission of the virus in case of infection during treatment [##UREF##33##78##]. Based on these findings and in accordance with studies on providing fertility care during covid-19 pandemic [##REF##34404622##79##, ##REF##34936981##80##], it is important to maintain the continuity of fertility care, with special attention paid to mental health of infertile patients, through all the possible measures including virtual care and telemedicine. To substitute the cancelled appointments and ensure patient satisfaction, fertility treatment centers could arrange virtual appointments.</p>", "<p id=\"Par69\">The main limitation of this study was the significant degree of heterogeneity across the studies, which should be taken into account when interpreting the data. The other limitation was that due to the lack of sufficient quantitative data in the reviewed studies, it was not possible to perform a meta-analysis on the relationship between treatment suspension and mental health of infertile patients. Further research with a larger sample size using validated tools is recommended. Also, the short-term and long-term effects of the coronavirus pandemic and treatment suspension on the mental health of infertile patients need to be investigated further.</p>", "<p id=\"Par70\">One of the strengths of this study was that not only it measured the prevalence of anxiety, depression, and stress in infertile women whose treatment were postponed or suspended, but also compared those results in relation to the pre covid-19 pandemic mental health status of infertile women and those of general public during covid-19 pandemic. Also provided quantitative data on the prevalence of patients who wished to resume their treatment. Another strength of this study was the diversity in the included studies in geographical, and socio-economic terms.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par71\">Treatment suspension due to coronavirus pandemic can negatively affect the mental health of infertile patients. Personalized planning could improve infertile patients' mental health. It is important to maintain the continuity of fertility care, with special attention paid to mental health of infertile patients, through all the possible measures including virtual care. Fertility healthcare providers must involve patients in the decision-making process about their treatments even in a public health crisis.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Access to fertility treatments is considered a reproductive right, but because of the quarantine due to the coronavirus pandemic most infertility treatments were suspended, which might affect the psychological and emotional health of infertile patients. Therefore, this study was conducted to review the mental health of infertile patients facing treatment suspension due to the coronavirus pandemic.</p>", "<title>Methods</title>", "<p id=\"Par2\">This study was conducted based on the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guideline. The Web of Science, PubMed, Embase, Scopus, and Cochrane library databases were searched by two independent researchers, without time limitation until 31 December 2022. All observational studies regarding the mental health of infertile patients facing treatment suspension including anxiety, depression, and stress were included in the study. Qualitative studies, editorials, brief communications, commentaries, conference papers, guidelines, and studies with no full text were excluded. Quality assessment was carried out using Newcastle–Ottawa Scale by two researchers, independently. The random effects model was used to estimate the pooled prevalence of mental health problems. Meta-regression and subgroup analysis were used to confirm the sources of heterogeneity.</p>", "<title>Results</title>", "<p id=\"Par3\">Out of 681 studies, 21 studies with 5901 infertile patients were systematically reviewed, from which 16 studies were included in the meta-analysis. The results of all pooled studies showed that the prevalence of anxiety, depression, and stress in female patients was 48.4% (95% CI 34.8–62.3), 42% (95% CI 26.7–59.4), and 55% (95% CI 45.4–65), respectively. Additionally, 64.4% (95% CI 50.7–76.1) of patients wished to resume their treatments despite the coronavirus pandemic.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Treatment suspension due to the coronavirus pandemic negatively affected the mental health of infertile patients. It is important to maintain the continuity of fertility care, with special attention paid to mental health of infertile patients, through all the possible measures even during a public health crisis.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12889-023-17628-x.</p>", "<title>Keywords</title>" ]
[ "<title>Other findings</title>", "<title>The pooled prevalence of patients who wished to resume treatment</title>", "<p id=\"Par63\">Ten studies reported either the number or percentage of patients who wished to resume infertility treatment [##UREF##21##52##, ##REF##35045244##54##–##REF##33558171##58##, ##UREF##26##63##, ##UREF##27##64##, ##REF##34180612##66##, ##UREF##30##71##]. The prevalence varied from study to study and it was reported from a low rate of 33 to a high rate of 98 percent. The estimated pooled prevalence was 64.4% (95% CI, 50.7–76.1) (Fig. ##FIG##4##5##). The I<sup>2</sup> index was 97.89, which indicated high heterogeneity. Meta-regression was conducted and the sample size was considered as the source of heterogeneity (<italic>p</italic> &lt; 0.001). Publication bias was not observed (Egger test p-value: 0.21).</p>", "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>The protocol of the study was registered in PROSPERO (International prospective register of systematic reviews) under the code of CRD42023399725, Available from: <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023399725\">https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023399725.</ext-link></p>", "<title>Authors’ contributions</title>", "<p>EI and AY performed the database search and study selection and prepared Fig. ##FIG##0##1## and Additional File ##SUPPL##0##1##. EI and EMG performed the quality assessment of the studies and prepared Additional Files ##SUPPL##1##2## and ##SUPPL##2##3##. EI and MM performed the data extraction from the studies and prepared Table ##TAB##0##1##, and Additional File ##SUPPL##3##4##. EI, RLR and AT performed analysis and interpretation of data for meta-analysis and prepared Figs. ##FIG##1##2##, ##FIG##2##3##, ##FIG##3##4##, ##FIG##4##5## and Tables ##TAB##1##2##, ##TAB##2##3##. RLR supervised the database search, study selection, quality assessment of the studies, and data extraction from the studies. EI and RLR wrote the main manuscript text. All the authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study was funded by the Vice president for Research, at Mashhad University of Medical Sciences, Mashhad, Iran.</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par72\">This study was approved by the Local Research Ethics Committee, Mashhad University of Medical Sciences, Mashhad, Iran (Code of ethics: IR.MUMS.NURSE.REC.1401.056).</p>", "<title>Consent for publication</title>", "<p id=\"Par73\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par74\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>PRISMA Flowchart of study selection</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The pooled prevalence of anxiety in female patients</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>The pooled prevalence of depression in female patients</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>The pooled prevalence of stress in female patients</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>The pooled prevalence of patients who wished to resume treatment</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Characteristics of published studies included in the systematic review</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">*</th><th align=\"left\"><bold>1st Author / Year</bold></th><th align=\"left\"><bold>Country</bold></th><th align=\"left\"><bold>Design</bold></th><th align=\"left\"><bold>Sample size</bold></th><th align=\"left\"><bold>Tools</bold></th><th align=\"left\"><bold>Outcome measures</bold></th><th align=\"left\"><bold>Findings</bold></th></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">Barra 2020 [##UREF##21##52##]</td><td align=\"left\">Italy</td><td align=\"left\">Cross-sectional</td><td align=\"left\">524 (308 F, 216 M)</td><td align=\"left\">GAD-7 PHQ-9</td><td align=\"left\"><p>Anxiety</p><p>Depression</p></td><td align=\"left\"><p>24% of female patients had anxiety</p><p>21% of female patients had depression</p><p>37% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">2</td><td align=\"left\">Ben-Kimhy 2020 [##UREF##26##63##]</td><td align=\"left\">Israel</td><td align=\"left\">Cross-sectional</td><td align=\"left\">168 F</td><td align=\"left\">Covid-19 anxiety score, MHI-5</td><td align=\"left\">Psychological distress</td><td align=\"left\"><p>50% of patients had psychological distress</p><p>72% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">3</td><td align=\"left\">Biviá-Roig 2021 [##UREF##28##65##]</td><td align=\"left\">Spain</td><td align=\"left\">Cross-sectional</td><td align=\"left\">85 F</td><td align=\"left\">HADS</td><td align=\"left\"><p>Anxiety</p><p>Depression</p></td><td align=\"left\"><p>62% of female patients had anxiety</p><p>28% of female patients had depression</p></td></tr><tr><td align=\"left\">4</td><td align=\"left\">Bortoletto 2021 [##REF##34180612##66##]</td><td align=\"left\">USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">117 F</td><td align=\"left\">HADS</td><td align=\"left\"><p>Anxiety</p><p>Depression</p></td><td align=\"left\"><p>61.5% of female patients had anxiety</p><p>28% of female patients had depression</p><p>37% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">5</td><td align=\"left\">Cao 2021 [##UREF##29##67##]</td><td align=\"left\">China</td><td align=\"left\">Cross-sectional</td><td align=\"left\">759 F</td><td align=\"left\">STAI</td><td align=\"left\">Anxiety</td><td align=\"left\">Women in the Quarantine zones had a higher tendency to be anxious</td></tr><tr><td align=\"left\">6</td><td align=\"left\">Cirillo 2021 [##REF##33545410##68##]</td><td align=\"left\">Italy</td><td align=\"left\">Cross-sectional</td><td align=\"left\">140 F</td><td align=\"left\">Researcher-made</td><td align=\"left\">Anxiety</td><td align=\"left\">30% of female patients had anxiety</td></tr><tr><td align=\"left\">7</td><td align=\"left\">Dillard 2022 [##REF##35270268##69##]</td><td align=\"left\">USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">304 F</td><td align=\"left\">PSS-10</td><td align=\"left\">Stress</td><td align=\"left\">Patients had a mean score of 19.9 on the Perceived stress scale</td></tr><tr><td align=\"left\">8</td><td align=\"left\">Dong 2021 [##REF##34669157##70##]</td><td align=\"left\">China</td><td align=\"left\">Case–control</td><td align=\"left\">474 Case (278 F, 196 M)</td><td align=\"left\">GAD-7 PHQ-9</td><td align=\"left\"><p>Anxiety</p><p>Depression</p></td><td align=\"left\"><p>34% of female patients had anxiety</p><p>43% of female patients had depression</p></td></tr><tr><td align=\"left\">9</td><td align=\"left\">Esposito 2020 [##UREF##30##71##]</td><td align=\"left\">Italy</td><td align=\"left\">Cross-sectional</td><td align=\"left\">627 (588 F, 39 M)</td><td align=\"left\">IES-R  STAI</td><td align=\"left\"><p>Anxiety</p><p>Stress</p></td><td align=\"left\"><p>72% of female patients had anxiety</p><p>65% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">10</td><td align=\"left\">Galhardo 2021 [##UREF##11##25##]</td><td align=\"left\">Portugal</td><td align=\"left\">Cross-sectional</td><td align=\"left\">89 F</td><td align=\"left\">DASS-21  PSS-10</td><td align=\"left\"><p>Anxiety</p><p>Depression</p><p>Stress</p></td><td align=\"left\"><p>Patients had a mean score of 5.1 in the DASS-21 anxiety section</p><p>Patients had a mean score of 6.7 in the DASS-21 depression section</p><p>Patients had mean score of 20.9 in Perceived stress scale</p></td></tr><tr><td align=\"left\">11</td><td align=\"left\">Gordon 2020 [##REF##32946479##53##]</td><td align=\"left\">Canada USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">92 F</td><td align=\"left\">PHQ-9</td><td align=\"left\">Depression</td><td align=\"left\">52% of female patients had depression</td></tr><tr><td align=\"left\">12</td><td align=\"left\">Jaiswal 2022 [##REF##35045244##54##]</td><td align=\"left\">India</td><td align=\"left\">Cross-sectional</td><td align=\"left\">250 F</td><td align=\"left\">Self-report PSS-4</td><td align=\"left\">Anxiety</td><td align=\"left\"><p>72% of female patients had anxiety</p><p>98% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">13</td><td align=\"left\">Kaur 2020 [##UREF##22##55##]</td><td align=\"left\">India</td><td align=\"left\">Cross-sectional</td><td align=\"left\">86 (81 F, 5 M)</td><td align=\"left\">Researcher-made</td><td align=\"left\"><p>Anxiety</p><p>Depression</p></td><td align=\"left\"><p>11% of female patients had anxiety</p><p>14% of female patients had depression</p><p>50% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">14</td><td align=\"left\">Lablanche 2022 [##REF##34638007##56##]</td><td align=\"left\">France</td><td align=\"left\">Cross-sectional</td><td align=\"left\">421 F</td><td align=\"left\">HADS  PSS-10</td><td align=\"left\"><p>Anxiety</p><p>Stress</p></td><td align=\"left\"><p>22% of female patients had anxiety</p><p>51% of patients had stress</p><p>84% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">15</td><td align=\"left\">Lawson 2021 [##REF##33400078##57##]</td><td align=\"left\">USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">787  (648 F, 48 M, 91 N/R)</td><td align=\"left\">GAD-7  PHQ-8</td><td align=\"left\"><p>Anxiety</p><p>Depression</p><p>Stress</p></td><td align=\"left\"><p>71% of female patients had anxiety</p><p>77% of female patients had depression</p><p>64% of patients had moderate to high distress</p><p>41% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">16</td><td align=\"left\">Marom-Haham 2021[##REF##33558171##58##]</td><td align=\"left\">Canada</td><td align=\"left\">Cross-sectional</td><td align=\"left\">181 F</td><td align=\"left\">MHI-5</td><td align=\"left\">Anxiety</td><td align=\"left\"><p>60% of female patients had anxiety</p><p>82% of patients wished to resume ART treatment</p></td></tr><tr><td align=\"left\">17</td><td align=\"left\">Mitrovic 2021 [##UREF##23##59##]</td><td align=\"left\">Serbia</td><td align=\"left\">Cross-sectional</td><td align=\"left\">176 F</td><td align=\"left\">DASS-21</td><td align=\"left\">Distress</td><td align=\"left\">Perceived threat that COVID-19 poses for infertility treatment had a relationship with general distress</td></tr><tr><td align=\"left\">18</td><td align=\"left\">Rasekh Jahromi 2022 [##UREF##24##60##]</td><td align=\"left\">Iran</td><td align=\"left\">Case control</td><td align=\"left\">86 (Case) F</td><td align=\"left\">BDI</td><td align=\"left\">Depression</td><td align=\"left\">60.5% of female patients had depression</td></tr><tr><td align=\"left\">19</td><td align=\"left\">Sahin 2021 [##UREF##25##61##]</td><td align=\"left\">Turkey</td><td align=\"left\">Cross-sectional</td><td align=\"left\">220 F</td><td align=\"left\">BDI</td><td align=\"left\">Depression</td><td align=\"left\">65% of female patients had depression</td></tr><tr><td align=\"left\">20</td><td align=\"left\">Seifer 2021 [##REF##33910567##62##]</td><td align=\"left\">USA</td><td align=\"left\">Cross-sectional</td><td align=\"left\">214 F</td><td align=\"left\">STAI-6</td><td align=\"left\">Anxiety</td><td align=\"left\">Higher stress scores were associated with increased anxiety</td></tr><tr><td align=\"left\">21</td><td align=\"left\">Tokgoz 2020 [##UREF##27##64##]</td><td align=\"left\">Turkey</td><td align=\"left\">Cross-sectional</td><td align=\"left\">101 F</td><td align=\"left\">STAI, FCV-19S</td><td align=\"left\">Anxiety</td><td align=\"left\"><p>71% of female patients had anxiety</p><p>33% of patients wished to resume ART treatment</p></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Subgroup analysis of the prevalence of anxiety by tools based on random effect analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Tool</th><th align=\"left\" rowspan=\"2\">Number of studies</th><th align=\"left\" rowspan=\"2\">Prevalence of anxiety</th><th align=\"left\" colspan=\"2\">Heterogeneity across studies</th></tr><tr><th align=\"left\">I<sup>2</sup></th><th align=\"left\"><italic>p</italic> Value</th></tr></thead><tbody><tr><td align=\"left\"><bold>GAD-7</bold></td><td align=\"left\">3</td><td align=\"left\">51.3 (95% CI, 48.2–54.4)</td><td align=\"left\">99.03</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><bold>HADS</bold></td><td align=\"left\">3</td><td align=\"left\">35.9 (95% CI, 31.9–40.2)</td><td align=\"left\">97.77</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><bold>MHI-5</bold></td><td align=\"left\">1</td><td align=\"left\">60.2 (95% CI, 52.9–67.1)</td><td align=\"left\">0</td><td align=\"left\">1.00</td></tr><tr><td align=\"left\"><bold>STAI</bold></td><td align=\"left\">2</td><td align=\"left\">72.1 (95% CI, 68.7–75.4)</td><td align=\"left\">0</td><td align=\"left\">0.83</td></tr><tr><td align=\"left\"><bold>Researcher-made</bold></td><td align=\"left\">3</td><td align=\"left\">51.8 (95% CI, 46.5–56.9)</td><td align=\"left\">97.99</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"4\"><bold>Heterogeneity between groups</bold></td><td align=\"left\">0.641</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Subgroup analysis of the prevalence of depression by tools based on random effect analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Tool</th><th align=\"left\" rowspan=\"2\">Number of studies</th><th align=\"left\" rowspan=\"2\">Prevalence of depression</th><th align=\"left\" colspan=\"2\">Heterogeneity across studies</th></tr><tr><th align=\"left\">I<sup>2</sup></th><th align=\"left\"><italic>P</italic> Value</th></tr></thead><tbody><tr><td align=\"left\"><bold>BDI</bold></td><td align=\"left\">2</td><td align=\"left\">62.9 (95% CI, 43.2–79)</td><td align=\"left\">0</td><td align=\"left\">0.45</td></tr><tr><td align=\"left\"><bold>HADS</bold></td><td align=\"left\">2</td><td align=\"left\">28.2 (95% CI, 14.8–47.2)</td><td align=\"left\">0</td><td align=\"left\">0.99</td></tr><tr><td align=\"left\"><bold>PHQ-8</bold></td><td align=\"left\">1</td><td align=\"left\">77 (95% CI, 53–90.9)</td><td align=\"left\">0</td><td align=\"left\">1</td></tr><tr><td align=\"left\"><bold>PHQ-9</bold></td><td align=\"left\">3</td><td align=\"left\">37.4 (95% CI, 23.8–53.3)</td><td align=\"left\">95.50</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"><bold>Researcher-made</bold></td><td align=\"left\">1</td><td align=\"left\">13.8 (95% CI, 4.4–35.7)</td><td align=\"left\">0</td><td align=\"left\">1</td></tr><tr><td align=\"left\" colspan=\"4\"><bold>Heterogeneity between groups</bold></td><td align=\"left\">0.001</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12889_2023_17628_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12889_2023_17628_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12889_2023_17628_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"12889_2023_17628_Fig4_HTML\" id=\"MO4\"/>", "<graphic xlink:href=\"12889_2023_17628_Fig5_HTML\" id=\"MO5\"/>" ]
[ "<media xlink:href=\"12889_2023_17628_MOESM1_ESM.pdf\"><caption><p><bold>Additional file 1.</bold> Search Strategy for each database.</p></caption></media>", "<media xlink:href=\"12889_2023_17628_MOESM2_ESM.pdf\"><caption><p><bold> Additional file 2.</bold> The Newcastle-Ottawa Scale.</p></caption></media>", "<media xlink:href=\"12889_2023_17628_MOESM3_ESM.pdf\"><caption><p><bold> Additional file 3.</bold> Quality assessment of the studies based on the Newcastle-Ottawa Scale (NOS).</p></caption></media>", "<media xlink:href=\"12889_2023_17628_MOESM4_ESM.pdf\"><caption><p><bold> Additional file 4.</bold> Data extraction table.</p></caption></media>" ]
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{ "acronym": [ "ART", "ASRM", "BDI", "CI", "DASS-21", "ESHRE", "FCV-19S", "GAD-7", "HADS", "IES-R", "IVF", "MHI", "MOOSE", "NOS", "PHQ", "PSS", "STAI" ], "definition": [ "Assisted Reproductive Technology", "American society of reproductive medicine", "Beck's Depression Inventory", "Confidence Interval", "Depression, Anxiety, and Stress Scale-21 Items", "European Society of Human Reproduction and Embryology", "Fear of Covid-19 Scale", "General Anxiety Disorder", "Hospital Anxiety and Depression Scale", "Impact of Event Scale-Revised", "In Vitro Fertilization", "Mental Health Inventory", "Meta-Analysis of Observational Studies in Epidemiology", "Newcastle-Ottawa Scale", "Patient Health Questionnaire", "Perceived Stress Scale", "State-Trait Anxiety Inventory" ] }
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2024-01-14 23:43:45
BMC Public Health. 2024 Jan 13; 24:174
oa_package/98/b3/PMC10787415.tar.gz
PMC10787416
0
[ "<title>Background</title>", "<p id=\"Par5\">Patients with chronic medical conditions such as congestive heart failure (CHF) or chronic obstructive pulmonary disease (COPD) face disease-related mortality and morbidity including hospitalization and decreased quality of life [##REF##11847161##1##–##REF##29975336##4##].Approximately 1 million heart failure hospitalizations occur annually in the US, with a 20% readmission rate within 30 days [##UREF##0##5##, ##REF##26432556##6##]. Barriers to effective care including limited access, symptom recognition, understanding, and medication adherence [##REF##23416934##7##].</p>", "<p id=\"Par6\">Remote patient monitoring (RPM) offers the potential to improve care and outcomes for patients with chronic conditions by addressing these challenges. RPM is a technology-enabled healthcare delivery model which allows providers to gather data and manage patients’ health outside of traditional healthcare settings. Mechanistically, RPM may improve access, promote patient self-management, detect early warning signs of clinical decompensation, and facilitates timely preventative or rescue interventions before hospitalization [##REF##27116181##8##].</p>", "<p id=\"Par7\">Prior studies of RPM in patients with chronic conditions have yielded mixed findings regarding hospital admission and mortality [##REF##21444883##9##–##REF##30153985##13##], potentially due to differences in the chronic condition studied, RPM intervention (e.g., monitoring frequency), and outcomes measured. Further, the extent to which RPM interventions (intended to focus on high-risk patients with chronic conditions) might benefit patients enrolled in accountable care organizations (ACOs), which have been shown to reduce hospitalizations regardless of patient risk, remains unclear [##UREF##1##14##]. In the US, ACOs are groups of clinicians and facilities jointly providing care for a defined group of patients (e.g., geographically, or with a specific condition) with the intent to reduce fragmentation improve care coordination across a health system, improve quality, and improve outcomes [##UREF##2##15##, ##UREF##3##16##]. ACOs are financially incentivized by Medicare to improve quality and outcomes and reduce spending, sharing in a proportion of cost savings and paying penalties if they provide fragmented, more costly care. We implemented and evaluated a post-hospitalization RPM program for patients with chronic conditions within a large academic hospital system’s ACO. We hypothesized that RPM participation would decrease all-cause readmission, mortality, and emergency department visits in this high-risk patient population.</p>" ]
[ "<title>Methods</title>", "<title>Design, setting, and study population</title>", "<p id=\"Par8\">This was a nonrandomized prospective study of adult patients enrolled in BJC HealthCare’s ACO. The ACO serves over 70,000 patients Medicare and Medicare Advantage patients in the St. Louis, MO, metropolitan area. All hospitalized ACO-enrolled patients enter a care transition program for 30 days upon hospital discharge, which includes medication review, disease-specific education, scheduling follow-up appointments, and addressing barriers to care (e.g., assigning chore workers). The ACO established an RPM program in February 2021, offering RPM to eligible patients on hospital discharge in addition to and concurrent with existing care transition services for those who elected to enroll.</p>", "<p id=\"Par9\">RPM eligibility required medically-diagnosed CHF, COPD, or a recommendation from the patient’s primary care provider for another chronic condition. Exclusion criteria for RPM eligibility were (1) discharge to hospice, (2) outpatient dialysis, and (3) a screening nurse’s determination that comorbid or socioeconomic obstacles (e.g., moderate to severe cognitive impairment, unstable housing) would preclude participation. Patients who elected not to enroll in RPM served as controls post hoc.</p>", "<p id=\"Par10\">Because over 96% of eligible patients had diagnoses of CHF or COPD, and because we expected the potential benefit of RPM to vary by condition, we restricted our evaluation to RPM-eligible patients with CHF or COPD. The study focused on RPM-eligible patients who were offered enrollment between February 2021 and December 2021, with a planned 30-day minimum for RPM and a predetermined 6-month follow-up period (because we expected that some potential benefits of increased monitoring might accrue past the actively-monitored period).</p>", "<p id=\"Par11\">This RPM program was initiated as an ACO-sponsored quality improvement activity. The post hoc study described here was designed subsequent to RPM program development and implementation. The Washington University Institutional Review Board reviewed and approved the analysis protocol (#202207118) prior to data collection and analysis. All methods were performed in accordance with relevant guidelines and regulations.</p>", "<title>RPM intervention</title>", "<p id=\"Par12\">The ACO provided RPM personnel and services using materials and equipment from a commercial vendor (Health Recovery Systems, Hoboken, NJ). The vendor managed distribution and between-patient cleaning of devices and materials but played no role in the design, oversight, or analysis of this study.</p>", "<p id=\"Par13\">ACO staff contacted eligible patients within 48 hours of discharge to offer RPM enrollment. To preclude immortal time bias, the 6-month follow-up period began on the day of ACO staff contact for all patients. Enrolled patients were mailed an RPM kit containing a Samsung tablet preloaded with RPM software and cellular capabilities (to allow patients without home internet to participate), an A&amp;D blood pressure monitor and cuff, scale, pulse oximeter, and written set-up instructions. All items were Bluetooth-enabled to sync with the tablet. Tablets included preloaded educational video about the relevant chronic condition.</p>", "<p id=\"Par14\">During participation, tablet devices alerted once daily to prompt participants to record vital signs and complete surveys. Abnormal vital signs or affirmative survey responses (Supplementary Table ##SUPPL##0##1##) triggered real-time alerts to assigned ACO nurses who then called the patient for further triage.</p>", "<p id=\"Par15\">ACO nurses assessed the need for continued enrollment after 30 days; patients who had not had an RPM alert within the prior 7 days were eligible, but not required, to “graduate” from the program (i.e., each nurse had discretion to recommend continued enrollment based on their clinical judgment and the patient’s desires). This allowed the limited number of RPM kits to be redistributed. Patients could disenroll from the program at any time. Hospital admission paused RPM enrollment, which resumed automatically at discharge.</p>", "<title>Data acquisition and management</title>", "<p id=\"Par16\">Demographics, insurance, comorbidities, social history, medications, procedures, and encounter data were extracted from the electronic health record (EHR; Epic, Verona, WI) through direct chart review. Because the other major health systems in the ACO’s catchment area use the same EHR, data from other health systems were extracted could also be we had access to the timing and details of essentially all local healthcare encounters via the vendor’s “Care Everywhere” interoperability feature (i.e., it is unlikely that patients experienced an outcome that we could not identify from their chart). Daily vital signs and surveys metadata were extracted from the RPM vendor for an exploratory <italic>post-hoc</italic> analysis.</p>", "<title>Outcomes</title>", "<p id=\"Par17\">We prespecified two primary outcomes for this analysis: (1) the composite of death, hospital admission, or emergency care not resulting in an admission within 180 days of RPM eligibility, and (2) the time to occurrence of this composite. Secondary outcomes included individual component of the composite, death or hospital admission, time to death or hospital admission, number of specialist office visits, number of nonspecialist office visits, and length of hospital stay for admitted patients. The 6-month follow-up period started on the day of RPM eligibility.</p>", "<title>Covariates</title>", "<p id=\"Par18\">Clinical data was measured at the time of RPM eligibility (e.g., subsequently-assigned comorbid diagnoses were not recorded). Because of uncertainty regarding how frequently social determinants of health (e.g., food insecurity) are recorded in discrete EHR fields [##REF##34549294##17##], we considered each patient to have any individual insecurity if they had been recorded as having such.</p>", "<p id=\"Par19\">We recorded the presence or absence of prescriptions in the following classes: (1) beta-blocker, (2) angiotensin-converting enzyme inhibitor, angiotensin II receptor antagonist, or angiotensin receptor neprilysin inhibitor, (3) mineralocorticoid receptor antagonist, (4) sodium/glucose cotransporter-2 inhibitor, (5) inhaler, and (6) insulin.</p>", "<title>Analyses</title>", "<p id=\"Par20\">Continuous data were presented as median (IQR), and categorical data as n (percent). Unadjusted comparisons between RPM enrollees and RPM-eligible control patients were made using Wilcoxon rank sum tests, Pearson’s Chi-squared tests, and Fisher’s exact test as appropriate. We produced Kaplan-Meier curves to visualize time to the primary outcome for each group and compared these using the log-rank test.</p>", "<p id=\"Par21\">Because patients self-determined their enrollment in RPM in this nonrandomized study, we expected significant confounding by indication in terms of the relationship between RPM participation and patient outcomes [##REF##27802529##18##]. Hence, we elected <italic>ex ante</italic> to compare categorical outcomes between RPM participants and control patients through doubly robust estimation [##REF##21385832##19##]. This approach combines propensity score estimation (i.e., the conditional likelihood that a patient would be in the exposure group, based on observed characteristics) with traditional multivariable logistic regression such that the final effect estimator is robust to misspecification of either model.</p>", "<p id=\"Par22\">A priori, we used a directed acyclic graph to prespecify, through study team consensus, relevant potential confounders (i.e., variables likely to be associated with both the decision to enroll in RPM and relevant outcomes, but not on the causal pathway between them) [##REF##30230362##20##]. These confounders were primary diagnosis (CHF vs COPD), age (modeled as a continuous linear variable), gender, insecurities related to housing, food, or living expenses (modeled as having any insecurity vs having no insecurities), current or prior use of tobacco products (modeled as ever vs never), number of healthcare encounters (admissions, ED visits, or office visits, to approximate baseline healthcare utilization) in the prior year to study eligibility, prescriptions of the previously listed medication classes, and individual comorbidities (Supplementary Table ##SUPPL##0##2##).</p>", "<p id=\"Par23\">Analysis of time-to-event data in the setting of confounding by indication is an emerging methodological area [##REF##30569832##21##–##REF##30133696##23##]. Under the assumption that such confounding would be present at baseline and not time-varying over the course of the study, we used the same potential confounders in a multivariable logistic regression model to obtain propensity scores (i.e., each patient’s model-derived propensity to choose RPM enrollment). We then fit Cox proportional-hazards models to estimate the adjusted relationship between RPM enrollment and time to the primary outcome with these propensity scores included as a covariate. Although this process does not directly employ a doubly robust estimator, it may be more accurate than other common propensity-based approaches (e.g., inverse probability of treatment weighting) if confounding by indication is strong [##REF##25934643##24##].</p>", "<title>Subgroup and sensitivity analyses</title>", "<p id=\"Par24\">To contextualize and strengthen our findings, and because patients with CHF and COPD may have differential mechanisms of potential benefit from RPM [##UREF##4##25##], we repeated our analyses in each of these cohorts separately.</p>", "<p id=\"Par25\">Next, because social determinants of health are (a) likely to confound the observed relationship between RPM enrollment and clinical outcomes and (b) frequently missing with unclear missingness patterns, we prespecified several sensitivity analyses to test the robustness of our findings to these challenges. First, we imputed all missing data regarding insecurities in housing, food, or living expenses for our baseline case as “no.” Second, we set all missing data to “yes,” and last, we set missing data to be “yes” or “no” contingent on the presence or absence of the primary outcome.</p>", "<p id=\"Par26\">In an exploratory post hoc sensitivity analysis, we performed the observational analog of a per-protocol analysis [##REF##31063192##26##, ##REF##21948059##27##], in which we considered the degree of RPM engagement as a component of the exposure. We performed multivariable logistic regression treating RPM exposure as a continuous variable between 0 and 1, based on proportion of completed surveys and vital sign recordings in vendor data. We then performed doubly robust estimation on a cohort in which RPM exposure was redefined by adherence of 90% or greater to any single RPM metric.</p>", "<p id=\"Par27\">We performed all analyses using R 4.2.1 (R Project for Statistical Computing, Vienna, Austria) and the tidyverse, drgee, survival, and survminer packages [##UREF##5##28##–##UREF##8##31##]. We adjusted <italic>p</italic>-values by the false discovery rate (FDR) methodology suggested by Benjamini &amp; Hochberg [##UREF##9##32##], and considered FDR <italic>p</italic>-values &lt; 0.05 statistically significant.</p>" ]
[ "<title>Results</title>", "<title>Patient characteristics</title>", "<p id=\"Par28\">Between February 2021 and December 2021, 375 patients were offered ACO RPM enrollment; of these, 212 had CHF and 150 had COPD (Supplementary Fig. ##SUPPL##0##1##). We excluded 14 patients due to uncommon enrollment diagnoses. Compared to eligible patients who did not enroll in RPM (<italic>n</italic> = 221 [145 CHF, 76 COPD]), patients who enrolled (<italic>n</italic> = 140 [106 CHF, 34 COPD]) were younger (median age 74 [IQR 66–83] vs 76 [70–84], <italic>p</italic> = 0.02), more likely to be nonsmokers (31% vs 19%, <italic>p</italic> = 0.01), and more likely to have Medicaid (22% vs 4.1%, <italic>p</italic> &lt; 0.01) (Table ##TAB##0##1##). Baseline comorbidities, medications, and healthcare utilization were similar between groups. Median participation duration for enrolled patients was 54 [IQR 34–85] days (Table ##TAB##1##2##).\n</p>", "<title>Unadjusted outcomes</title>", "<p id=\"Par29\">Neither the 6-month frequency of the co-primary composite outcome (Table ##TAB##2##3##) nor the time to this composite (Fig. ##FIG##0##1##) differed between the RPM and control groups. However, the RPM group had lower 6-month mortality (6.4% vs 17%, FDR <italic>p</italic>-value = 0.02). The RPM group had more overall (median 6 [IQR 4–8] vs 4 [2–7], <italic>p</italic> = 0.02) and subspecialty (median 6 [IQR 4–8] vs 4 [2–7], FDR <italic>p</italic> value = 0.02) outpatient encounters during the follow-up period. The RPM group had a trend towards fewer time in days to first ED visit (median 42 [IQR 20–94] vs 73 [31–112], FDR <italic>p</italic>-value = 0.18).\n</p>", "<title>Adjusted analyses</title>", "<p id=\"Par30\">After doubly-robust estimation to adjust for prespecified confounders, including confounding by indication, we found nonsignificantly decreased odds for the primary composite outcome (adjusted odds ratio [aOR] 0.68, 99% CI 0.25 to 1.11, FDR <italic>p</italic>-value = 0.30), and a decrease in the 6-month mortality (aOR 0.41, 99% CI 0.00 to 0.86, FDR <italic>p</italic>-value = 0.20) that did not reach FDR-adjusted statistical significance. The propensity-adjusted time-to-event analysis showed no significant risk for the composite outcome in the study cohort compared to the control group (adjusted HR [aHR] 1.07, 99% CI 0.74 to 1.44, FDR <italic>p</italic>-value = 0.90), but did show a non-significant decrease in time to first ED visit (aHR 1.79, 99% CI 0.99 to 3.26, FDR <italic>p</italic>-value = 0.05). Adjusted analysis for secondary outcomes generally followed this pattern (Fig. ##FIG##1##2##<bold>,</bold> Table ##TAB##3##4##).</p>", "<title>Subgroup analysis</title>", "<p id=\"Par31\">In the subgroups of RPM-eligible patients with CHF (<italic>n</italic> = 251 [106 RPM, 145 control]) and COPD (<italic>n</italic> = 110 [34 RPM, 76 control]), patient characteristics (Supplementary Table ##SUPPL##0##3##) and outcomes (Supplementary Tables ##SUPPL##0##4## and ##SUPPL##0##5##) were similar to those of the overall cohort. In the CHF group, the unadjusted RPM-associated 180-day mortality was lower (6.6% vs 17%, FDR <italic>p</italic>-value = 0.05). The adjusted primary outcome and 6-month mortality in the CHF group were both decreased.</p>", "<title>Sensitivity analyses</title>", "<p id=\"Par32\">Sensitivity analyses in which we quantified social determinants of health through different approaches yielded similar results to the primary analysis (Supplementary Table ##SUPPL##0##6##). When the missing data is set based on the outcome, the adjusted OR for disk loses significance.</p>", "<p id=\"Par33\">Among RPM-enrolled patients, those without the primary outcome had higher adherence to logging vital signs and symptoms in the RPM portal (BP Adherence 94% vs 74%, <italic>p</italic> &lt; 0.01) (Supplementary Table ##SUPPL##0##7##). Duration of enrollment did not differ between these groups (<italic>p</italic> = 0.70). In an exploratory analysis based on these findings, RPM engagement was associated with decreased adjusted odds for the composite outcome (aOR 0.34, 99% CI 0.04–0.65). When defining adherence as greater than 90% for any measurement, we found that RPM enrollment was associated with decreased odds for all outcomes except ED visit (Supplementary Table ##SUPPL##0##8##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par34\">This prospective analysis of ACO patients with CHF or COPD found that RPM enrollment was associated with significantly lower unadjusted mortality, decreased adjusted odds of 6-month mortality, and nonsignificantly decreased adjusted odds for the primary composite outcome of death, rehospitalization, or emergency care. These findings suggest there may be benefit of RPM interventions for selected populations. Critically, there was no significant increase for time-to-event in our cohort, an expected finding given that the benefit of RPM should not be instantaneous.</p>", "<p id=\"Par35\">These results, primarily driven by patients with CHF, align with prior work demonstrating a positive relationship between RPM and decreased hospitalizations and mortality [##REF##29940936##11##, ##REF##30153985##13##, ##REF##28108430##33##–##REF##23808885##36##]. However, they contrast with several randomized trials which did not demonstrate clear benefits from RPM [##REF##21444883##9##, ##REF##26857383##37##, ##REF##35532915##38##]. Such a contrast might be considered unsurprising, given the complexity and heterogeneity in most chronic conditions. Some flares of chronic conditions, for example shortness of breath in heart failure or uncontrolled sugars in diabetes, may allow for actionable responses through early detection, thus offering greater potential for improvement with RPM. The mixed benefit seen in prior studies may also be due to the heterogeneity in RPM interventions: there are many non-standardized variables that have been implemented across studies including the types of data collected, data collection methods, and the frequency and timeliness of data transmission to health care providers for actionable responses.</p>", "<p id=\"Par36\">Conflicting RPM benefit may also be due to the complexity of outcome selection. While we selected a composite primary outcome to maximize statistical power and our follow-up period extended past the RPM duration period to capture lagging indicators, it seems likely that enrollment in RPM had an impact on how patients interacted with health care. For example, RPM-enrolled patients had a decreased time to first ED visit, while risk for any ED visit was unchanged. This may suggest that RPM alerts facilitate early detection and timely intervention, enabling patients to receive appropriate care sooner. Additionally, RPM-enrolled patients had increased outpatient office visits which was not associated with lower risk for hospitalizations or ED visits, but may have contributed to the observed mortality reduction. Thus, selecting outcomes and measurement frequency that more accurately capture changes in disease state may inform the findings of future RPM studies.</p>", "<p id=\"Par37\">Our findings were robust to multiple sensitivity analyses, including an exploratory investigation into the possibility of “dose-dependence” in terms of RPM’s potential benefit. Interestingly, patients who experienced the composite outcome also had lower RPM usage, while those who did not experience an outcome more frequently recorded their symptoms and vital signs. In adjusted analysis, the RPM “dose” was positively associated with the adjusted odds of the primary outcome, suggesting that increased usage improves overall management of patients’ chronic conditions. Indeed, a prominent recent negative study of RPM in heart failure described overall lower engagement (~ 80%) than the rates in our study [##REF##35532915##38##]. Future research should strive to explicate the mechanisms by which RPM works in terms of improving outcomes, determine the extent to which implementation strategies and duration of follow-up contribute to particular benefits.</p>", "<p id=\"Par38\">The largest limitation to this work is its nonrandomized nature and the likelihood of confounding by indication. Notably, baseline comorbidities, medications, and healthcare utilization were similar between the RPM and control groups, suggesting that such confounding may not have been as strong as anticipated. Further, modern methods, including doubly robust estimation, offer an opportunity to minimize the bias from such confounding. However, even these methods cannot account for unmeasured confounders. Ultimately, confounding by indication will depend on the extent to which unmeasured factors (e.g., trust in the health care system) contribute causally to outcome differences based on RPM enrollment. An additional limitation is that mortality and health care utilization incompletely reflect of a patient’s overall health; without important outcomes such as patient-reported measures and costs, we risk misestimating this program’s impact. Third, we did not systematically collect patients’ reasons for RPM discontinuation (i.e., before 30 days). Because these reasons might be closely tied to patient outcomes (e.g., discontinued because of low motivation, discontinued because of entry into a long-term care facility), they represent an important variable to collect in future projects, as well as an important barrier to adoption. Just as early discontinuation may have limited our findings, so too could have our choice to offer patients “graduation” after 30 days. While our intent in this decision was to maximize the total number of patients offered RPM, doing so could have biased our results towards the null.</p>", "<p id=\"Par39\">This study has several notable strengths. First, doubly robust regression is a modern and sophisticated approach to account for confounding by indication, increasing our confidence in these findings. Second, our strict control for potential false discovery helps minimize over-interpretation of our findings. Third, we achieved complete data capture via detailed chart review and vendor data extraction; because of our specific study population (and the availability of outcomes from other health systems via our EHR), we likely achieved complete capture of outcomes as well. Fourth, our deliberate and pragmatic approach to RPM enrollment (e.g., accounting for lack of home internet) allowed us to include a diverse group of patients.</p>", "<p id=\"Par40\">In conclusion, RPM enrollment was associated with decreased adjusted odds of 6-month mortality in this prospective observational study of post-hospitalization patients with CHF and COPD. These findings suggest RPM interventions may have benefit for selected populations.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Post-hospitalization remote patient monitoring (RPM) has potential to improve health outcomes for high-risk patients with chronic medical conditions. The purpose of this study is to determine the extent to which RPM for patients with congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) is associated with reductions in post-hospitalization mortality, hospital readmission, and ED visits within an Accountable Care Organization (ACO).</p>", "<title>Methods</title>", "<p id=\"Par2\">Nonrandomized prospective study of patients in an ACO offered enrollment in RPM upon hospital discharge between February 2021 and December 2021. RPM comprised of vital sign monitoring equipment (blood pressure monitor, scale, pulse oximeter), tablet device with symptom tracking software and educational material, and nurse-provided oversight and triage. Expected enrollment was for at least 30-days of monitoring, and outcomes were followed for 6 months following enrollment. The co-primary outcomes were (a) the composite of death, hospital admission, or emergency care visit within 180 days of eligibility, and (b) time to occurrence of this composite. Secondary outcomes were each component individually, the composite of death or hospital admission, and outpatient office visits. Adjusted analyses involved doubly robust estimation to address confounding by indication.</p>", "<title>Results</title>", "<p id=\"Par3\">Of 361 patients offered remote monitoring (251 with CHF and 110 with COPD), 140 elected to enroll (106 with CHF and 34 with COPD). The median duration of RPM-enrollment was 54 days (IQR 34–85). Neither the 6-month frequency of the co-primary composite outcome (59% vs 66%, FDR <italic>p</italic>-value = 0.47) nor the time to this composite (median 29 vs 38 days, FDR <italic>p</italic>-value = 0.60) differed between the groups, but 6-month mortality was lower in the RPM group (6.4% vs 17%, FDR p-value = 0.02). After adjustment for confounders, RPM enrollment was associated with nonsignificantly decreased odds for the composite outcome (adjusted OR [aOR] 0.68, 99% CI 0.25–1.34, FDR <italic>p</italic>-value 0.30) and lower 6-month mortality (aOR 0.41, 99% CI 0.00–0.86, FDR p-value 0.20).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">RPM enrollment may be associated with improved health outcomes, including 6-month mortality, for selected patient populations.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12913-023-10496-6.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Authors’ contributions</title>", "<p>SH made substantial contributions to the design of the work, led the data acquisition, analysis, and interpretation, and wrote the manuscript's initial draft. KP, MG, and JF made substantial contributions to the conception of the work and to the acquisition and interpretation of data, and they substantively revised the manuscript. NM made substantial contributions to the conception and design of the work and the acquisition and interpretation of data, as well as substantive revisions to the manuscript. TM made substantial contributions to the conception and design of the work, the acquisition, analysis, and interpretation of data, and substantively revised the manuscript. PL made substantial contributions to the conception and design of the work, the acquisition, analysis, and interpretation of data, and substantively revised the manuscript. All authors have approved the submitted version and agree to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.</p>", "<title>Funding</title>", "<p>This work was funded by BJC Medical Group.</p>", "<title>Availability of data and materials</title>", "<p>While raw data containing protected health information are unable to be shared, the final analysis dataset will be available at [link to come] on date of publication.</p>", "<p>The datasets generated and analysed during the current study are not publicly available because they contain protected health information and patient identifiers, but are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par41\">The Washington University Institutional Review Board reviewed and approved the analysis protocol (#202207118) prior to data collection and analysis. The Washington University Institutional Review Board determined that informed consent was waived (not required).</p>", "<title>Consent for publication</title>", "<p id=\"Par42\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par43\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Cumulative incidence plot of time to death, hospital admission, or emergency department visit. RPM, remote patient monitoring. RPM: Remote patient monitoring</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Adjusted primary and secondary outcomes (via doubly robust estimation) for overall population and sub-populations. CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Patient characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>Control, <italic>N</italic> = 221</th><th>RPM, <italic>N</italic> = 140</th><th><italic>p</italic>-value</th></tr></thead><tbody><tr><td colspan=\"4\"><bold><italic>Baseline Demographics</italic></bold></td></tr><tr><td> Age, median (IQR)</td><td>76 (70, 84)</td><td>74 (66, 83)</td><td>0.02</td></tr><tr><td> Female gender, n (%)</td><td>114 (52)</td><td>86 (61)</td><td>0.07</td></tr><tr><td> Race, White, n (%)</td><td>173 (78)</td><td>99 (71)</td><td>0.10</td></tr><tr><td> Race, Black, n (%)</td><td>48 (22)</td><td>41 (29)</td><td>0.10</td></tr><tr><td> Any Insecurity, n (%)</td><td>26 (12)</td><td>18 (13)</td><td>0.80</td></tr><tr><td> Smoking, ever, n (%)</td><td>180 (81)</td><td>96 (69)</td><td>0.01</td></tr><tr><td> RPM eligibility for CHF, n (%)</td><td>145 (66)</td><td>106 (76)</td><td>0.04</td></tr><tr><td> Medicaid, n (%)</td><td>9 (4.1)</td><td>31 (22)</td><td>&lt; 0.001</td></tr><tr><td colspan=\"4\"><bold><italic>Baseline Health Care Utilization Year Prior to Admission</italic></bold>, median (IQR)</td></tr><tr><td> Number of Admissions</td><td>2 (1, 3)</td><td>2 (1, 3)</td><td>0.50</td></tr><tr><td> Number of Office Visits</td><td>7 (4, 12)</td><td>9 (6, 12)</td><td>0.04</td></tr><tr><td> Number of Specialist Visits</td><td>3 (1, 7)</td><td>3 (1, 7)</td><td>0.40</td></tr><tr><td> Number of ED Visits without Admission</td><td>0 (0, 1)</td><td>0 (0, 1)</td><td>0.40</td></tr><tr><td colspan=\"4\"><bold><italic>Baseline Medical Diagnoses, n (%)</italic></bold></td></tr><tr><td> Systolic Heart Failure</td><td>81 (37)</td><td>60 (43)</td><td>0.20</td></tr><tr><td> Diastolic Heart Failure</td><td>129 (58)</td><td>85 (61)</td><td>0.70</td></tr><tr><td> COPD</td><td>126 (57)</td><td>80 (57)</td><td>&gt; 0.90</td></tr><tr><td> Atrial Fibrillation</td><td>105 (48)</td><td>57 (41)</td><td>0.20</td></tr><tr><td> Hypertension</td><td>202 (91)</td><td>126 (90)</td><td>0.70</td></tr><tr><td> Coronary or Peripheral Arterial Disease</td><td>150 (68)</td><td>72 (51)</td><td>0.002</td></tr><tr><td> Diabetes</td><td>89 (40)</td><td>73 (52)</td><td>0.03</td></tr><tr><td> Obesity</td><td>98 (44)</td><td>70 (50)</td><td>0.30</td></tr><tr><td> Chronic Kidney Disease</td><td>146 (66)</td><td>94 (67)</td><td>0.80</td></tr><tr><td> Cancers, excluding non-metastatic skin cancers</td><td>55 (25)</td><td>32 (23)</td><td>0.70</td></tr><tr><td colspan=\"4\"><bold><italic>Medications at Time of Cohort Entry,</italic></bold> median (IQR)</td></tr><tr><td> Total Number of Prescriptions</td><td>14 (11, 18)</td><td>15 (12, 19)</td><td>0.14</td></tr><tr><td> Total GDMT Meds</td><td>1 (1, 2)</td><td>2 (1, 2)</td><td>0.02</td></tr><tr><td> Inhaler</td><td>1 (0, 2)</td><td>1 (0, 2)</td><td>0.20</td></tr><tr><td> Insulin</td><td>0 (0, 0)</td><td>0 (0, 0)</td><td>0.14</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Adherence to RPM</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>Adherence, Median (IQR)</th><th>Readings Taken, Median (IQR)</th></tr></thead><tbody><tr><td>Blood pressure</td><td>86% (60, 97)</td><td>43 (25, 65)</td></tr><tr><td>Pulse</td><td>86% (62, 97)</td><td>42 (24, 63)</td></tr><tr><td>Weight</td><td>88% (58, 97)</td><td>42 (23, 67)</td></tr><tr><td>Survey</td><td>68% (37, 92)</td><td>35 (16, 56)</td></tr><tr><td>RPM Duration, days</td><td>54 (34, 85)</td><td/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Unadjusted outcomes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>Control, <italic>N</italic> = 221</th><th>RPM, <italic>N</italic> = 140</th><th>FDR <italic>p</italic>-value</th></tr></thead><tbody><tr><td>Composite Outcome</td><td>145 (66)</td><td>82 (59)</td><td>0.47</td></tr><tr><td>Admission or Death</td><td>124 (56)</td><td>68 (49)</td><td>0.47</td></tr><tr><td>Death</td><td>37 (17)</td><td>9 (6.4)</td><td>0.02</td></tr><tr><td>ED Visit</td><td>59 (27)</td><td>41 (29)</td><td>0.75</td></tr><tr><td>Admission</td><td>113 (51)</td><td>67 (48)</td><td>0.70</td></tr><tr><td>Total Length of Stay for Admissions, days</td><td>6 (3, 14)</td><td>8 (4, 16)</td><td>0.62</td></tr><tr><td>Num. Office Visits in 1 Month</td><td>1 (1, 2)</td><td>1 (1, 2)</td><td>0.62</td></tr><tr><td>Num. Office Visits in 6 Month</td><td>4 (2, 7)</td><td>6 (4, 8)</td><td>0.02</td></tr><tr><td>Num. Office Visits with Specialist in 6 months</td><td>4 (2, 7)</td><td>6 (4, 8)</td><td>0.02</td></tr><tr><td>Time to Composite Outcome, days</td><td>38 (15, 83)</td><td>29 (11, 71)</td><td>0.60</td></tr><tr><td>Time to Admission or Death, days</td><td>39 (15, 82)</td><td>41 (12, 86)</td><td>0.75</td></tr><tr><td>Time to Death, days</td><td>72 (42, 124)</td><td>88 (37, 98)</td><td>0.75</td></tr><tr><td>Time to ED Visit, days</td><td>73 (31, 112)</td><td>42 (20, 94)</td><td>0.18</td></tr><tr><td>Time to Admission, days</td><td>38 (15, 84)</td><td>43 (13, 87)</td><td>0.80</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Adjusted outcomes</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td colspan=\"5\"><italic>Doubly Robust Regression Analysis</italic></td></tr><tr><td/><td><bold>aOR</bold></td><td><bold>99% Low CI</bold></td><td><bold>99% High CI</bold></td><td>FDR <italic>p</italic>-value</td></tr><tr><td>Composite of Death, Admission, or ED Visit</td><td>0.68</td><td>0.25</td><td>1.11</td><td>0.30</td></tr><tr><td>Admission or Death</td><td>0.76</td><td>0.29</td><td>1.24</td><td>0.43</td></tr><tr><td>Death</td><td>0.41</td><td>0.00</td><td>0.86</td><td>0.20</td></tr><tr><td>ED Visit</td><td>1.01</td><td>0.30</td><td>1.73</td><td>0.96</td></tr><tr><td>Admission</td><td>0.91</td><td>0.35</td><td>1.47</td><td>0.86</td></tr><tr><td colspan=\"2\"><italic>Time to Event Analysis</italic></td><td/><td/><td/></tr><tr><td/><td><bold>HR</bold></td><td><bold>99% Low CI</bold></td><td><bold>99% High CI</bold></td><td>FDR <italic>p</italic>-value</td></tr><tr><td>Composite of Death, Admission, or ED Visit</td><td>1.07</td><td>0.74</td><td>1.55</td><td>0.90</td></tr><tr><td>Admission or Death</td><td>1.02</td><td>0.68</td><td>1.54</td><td>0.90</td></tr><tr><td>Death</td><td>2.20</td><td>0.44</td><td>11.10</td><td>0.53</td></tr><tr><td>ED Visit</td><td>1.79</td><td>0.99</td><td>3.26</td><td>0.05</td></tr><tr><td>Admission</td><td>1.02</td><td>0.66</td><td>1.58</td><td>0.90</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Baseline demographics, medical diagnoses, and medications extracted at the time of cohort eligibility. Health care utilization measured between 1year prior to cohort eligibility and day of cohort eligibility. Pearson’s Chi-squared test and Wilcoxon Rank Sum Test used for categorical and continuous data, respectively</p></table-wrap-foot>", "<table-wrap-foot><p>Adherence data to each RPM metric for enrolled patients. Adherence measured as daily vital sign logging and survey submission. Of note, if a patient was admitted to the hospital during their RPM enrolled time, this time was excluded from adherence calculations. Reported as median and IQR for % adherence, and number of readings taken or days’ duration</p></table-wrap-foot>", "<table-wrap-foot><p>Outcomes were measured for 6 months following time of RPM eligibility. The primary outcomes are a composite of (1) hospital admission, (2) death, (3) ED visit not resulting in hospital admission, and time to composite outcome. Presence or absence of outcome specified as n, (%). All other data reported as median (IQR). Pearson’s Chi-squared test and Wilcoxon Rank Sum Test used for categorical and continuous data, respectively</p></table-wrap-foot>", "<table-wrap-foot><p>Doubly robust estimation was used for binary outcomes and Cox proportional hazard models with adjustment for logistic-estimated propensity scores were used for time-to-event outcomes</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12913_2023_10496_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12913_2023_10496_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"12913_2023_10496_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1.</bold>\n</p></caption></media>" ]
[{"label": ["5."], "mixed-citation": ["Hall MJ, Levant S, DeFrances CJ. Hospitalization for congestive heart failure: United States, 2000-2010. NCHS Data Brief. 2012;1\u20138.\u00a0"], "ext-link": ["https://pubmed.ncbi.nlm.nih.gov/23102190/"]}, {"label": ["14."], "surname": ["McWilliams", "Chernew", "Landon"], "given-names": ["JM", "ME", "BE"], "article-title": ["Medicare ACO program savings not tied to preventable hospitalizations or concentrated among high-risk patients"], "source": ["Health Aff."], "year": ["2017"], "volume": ["36"], "fpage": ["2085"], "lpage": ["2093"], "pub-id": ["10.1377/hlthaff.2017.0814"]}, {"label": ["15."], "mixed-citation": ["Accountable Care Organizations. American Hospital Association "], "ext-link": ["https://www.aha.org/accountable-care-organizations-acos/accountable-care-organizations"]}, {"label": ["16."], "mixed-citation": ["Accountable Care Organizations (ACOs): General information. "], "ext-link": ["https://www.cms.gov/priorities/innovation/innovation-models/aco"]}, {"label": ["25."], "surname": ["van der Burg"], "given-names": ["JMM"], "article-title": ["Long-term effects of telemonitoring on healthcare usage in patients with heart failure or COPD"], "source": ["Clinical eHealth."], "year": ["2020"], "volume": ["3"], "fpage": ["40"], "lpage": ["48"], "pub-id": ["10.1016/j.ceh.2020.05.001"]}, {"label": ["28."], "mixed-citation": ["Wickham H, et al. Welcome to the tidyverse. J Open Source Softw. 2019;4 10.21105/joss.01686."]}, {"label": ["29."], "surname": ["Zetterqvist", "Sj\u00f6lander"], "given-names": ["J", "A"], "article-title": ["Doubly robust estimation with the R package drgee"], "source": ["Epidemiol Method."], "year": ["2015"], "volume": ["4"], "fpage": ["69"], "lpage": ["86"], "pub-id": ["10.1515/em-2014-0021"]}, {"label": ["30."], "mixed-citation": ["Kassambara A, Kosinski M, Biecek P. _survminer: Drawing survival curves using 'ggplot2'_. R package version 0.4.9. 2021."]}, {"label": ["31."], "surname": ["Therneau", "Lumley"], "given-names": ["T", "T"], "source": ["R survival package"], "year": ["2013"], "publisher-name": ["R Core Team"]}, {"label": ["32."], "surname": ["Benjamini", "Hochberg"], "given-names": ["Y", "Y"], "article-title": ["Controlling the false discovery rate: a practical and powerful approach to multiple testing"], "source": ["J R Stat Soc Series B Stat Methodol."], "year": ["1995"], "volume": ["57"], "fpage": ["289"], "lpage": ["300"]}]
{ "acronym": [], "definition": [] }
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2024-01-14 23:43:45
BMC Health Serv Res. 2024 Jan 13; 24:69
oa_package/22/ef/PMC10787416.tar.gz
PMC10787417
0
[ "<title>Introduction</title>", "<p id=\"Par27\">Rheumatoid arthritis (RA) is a condition resulting from autoimmune hyperactivity, characterized by joint inflammation, proliferation of synovial tissue, and angiogenesis. Prolonged RA can result in disability and adversely affect an individual's quality of life [##REF##34831081##1##]. The statistics indicate that approximately 1% of the global population is affected by RA. The pathogenesis is intricate and influenced by genetic and environmental factors, along with various other determinants. Moreover, research on the pathogenesis of RA is still in its exploratory phase [##REF##34305919##2##].</p>", "<p id=\"Par28\">Research has identified pattern recognition receptors (PRRs) as a significant contributor to the pathogenesis of RA. The Toll-like receptor (TLR) family comprises the key molecule in pattern recognition receptors (PRRs) and is able to present antigens to effector cells, thereby activating them [##REF##25687121##3##]. As researchers delve deeper into this area, they have identified around 13 receptors within the Toll family [##REF##32164908##4##]. TLRs are protein structures that link the inner and outer membranes of a cell, regulating non-specific immunity. Research has demonstrated that when lipopolysaccharide (LPS) binds to TLR4, it leads to an increase in its expression. This, in turn, leads to abnormalities in the expression of associated proteins downstream, triggers a cascade of inflammatory pathways. The resulting effect can exacerbate joint inflammation in patients [##REF##19252480##5##, ##REF##18304834##6##]. Activation of TLR4 further enhances the activation of nuclear factor-κB (NF-κB). The NF-κB pathway plays an equally influential role in promoting the development of RA. Elevated NF-κB protein expression was found in the synovium of RA, which enters the nucleus and contributes to the transcription and secretion of relevant inflammatory factors [##REF##33340772##7##]. The aforementioned inflammatory factors exacerbate inflammation and joint damage, thereby perpetuating the progression of RA [##REF##22465880##8##]. Additionally, an excessive TLRs response induces the uncontrolled release of matrix metalloproteinases (MMPs) [##REF##27236686##9##]. Matrix metalloproteinases are deemed to play a noteworthy role in the degradation of articular cartilage within affected joints [##REF##23201917##10##]. The overexpression of MMPs can result in joint surface and cartilage erosion in RA [##REF##20193003##11##, ##REF##23562164##12##]. Thus, matrix metalloproteinase imbalance may be an important factor contributing to joint destruction in RA.</p>", "<p id=\"Par29\">According to TCM, rheumatoid arthritis is a pathological condition arising from the invasion of external factors, including wind, dampness, cold and other unfavorable environmental factors. Throughout the extensive history of Chinese medicine’s treatment of RA, traditional Chinese medicine has extensively employed herbs, whether in compound formulas or single-flavored preparations, which function to dispel wind, cold, and dampness from the body. Several studies have shown that when DMARDs are used in conjunction with Chinese herbal medicines, the drugs are significantly more effective in relieving RA symptoms and reducing associated side effects. In recent years, therapeutic drugs targeting immune cells and related cytokines (e.g. TNF-α, IL-6, etc.) have also achieved excellent clinical efficacy [##REF##28778870##13##, ##REF##32635779##14##]. Although there have been advancements in treating RA, some patients experience swift joint destruction while under treatment. However, the clinical options are also limited due to drugs' side effects, such as liver and kidney damage, immunosuppression, and the high cost of biologics. As a result, the quest for new anti-rheumatoid arthritis drugs from traditional Chinese medicine could become a new approach [##REF##35854675##15##].</p>", "<p id=\"Par30\">The Wu Mei Pill (WMP) is a traditional Chinese compound medicine dating back to the Han Dynasty. This medicine is primarily composed of 16 traditional Chinese herbs, including dark plum, Chinese prickly ash, Asarum and Coptic chinensis. Previous studies have shown that WMP is able to regulate the body's immunity and has an inhibitory effect on inflammation [##UREF##0##16##, ##UREF##1##17##]. Relevant research has demonstrated that WMP effectively reduces serum levels of inflammatory factors and inhibits the overactivation of the TLR4-MyD88-NF-κB inflammatory pathway in mice exhibiting intestinal mucositis. Moreover, WMP has been shown to restore balance to intestinal flora and alleviate intestinal mucosal inflammation in mice [##REF##36157934##18##]. Furthermore, WMP inhibits macrophage activation by impacting the Notch/NF-κB/NLRP3 pathway. It also exerts an inhibitory effect on immune overactivation and anti-inflammatory bursts within the body [##REF##35947900##19##]. In summary, scientific studies confirm that WMP exhibits substantial anti-inflammatory properties and shown to regulate key proteins related to inflammation, such as TLR4 and NF-κB, which are closely associated with RA pathogenesis. According to the traditional Chinese medicine theory, WMP is primarily administered to address various ailments triggered by cold. RA is classified as a “Bi” syndrome caused by cold, wind, and dampness, and is within the therapeutic domain of WMP in ancient Chinese medicine. Consequently, this experiment primarily explored the specific mechanism through which WMP alleviates the progression of RA.</p>" ]
[ "<title>Methods</title>", "<title>Drug and drug-containing serum preparation</title>", "<p id=\"Par46\">WMP has been included in the 2020 edition of the Chinese Pharmacopoeia. The study introduced six more Chinese herbal medicines, resulting in a total of 16 Chinese herbal medicines (refer to Table ##TAB##0##1##).</p>", "<p id=\"Par47\">The drug formulation containing WMP serum: The drug is dissolved in 0.1% sodium carboxymethylcellulose and administered by gavage to mice at a dose of 2 g/kg/day for 7 days. After 15 h of fasting and dehydration, blood is collected and centrifuged to obtain serum. The serum was incubated in a water bath for 25 min to produce drug-containing serum for inactivation. The serum is then filtered through a sterile 0.22 μm microporous membrane under controlled aseptic conditions and stored at − 80 °C. (Note: Different sera can be used. (Note: Different concentrations of drug serum were diluted from normal mouse serum).</p>", "<title>UPLC-MS spectrometry detection</title>", "<p id=\"Par48\">Column: Waters UPLC HSS T3. Mobile phase: methanol, water + 0.1% formic acid. Flow rate: 0.3 ml/min. Sample injection volume: 10 µl. The mass spectrometer was a quadrupole orbital ion trap mass spectrometer (containing a thermospray ion source, Q Active ™) (Table ##TAB##1##2##).</p>", "<title>Establishment of a rheumatoid arthritis model and isolation and cultivation of RA-FLS</title>", "<p id=\"Par49\">The study utilized female Wistar rats (180 ± 20 g, Ease Animal Technology Ltd.), fed a high-fat diet with normal water intake and 12-h cycles of day and night. The Animal Ethics Committee of Jilin Agricultural University approved all experiments.</p>", "<p id=\"Par50\">CAI modeling: 1 ml of bovine type II collagen solution was repeatedly mixed with 1 ml of IFA to make a water-in-oil emulsion. The resulting emulsion was subcutaneously injected into the tails of rats at a dose of 0.2 ml per rat. After 1 week, the same dosage of emulsion was injected again to improve the immunization.</p>", "<p id=\"Par51\">From the first injection of type II collagen to establish a model, the joint swelling of each group of rats is recorded every 2 days. The arthritis index score is a slight adjustment based on previous studies [##UREF##2##37##]. The score mainly evaluates the joint redness and swelling in rats after the onset of the disease. Each foot is scored out of 4 points, with a total of 16 points. A score of 6 or more indicates successful modeling. The score is based on the degree and extent of joint redness and swelling, as well as joint swelling and deformity. The scoring system is based on a 1–4 point scale, with the following criteria: (1) 0 points: No redness or swelling; (2) 1 point: Slight redness and swelling in a single area of the tarsal joint or ankle joint; (3) 2 points: Mild redness and swelling extending to the tarsal joint; (4) 3 points: Moderate redness and swelling in the ankle joint extending to the metatarsal bones; (5) 4 points: Severe redness and swelling in the ankle joint extending to the metatarsal bones, joint stiffness, and deformity.</p>", "<p id=\"Par52\">RA-FLS extraction: Synovial tissue from CIA rats was taken, cut and enzymatically digested (Type II collagenase. Sigma-Aldrich, Shanghai, China). The incompletely digested tissue was filtered. Cells were placed in DMEM complete medium (Procell Life Technologies Ltd.) and incubated in an incubator at CO<sub>2</sub>.</p>", "<p id=\"Par53\">Control group: without any drug treatment. LPS group: RA-FLS was treated with LPS (1 μg/ml) for 12 h. Methotrexate (MTX, 100 nM, Shanghai Mellin Biochemical Technology Co., Ltd.) group: add MTX and continue incubation for 12 h. WMP group: add WMP and continue incubation for 12 h.</p>", "<title>RA-FLS viability detection</title>", "<p id=\"Par54\">Incubate RA-FLS (5 × 10<sup>3</sup> cells/well) in a 96-well plate for 12 h. The WMP group was then exposed to serum concentrations containing drugs at 1%, 2%, 4%, 8%, 10%, 20%, 50%, and 100%. After an additional 24 h of incubation, 20 μl of CCK-8 was added to each well and incubated for 30 min. The cell viability was assessed by measuring the OD value of each group at 450 nm using an enzyme marker.</p>", "<title>RA-FLS migration detection</title>", "<p id=\"Par55\">Inoculate RA-FLS (5 × 10<sup>4</sup> cells/well) into a 6-well plate and incubate for 12 h, then use a 200-μl gun tip to scratch cells perpendicular to the well plate. Gently rinse off the floating cells from each well with PBS. Re-add the appropriate drug to each group. Each group was photographed and recorded at 0 h and 12 h, and the migration distance of RA-FLS in each group was calculated.</p>", "<title>RA-FLS invasion detection</title>", "<p id=\"Par56\">The RA-FLS (1 × 10<sup>4</sup>cells/well) pretreated with LPS for 12 h was inoculated into materigel-coated transwell chambers, and the corresponding dose of drug was added and incubated for 12 h. After cell culture was completed, each group of transwells was sequentially fixed, stained, and rinsed with PBS. The number of cells attached to the outer ventricular membrane was observed under the microscope. Four fields of view were randomly selected for counting.</p>", "<title>Inflammatory factor testing</title>", "<p id=\"Par57\">Cell supernatant preparation: Firstly, RA-FLS (1 × 105 cells/well) were seeded into a 6-well plate and incubated for 12 h. Next, all groups except for the control group were treated with the corresponding drugs and then incubated for 24 h. Finally, the supernatants from each group of cells were collected and placed into 1 ml centrifuge tubes, which were then centrifuged at 80×100<italic>g</italic> for 10 min at 4 °C. The supernatants were extracted and stored at − 80 °C for later use.</p>", "<p id=\"Par58\">Preparation of rat serum: After administering the drug treatment, we obtained blood samples from each group of rats by collecting it from the eyeball vein. Blood at 4 °C, 80×100<italic>g</italic> centrifuge with force for 10 min, take the supernatant and store it at − 80 °C for later use.</p>", "<p id=\"Par59\">ELISA kits are from Biyuntian Biotechnology Co. The specific test method is strictly according to the instruction of the kit.</p>", "<title>CIA rat modeling and grouping</title>", "<p id=\"Par60\">The CIA rat model was replicated using the method outlined in “<xref rid=\"Sec5\" ref-type=\"sec\">Effect of WMP on RA-FLS migration and invasion</xref>” section. The rats were allocated randomly into five groups (<italic>n</italic> = 5), namely the control, CIA, positive (methotrexate, MTX, 30 mg/kg), WMP sub-effective dose (0.5 g/kg) and WMP effective dose (2 g/kg) groups. After successful modeling, the control and model groups were orally administered physiological saline once a day for 15 consecutive days. In the positive group, methotrexate powder was dissolved in 0.1% carboxymethyl cellulose sodium solution at a dose of 30 mg/kg/day (MTX). WMP powder was dissolved in 0.1% carboxymethyl cellulose sodium solution and then orally administered at low and high doses of 0.5 g/kg/day and 2 g/kg/day respectively. The arthritis index was scored every 2 days for each group of rats. Fifteen days of treatment were carried out, followed by the collection of serum, synovial fluid, spleen, thymus, and knee tissue for analysis of pertinent physical and chemical indices.</p>", "<title>CIA rat immune organ index</title>", "<p id=\"Par61\">Extract the thymus and spleen from each group of CIA rats, weigh them, and compare their weight to calculate the immune organ index of each rat group.</p>", "<title>Histopathology assessment</title>", "<p id=\"Par62\">Knee joints were extracted from the hind limbs of rats and subsequently decalcified using 10% ethylenediaminetetraacetic acid (EDTA). The joints were then fixed in paraffin, cut into 5 μm sections, and ultimately stained with hematoxylin–eosin and Anna Red O/Fast Green dyes, respectively.</p>", "<title>Western blot</title>", "<p id=\"Par63\">Cell sample processing: RA-FLS cells were seeded at a density of 5 × 10<sup>5</sup> cells per well on a 6-well plate and incubated for 12 h. Replace the appropriate medication dosage and continue to cultivate for another 24 h. Subsequently, remove the culture medium and add 200 μl Radio immunoprecipitation assay (RIPA) cracking solution. Employ a centrifuge at 120×100<italic>g</italic> and 4 °C for 10 min. Lastly, extract the supernatant and store it at − 80 °C for future use. Synovial tissue processing: The synovium was lysed using 200 μl of RIPA lysate for every 20 mg of tissue. The tissue was homogenized in an ice bath employing a glass homogenizer until it completely dissolved.</p>", "<p id=\"Par64\">The protein concentration of each group was determined using the Bicinchoninic Acid Assay (BCA) kit and standardized accordingly. Subsequently, the samples underwent electrophoresis and were transferred via electro transfer onto a PVDF membrane. Following a 2-h closure in 5% skimmed milk powder, each group was subjected to overnight incubation with the relevant primary antibody, washed thrice with Tris-buffered saline with Tween (TBST), and then incubated for 2 h with the secondary antibody. The PVDF membranes underwent development in a visualiser after being placed in Enhanced chemiluminescence (ECL) luminous reagent for 30 s. Technical term abbreviations were explained accordingly. The text adheres to a clear, concise, and formal writing style. The ImageJ software was used to analyze the gray scale values of each group of bands, and subsequent statistical analysis was conducted. The antibodies, including TLR4 (AY9008), TRAF6 (CY8163), NF-κB (CY5034), β-actin (AY0573) from Shanghai Abways Biotechnology Co., and IκB-α (bs-1287R), p-IκB-α (bs-2513R), MMP-2 (bs-20705R), MMP-9 (bs-7059R), TIMP-2 1 (bs-43009R), TIMP-12 (bs-0416R), Lamin B (bs-1840R) from Beijing Bioss Biotechnology Co. The reagents utilized in the experiment included BCA (P0010), TBST (ST673), ECL (P0018S), RIPA (P0013B) from Buffer Biyuntian Biotechnology Co.</p>", "<p id=\"Par65\">All protein bands were detected by ImageJ 2.9.0 software for gray scale values and subsequent graphical analysis (Original images of all the western blot are in Additional file ##SUPPL##0##1##: supplemental material Figure 3).</p>", "<title>Statistical analysis</title>", "<p id=\"Par66\">All figures were performed using GraphPad Prism 6. Data were expressed as the mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was used for statistical analysis of data, followed by <italic>Tukey</italic>’s post-hoc multiple comparison test. Statistical significance was defined as (#) or (*) <italic>p</italic> &lt; 0.05, (##) or (**) <italic>p</italic> &lt; 0.01, (###) or (***) <italic>p</italic> &lt; 0.001.</p>" ]
[ "<title>Result</title>", "<title>Identification of the chemical composition of WMP</title>", "<p id=\"Par31\">A total of 181 compounds were detected in the WMP in both positive (Fig. ##FIG##0##1##A) and negative (Fig. ##FIG##0##1##B) ionization modes. Additional file ##SUPPL##0##1##: Table S1 lists the compounds contained in each herb. Wumeirou comprises of 2 compounds, Xixin comprises of 2 compounds, Huanglian comprises of 3 compounds, Huangbai comprises of 1 compound, Ganjiang comprises of 51 compounds, Heishunpian comprises of 4 compounds, Guizhi comprises of 2 compounds, Renshen comprises of 6 compounds, Danggui comprises of 29 compounds, Zhike comprises of 4 compounds, Jiegeng comprises of 1 compound, Baishao comprises of 16 compounds, and Zhigancao comprises of 74 compounds. The entire list of 181 compounds can be found as Additional file ##SUPPL##0##1##: Table S1 online. Furthermore, we have identified every herb based on its markers to verify the precision of the herbs employed. The fingerprints for specific experiments can be found as Additional file ##SUPPL##0##1##: Fig. S2 online.</p>", "<title>Effect of WMP on the activity and inflammatory factors of RA-FLS cells</title>", "<p id=\"Par32\">The dose-dependent impact of WMP on RA-FLS activity is illustrated in Fig. ##FIG##1##2##A. Our research objectives were twofold: to investigate the mechanisms underlying WMP's anti-inflammatory properties and its influence on RA-FLS migration and invasion. Cell Counting Kit-8 (CCK-8) tests showed no significant effect on the viability of RA-FLS when treated with 2% or 8% WMP, or 100 nM MTX. Therefore, these experimental doses were used for subsequent migration and invasion assay experiments, as well as for studying mechanisms related to anti-inflammatory activity.</p>", "<p id=\"Par33\">Based on the ELISA results, it was found that LPS had a significant impact on increasing the levels of TNF-α and IL-6 in RA-FLS cells (<italic>p</italic> &lt; 0.01). This suggests that RA-FLS cells remained activated in an inflammatory environment. Conversely, Fig. ##FIG##1##2##B and C showed that WMP significantly inhibited the secretion of both TNF-α (<italic>p</italic> &lt; 0.001) and IL-6 (<italic>p</italic> &lt; 0.001). This implies that WMP has a significant anti-RA inflammatory effect.</p>", "<title>Effect of WMP on RA-FLS migration and invasion</title>", "<p id=\"Par34\">In the wound healing assay, Fig. ##FIG##1##2##D and F depict considerable migration of RA-FLS in both the control and LPS groups, with scratches nearly disappearing within 12 h. However, the horizontal migration of RA-FLS was significantly inhibited by application of MTX (100 nM) and WMP (2%, 8%) (<italic>p</italic> &lt; 0.01). As evidenced in Fig. ##FIG##1##2##E and G, the vertical invasion of RA-FLS was significantly inhibited by MTX (100 nM) and WMP (2%, 8%) in the transwell assay (<italic>p</italic> &lt; 0.05 and <italic>p</italic> &lt; 0.001, respectively).</p>", "<title>Effect of WMP on the expression of inflammatory related proteins in RA-FLS</title>", "<p id=\"Par35\">The TLR4/NF-κB pathway is a subject of frequent study in the context of RA. We scrutinized the effects of WMP on this particular pathway in RA-FLS cells through protein immunoblotting. In contrast to the control group, the LPS group exhibited elevated levels of inflammation-related protein expression, signifying a further exacerbation of RA-FLS inflammation. As demonstrated in Fig. ##FIG##2##3##B–E of the experimental results, the use of WMP yielded significant inhibitory effects on TLR4 protein expression (<italic>p</italic> &lt; 0.001), TRAF6 protein expression (<italic>p</italic> &lt; 0.01), nuclear translocation of NF-κB proteins (<italic>p</italic> &lt; 0.01), and the phosphorylation of IκB-α (<italic>p</italic> &lt; 0.05), in comparison to the LPS group. Furthermore, the experimental results Fig. ##FIG##2##3##F–I demonstrate that WMP significantly hindered the expression of MMP-2/9 protein in RA-FLS cells (<italic>p</italic> &lt; 0.01) and encouraged the expression of TIMP-1/2 protein in RA-FLS cells compared to the LPS group (<italic>p</italic> &lt; 0.001, <italic>p</italic> &lt; 0.01).</p>", "<title>Effect of WMP on arthritis index, immune organ index and inflammatory factors in CIA rats</title>", "<p id=\"Par36\">In this experiment, while performing the modeling, and WMP administration, the arthritis index scores of rats in each group were performed every 2 days, and the results are shown in the results of Fig. ##FIG##3##4##A. Except for the control group, the rats in the remaining groups reached a score of 6 or more around day 15, and WMP administration was started. The arthritis index of the WMP (2 g/kg) group was significantly suppressed until the 30th day.</p>", "<p id=\"Par37\">Figure ##FIG##3##4##B and C demonstrates a marked inflammatory response in rats following collagen induction, as indicated by the elevated ratio of immune organs (thymus, spleen) to body weight, which was significantly greater than that of the control group (<italic>p</italic> &lt; 0.01). Positive drug and WMP administration began early in the model stage. After one cycle of treatment, inflammation reduced in rats. Evidence of this is shown by a decrease in immune organ ratios (thymus, spleen) to body weight in CIA rats who received WMP treatment, which was significantly different from the model group (<italic>p</italic> &lt; 0.01 and <italic>p</italic> &lt; 0.05, respectively). This indicates that when compared to the hyperimmunity of RA rats, WMP effectively reduces it.</p>", "<p id=\"Par38\">In this research, we evaluated the level of inflammation in rat serum. Figure ##FIG##3##4##F and G demonstrates a substantial increase in levels of both TNF-α and IL-6 in the serum of rats with CIA, providing evidence of elevated autoinflammation. Our findings were consistent with the immune index analysis. Comparatively, rats in the WMP group had significantly reduced levels of TNF-α and IL-6 when compared with the CIA group (<italic>p</italic> &lt; 0.001, <italic>p</italic> &lt; 0.001 respectively). This supports our conclusion that WMP has a significant anti-inflammatory effect on RA rats in vivo.</p>", "<title>Effect of WMP on knee joint swelling in CIA rats</title>", "<p id=\"Par39\">As depicted in Fig. ##FIG##3##4##D, examination of the knee joint pathological sections revealed that the RA model rats induced by collagen exhibited joint irregularities and showed evident cartilage erosion compared to the healthy rats. This was accompanied by thickening of synovial tissue and inflammatory infiltration. However, after treatment with WMP, the articular surface appeared notably intact, and the inflammatory infiltration was less prominent.</p>", "<p id=\"Par40\">The articular cartilage structure in the knee and ankle joints of rats from each group was examined using safranin O/fast green staining. Figure ##FIG##3##4##E demonstrates that the surface of the knee joints of the rats in the control group was smooth, and the cartilage (red part) bands were firmly attached to the bone surface. The rats in the CIA group showed varying degrees of joint damage, including cartilage thinning or disappearance, as well as areas of severe cartilage destruction. Nevertheless, following WMP treatment, the cartilage bands appeared smooth and complete, and the bone tissue structure remained intact. In addition, synovial hyperplasia was relieved, and no obvious inflammatory infiltration was observed.</p>", "<title>Effect of WMP on the expression of inflammatory and invasive proteins in the synovium of CIA rats</title>", "<p id=\"Par41\">The proteins related to the synovium in rats with collagen-induced arthritis (CIA) were analyzed through Western blotting. Figure ##FIG##4##5##B–E illustrates a significant increase in the expression levels of TLR4 and TRAF6 proteins in the CIA group (<italic>p</italic> &lt; 0.01 and <italic>p</italic> &lt; 0.001, respectively). The CIA group also experienced marked nuclear translocation of NF-κB (<italic>p</italic> &lt; 0.05) and phosphorylation of IκB-α (<italic>p</italic> &lt; 0.001). The study's results indicate that WMP significantly hindered the expression of TLR4 and TRAF6 proteins compared to CIA (<italic>p</italic> &lt; 0.05). In addition, nuclear translocation of NF-κB was significantly inhibited (<italic>p</italic> &lt; 0.05), as was phosphorylation of IκB-α (<italic>p</italic> &lt; 0.01). In the study of migration and invasion mechanisms, a significant increase in MMP-2/9 expression in the CIA group (<italic>p</italic> &lt; 0.001) was shown to be associated with synovial migration and invasion according to the results F–I. In contrast, the expression of TIMP-1/2, which prevents synovial migration and invasion by binding to MMP-2/9, was dramatically decreased (<italic>p</italic> &lt; 0.01). In addition, after WMP treatment, excess free MMP-2/9 protein was inhibited (<italic>p</italic> &lt; 0.01, <italic>p</italic> &lt; 0.001) and TIMP-1/2 expression was elevated ((<italic>p</italic> &lt; 0.001, <italic>p</italic> &lt; 0.01), inhibiting synovial inflammation from invading periarticular tissues and cartilage.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par42\">WMP is best described in the Han Dynasty Chinese Treatise on <italic>Typhoid Fever</italic>. It primarily treats a variety of cold and heat-induced ailments in Traditional Chinese Medicine theory. The theory posits that RA is mainly caused by external agents like wind, cold, and dampness invading the body. Consequently, the application of WMP in treating RA aligns perfectly with Traditional Chinese Medicine theory. Additionally, recent medical research has indicated a positive anti-inflammatory effect of WMP. Furthermore, scholars have utilized WMP in the treatment of RA, although the exact mechanisms of action remain unclear. Hence, this paper aims to explore the mechanism of WMP in the prevention and management of RA. Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS) analysis revealed that WMP contains 181 chemical components. Wumeirou has 2 compounds, Xixin has 2 compounds, Huanglian has 3 compounds, Huangbai has 1 compound, Ganjiang has 51 compounds, Heishunpian has 4 compounds, Guizhi has 2 compounds, Renshen has 6 compounds, Danggui has 29 compounds, Zhike has 4 compounds, Jiegeng has 1 compound, Baishao has 16 compounds, and Zhigancao has 74 compounds. Among the compounds detected in WMP, some have been confirmed to possess significant anti-inflammatory and antioxidant activity. For instance, Neochlorogenic acid in Wumeirou mitigates hepatic lipid accumulation and inflammation by modulating miR-34a [##REF##34884968##20##]. Coptisine in Huanglian can be used to treat NLRP3 inflammasome-mediated gouty arthritis by inhibiting caspase-1 to block NLRP3 inflammasome activation [##REF##31336157##21##]. Zingerone in dried ginger attenuates Ti particle-induced inflammatory osteolysis by inhibiting the NF-κB signaling pathway in osteoclasts [##REF##37724956##22##].</p>", "<p id=\"Par43\">RA is a multifactorial and complex immune-mediated disease with an unclear pathogenesis. Clinical treatment aims to reduce disease activity and alleviate symptoms. Studies suggest that the immune-inflammatory response plays a crucial role in the development of RA and is continuously activated throughout the disease process [##REF##30285183##23##]. TLR4 receptors are transmembrane proteins situated on the cell membrane, which play a critical role in non-specific immunity and can trigger inflammation. Numerous studies support the notion that activation of TLR4 can worsen RA symptoms. Thus, exploring this receptor's properties and analyzing its corresponding pathways could serve as a basis for elucidating RA's pathogenesis [##REF##9237759##24##]. Upon activation by external stimuli, TLR4triggers the secretion of inflammatory factors and chemokines via a MyD88-dependent pathway. Pro-inflammatory factors and chemokines govern intracellular signaling pathways, thereby modulating cellular inflammatory responses in terms of their nature, extent, and timing [##REF##36360148##25##]. Activation of the MyD88-dependent pathway through interference with TLR4 interacts with IRAK, leading to an increase in TRAF6 protein expression [##REF##14751757##26##]. TRAF6 additionally enhances the nuclear translocation of NF-kB, a prominent pro-inflammatory transcription factor, and produces inflammatory factors and mediators [##REF##33176281##27##]. The elevated expression of TLRs in activated FLS has been linked to the activation of the NF-kB pathway and transcription of inflammatory factors like TNF-α and IL-6 [##REF##27988432##28##]. The experiment illustrated that WMP significantly diminished the arthritis and immune organ indices of CIA rats, while also mitigating joint swelling and autoimmune hyperactivation. revealed that WMP notably diminished inflammatory infiltration in the rats' knee joints and conserved cartilage tissue. Furthermore, WMP substantially decreased the levels of TNF-α and IL-6 levels in the CIA rat model. The Western blot analysis results indicate that WMP significantly decreased the expression of TLR4 and TRAF6 proteins. Furthermore, WMP has the ability to suppress the classical NF-κB inflammatory pathway by preventing the nuclear transportation of NF-κB and the phosphorylation of IκB-α.</p>", "<p id=\"Par44\">FLS constitute 70–80% of synovial tissue and serve to uphold the structural integrity of the synovial lining while secreting lubricating fluid. Numerous studies indicate that RA-FLS play a crucial role in the development of RA and are the principal effector cells in the disease. It is important to note that these statements are objective and supported by scientific evidence [##REF##20131230##29##]. The hyperproliferation of RA-FLS, which promotes the production of inflammatory factors and extracellular matrix regulators, has been identified as the primary cause of RA development, leading to joint destruction. Additionally, RA-FLS exhibits tumor-like properties and secretes substantial quantities of MMPs during proliferation, leading to the erosion of cartilage and joint destruction [##REF##28662826##30##]. MMP-2 (also referred to as gelatinase-A) and MMP-9 (also known as gelatinase-B) are both capable of degrading the intercellular matrix, thus promoting the migration and invasion of RA-FLS cells. Subsequently, it is suggested that these MMPs play a role in RA pathogenesis [##REF##35804363##31##, ##REF##29799160##32##]. Significant increases in MMP-2 and MMP-9 proteins have been found to contribute to joint opacification and irreversible cartilage erosion in RA patients, leading to impaired mobility [##REF##20665024##33##]. Under normal circumstances, tissue inhibitors of MMPs (TIMPs) bind to MMPs in a 1:1 ratio, inhibiting the excessive production of MMPs. When rheumatoid arthritis (RA) develops, the balance is disrupted due to the concentration of specific inflammatory factors present in the joints. Therefore, there is an excessive production of MMPs, further accelerating ECM degradation, thereby leading to RA-FLS migration and invasion [##REF##20470890##34##]. TIMP-1 and TIMP-2 bind with MMP-9 and MMP-2 proteins to create a complex and prevent their excessive production [##REF##23969736##35##]. Previous studies have reported elevated MMP expression in the synovial tissue, synovial fluid, and peripheral blood of patients with rheumatoid arthritis [##REF##22193222##36##]. This article examines the mechanism of action of WMP on RA-FLS. Firstly, WMP significantly reduces the secretion of TNF-α and IL-6 inflammatory factors by RA-FLS. Additionally, WMP inhibits RA-FLS migration and invasion significantly through the cell scratch assay and transwell assay. The Western blotting results revealed that WMP substantially reduced the protein expression of MMP-2 and MMP-9 in RA-FLS, increased the protein expression of TIMP-1 and TIMP-2, and rectified the dynamic equilibrium of MMPs' protein expression. This intrinsic mechanism of WMP inhibits RA-FLS's migration and invasion.</p>", "<p id=\"Par45\">In conclusion, WMP demonstrates a significant impact in hindering RA lesions and joint degradation. WMP operates by reducing the levels of TLR4 and TRAF6 proteins, thereby suppressing immune hyperactivity in RA, ultimately impeding the nuclear translocation of NF-κB and IκB-α phosphorylation, thus curtailing the production of inflammatory cytokines (e.g., TNF and IL-6) in RA-α. Additionally, WMP regulates the MMP-2/TIMP-2 and MMP-9/TIMP-1 balance, ultimately hindering RA-FLS migration and invasion. Thus, WMP may hold potential as a future drug for the prevention and treatment of RA.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Wu Mei Pills (WMP) is a traditional Chinese medication that exhibits considerable anti-inflammatory effects. While WMP has been documented for its efficacy in treating RA, its mechanism of action on the condition remains unestablished.</p>", "<title>Methods</title>", "<p id=\"Par2\">The chemical composition of WMP was analyzed through UPLC-MS. Next, the enzyme-linked immunosorbent assay, cell scratch, Transwell, and Western blotting techniques were used to investigate its intrinsic mechanism. Lastly, the effect of WMP in inhibiting RA was explored by applying it to CIA rats.</p>", "<title>Result</title>", "<p id=\"Par3\">UPLC-MS analysis detected 181 compounds in WMP. RA-FLS migration and invasion mechanisms were significantly hindered by serum containing WMP (2%, 8%). Moreover, WMP (0.5 g/kg, 2 g/kg) restricted arthritis and immune organ indices in CIA rats with type II collagen-induced rheumatoid arthritis by blocking TLR4-NF-κB inflammatory pathway activation.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">WMP is valuable in mitigating the course of RA through inhibiting the classical TLR4-NF-κB inflammatory pathway and reducing the secretion of inflammatory factors in the serum of RA-FLS and CIA rats. Moreover, it regulates the dynamic balance of MMP-2/TIMP-2, MMP-9/TIMP-1, modulates the mechanism of RA-FLS invasion, and safeguards articular cartilage tissues in RA.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13018-024-04551-z.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>YF, HZ, YZ contributed to conceptualization; CG contributed to methodology and formal analysis; XS helped in writing—original draft.</p>", "<title>Funding</title>", "<p>The authors are grateful for the Jilin Province Science and Technology Development Plan Project: Research on the Development of Classic Famous Formula Modified Wu Mei Pill Preparation (20220204009YY).</p>", "<title>Availability of data and materials</title>", "<p>All data generated or analyzed during this study are included in this published article [and its supplementary information files].</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par67\">The experiments were approved by the Animal Ethics Committee of Jilin Agricultural University.</p>", "<title>Consent for publication</title>", "<p id=\"Par68\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par69\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Total ion chromatogram of constituents in WMP. <bold>A</bold> Positive ion mode. <bold>B</bold> Negative ion mode</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>WMP decreased RA-FSL viability migration and invasion. <bold>A</bold> Cell viability assay by CCK-8 assay. <bold>B</bold> and <bold>C</bold> show the levels of TNF-α, IL-6 in RA-FSL in each group by ELISA. The <bold>D</bold> and <bold>E</bold> are WMP inhibition of RA-FLS migration and invasion (magnification × 400). The <bold>F</bold> and <bold>G</bold> are data statistics Data are expressed as mean ± standard deviation. (#) <italic>p</italic> &lt; 0.05, (##) <italic>p</italic> &lt; 0.01 and (###) <italic>p</italic> &lt; 0.001 versus control. (*) <italic>p</italic> &lt; 0.05, (**) <italic>p</italic> &lt; 0.01 and (***) <italic>p</italic> &lt; 0.001 versus LPS</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>WMP reduces RA-FLS inflammation by inhibiting the TLR4/NF-κB signaling pathway and decreases RA-FLS migration and invasion by inhibiting MMPs. <bold>A</bold> depicts the western blot illustrating the impact of WMP on the expression of RA-FLS proteins in each group. <bold>B</bold>–<bold>I</bold> depict the expression levels of TLR4, TRAF6, NF-κB, IκB-α, MMP-2, MMP-9, TIMP-1, and TIMP-2 proteins in each group of RA-FLS. Data are expressed as mean ± standard deviation (<italic>n</italic> = 3). (#) <italic>p</italic> &lt; 0.05, (##) <italic>p</italic> &lt; 0.01 and (###) <italic>p</italic> &lt; 0.001 versus control. (*) <italic>p</italic> &lt; 0.05, (**) <italic>p</italic> &lt; 0.01 and (***) <italic>p</italic> &lt; 0.001 versus LPS</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>WMP significantly reduced joint inflammation in CIA rats. <bold>A</bold> indicates the arthritis index score of rats in each group. <bold>B</bold> and <bold>C</bold> display the spleen and thymus immunity index of CIA rats in each group. <bold>D</bold> indicates H&amp;E staining (green arrow indicates synovial hyperplasia, yellow arrow indicates inflammatory infiltrate). <bold>E</bold> indicates safranin O/fast green staining (orange arrow indicates cartilage band erosion). <bold>F</bold> and <bold>G</bold> depict the expression of TNF-α and IL-6 in the serum of rats in each group. Data are expressed as mean ± standard deviation (<italic>n</italic> = 5). (#) <italic>p</italic> &lt; 0.05, (##) <italic>p</italic> &lt; 0.01 and (###) <italic>p</italic> &lt; 0.001 versus control. (*) <italic>p</italic> &lt; 0.05, (**) <italic>p</italic> &lt; 0.01 and (***) <italic>p</italic> &lt; 0.001 versus CIA</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>WMP reduces inflammation in CIA rats by inhibiting the TLR4/NF-κB signaling pathway and reduces cartilage invasion by decreasing MMPs. <bold>A</bold> indicates western blot of WMP-affected synovial membrane-associated protein expression in CIA rats. <bold>B</bold>–<bold>I</bold> shows the levels of TLR4, TRAF6, NF-κB, IκB-α, MMP-2, MMP-9, TIMP-1, and TIMP-2 protein expression in the synovial membrane of each group. Data are expressed as mean ± standard deviation (<italic>n</italic> = 3). (#) <italic>p</italic> &lt; 0.05, (##) <italic>p</italic> &lt; 0.01 and (###) <italic>p</italic> &lt; 0.001 versus control. (*) <italic>p</italic> &lt; 0.05, (**) <italic>p</italic> &lt; 0.01 and (***) <italic>p</italic> &lt; 0.001 versus CIA</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Herbal constituents of WMP</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Chinese name</th><th align=\"left\">Latin name</th><th align=\"left\">Dose (g)</th></tr></thead><tbody><tr><td align=\"left\">Wumei</td><td align=\"left\"><italic>Prunus mume</italic> (Siebold) Siebold &amp; Zucc</td><td char=\".\" align=\"char\">120</td></tr><tr><td align=\"left\">Huajiao</td><td align=\"left\"><italic>Zanthoxylum bungeanum</italic> Maxim</td><td char=\".\" align=\"char\">12</td></tr><tr><td align=\"left\">Xixin</td><td align=\"left\"><italic>Asarum heterotropoides</italic> F.Schmidt</td><td char=\".\" align=\"char\">18</td></tr><tr><td align=\"left\">Huanglian</td><td align=\"left\"><italic>Coptis omeiensis</italic> (F.H.Chen) C.Y.Cheng</td><td char=\".\" align=\"char\">48</td></tr><tr><td align=\"left\">Huangbai</td><td align=\"left\"><italic>Phellodendron chinense</italic> C.K.Schneid</td><td char=\".\" align=\"char\">18</td></tr><tr><td align=\"left\">Ganjiang</td><td align=\"left\"><italic>Zingiber officinale</italic> Roscoe</td><td char=\".\" align=\"char\">30</td></tr><tr><td align=\"left\">Heishunpian</td><td align=\"left\"><italic>Aconitum carmichaelii</italic> Debeaux</td><td char=\".\" align=\"char\">18</td></tr><tr><td align=\"left\">Guizhi</td><td align=\"left\"><italic>Neolitsea cassia</italic> (L.) Kosterm</td><td char=\".\" align=\"char\">18</td></tr><tr><td align=\"left\">Renshen</td><td align=\"left\"><italic>Panax ginseng</italic> C.A.Mey</td><td char=\".\" align=\"char\">18</td></tr><tr><td align=\"left\">Danggui</td><td align=\"left\"><italic>Angelica sinensis</italic> (Oliv.) Diels</td><td char=\".\" align=\"char\">12</td></tr><tr><td align=\"left\">Zhike</td><td align=\"left\"><italic>Citrus</italic> × <italic>aurantium</italic> L.</td><td char=\".\" align=\"char\">12</td></tr><tr><td align=\"left\">Jiegeng</td><td align=\"left\"><italic>Platycodon grandiflorus</italic> (Jacq.) A.DC</td><td char=\".\" align=\"char\">12</td></tr><tr><td align=\"left\">Baishao</td><td align=\"left\"><italic>Paeonia lactiflora</italic> Pall</td><td char=\".\" align=\"char\">12</td></tr><tr><td align=\"left\">Zhigancao</td><td align=\"left\"><italic>Glycyrrhiza glabra</italic> L.</td><td char=\".\" align=\"char\">12</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Elution gradient table</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Time (min)</th><th align=\"left\" colspan=\"2\">Mobile phase</th></tr><tr><th align=\"left\"><italic>A</italic> (v%)</th><th align=\"left\"><italic>B</italic> (v%)</th></tr></thead><tbody><tr><td align=\"left\">0</td><td char=\".\" align=\"char\">2</td><td char=\".\" align=\"char\">98</td></tr><tr><td align=\"left\">1.0</td><td char=\".\" align=\"char\">2</td><td char=\".\" align=\"char\">98</td></tr><tr><td align=\"left\">41.0</td><td char=\".\" align=\"char\">100</td><td char=\".\" align=\"char\">0</td></tr><tr><td align=\"left\">50.0</td><td char=\".\" align=\"char\">100</td><td char=\".\" align=\"char\">0</td></tr><tr><td align=\"left\">50.1</td><td char=\".\" align=\"char\">2</td><td char=\".\" align=\"char\">98</td></tr><tr><td align=\"left\">52.0</td><td char=\".\" align=\"char\">2</td><td char=\".\" align=\"char\">98</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Yuheng Fu, Chunyu Gao and Xialin Sun contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13018_2024_4551_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13018_2024_4551_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"13018_2024_4551_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"13018_2024_4551_Fig4_HTML\" id=\"MO4\"/>", "<graphic xlink:href=\"13018_2024_4551_Fig5_HTML\" id=\"MO5\"/>" ]
[ "<media xlink:href=\"13018_2024_4551_MOESM1_ESM.pdf\"><caption><p><bold>Additional file 1.</bold> WMP composition analysis and western blot of the original image.</p></caption></media>" ]
[{"label": ["16."], "surname": ["Wang", "Ding", "Wang", "Yan", "Xu", "Deng"], "given-names": ["J", "K", "Y", "T", "Y", "Z"], "article-title": ["Wumei pill ameliorates AOM/DSS-induced colitis-associated colon cancer through inhibition of inflammation and oxidative stress by regulating S-adenosylhomocysteine hydrolase- (AHCY-) mediated hedgehog signaling in mice"], "source": ["Oxid Med Cell Longev"], "year": ["2022"], "volume": ["2022"], "fpage": ["1"], "lpage": ["28"]}, {"label": ["17."], "surname": ["Ding", "Sun", "Wang", "Zheng", "Yu", "Hao"], "given-names": ["X", "X", "Z", "Q", "X", "W"], "article-title": ["The effects of Wumei pill on TLRs/NF-kB signaling pathway in rats with diarrhea-predominant irritable bowel syndrome"], "source": ["Pak J Zool"], "year": ["2018"], "volume": ["51"], "fpage": ["57"], "lpage": ["65"], "pub-id": ["10.17582/journal.pjz/2019.51.1.57.65"]}, {"label": ["37."], "surname": ["Bevaart", "Vervoordeldonk", "Tak"], "given-names": ["L", "MJ", "PP"], "source": ["Collagen-induced arthritis in mice"], "year": ["2010"], "publisher-loc": ["Totowa"], "publisher-name": ["Humana Press"], "fpage": ["181"], "lpage": ["192"]}]
{ "acronym": [ "WMP", "RA", "TLR", "LPS", "RIPA", "ELISA", "TBST", "UPLC-MS", "CCK-8", "TCM", "DMARDs", "TNF-α", "IL-6", "MyD88", "NLRP3", "NF-κB", "IκB-α", "MMP-2", "MMP-9", "TIMP-1", "TIMP-2", "MTX" ], "definition": [ "Wu Mei Pill", "Rheumatoid arthritis", "Toll-like receptor", "Lipopolysaccharide", "Radio immunoprecipitation assay", "Enzyme-linked immunosorbent assay", "Tris-buffered saline with Tween", "Ultra-performance liquid chromatography/tandem mass spectrometry", "Cell counting kit-8", "Traditional Chinese medicine", "Disease-modifying anti-rheumatic drugs", "Tumor necrosis factor-α", "Interleukin-6", "Myeloid differentiation primary response protein 88", "NOD-like receptor thermal protein domain associated protein 3", "Nuclear factor kappa-B", "Inhibitor κ B-α", "Matrix metallopeptidase 2", "Matrix metallopeptidase 9", "Tissue inhibitor of metalloproteinase 1", "Tissue inhibitor of metalloproteinase 2", "Methotrexate" ] }
37
CC BY
no
2024-01-14 23:43:45
J Orthop Surg Res. 2024 Jan 13; 19:65
oa_package/1d/27/PMC10787417.tar.gz
PMC10787418
38216936
[ "<title>Introduction</title>", "<p id=\"Par5\">\nIn recent years, the incidence of thyroid cancer has increased significantly worldwide, with papillary thyroid carcinoma (PTC) accounting for most cases [##REF##33538338##1##]. PTC is characterized by early metastasis to cervical lymph nodes (LNs), particularly in the central region [##REF##17347896##2##]. The reported rate of central LN metastasis (CLNM) in patients is approximately 50% [##REF##30131586##3##], which is a known risk factor for recurrence and adversely affects overall survival [##UREF##0##4##, ##REF##26077238##5##]. The necessity of prophylactic central LN dissection (pCLND) remains a subject of debate in thyroid cancer treatment. In China, the latest guidelines recommend routine pCLND at least ipsilateral to the lesion [##UREF##1##6##]. While pCLND can effectively reduce the need for reoperation in cases of recurrence, it also leads to unnecessary CLND procedures. US is the most commonly used method for preoperative LN assessment in PTC [##REF##26462967##7##]. However, its sensitivity in identifying CLNM ranges from only 26–47%, which is insufficient for accurate assessment [##REF##30777203##8##]. Hence, a more sensitive preoperative assessment of CLNM is crucial for patients with PTC to reduce unnecessary CLND.</p>", "<p id=\"Par6\">Radiomics represents a high-throughput data mining approach for the discovery of novel imaging biomarkers and uses two main approaches: hand-crafted radiomics and deep learning [##REF##37499847##9##]. In recent years, both hand-crafted radiomics and deep learning, have shown powerful analytical capabilities in extracting intricate and multi-layered features from medical images [##REF##28975929##10##, ##UREF##2##11##]. Hand-crafted radiomics focuses on the mathematical manipulation of images to produce traditional features of texture and shape, etc. whereas the DL approaches can generate high-dimensional features to represent the deep image information of the tumour through end-to-end learning [##REF##30898263##12##]. We previously reported a preliminary small sample study of CLNM using hand-crafted radiomics, which acquired good performance [##REF##31640963##13##]. To date, most studies have independently employed DL and hand-crafted radiomics features, and far fewer studies have attempted to fuse these two features from US images. It is worth noting that features extracted by DL models may be sensitive to global translation, rotation, and scaling while hand-crafted radiomics features such as intensity features are not [##UREF##3##14##, ##REF##28681390##15##], Therefore, we hypothesize that hand-crafted radiomics features and DL features extracted from US images could be complementary, and their combination may yield improved prediction outcomes.</p>", "<p id=\"Par7\">However, unlike radiologists who incorporate clinical and US information to make diagnoses, most AI models only provide output results without revealing their decision-making process. This lack of transparency is considered one of the reasons why radiologists are skeptical about the clinical application of AI models. Previous studies have highlighted the significance of clinical and US characteristics (e.g., age, gender, and tumour size) in distinguishing CLNM [##REF##35226156##16##]. Nevertheless, the lack of information such as age and gender in the images, and data pre-processing such as resizing and normalisation, makes detecting these information challenging in machine learning [##REF##34674280##17##]. By integrating clinical and US features into AI models, it may be possible to improve the predictive efficacy of the models as well as the acceptance from radiologists.</p>", "<p id=\"Par8\">Hence, this study aimed to develop and validate whether an integrated model incorporating DL, hand-crafted radiomics and clinical and US features can improve the performance to diagnose CLNM in patients with PTC, in order to reduce the miss rate of CLNM, unnecessary CLND and improve the acceptance of AI-assisted US diagnosis for radiologists.</p>" ]
[ "<title>Patients and methods</title>", "<title>Patients</title>", "<p id=\"Par9\">The Ethics Committees of Nanfang Hospital of South Medical University and the First People’s Hospital of Foshan (NFEC-202,008-K6) approved this retrospective study. The requirement for informed consent was waived. The checklist for Artificial Intelligence in Medical Imaging (CLAIM) and EvaluAtion of Radiomics research (CLEAR) were applied as step-by-step reporting guideline for this study, which is presented in a Supplementary Material 1 and 2 [##UREF##4##18##, ##REF##33937821##19##]. The inclusion and exclusion criteria were as follows:</p>", "<title>Inclusion criteria</title>", "<p id=\"Par10\">Patients were enrolled if they satisfied all the following inclusion criteria: (1) were confirmed to have PTC after lobectomy or total thyroidectomy; (2) underwent CLND with a pathological examination; (3) the thyroid US examination was performed at our hospital within one month before the operation.</p>", "<title>Exclusion criteria</title>", "<p id=\"Par11\">(1) had other malignancies or distant metastases at diagnosis; (2) received preoperative head and neck therapies such as radiotherapy, chemotherapy, or radiofrequency ablation; (3) with missing data; (4) with poor image quality.</p>", "<p id=\"Par12\">After undergoing a rigorous inclusion and exclusion process, datasets of 613 patients treated in our clinical centres from March 2019 to July 2020 were included. The participant recruitment flow is shown in Fig. ##FIG##0##1##. The participants were randomly divided into training and independent test cohorts for further analysis.</p>", "<p id=\"Par13\">\n\n</p>", "<title>Acquisition and selection of clinical and ultrasound features</title>", "<p id=\"Par14\">The choice of US machine was not limited, and most data was obtained using devices such as Siemens Sequoia, Supersonic Aixplorer, and Toshiba Aplio 500, stored in the DICOM format. The risk factors for CLNM were identified by the following variables: gender, age, and US features of thyroid tumours following the C-TIRADS and ATA guidelines [##REF##26462967##7##, ##REF##32827126##20##]. These features encompassed tumour size, hypoechoic solid composition, multifocality, aspect ratio, posterior acoustic attenuation, tumour location, extrathyroidal extension (ETE), acoustic halo, microcalcification, and the internal tumour vascularity. Age was dichotomized at 55 years following the 8th American Joint Commission on Cancer staging system. In cases with multifocality, the largest nodule was chosen as the representative. The tumour vascularity was graded from 0 to 3 by colour Doppler flow imaging (CDFI) following the Adler standard [##REF##2238263##21##]. The US features were re-evaluated by two radiologists with four and seven years of experience in thyroid US diagnosis. Both radiologists were blinded to clinical information and pathological diagnosis. The agreement between them was assessed, and in case of any disagreement, a senior radiologist with over 20 years of experience made the final decision. Subsequently, multivariate logistic regression analysis and likelihood ratio tests for positive selection were used in the training cohort to screen for the above mentioned clinical and US features that can effectively differentiate the presence of CLNM.</p>", "<title>Evaluation of lymph node metastases by radiologists</title>", "<p id=\"Par15\">The preoperative examination of LNs was conducted on all patients by a team of five radiologists, comprising two senior radiologists with 15 and 17 years of experience, and three junior radiologists with 3, 5, and 6 years of experience, respectively. The diagnostic accuracy of the two groups of radiologists, differing in seniority, was determined by comparing the LNs status reported by US with the corresponding postoperative pathological results. Based on the ACR TI-RADS [##REF##28372962##22##], LNs exhibiting one or more suspicious US features (roundness, loss of the normal echogenic hilum, internal microcalcifications, cystic changes, hyperechogenicity, or presence of peripheral flow) were classified as US-reported CLNM.</p>", "<title>Region of interest segmentation and development of the hand-crafted radiomics model</title>", "<p id=\"Par16\">The manual segmentation of regions of interest (ROI) was independently performed using ITK-SNAP (version 3.8) by a radiologist with five years of experience, followed by another radiologist with seven years of experience reviewing the ROI and reaching a consensus. Before formally drawing ROIs, we randomly selected 30 images for consistency analysis, and the two radiologists have excellent consistency, with a dice coefficient of 0.946.</p>", "<p id=\"Par17\">Radiomic features were extracted using the open-source Python package “pyradiomics” (version 3.1.0) [##REF##29092951##23##]. A total of 783 features including 18 first-order statistics, 68 texture features, 9 shape features, 344 wavelet decompositions, and 344 Laplacian of Gaussian features were extracted from the US images by the delineated ROI. The definitions of each feature group are listed in Supplementary Material 3 S1. The least absolute shrinkage and selection operator (LASSO) logistic regression analysis method was employed to select the radiomics feature on the training dataset. The selected radiomics features are listed in Supplementary Material 3 S2. We followed a support vector machine (SVM) to establish the prediction model, with the regularization parameter and kernel type tuning conducted by 10-fold cross-validation in the training set. The LASSO and SVM were performed by the “scikit-learn” package (version 0.24.2).</p>", "<title>Development of the deep learning model</title>", "<p id=\"Par18\">A convolution neural network (CNN) was built to utilize deep features of US images to predict central lymph node metastasis. The US images of the patient in the training cohort were randomly divided into training and validation datasets with a ratio of 2:1. These images were cropped based on the delineated ROIs, resized to 224 × 224, and then normalized the grayscale to [0, 1] in the pre-processing stage. To improve the generalization performance of the model, we developed the model using the transfer learning technique. The constructed CNN was initialized by the pre-trained parameters on ImageNet-21k [##UREF##5##24##]. Supplementary Material 3 S3 shows the result of four tested backbones. The best-performing ResNet50 was adopted to develop the prediction model. Following the tricks proposed in big data transfer [##UREF##6##25##], we used group normalization and weight standardization instead of batch normalization in the ResNet50. The detailed structure of the network is presented in Supplementary Material 3 S4. During the training stage, we adopted the cross-entropy as the loss function, Adam optimizer with the initial learning rate of 0.003, and the learning rate multiplied by 0.1 every 100 epochs with the total epoch number: 500. Image augmentation was also used to alleviate overfitting. The images were randomly cropped, horizontally flipped and rotated in the range of [-20, 20] degrees.</p>", "<title>Development and explanation of the integrated prediction model</title>", "<p id=\"Par19\">The integrated prediction model mainly includes three branches, the deep learning branch, the hand-crafted radiomics branch, and the clinical and US feature branch. The flowchart outlining the integrated prediction model can be seen in Fig. ##FIG##1##2##. The deep learning branch was used to obtain the score value predicted by the ResNet50 with frozen parameters. In the hand-crafted radiomics branch, we adopted the predicted malignancy probability of the hand-crafted radiomics model for further integration. The already filtered clinical and US features were then used to create the final prediction model along with the predicted malignancy probabilities from the hand-crafted radiomics model and the deep learning model. We also employed a multivariable logistic regression for the integrated prediction model, with 10-fold cross-validation in the training set. To assess the performance of the integrated model, the performance of the model was compared with that of the hand-crafted radiomics model, DL model, and junior and senior radiologists on the independent test set.</p>", "<p id=\"Par20\">In addition, the visualized explanation methods named SHapley Additive exPlanations (SHAP) plot and Gradient-weighted Class Activation Mapping (Grad-CAM) were applied to improve the clinical explanation of our model. We used Grad-CAM to extract the areas of interest and generate saliency maps for the DL model, while the SHAP plot was used to calculate the contribution value of each variable to the integrated model. These visualization methods aim to improve the clinical understanding and explanation of our model’s predictions.</p>", "<p id=\"Par21\">\n\n</p>", "<title>Statistical analysis</title>", "<p id=\"Par22\">Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 20.0 (IBM Corp.).</p>", "<p id=\"Par23\">Categorical variables are presented as numbers and percentages and analyzed using the chi-squared or Fisher’s exact test. The Mann-Whitney U test analyzed continuous variables, and Kappa statistics analyzed the inter-observer agreement. The performance of predictive models was evaluated by the receiver operating characteristic (ROC) curve analysis and the area under curve (AUC). DeLong’s test compared the combined prediction model and other methods in predicting CLNM. Other performance measures, including accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were also assessed. The two-sided statistical significance was set at 0.05.</p>" ]
[ "<title>Results</title>", "<title>Patient demographics and feature selection</title>", "<p id=\"Par24\">Patient characteristics and US features of the thyroid nodules in the training and test cohorts were shown in Table ##TAB##0##1##. The training cohort included 460 patients (136 males, 324 females) with a mean age of 40.70 ± 11.16 years (range, 11–73 years). The independent test cohort included 153 patients (45 males and 108 females) with a mean age of 42.59 ± 11.33 years (range, 13–69 years). These two datasets were comparable as there were no significant differences. The inter-observer consistency was satisfactory, with Kappa coefficients between 0.82 and 0.92 (Supplementary Material 3 S5).</p>", "<p id=\"Par25\">\n\n</p>", "<p id=\"Par26\">To better understand the relationship between CLNM and clinical and US features, a multivariate analysis was performed in the training cohort. The results showed that age, sex, tumour size, multifocality, and ETE were independent risk factors for CLNM (Table ##TAB##1##2##).</p>", "<p id=\"Par27\">\n\n</p>", "<title>Diagnostic performance of CLNM-predicting model</title>", "<p id=\"Par28\">We successfully built a hand-crafted radiomics model, a DL model, and an integrated model. In the testing set, our result showed that the DL model exhibited higher sensitivity (75.00% vs. 52.63%) but slightly lower specificity (71.43% vs. 74.03%) compared to the hand-crafted radiomics model (Table ##TAB##2##3##). By combining hand-crafted radiomics, DL and clinical features, the integrated model showed good predictive efficacy (the specificity and sensitivity were 81.82% and 72.37%, and the PPV and NPV were 79.71% and 75.00%). Meanwhile, the integrated model had most outstanding performance with the AUC of 0.841, which was superior to the hand-crafted radiomics model (0.841 vs. 0.706, <italic>p</italic> &lt; 0.001) as well as the DL model (0.841 vs. 0.819, <italic>p</italic> = 0.26) (Fig. ##FIG##2##3##). These findings highlight the superior performance of the integrated model over the individual models.</p>", "<p id=\"Par29\">\n\n</p>", "<p id=\"Par30\">\n\n</p>", "<title>Performance comparison among integrated model and radiologists</title>", "<p id=\"Par31\">The results indicated that the integrated model exhibited a significantly higher AUC compared to both junior and senior radiologists (0.841 vs. 0.561 and 0.640, <italic>p</italic> &lt; 0.001). In comparison to the junior and senior radiologists, the integrated model demonstrated a decrease in the missed CLNM rate by 30.26% and 17.11% respectively. Additionally, the rate of unnecessary CLND decreased by 11.69% and 9.09%. A detailed comparison of the integrated model and radiologists were summarized in Table ##TAB##3##4##. These results indicated that integrated model could improve the efficiency of metastatic LNs detection and reduce the rate of unnecessary CLND.</p>", "<p id=\"Par32\">\n\n</p>", "<title>Explanation of the integrated model</title>", "<p id=\"Par33\">To better compensate for the problem of “cognitive opacity” of AI models, we utilized SHAP plots to illustrate the contribution of each key parameter in the integrated model. The result showed that the DL model contributed the most to CLNM prediction, followed by ETE, tumour size, age, gender, and multifocality. The hand-crafted radiomics model played a relatively minor role within the integrated model (Fig. ##FIG##3##4##). In Fig. ##FIG##4##5##, two representative examples were presented to demonstrate how each key parameter contributed to the personalized decision-making process in the integrated model. Furthermore, we employed Grad-CAM to identify the areas of interest for the DL model. Figure ##FIG##5##6## showcased several representative cases, indicating that the areas of interest were predominantly located around the thyroid capsule, consistent with the radiologists focusing on areas significantly associated with CLNM.</p>", "<p id=\"Par34\">\n\n</p>", "<p id=\"Par35\">\n\n</p>", "<p id=\"Par36\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par37\">In this study, we developed an integrated model for predicting CLNM that incorporated deep learning, hand-crafted radiomics, and clinical and US features. Our integrated model outperformed models based solely on hand-crafted radiomics or DL features, as well as junior and senior radiologists. The integrated model decreased the rate of missed CLNM and unnecessary CLND, thus improving preoperative CLND decision-making. Furthermore, the integrated model’s visual explanation aligned with radiologists’ typical judgments, which contributed to the acceptance of AI-assisted US diagnosis.</p>", "<p id=\"Par38\">Currently, one of the primary objectives of US in patients with PTC is to provide preoperative guidance for CLND by detecting the presence of CLNM. However, the presence of air interference in the trachea and esophagus, along with the small size of LNs, leads to unsatisfactory diagnostic accuracy [##REF##21344423##26##]. Encouragingly, hand-crafted radiomics and DL methods can effectively reveal information that is imperceptible to the human eye, thereby enhancing diagnostic capabilities. Previous studies focusing solely on either hand-crafted radiomics or DL methods in diagnosing CLNM have yielded favourable results [##REF##32076595##27##, ##REF##32038495##28##]. However, our findings indicated limitations in the diagnostic efficacy of standalone DL and hand-crafted radiomics models. The DL model exhibited higher sensitivity, while the hand-crafted radiomics model showed higher specificity, indicating a distinction between traditional image features extracted by hand-crafted radiomics and the high-dimensional features extracted by DL. These observations motivated us to develop an integrated model that combines both types of features, resulting in superior performance compared to models based solely on hand-crafted radiomics or DL features. Furthermore, when compared with junior and senior radiologists, the integrated model significantly reduced the missed rate of CLNM by 30.26% and 17.11%, respectively, and decreased the rate of unnecessary CLND by 11.69% and 9.09%. Our findings indicate that the utilization of this model in clinical practice can be beneficial for PTC patients. Radiologists also can benefit from the integrated model, as it can serve as a valuable second opinion during the diagnosis of CLNM, assisting them in making more precise judgments and boosting their diagnostic confidence.</p>", "<p id=\"Par39\">Consistent with the results of previous studies [##REF##32144248##29##], we conducted a screening of clinical and US factors associated with CLNM during routine diagnostic work. These factors were then integrated into our AI model, resulting in improved efficacy. Upon further analysis using the SHAP plot, the integrated model demonstrated that the clinical and US factors provided valuable additional information. Among these crucial factors, ETE had the highest contribution, indicating that tumour cells could breach the thyroid capsule and enter the lymphatic system, leading to the development of metastatic LNs [##UREF##7##30##]. Additionally, tumour size, gender, age, and multifocality were also found to be associated with CLNM [##REF##34377246##31##]. Interestingly, our findings revealed that the integrated model focused primarily on the thyroid capsule, which aligns with the areas of emphasis for radiologists when assessing CLNM. These results suggest that the clinical and US factors incorporated into the integrated model, as well as the regions of the model’s interest, are generally consistent with radiologists’ judgments, thereby providing the model with some clinical explainability. Overall, the visual explanation provided by the integrated model not only aligns with radiologists’ usual judgments but also the integrated model demonstrates higher diagnostic efficacy compared to radiologists. This enhances the clinical acceptance of AI-assisted US diagnosis among radiologists.</p>", "<p id=\"Par40\">In contrast to the integrated models derived from CT or MRI images, where hand-crafted radiomics features played a prominent role [##UREF##8##32##, ##UREF##9##33##], our findings indicated that the contribution of hand-crafted radiomics features to our integrated model was relatively modest. This discrepancy may arise from the fact that some of the features extracted from US images through hand-crafted radiomics, such as shape, grayscale, and texture, can also be obtained through DL methods. Additionally, during US imaging, noise can be generated due to variations in signal intensity, which can degrade image quality and affect the extraction of certain hand-crafted radiomics features. Consequently, these circumstances may account for the relatively limited contribution of hand-crafted radiomics to the model.</p>", "<p id=\"Par41\">Several limitations should be acknowledged in this study. Firstly, due to the interference of anatomical structures and the small size of the central LNs, US images of central LNs were not included in the analysis. Secondly, although the incorporation of clinical and US features enhances the acceptance of AI-assisted US diagnosis by radiologists, the interpretability of features learned by the DL and radiomics model remains limited. Future advancements in the field of interpretable AI will inspire further exploration. Finally, the results obtained may be influenced by the limited amount of data utilized. Further investigation of the value of integrated models in prospective studies with larger sample sizes is warranted.</p>", "<p id=\"Par42\">In conclusion, the integrated model demonstrated superior performance compared to models relying solely on hand-crafted radiomics or DL features, exceeding the diagnostic capabilities of both junior and senior radiologists. The application of integrated models can significantly reduce missed CLNMs and unnecessary CLNDs along with increasing radiologists’ acceptance of AI-assisted US diagnoses.</p>" ]
[]
[ "<title>Objective</title>", "<p id=\"Par1\">To evaluate the value of an integrated model incorporating deep learning (DL), hand-crafted radiomics and clinical and US imaging features for diagnosing central lymph node metastasis (CLNM) in patients with papillary thyroid cancer (PTC).</p>", "<title>Methods</title>", "<p id=\"Par2\">This retrospective study reviewed 613 patients with clinicopathologically confirmed PTC from two institutions. The DL model and hand-crafted radiomics model were developed using primary lesion images and then integrated with clinical and US features selected by multivariate analysis to generate an integrated model. The performance was compared with junior and senior radiologists on the independent test set. SHapley Additive exPlanations (SHAP) plot and Gradient-weighted Class Activation Mapping (Grad-CAM) were used for the visualized explanation of the model.</p>", "<title>Results</title>", "<p id=\"Par3\">The integrated model yielded the best performance with an AUC of 0.841. surpassing that of the hand-crafted radiomics model (0.706, <italic>p</italic> &lt; 0.001) and the DL model (0.819, <italic>p</italic> = 0.26). Compared to junior and senior radiologists, the integrated model reduced the missed CLNM rate from 57.89% and 44.74–27.63%, and decreased the rate of unnecessary central lymph node dissection (CLND) from 29.87% and 27.27–18.18%, respectively. SHAP analysis revealed that the DL features played a primary role in the diagnosis of CLNM, while clinical and US features (such as extrathyroidal extension, tumour size, age, gender, and multifocality) provided additional support. Grad-CAM indicated that the model exhibited a stronger focus on thyroid capsule in patients with CLNM.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Integrated model can effectively decrease the incidence of missed CLNM and unnecessary CLND. The application of the integrated model can help improve the acceptance of AI-assisted US diagnosis among radiologists.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12885-024-11838-1.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>YJ and YG were contributed to the conception and design of the study. WJ organized the database. WY and YY were responsible for the software and statistics. YG and WZ took charge of the writing of this paper. ST, YS, and TL to data collection. ZT, LY for data analysis. All authors have read and approved the manuscript.</p>", "<title>Funding</title>", "<p>This study was funded by the National Natural Science Foundation of China (Grant Nos. 82271998 and 82071949).</p>", "<title>Data availability</title>", "<p>The codes used during the current study can be accessed at <ext-link ext-link-type=\"uri\" xlink:href=\"https://github.com/yytangxiaoyuan/metastasis_predict_model/tree/main\">https://github.com/yytangxiaoyuan/metastasis_predict_model/tree/main</ext-link>. Other analyzed datasets from the current study are not publicly available because the data contain information that may compromise patients, but are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par43\">The study has been performed in accordance with the Declaration of Helsinki and was approved by The Ethics Committees of Nanfang Hospital of South Medical University and the First People’s Hospital of Foshan (NFEC-202008-K6). The requirement for informed consent was waived by the Ethics Committee of Nanfang Hospital of South Medical University because of the retrospective nature of the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par44\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par45\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow Chart of participants recruitment. CLND, central lymph node dissection; PTC, papillary thyroid carcinoma</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The flow chart of the artificial intelligence integrated model</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Diagnostic performance comparison among artificial intelligence models and radiologists in the independent testing cohort</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>The SHAP plot reflected the contribution of each parameter to diagnose central lymph node metastasis in the integrated model</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Two representative cases for the real output of the integrated model. (<bold>a</bold>). A 31-year-old female suffering from PTC with CLNM. The hand-crafted radiomics model outputs a probability of 48.30% for CLNM. The deep learning model outputs a probability of 81.77%, and the integrated model fuses the risk factors and gives a final probability of 94.32%. The result is inconsistent with the radiologist’s diagnosis, so the radiologist is recommended to conduct a second scan and then consult the classification provided by the integrated model. (<bold>b</bold>) A 28-year-old female suffering from PTC without CLNM. The hand-crafted radiomics model represented a probability of 46.20% for CLNM. The deep learning model and the integrated model output probabilities of 15.10% and 5.91%, respectively. The result is consistent with the diagnosis of the radiologist. CLNM, central lymph node metastasis; ETE, extrathyroidal extension; PTC, papillary thyroid carcinoma</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Representative examples of the saliency maps. (<bold>A</bold>) Saliency maps of one CLNM case evaluated by integrated model. The red colour highlighted the activation region associated with the thyroid capsule, consistent with the radiologists’ concentration on areas significantly associated with CLNM. (<bold>B</bold>) Saliency maps of a case without CLNM evaluated by integrated model. CLNM, central lymph node metastasis</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Demographic comparison between training and independent test cohorts</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Characteristics<break/>and US features</th><th align=\"left\">Training cohort<break/>(<italic>n</italic> = 460)</th><th align=\"left\">Independent test cohort<break/>(<italic>n</italic> = 153)</th><th align=\"left\">p value</th></tr></thead><tbody><tr><td align=\"left\">Size (mean ± SD)</td><td align=\"left\">1.24 ± 0.92</td><td align=\"left\">1.16 ± 0.69</td><td char=\".\" align=\"char\">0.433</td></tr><tr><td align=\"left\">\n<bold>Sex</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.971</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">136(75.1%)</td><td align=\"left\">45(24.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Female</td><td align=\"left\">324(75.0%)</td><td align=\"left\">108(25.0%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Age</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.484</td></tr><tr><td align=\"left\">≤ 55</td><td align=\"left\">415(75.5%)</td><td align=\"left\">135(24.5%)</td><td align=\"left\"/></tr><tr><td align=\"left\">≤55</td><td align=\"left\">45(71.4%)</td><td align=\"left\">18(28.6%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Tumour location</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.711</td></tr><tr><td align=\"left\">Right lobe</td><td align=\"left\">228(73.8%)</td><td align=\"left\">81(26.2%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Left lobe</td><td align=\"left\">213(76.6%)</td><td align=\"left\">65(23.4%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Isthmus</td><td align=\"left\">19(73.1%)</td><td align=\"left\">7(26.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Tumour position</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.095</td></tr><tr><td align=\"left\">Upper</td><td align=\"left\">152(81.7%)</td><td align=\"left\">34(18.3%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Mid</td><td align=\"left\">164(71.9%)</td><td align=\"left\">64(28.1%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Lower</td><td align=\"left\">125(72.3%)</td><td align=\"left\">48(27.7%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Isthmus</td><td align=\"left\">19(73.1%)</td><td align=\"left\">7(26.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Solid composition with hypoechoic echo</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.110</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">417(74.2%)</td><td align=\"left\">145(25.8%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">43(84.3%)</td><td align=\"left\">8(15.7%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Tumour multifocality</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.769</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">83(76.1%)</td><td align=\"left\">26(23.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">377(74.8%)</td><td align=\"left\">127(25.2%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Aspect ratio</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.198</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">201(726%)</td><td align=\"left\">76(27.4%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">259(77.1%)</td><td align=\"left\">77(22.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Microcalcification</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.769</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">360(75.3%)</td><td align=\"left\">118(24.7%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">100(74.1%)</td><td align=\"left\">35(25.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Tumour vascularity</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.320</td></tr><tr><td align=\"left\">0–1</td><td align=\"left\">401(74.4%)</td><td align=\"left\">138(25.6%)</td><td align=\"left\"/></tr><tr><td align=\"left\">2–3</td><td align=\"left\">59(79.7%)</td><td align=\"left\">15(20.3%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Acoustic halo</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.804</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">42(73.7%)</td><td align=\"left\">15(26.3%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">418(75.2%)</td><td align=\"left\">138(24.8%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>ETE</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.947</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">119(74.8%)</td><td align=\"left\">40(25.2%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">341(75.1%)</td><td align=\"left\">113(24.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Posterior acoustic attenuation</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.282</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">67(79.8%)</td><td align=\"left\">17(20.2%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">393(74.3%)</td><td align=\"left\">136(25.7%)</td><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>CLNM in the pathology outcomes</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.982</td></tr><tr><td align=\"left\">Present</td><td align=\"left\">228 (75.0%)</td><td align=\"left\">76 (25.0%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Absent</td><td align=\"left\">232 (75.1%)</td><td align=\"left\">77 (24.9%)</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Independent risk factors after multiple logistic regression analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Ultrasound features</th><th align=\"left\">β</th><th align=\"left\">Odds ratio (95% CI)</th><th align=\"left\">p value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"4\">\n<bold>Prediction of CLNM status</bold>\n</td></tr><tr><td align=\"left\">Size</td><td char=\".\" align=\"char\">0.533</td><td char=\".\" align=\"char\">1.704 (1.225–2.370)</td><td char=\".\" align=\"char\">0.002</td></tr><tr><td align=\"left\">Age</td><td char=\".\" align=\"char\">-1.301</td><td char=\".\" align=\"char\">0.272 (0.125–0.595)</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\">Sex</td><td char=\".\" align=\"char\">-0.598</td><td char=\".\" align=\"char\">0.550 (0.353–0.857)</td><td char=\".\" align=\"char\">0.008</td></tr><tr><td align=\"left\">Tumour multifocality</td><td char=\".\" align=\"char\">0.738</td><td char=\".\" align=\"char\">2.092 (1.224–3.577)</td><td char=\".\" align=\"char\">0.007</td></tr><tr><td align=\"left\">ETE</td><td char=\".\" align=\"char\">1.418</td><td char=\".\" align=\"char\">4.130 (2.434–7.008)</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Performance comparison of different AI models in prediction of CLNM</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Test cohort</th><th align=\"left\">AUC</th><th align=\"left\">95%CI</th><th align=\"left\">ACC (%)</th><th align=\"left\">SEN (%)</th><th align=\"left\">SPE (%)</th><th align=\"left\">PPV (%)</th><th align=\"left\">NPV (%)</th></tr></thead><tbody><tr><td align=\"left\">ResNet</td><td char=\".\" align=\"char\">0.8189</td><td char=\".\" align=\"char\">[0.7542, 0.8835]</td><td char=\".\" align=\"char\">73.20</td><td char=\".\" align=\"char\">75.00</td><td char=\".\" align=\"char\">71.43</td><td char=\".\" align=\"char\">72.15</td><td char=\".\" align=\"char\">74.32</td></tr><tr><td align=\"left\">SVM</td><td char=\".\" align=\"char\">0.7061*</td><td char=\".\" align=\"char\">[0.6246, 0.7875]</td><td char=\".\" align=\"char\">63.40</td><td char=\".\" align=\"char\">52.63</td><td char=\".\" align=\"char\">74.03</td><td char=\".\" align=\"char\">66.67</td><td char=\".\" align=\"char\">61.29</td></tr><tr><td align=\"left\">Integrated Model</td><td char=\".\" align=\"char\">0.8406</td><td char=\".\" align=\"char\">[0.7792, 0.9020]</td><td char=\".\" align=\"char\">77.12</td><td char=\".\" align=\"char\">72.37</td><td char=\".\" align=\"char\">81.82</td><td char=\".\" align=\"char\">79.71</td><td char=\".\" align=\"char\">75.00</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Performance comparison of radiologists and integrated model in prediction of CLNM</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Test cohort</th><th align=\"left\">AUC</th><th align=\"left\">95%CI</th><th align=\"left\">Undetected CLNM (%)</th><th align=\"left\">Unnecessary CLND (%)</th><th align=\"left\">ACC (%)</th><th align=\"left\">SEN (%)</th><th align=\"left\">SPE (%)</th><th align=\"left\">PPV (%)</th><th align=\"left\">NPV (%)</th></tr></thead><tbody><tr><td align=\"left\">Junior Radiologists</td><td char=\".\" align=\"char\">0.5612*</td><td char=\".\" align=\"char\">[0.4852, 0.6371]</td><td align=\"left\"><p>57.89</p><p>(44/76)</p></td><td align=\"left\"><p>29.87</p><p>(23/77)</p></td><td char=\".\" align=\"char\">56.21</td><td char=\".\" align=\"char\">42.11</td><td char=\".\" align=\"char\">70.13</td><td char=\".\" align=\"char\">58.18</td><td char=\".\" align=\"char\">55.10</td></tr><tr><td align=\"left\">Senior Radiologists</td><td char=\".\" align=\"char\">0.6400*</td><td char=\".\" align=\"char\">[0.5646, 0.7153]</td><td align=\"left\"><p>44.74</p><p>(34/76)</p></td><td align=\"left\"><p>27.27</p><p>(21/77)</p></td><td char=\".\" align=\"char\">64.05</td><td char=\".\" align=\"char\">55.26</td><td char=\".\" align=\"char\">72.73</td><td char=\".\" align=\"char\">66.67</td><td char=\".\" align=\"char\">62.22</td></tr><tr><td align=\"left\">Integrated Model</td><td char=\".\" align=\"char\">0.8406</td><td char=\".\" align=\"char\">[0.7792, 0.9020]</td><td align=\"left\"><p>27.63</p><p>(21/76)</p></td><td align=\"left\"><p>18.18</p><p>(14/77)</p></td><td char=\".\" align=\"char\">77.12</td><td char=\".\" align=\"char\">72.37</td><td char=\".\" align=\"char\">81.82</td><td char=\".\" align=\"char\">79.71</td><td char=\".\" align=\"char\">75.00</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>Abbreviations</italic>: US, ultrasound; ETE, extrathyroidal extension; CLNM, central lymph node metastasis</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Abbreviations</italic>: CLNM, central lymph node metastasis; US, ultrasound; CI: confidence interval; ETE, extrathyroidal extension</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Abbreviations</italic>: CLNM, central lymph node metastasis; ACC, accuracy; SEN, sensitivity; SPE, specificity; PPV, positive predictive value; NPV, negative predictive value; AUC, area under the receiver operating curve; CI, confidence interval *Compared with integrated model, <italic>p</italic> &lt; 0.05</p></table-wrap-foot>", "<table-wrap-foot><p>Abbreviations: CLNM, central lymph node metastasis; CLND, central lymph node dissection; ACC, accuracy; SEN, sensitivity; SPE, specificity; PPV, positive predictive value; NPV, negative predictive value; AUC, area under the receiver operating curve; CI, confidence interval *Compared with integrated model, <italic>p</italic> &lt; 0.05</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Yang Gao, Weizhen Wang and Yuan Yang contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12885_2024_11838_Fig1_HTML\" id=\"d32e365\"/>", "<graphic xlink:href=\"12885_2024_11838_Fig2_HTML\" id=\"d32e423\"/>", "<graphic xlink:href=\"12885_2024_11838_Fig3_HTML\" id=\"d32e1072\"/>", "<graphic xlink:href=\"12885_2024_11838_Fig4_HTML\" id=\"d32e1223\"/>", "<graphic xlink:href=\"12885_2024_11838_Fig5_HTML\" id=\"d32e1240\"/>", "<graphic xlink:href=\"12885_2024_11838_Fig6_HTML\" id=\"d32e1257\"/>" ]
[ "<media xlink:href=\"12885_2024_11838_MOESM1_ESM.pdf\"><caption><p><bold>Supplementary Material 1:</bold> CheckList for Artificial Intelligence in Medical Imaging (CLAIM)</p></caption></media>", "<media xlink:href=\"12885_2024_11838_MOESM2_ESM.pdf\"><caption><p><bold>Supplementary Material 2:</bold> CheckList for EvaluAtion of Radiomics research (CLEAR)</p></caption></media>", "<media xlink:href=\"12885_2024_11838_MOESM3_ESM.docx\"><caption><p><bold>Supplementary Material 3:</bold> S1. Definition of extracted radiomic features. S2. Name of the extracted radiomics feature. S3. Performance comparison of the deep learning algorithms in the training and test datasets. S4. Structure of the ResNet50 used in the paper. S5. Intra-operator ultrasound feature measurement consistency</p></caption></media>" ]
[{"label": ["4."], "surname": ["Medas", "Canu", "Cappellacci", "Anedda", "Conzo", "Erdas"], "given-names": ["F", "GL", "F", "G", "G", "E"], "article-title": ["Prophylactic central lymph node dissection improves disease-free survival in patients with intermediate and high risk differentiated thyroid carcinoma: a retrospective analysis on 399 patients"], "source": ["Cancers (Basel)"], "year": ["2020"], "volume": ["12"], "fpage": ["1"], "lpage": ["12"], "pub-id": ["10.3390/cancers12061658"]}, {"label": ["6."], "collab": ["Chinese Society of Endocrinology; Thyroid and Metabolism Surgery Group of the Chinese Society of Surgery;Chinese Society of Nuclear Medicine"], "article-title": ["Chinese Society of Ultrasound in Medicine. Guidelines for the diagnosis and management of thyroid nodules and differentiated thyroid cancer (second edition)"], "source": ["Chin J Endocrinol Metab"], "year": ["2023"], "volume": ["39"], "fpage": ["181"], "lpage": ["226"]}, {"label": ["11."], "surname": ["Liu", "Wang", "Yang", "Lei", "Liu", "Li"], "given-names": ["S", "Y", "X", "B", "L", "SX"], "source": ["Deep Learn Med Ultrasound Analysis: Rev Eng"], "year": ["2019"], "volume": ["5"], "fpage": ["261"], "lpage": ["75"]}, {"label": ["14."], "surname": ["Wang", "Hou", "Li", "Dong", "Tang"], "given-names": ["S", "Y", "Z", "J", "C"], "article-title": ["Combining ConvNets with hand-crafted features for action recognition based on an HMM-SVM classifier"], "source": ["Multimed Tools Appl"], "year": ["2018"], "volume": ["77"], "fpage": ["18983"], "lpage": ["98"], "pub-id": ["10.1007/s11042-017-5335-0"]}, {"label": ["18."], "mixed-citation": ["Kocak B, Baessler B, Bakas S, Cuocolo R, Fedorov A, Maier-Hein L et al. CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII. Insights Imaging. 2023;14."]}, {"label": ["24."], "mixed-citation": ["Deng J, Dong W, Socher R, Li L-J, Li K, Fei-Fei L. ImageNet: A large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2009. p. 248\u201355."]}, {"label": ["25."], "mixed-citation": ["Kolesnikov A, Beyer L, Zhai X, Puigcerver J, Yung J, Gelly S et al. Big Transfer (BiT): General Visual Representation Learning. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics). 2020;12350 LNCS:491\u2013507."]}, {"label": ["30."], "surname": ["Zou", "Shi", "Liu", "Cui", "Yang", "Liu"], "given-names": ["Y", "Y", "J", "G", "Z", "M"], "article-title": ["A comparative analysis of six machine learning models based on Ultrasound to Distinguish the Possibility of Central Cervical Lymph Node Metastasis in patients with papillary thyroid carcinoma"], "source": ["Front Oncol"], "year": ["2021"], "volume": ["11"], "fpage": ["1"], "lpage": ["10"], "pub-id": ["10.3389/fonc.2021.656127"]}, {"label": ["32."], "surname": ["Paul", "Hawkins", "Schabath", "Gillies", "Hall", "Goldgof"], "given-names": ["R", "SH", "MB", "RJ", "LO", "DB"], "article-title": ["Predicting malignant nodules by fusing deep features with classical radiomics features"], "source": ["J Med Imaging"], "year": ["2018"], "volume": ["5"], "fpage": ["1"], "pub-id": ["10.1117/1.JMI.5.1.011021"]}, {"label": ["33."], "mixed-citation": ["Hu X, Gong J, Zhou W, Li H, Wang S, Wei M et al. Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features. Phys Med Biol. 2021;66."]}]
{ "acronym": [ "AI", "AUC", "CLND", "CLNM", "DL", "Grad-CAM", "LN", "PTC", "ROI", "SHAP", "SVM" ], "definition": [ "Artificial intelligence", "Area under curve", "Central lymph node dissection", "Central lymph node metastases", "Deep learning", "Gradient-weighted Class Activation Mapping", "Lymph node", "Papillary thyroid carcinoma", "Region of interest", "SHapley Additive exPlanation", "Support vector machine" ] }
33
CC BY
no
2024-01-14 23:43:45
BMC Cancer. 2024 Jan 12; 24:69
oa_package/3f/91/PMC10787418.tar.gz
PMC10787419
38216922
[ "<title>Background</title>", "<p id=\"Par5\">The number of people worldwide living with dementia in 2020 was more than 55 million people and numbers are expected to increase to 78 million in 2030 and 139 million in 2050 [##UREF##0##1##]. In South Korea (henceforth Korea), analysis of big data from the National Health Insurance Service (NHIS) for dementia and hospital utilization for dementia show that the prevalence of dementia has increased significantly in recent years, notably among the elderly population (aged ≥65 years) [##REF##33835746##2##–##UREF##1##4##]. In 2021, the prevalence of dementia in Korea was estimated to be more than 786,000 with numbers expected to continue to rise over the next two decades or more [##REF##35508924##5##]. The health-economic burden of dementia in Korea is substantial and was estimated at US$6,957 per capita, with indirect costs accounting for 48.0% of the total burden, mainly from loss of productivity for family members and caregivers [##REF##34645415##6##]. The total annual national dementia management cost for dementia patients in 2021 (approx. US$138 billion) accounted for about 0.9% of Korea’s GDP and, during a 6-year period from 2017, the cost increased by 31.9% [##UREF##2##7##].</p>", "<p id=\"Par6\">In Korea, AD medication is available from hospitals and clinics. Data from 2021 for people with dementia in Korea (approx. 1.66 million), show that most treatments received were as outpatients (52.3%), followed by from a pharmacy (35.4%) or as inpatients (12.3%). Many people with dementia (<italic>n</italic> = 382,155) accessed long-term care insurance services for the elderly in 2021, with over two-thirds choosing to receive care at home (67.5%) rather than in care facilities [##UREF##2##7##].</p>", "<p id=\"Par7\">The Korean government has been actively involved in plans to combat dementia, implementing a series of national strategies and plans, beginning in 2008 when the first national dementia plan was announced. Both the first and second national dementia plans, the latter being announced in 2012, focused primarily on promoting early detection and diagnosis of dementia by healthcare providers. The Dementia Management Act of 2012 established a statutory basis for the organization of national dementia plans. The third national dementia plan, released in 2016, focused on the community-based prevention and management of dementia and the fourth, released in 2020, deals with the prevention, early detection, and early post-diagnosis management of Alzheimer’s disease (AD) [##UREF##3##8##, ##REF##36218064##9##].</p>", "<p id=\"Par8\">Mandatory long-term care insurance (LTCI) was introduced in Korea in 2008 and eligibility was extended in July 2014 to people with dementia (including mild dementia). Prior to the 2014 revision, people with cognitive disorders but without severe physical disability were not eligible for LTCI [##UREF##3##8##, ##REF##31514668##10##]. The revision enabled access to appropriate long-term care for many dementia patients (including mild AD patients) and their families including the cognitive function training program and home nursing services [##REF##31268493##11##]. National policies continue to play a vital role in dementia care for the elderly, especially those with low income. These policies are essential for supporting the treatment of dementia including medications for AD and dementia.</p>", "<p id=\"Par9\">This study aimed to investigate changes in treatment patterns for AD and assessed their effectiveness during two consecutive 3-year periods (July 2011 – June 2014 and July 2014 – June 2017) which spanned revision of the LTCI system regarding eligibility for dementia patients, in July 2014.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par10\">The multicenter, retrospective, observational CAPTAIN (<underline>C</underline>hange of treatment patterns for newly diagnosed <underline>A</underline>lzheimer’s Disease <underline>P</underline>a<underline>t</underline>ients <underline>A</underline>ccording to Korean <underline>N</underline>ational Policy [Long <underline>T</underline>erm Care <underline>I</underline>nsurance] for dementia) study of patients with newly diagnosed AD analyzed electronic medical records (EMRs) from 17 general hospitals across Korea between July 2011 and June 2017. A complete list of all study sites and corresponding Institutional Review Boards (IRBs) that reviewed and approved the study protocol is provided in Supplementary Table ##SUPPL##0##1##. Subjects were categorized into two cohorts based on the time of AD diagnosis: from 1 July 2011 to 30 June 2014 (Cohort 1) and from 1 July 2014 to 30 June 2017 (Cohort 2).</p>", "<title>Variables</title>", "<p id=\"Par11\">Data retrieved from patient EMRs included age, highest attained educational level, past medical history including comorbidities defined by MedDRA v24.1 System Organ Class (SOC) and Preferred Term (PT), AD-related medication history, Mini-Mental State Examination (MMSE) score [##REF##1512391##12##], Clinical Dementia Rating (CDR) [##REF##9447441##13##], and Global Deterioration Scale (GDS) [##REF##7114305##14##].</p>", "<title>Inclusion and exclusion criteria</title>", "<p id=\"Par12\">Inclusion criteria were patients who were newly diagnosed with AD between 1 July 2011 and 30 June 2017, attended a general hospital as an outpatient, and started acetylcholinesterase inhibitor (AChEI) or memantine administration during this period. Patients were required to have a verifiable MMSE score within 6 months prior to AD diagnosis or the start of initial treatment.</p>", "<p id=\"Par13\">Exclusion criteria were patients with no records available for MMSE, CDR, and/or GDS between 1 July 2011 and 30 June 2017, and/or with a medication history of AChEI or memantine treatment prior to AD diagnosis.</p>", "<title>Objectives</title>", "<p id=\"Par14\">The primary objective of this study was to compare MMSE scores between cohorts at the time of AD diagnosis or start of initial treatment. Secondary objectives were comparisons between cohorts of changes in MMSE scores after 1 year’s treatment, initial treatment medication and reasons for the discontinuation or change (add-on, switching) of treatment, and time from initial treatment initiation to diagnosis of depression or prescription of antidepressants.</p>", "<title>Statistical analyses</title>", "<p id=\"Par15\">Continuous variables were summarized by mean, standard deviation (SD), median and range; and categorical variables by number and percentage. Statistical comparisons were made using Wilcoxon rank-sum, Chi-square or Fisher's exact tests except for Kaplan-Meier analyses which used log-rank tests. The significance level was set at 0.05 (two sided). All statistical analyses were conducted using SAS version 9.4.</p>" ]
[ "<title>Results</title>", "<p id=\"Par16\">In total, 3,997 subjects were enrolled in the study and there were no exclusions. Based on their time of diagnosis, subjects were divided into Cohort 1 (July 2011 – June 2014; <italic>n</italic> = 1,998) and Cohort 2 (July 2014 – June 2017; <italic>n</italic> = 1,999). Subjects were mostly female (66.4%) with a mean age of 84.4 years. Subjects in Cohort 1 were significantly older than those in Cohort 2 (mean age 84.9 <italic>vs</italic> 84.0 years; <italic>P</italic> &lt; 0.0001). By age category, Cohort 1 had a lower proportion of subjects in the ≥70 to &lt;80 years (19.3% <italic>vs</italic> 22.4%) and ≥80 to &lt;90 years (46.2% <italic>vs</italic> 51.6%) age groups, but a higher proportion of subjects in the ≥90 years age group (30.2% <italic>vs</italic> 22.3%). The highest educational level attained was significantly different between cohorts (<italic>P</italic> &lt; 0.0001). Approximately three quarters of subjects (75.7%) had one or more comorbidities. By PT, the most common comorbidities were hypertension (45.5%, <italic>n</italic> = 1,817) followed by diabetes mellitus (20.5%, <italic>n</italic> =820) and hyperlipidemia (8.8% <italic>n</italic> = 350). Cohort 1 had a lower proportion of subjects with ≥1 comorbidity compared with Cohort 2 (73.6% <italic>vs</italic> 77.8%; <italic>P</italic> = 0.0019). Cohort 1 had a lower prevalence of depression (11.8% <italic>vs</italic> 14.0%; <italic>P</italic> = 0.004), diabetes mellitus (19.1% vs. 21.9%;<italic> P</italic> = 0.0403) and hypertension (43.8% vs. 47.1%; <italic>P</italic> = 0.0289) compared with Cohort 1; and stroke was more common in Cohort 1 (24.5% <italic>vs</italic> 21.0%; <italic>P</italic> = 0.0137) (Table ##TAB##0##1##).\n</p>", "<p id=\"Par17\">Mean ± SD MMSE scores in Cohorts 1 and 2 at the time of AD diagnosis or start of initial treatment were 16.9 ± 6.1 and 17.1 ± 5.8, respectively (<italic>P</italic> = 0.2790). At 1 year, mean ± SD MMSE scores in Cohort 1 (<italic>n</italic> = 588) and Cohort 2 (<italic>n</italic> = 707) were 17.9 ± 6.1 and 17.4 ± 5.5, respectively. Differences in 1-year MMSE between cohorts were not significantly different (<italic>P</italic> = 0.1524). Mean ± SD change in MMSE score from treatment start to end of 1 year's treatment was +0.2 ± 3.6 in Cohort 1 (<italic>n</italic> = 588) and –0.2 ± 3.6 in Cohort 2 (<italic>n</italic> = 707). These differences were not statistically significant (<italic>P</italic> = 0.0711). In subjects stratified by disease severity at baseline [baseline MMSE score: 30-27 (normal), 26-21 (mild), 20-10 (moderate), &lt;10 (severe)], there was a significant difference between cohort subgroups in change in MMSE at 1 year in subjects with mild disease (<italic>P</italic> = 0.0021), but not in subjects with normal, moderate or severe disease status (Supplementary Table ##SUPPL##1##2##).</p>", "<p id=\"Par18\">Initial medications administered to AD patients differed significantly between cohorts (<italic>P</italic> &lt; 0.0001). Donepezil monotherapy was the most administered medication overall (75.0%) and the administration rate in Cohort 1 was higher in Cohort 2 (77.1% and 72.9%, respectively). Rivastigmine was more commonly administered to patients in Cohort 1 (12.5% <italic>vs.</italic> 9.0%) while galantamine (6.81% <italic>vs.</italic> 10.91%) and memantine (3.6% <italic>vs.</italic> 3.8%) were more frequently administered to Cohort 2 patients. Combination donepezil + memantine was only administered to Cohort 2 subjects (3.4%) (Table ##TAB##1##2##). In a subgroup analysis (by 12-month period) of each cohort, donepezil was consistently the most common medication administered with some variation between the 12-monthly periods analyzed. Combination donepezil + memantine was most frequently administered during July 2014–June 2015 (Cohort 2-1) (Supplementary Table ##SUPPL##2##3##).\n</p>", "<p id=\"Par19\">Medication persistence, defined as the proportion of time during the prescribed duration for which patients continued treatment, was high (≥98%) for donepezil, galantamine, rivastigmine and memantine (Table ##TAB##2##3##). Mean medication persistence was significantly higher in Cohort 1 <italic>vs</italic> 2 for donepezil (98.7 <italic>vs.</italic> 98.4; <italic>P</italic> = 0.0001) and memantine (98.8 <italic>vs.</italic>98.7; <italic>P</italic> = 0.0339). In subjects stratified by disease severity at baseline, medication persistence for ChEIs or memantine was significantly different in mild (galantamine: <italic>P</italic> = 0.0285), moderate (donepezil: <italic>P</italic> = 0.0023; memantine: <italic>P</italic> = 0.0230), and severe (donepezil: <italic>P</italic> = 0.0424) AD subgroups (Supplementary Table ##SUPPL##1##2##).\n</p>", "<p id=\"Par20\">Overall, the mean ± SD time from AD diagnosis to the start of initial therapy was 8.3 ± 39.6 days. Time to the start of therapy was significantly shorter in Cohort 1 (7.8 ± 41.0 days) compared with Cohort 2 (8.8 ± 38.2 days) (<italic>P</italic> = 0.0007). In subjects stratified by disease severity at treatment start, this difference was statistically significant in patients in the mild (<italic>P</italic> = 0.0427) and moderate (<italic>P</italic> = 0.0034) AD subgroups (Supplementary Table ##SUPPL##1##2##).</p>", "<p id=\"Par21\">Discontinuation and adjustment of initial treatment rates were significantly lower in Cohort 2 <italic>vs.</italic> Cohort 1 (49.7% <italic>vs.</italic> 58.0%; <italic>P</italic> &lt; 0.0001). In subjects stratified by disease severity at baseline, this difference was statistically significant in the moderate AD subgroup (<italic>P</italic> &lt; 0.0001) (Supplementary Table ##SUPPL##1##2##). For subjects who discontinued or changed their initial treatment, the mean ± SD overall duration of initial treatment was 324.8 ± 315.0 days. Kaplan-Meier analysis of initial treatment duration in Cohorts 1 and 2 who discontinued or changed their initial treatment is shown in Fig. ##FIG##0##1##. Mean duration of initial treatment was significantly longer in Cohort 2 (349.8 ± 316.1 days) than Cohort 1 (300.2 ± 312.0 days) (Log-rank test <italic>P</italic> &lt; 0.0001). In subjects stratified by disease severity at treatment start, statistically significant differences were observed in the mild (<italic>P =</italic>0.0317), moderate (<italic>P</italic> &lt; 0.0001), and severe (<italic>P =</italic>0.0286) AD subgroups (Supplementary Table ##SUPPL##1##2##).</p>", "<p id=\"Par22\">Treatment interruption/discontinuation occurred in 2,190 subjects: 1,159 subjects in Cohort 1 (52.9%) and 1031 in Cohort 2 (47.1%). Overall, 1,587 subjects were lost to follow-up (39.7% of all subjects) and included 901 (45.1%) and 686 (34.3%) in Cohorts 1 and 2, respectively. The most frequent reason for discontinuation or change of initial treatment was lack of effectiveness (8.1%<italic>vs</italic> 11.1%, respectively), followed by adverse effects (2.3% <italic>vs</italic> 3.2%) and death (0.3% <italic>vs</italic> 0.7%) (Table ##TAB##3##4##). In subgroup analysis (by 12-month periods) of each cohort, interruption/discontinuation due to lack of effectiveness was higher during the first 12 months although numbers of subjects in each subgroup are low (Supplementary Table ##SUPPL##3##4##).\n</p>", "<p id=\"Par23\">Overall, 136 patients added therapy due to lack of effectiveness of initial treatment medication: 29 subjects in Cohort 1 and 107 in Cohort 2. Change to add-on therapy occurred in most subjects during the first 12 months of analysis in both cohorts: 69.0% (<italic>n</italic> = 20) in Cohort 1-1 (July 2011–June 2012) and 67.3% (<italic>n</italic> = 72) in Cohort 2-2 (July 2014–June 2015).</p>", "<p id=\"Par24\">In total, 335 subjects (8.38%) switched AD medication: 169 (8.5%) in Cohort 1 and 166 (8.3%) in Cohort 2. In Cohort 1, the most common reason for switching drugs was lack of effectiveness (<italic>n</italic> = 120; 6.0%), followed by adverse effects (<italic>n</italic> = 38; 1.9%), other (<italic>n</italic> = 10; 0.5%) and economic burden (<italic>n</italic> = 1; 0.1%). In Cohort 2, reasons for switching were lack of effectiveness (<italic>n</italic> = 103; 5.2%), adverse effects (<italic>n</italic> = 49; 2.5%), and other (<italic>n</italic> = 14; 0.7%). Differences between cohorts regarding reasons for switching medication were not statistically significant (<italic>P</italic> = 0.1866).</p>", "<p id=\"Par25\">In subgroup analysis of Cohort 1, most subjects switched medications due to lack of effectiveness (<italic>n</italic> = 119) during the first year (Cohort 1-1, 57.1%), compared with the second (Cohort 1-2; 33.6%), and third year of study (Cohort 1-3; 9.2%); and rates for switching due to adverse effects (<italic>n</italic> = 38) in Cohorts 1-1, 1-2 and 1-3 were 63.2%, 10.5% and 26.3%, respectively. In subgroup analysis of Cohort 2, rates of subjects switching medications due to lack of effectiveness (<italic>n</italic> = 102) in Cohorts 2-1, 2-2 and 2-3 were 38.2%, 39.2% and 22.6%, respectively; and for those switching due to adverse effects (<italic>n</italic> = 49) were 49.0%, 24.5% and 26.5%, respectively.</p>", "<p id=\"Par26\">Overall, mean ± SD time from initial AD treatment to diagnosis of depression or antidepressant prescription was 517.0 ± 350.4 days (<italic>n</italic> = 3,222). Kaplan-Meier analysis of time from initial AD treatment to diagnosis of depression or antidepressant prescription in Cohorts 1 and 2 is shown in Fig. ##FIG##1##2##. Mean ± SD time to depression diagnosis/antidepressant prescription was significantly prolonged in Cohort 2 (<italic>n</italic> = 1,586) compared with Cohort 1 (<italic>n</italic> = 1,636): 530.8 ± 352.6 <italic>vs</italic> 503.6 ± 347.9 days (Log-rank test <italic>P</italic> &lt; 0.0001). In subjects stratified by disease severity at baseline, Cohort 2 prolongation of time to depression diagnosis/antidepressant prescription was found in the mild (<italic>P</italic> = 0.0001) and moderate (<italic>P</italic> = 0.0209) AD subgroups (Supplementary Table ##SUPPL##1##2##).</p>", "<p id=\"Par27\">In patients who did not have a diagnosis of depression at baseline, time from initial treatment of AD to diagnosis of depression or antidepressant prescription for each medication is shown in Table ##TAB##4##5##. Mean time to diagnosis of depression or antidepressant prescription was significantly longer in Cohort 2 <italic>vs</italic> Cohort 1 for donepezil (521.9 <italic>vs</italic> 520.7 days; <italic>P</italic> = 0.0026) and rivastigmine (678.7 <italic>vs</italic> 505.8 days; <italic>P</italic> = 0.0220).\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par28\">This retrospective cohort study investigated changes in treatment patterns for subjects with newly diagnosed AD in Korea during two consecutive 3-year periods which were before (Cohort 1) and after (Cohort 2) the July 2014 revision of the national LTCI system regarding eligibility for dementia patients.</p>", "<p id=\"Par29\">At baseline, a higher proportion of patients in Cohort 2 (July 2014 – June 2017) than Cohort 1 (July 2011 – June 2014) had one or more comorbidities which may reflect increased diagnosis and treatment of dementia in clinics visited for evaluation of non-dementia conditions. Depression was more commonly diagnosed in Cohort 2 which may reflect increased recognition of cognitive disturbances associated with depressive symptoms [##REF##38017154##15##]. In contrast, stroke was less common in Cohort 2 and the reasons for this are unclear. Although stroke mortality in Korea has steadily decreased from 2010 to 2019 (by 12.8% from 2014 to 2019) due to better management of risk factors and improved medical interventions, the absolute number of incident strokes increased by 29.7% from 2014 to 2019 [##REF##35272435##16##]. Moreover, based on an analysis of health insurance big data, the female incidence of stroke has decreased in Korea [##UREF##4##17##] and, as the AD patient population in our study was predominantly female, this may account for the observed decrease in stroke between Cohort 1 and Cohort 2.</p>", "<p id=\"Par30\">Mean MMSE scores at the time of AD diagnosis or start of initial treatment were not significantly different between cohorts but, as there were significant differences in mean age and age category, then it is possible that age-related MMSE scores may differ for some age groups. These analyses remain to be done. Similarly, no significant difference was found in 1-year MMSE scores between cohorts and a “trend” of statistical significance was observed for change in MMSE scores from treatment start to 1 year’s end of treatment.</p>", "<p id=\"Par31\">Initial medications administered to AD patients differed significantly between cohorts, and donepezil was most frequently administered – to more than three-quarters of patients. Combination AChEI + memantine was only given to Cohort 2 patients as insurance coverage for combination therapy was only available from October 2014. Recent results from the Observational Medical Outcome Partnership Common Data Model (OMOP CDM) which analyzed data from five hospitals in Korea during 2009-2019 also found that donepezil was the most prescribed anti-dementia medication (48.8%) among patients with newly diagnosed AD (<italic>n</italic> = 8,653), followed by memantine (18.1%), rivastigmine (9.0%), and galantamine (5.7%) [##REF##35292697##18##].</p>", "<p id=\"Par32\">Low medication persistence and/or adherence represents a significant challenge in treating patients with chronic diseases, including those with dementia [##UREF##5##19##, ##REF##25702361##20##]. Medication persistence rates in the present study for donepezil, galantamine, rivastigmine and memantine were all high (≥98%). For comparison, the OMOP CDM study reported 12-month persistence rates of approximately 50% for donepezil and memantine and around 40% for rivastigmine and galantamine [##REF##35292697##18##]. Differences in persistence rates may be due to differences in definitions of persistence and in study populations. Although mean medication persistence in our study was statistically higher in Cohort 1 <italic>vs</italic> 2 for donepezil and memantine, this was not clinically meaningful. Data indicate that several factors may influence persistence with dementia pharmacotherapy, including patient age, sex, ethnic/racial background, socioeconomic status, and region-specific reimbursement criteria, in addition to the extent and quality of interactions among patients, caregivers, and providers [##REF##25702361##20##].</p>", "<p id=\"Par33\">Depressive symptoms are common in AD, occurring in approximately 15% of patients [##UREF##6##21##]. Mean time to depression diagnosis/antidepressant prescription was significantly prolonged in Cohort 2 compared with Cohort 1. The prescription of depressive drugs other than those issued by psychiatry departments was more tightly regulated in earlier years which may have contributed to these results. In addition, prescriptions were checked only in EMRs from neurology departments. Mean time to diagnosis of depression or antidepressant prescription was significantly longer for donepezil (by approximately 1 day) and rivastigmine (by nearly 173 days).</p>", "<p id=\"Par34\">The mean time from AD diagnosis to the start of initial therapy was slightly longer (by approximately 1 day) in Cohort 2 compared with Cohort 1. This may be due to a strain on AD diagnostic facilities due to increased patient numbers. However, in patients who discontinued or changed their initial treatment, the mean duration of treatment was significantly longer in Cohort 2 (by 49 days). This likely reflects the change in LTCI policy which enabled increased access to long-term care for patients. Introduction of the national LTCI-funded cognitive function training program was also associated with a significant reduction in the decline of cognitive function in older people with mild dementia after, compared to before, its introduction [##REF##31268493##11##].</p>", "<p id=\"Par35\">The proportion of patients who discontinued or changed their initial treatment was also significantly lower in Cohort 2 and appear to be associated with the policy revision in 2014. Lack of effectiveness and adverse effects were the main reasons for discontinuing or changing treatment, but as many subjects (<italic>n</italic> = 1,587; 39.7% of all subjects) were lost to follow-up, differences between cohorts were limited by relatively low numbers of patients. Predictors of discontinuation or change in therapy was beyond the scope of this study. However, a 2-year European prospective cohort study of patients with mild-to-moderate AD initiating AChEIs (<italic>n</italic> = 557) reported that predictors of discontinuation were behavioral disturbances, decline in MMSE score, AD-related hospitalization, low body mass index (BMI) and falls; and predictors of switching treatment were MMSE score, decline in activities of daily living score, shorter AD duration, aberrant motor behavior, and higher nurse resource use [##UREF##7##22##].</p>", "<p id=\"Par36\">The main limitations of the current study reflect those associated with the retrospective nature of the study design which analyzed data from EMRs. Data pre-processing and data quality (e.g. incomplete, inaccurate and/or missing data) challenges, and the potential for limited generalizability, are recognized challenges encountered when using EMR data for secondary research purposes [##REF##32149742##23##]. For example, this may have impacted findings relating to medication persistence because it was not possible to differentiate between patients who actually took the medication and those who did not. There may also be differences in patient care between hospitals such as neuropsychological examinations, interval between examinations etc. although all patients were treated by neurologists. Antidepressants are often prescribed by psychiatrists due to insurance regulations, and this may have also led to differences in care of patients between hospitals. As there were a number of policy changes over several years, only large changes to policy were considered. Finally, as the primary aim of the study was to examine change in treatment patterns between cohorts, in depth statistical analyses such as Cox regression to account for confounding factors for differences in MMSE were not performed. However, we are planning more detailed <italic>post-hoc</italic> analyses (including Cox regression) for a subsequent publication.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par37\">This study compared cohorts before and after revision of the national LTCI system for dementia patients in Korea and found no significant difference between cohorts in mean MMSE scores at the time of AD diagnosis or start of initial treatment. The reduction in the proportion of patients who discontinued or changed their initial treatment, and the significant increase in mean duration of treatment, were observed following revision of the LTCI policy including national dementia management, which enabled increased access to long-term care for patients with dementia and positive effects on care of depression. Large-scale research projects including long-term prospective studies are needed to continue to monitor the care of dementia patients in Korea.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The South Korean government has been actively involved in plans to combat dementia, implementing a series of national strategies and plans since 2008. In July 2014, eligibility for mandatory long-term care insurance (LTCI) was extended to people with dementia enabling access to appropriate long-term care including the cognitive function training program and home nursing service. This study aimed to investigate changes in treatment patterns for Alzheimer’s disease (AD) between July 2011 and June 2017 which spanned the 2014 revision.</p>", "<title>Methods</title>", "<p id=\"Par2\">This multicenter, retrospective, observational study of patients with newly diagnosed AD analyzed electronic medical records from 17 general hospitals across South Korea. Based on their time of AD diagnosis, subjects were categorized into Cohort 1 (1 July 2011 to 30 June 2014) and Cohort 2 (1 July 2014 to 30 June 2017).</p>", "<title>Results</title>", "<p id=\"Par3\">Subjects (<italic>N</italic>=3,997) divided into Cohorts 1 (<italic>n</italic>=1,998) and 2 (<italic>n</italic>=1,999), were mostly female (66.4%) with a mean age of 84.4 years. Cohort 1 subjects were significantly older (<italic>P</italic>&lt;0.0001) and had a lower number of comorbidities (<italic>P</italic>=0.002) compared with Cohort 2. Mean Mini-Mental State Examination (MMSE) scores in Cohorts 1 and 2 at the time of AD diagnosis or start of initial treatment were 16.9 and 17.1, respectively (<italic>P</italic>=0.2790). At 1 year, mean MMSE scores in Cohorts 1 and 2 increased to 17.9 and 17.4, respectively (<italic>P</italic>=0.1524). Donepezil was the most frequently administered medication overall (75.0%), with comparable rates between cohorts. Rates of medication persistence were ≥98% for acetylcholinesterase inhibitor or memantine therapy. Discontinuation and switch treatment rates were significantly lower (49.7% <italic>vs.</italic> 58.0%; <italic>P</italic>&lt;0.0001), and mean duration of initial treatment significantly longer, in Cohort 2 <italic>vs.</italic> 1 (349.3 <italic>vs</italic>. 300.2 days; <italic>P</italic>&lt;0.0001).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Comparison of cohorts before and after revision of the national LTCI system for dementia patients found no significant difference in mean MMSE scores at the time of AD diagnosis or start of initial treatment. The reduction in the proportion of patients who discontinued or changed their initial treatment, and the significant increase in mean duration of treatment, were observed following revision of the LTCI policy which enabled increased patient access to long-term care.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12889-024-17671-2.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank the following investigators for assistance with data gathering: Hyung-Gyun Oh (Gwangju Veterans Hospital), Sae-Hoon Lee (Chamjoeun Hospital), Seong-Hee Kim (Changwon Fatima Hospital), Kyung-Yeol Cheon (Hallym Hospital), and Sung-Man Jun (BongSeng Memorial Hospital). Editorial assistance was provided by Robert A. Furlong PhD and David P. Figgitt PhD, ISMPP CMPP™, Content Ed Net, with funding from Eisai Korea Inc.</p>", "<title>Authors’ contributions</title>", "<p>Young Jin Kim: data gathering as a Principal Investigator (PI) and publication drafting; Ki- Yoon So: data gathering as a PI; Hyo Min Lee: data gathering as a PI; Changtae Hahn: data gathering as a PI; Seung-Hoon Song: data gathering as a PI; Yong-Seok Lee: data gathering as a PI; Sang Woo Kim: data gathering as a PI; Heui Cheun Park: data gathering as a PI; Jaehyung Ryu: data gathering as a PI; Jung Seok Lee: data gathering as a PI; Min Ju Kang: data gathering as a PI; Jun Hong Lee: data gathering as a PI; JinRan Kim: project management, publication support; Yoona Lee: project management. All authors provided critical input on draft versions of the manuscript and approved the final manuscript prior to submission.</p>", "<title>Funding</title>", "<p>This work was supported by Eisai Korea Inc.</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated and/or analyzed during the current study are not publicly available due to ethical constraints but are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par38\">Institutional Review Board (IRB) and regulatory authority review and approval of the study protocol were obtained according to local laws and regulations, as applicable. A complete list of all study sites and corresponding IRBs is provided in Supplementary Table ##SUPPL##0##1##. The following IRBs reviewed and approved the study protocol and waived the need for informed consent: Sungae Hospital IRB, Gwangju Veterans Hospital IRB, The Public Institutional Review Board (Public IRB), Daegu Fatima Hospital IRB, Daejeon St. Mary's Hospital IRB, Seoul Metropolitan Government-Seoul National University Boramae Medical Center IRB, Busan St. Mary's Hospital IRB, Andong Medical Group Hospital IRB, Jeju National University Hospital IRB, Veterans Healthcare Medical Center IRB, Changwon Fatima Hospital IRB, National Health Insurance Service Ilsan Hospital IRB, BongSeng Memorial Hospital IRB. This was a retrospective observational study and because the study did not involve more than minimum risks to subjects, the need for informed consent was not required by any of the IRBs that reviewed and approved the study protocol. The study was conducted in compliance with the relevant regulations provided by the Declaration of Helsinki and International Conference for Harmonization (ICH) Good Clinical Practice guidelines. Anonymity of subjects was maintained rigorously throughout the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par39\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par40\">JinRan Kim and Yoona Lee are both employees of Eisai Korea Inc. The other authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Kaplan-Meier analysis of initial treatment duration in subjects who discontinued or changed their initial treatment</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Kaplan-Meier analysis of time from initial Alzheimer’s disease treatment to diagnosis of depression or antidepressant prescription</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Demographics and baseline characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"><bold>Cohort 1 (</bold><bold><italic>n</italic></bold><bold> = 1,998)</bold></th><th align=\"left\"><bold>Cohort 2 (</bold><bold><italic>n</italic></bold><bold> = 1,999)</bold></th><th align=\"left\"><bold>Total (</bold><bold><italic>N</italic></bold><bold> = 3,997)</bold></th><th align=\"left\"><bold><italic>P</italic></bold><bold> value*: Cohort 1 </bold><bold><italic>vs</italic></bold><bold> 2</bold></th></tr></thead><tbody><tr><td align=\"left\">Sex: male/female, n (%)</td><td align=\"left\">657 (32.9)/ 1,341 (67.1)</td><td align=\"left\">685 (34.3)/ 1,314 (65.7)</td><td align=\"left\">1,342 (33.6)/ 2,655 (66.4)</td><td align=\"left\">0.3542</td></tr><tr><td align=\"left\">Age (years), Mean ± SD</td><td align=\"left\">84.9 ± 8.6</td><td align=\"left\">84.0 ± 7.5</td><td align=\"left\">84.4 ± 8.0</td><td align=\"left\">&lt;0.0001</td></tr><tr><td align=\"left\" colspan=\"5\">Age range (years)</td></tr><tr><td align=\"left\"> &lt;40</td><td align=\"left\">1 (0.1)</td><td align=\"left\">0 (0.0)</td><td align=\"left\">1 (0.0)</td><td align=\"left\" rowspan=\"7\">&lt;0.0001</td></tr><tr><td align=\"left\"> ≥40 to &lt;50</td><td align=\"left\">5 (0.3)</td><td align=\"left\">0 (0.0)</td><td align=\"left\">5 (0.1)</td></tr><tr><td align=\"left\"> ≥50 to &lt;60</td><td align=\"left\">10 (0.5)</td><td align=\"left\">5 (0.3)</td><td align=\"left\">15 (0.4)</td></tr><tr><td align=\"left\"> ≥60 to &lt;70</td><td align=\"left\">71 (3.6)</td><td align=\"left\">70 (3.5)</td><td align=\"left\">141 (3.5)</td></tr><tr><td align=\"left\"> ≥70 to &lt;80</td><td align=\"left\">385 (19.3)</td><td align=\"left\">447 (22.4)</td><td align=\"left\">832 (20.8)</td></tr><tr><td align=\"left\"> ≥80 to &lt;90</td><td align=\"left\">923 (46.2)</td><td align=\"left\">1,031 (51.6)</td><td align=\"left\">1,954 (48.9)</td></tr><tr><td align=\"left\"> ≥90</td><td align=\"left\">603 (30.2)</td><td align=\"left\">446 (22.3)</td><td align=\"left\">1,049 (26.2)</td></tr><tr><td align=\"left\" colspan=\"5\">Highest educational level</td></tr><tr><td align=\"left\"> No formal school education</td><td align=\"left\">383 (19.2)</td><td align=\"left\">471 (23.6)</td><td align=\"left\">854 (21.4)</td><td align=\"left\" rowspan=\"6\">&lt;0.0001</td></tr><tr><td align=\"left\"> Elementary school or below</td><td align=\"left\">544 (27.2)</td><td align=\"left\">600 (30.0)</td><td align=\"left\">1,144 (28.6)</td></tr><tr><td align=\"left\"> Middle school</td><td align=\"left\">102 (5.1)</td><td align=\"left\">133 (6.7)</td><td align=\"left\">235 (5.9)</td></tr><tr><td align=\"left\"> High school</td><td align=\"left\">111 (5.6)</td><td align=\"left\">147 (7.4)</td><td align=\"left\">258 (6.5)</td></tr><tr><td align=\"left\"> College/graduate school</td><td align=\"left\">58 (2.9)</td><td align=\"left\">80 (4.0)</td><td align=\"left\">138 (3.5)</td></tr><tr><td align=\"left\"> Unknown</td><td align=\"left\">800 (40.0)</td><td align=\"left\">568 (28.4)</td><td align=\"left\">1,368 (34.2)</td></tr><tr><td align=\"left\" colspan=\"5\">Past medical history</td></tr><tr><td align=\"left\"> Depression, n (%)</td><td align=\"left\">235 (11.8)</td><td align=\"left\">280 (14.01)</td><td align=\"left\">515 (12.9)</td><td align=\"left\">0.0040</td></tr><tr><td align=\"left\"> Diabetes mellitus</td><td align=\"left\">382 (19.1)</td><td align=\"left\">438 (21.9)</td><td align=\"left\">820 (20.5)</td><td align=\"left\">0.0403</td></tr><tr><td align=\"left\"> Hypertension</td><td align=\"left\">876 (43.8)</td><td align=\"left\">941 (47.1)</td><td align=\"left\">1,817 (45.5)</td><td align=\"left\">0.0289</td></tr><tr><td align=\"left\"> Stroke, n (%)</td><td align=\"left\">490 (24.5)</td><td align=\"left\">419 (21.0)</td><td align=\"left\">909 (22.7)</td><td align=\"left\">0.0137</td></tr><tr><td align=\"left\"> ≥1 comorbidity, n (%)</td><td align=\"left\">1,470 (73.6)</td><td align=\"left\">1,555 (77.8)</td><td align=\"left\">3,025 (75.7)</td><td align=\"left\">0.0019</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Initial medications administered</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\"><bold>Cohort 1 (</bold><bold><italic>n</italic></bold><bold> = 1,998)</bold></th><th align=\"left\"><bold>Cohort 2 (</bold><bold><italic>n</italic></bold><bold> = 1,999)</bold></th><th align=\"left\"><bold>Total (N = 3,997)</bold></th><th align=\"left\" rowspan=\"2\"><bold><italic>P</italic></bold><bold> value*: Cohort 1 </bold><bold><italic>vs</italic></bold><bold> 2</bold></th></tr><tr><th align=\"left\" colspan=\"3\">n (%)</th></tr></thead><tbody><tr><td align=\"left\">Donepezil</td><td align=\"left\">1,541 (77.1)</td><td align=\"left\">1,457 (72.9)</td><td align=\"left\">2,998 (75.0)</td><td align=\"left\" rowspan=\"5\">&lt;0.0001</td></tr><tr><td align=\"left\">Rivastigmine</td><td align=\"left\">250 (12.5)</td><td align=\"left\">180 (9.0)</td><td align=\"left\">430 (10.8)</td></tr><tr><td align=\"left\">Galantamine</td><td align=\"left\">136 (6.8)</td><td align=\"left\">218 (10.9)</td><td align=\"left\">354 (8.9)</td></tr><tr><td align=\"left\">Memantine</td><td align=\"left\">71 (3.6)</td><td align=\"left\">76 (3.8)</td><td align=\"left\">147 (3.7)</td></tr><tr><td align=\"left\">Combination donepezil + memantine</td><td align=\"left\">0 (0.0)</td><td align=\"left\">68 (3.4)</td><td align=\"left\">68 (1.7)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Medication persistence<sup>a</sup> (%)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"/><th align=\"left\"><bold>Cohort 1</bold></th><th align=\"left\"><bold>Cohort 2</bold></th><th align=\"left\"><bold>Total</bold></th><th align=\"left\"><bold><italic>P</italic></bold><bold> value†: Cohort 1 </bold><bold><italic>vs</italic></bold><bold> 2</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Donepezil</td><td align=\"left\">n</td><td align=\"left\">1,514</td><td align=\"left\">1,473</td><td align=\"left\">2,987</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">98.7 ± 7.3</td><td align=\"left\">98.4 ± 6.8</td><td align=\"left\">98.57 ± 7.0</td><td char=\".\" align=\"char\">0.0001</td></tr><tr><td align=\"left\" rowspan=\"2\">Rivastigmine</td><td align=\"left\">n</td><td align=\"left\">249</td><td align=\"left\">178</td><td align=\"left\">427</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">98.3 ± 10.6</td><td align=\"left\">99.8 ± 2.8</td><td align=\"left\">98.9 ± 8.3</td><td char=\".\" align=\"char\">0.0500</td></tr><tr><td align=\"left\" rowspan=\"2\">Galantamine</td><td align=\"left\">n</td><td align=\"left\">136</td><td align=\"left\">215</td><td align=\"left\">351</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">98.7 ± 5.9</td><td align=\"left\">99.5 ± 3.8</td><td align=\"left\">99.2 ± 4.7</td><td char=\".\" align=\"char\">0.0785</td></tr><tr><td align=\"left\" rowspan=\"2\">Memantine</td><td align=\"left\">n</td><td align=\"left\">71</td><td align=\"left\">142</td><td align=\"left\">213</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">98.8 ± 7.2</td><td align=\"left\">98.7 ± 6.8</td><td align=\"left\">98.7 ± 6.9</td><td char=\".\" align=\"char\">0.0339</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Reasons for discontinuation or change of initial treatment in Cohorts 1 and 2</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\"><bold>Cohort 1 (</bold><bold><italic>n</italic></bold><bold> = 1,998)</bold></th><th align=\"left\"><bold>Cohort 2 (</bold><bold><italic>n</italic></bold><bold> = 1,999)</bold></th><th align=\"left\"><bold>Total (</bold><bold><italic>N</italic></bold><bold> = 3,997)</bold></th></tr><tr><th align=\"left\" colspan=\"3\">n (%)</th></tr></thead><tbody><tr><td align=\"left\">Lost to follow-up</td><td align=\"left\">901 (45.1)</td><td align=\"left\">686 (34.3)</td><td align=\"left\">1,587 (39.7)</td></tr><tr><td align=\"left\">Lack of effectiveness</td><td align=\"left\">161 (8.1)</td><td align=\"left\">222 (11.1)</td><td align=\"left\">383 (9.6)</td></tr><tr><td align=\"left\">Adverse effects</td><td align=\"left\">45 (2.3)</td><td align=\"left\">63 (3.2)</td><td align=\"left\">108 (2.7)</td></tr><tr><td align=\"left\">Death</td><td align=\"left\">6 (0.3)</td><td align=\"left\">13 (0.7)</td><td align=\"left\">19 (0.5)</td></tr><tr><td align=\"left\">Economic burden</td><td align=\"left\">1 (0.1)</td><td align=\"left\">2 (0.1)</td><td align=\"left\">3 (0.1)</td></tr><tr><td align=\"left\">Symptom improvement</td><td align=\"left\">1 (0.1)</td><td align=\"left\">0 (0.0)</td><td align=\"left\">1 (0.0)</td></tr><tr><td align=\"left\">Other</td><td align=\"left\">44 (2.2)</td><td align=\"left\">45 (2.3)</td><td align=\"left\">89 (2.2)</td></tr><tr><td align=\"left\">Total</td><td align=\"left\">1,159 (58.0)</td><td align=\"left\">1,031 (51.6)</td><td align=\"left\">2,190 (54.8)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Time from initial treatment (days) of Alzheimer's disease to diagnosis of depression or antidepressant prescription</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"/><th align=\"left\"><bold>Cohort 1</bold></th><th align=\"left\"><bold>Cohort 2</bold></th><th align=\"left\"><bold>Total</bold></th><th align=\"left\"><bold><italic>P</italic></bold><bold> value*: Cohort 1 </bold><bold><italic>vs</italic></bold><bold> 2</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">Donepezil</td><td align=\"left\">n</td><td align=\"left\">1,406</td><td align=\"left\">1,335</td><td align=\"left\">2,741</td><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">520.7 ± 343.7</td><td align=\"left\">521.9 ± 353.8</td><td align=\"left\">521.3 ± 348.6</td><td align=\"left\">0.0026</td></tr><tr><td align=\"left\" rowspan=\"2\">Rivastigmine</td><td align=\"left\">n</td><td align=\"left\">247</td><td align=\"left\">162</td><td align=\"left\">409</td><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">505.8 ± 368.7</td><td align=\"left\">678.7 ± 316.4</td><td align=\"left\">574.3 ± 358.6</td><td align=\"left\">0.0220</td></tr><tr><td align=\"left\" rowspan=\"2\">Galantamine</td><td align=\"left\">n</td><td align=\"left\">134</td><td align=\"left\">213</td><td align=\"left\">347</td><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">433.2 ± 353.1</td><td align=\"left\">460.4 ± 314.0</td><td align=\"left\">449.9 ± 329.4</td><td align=\"left\">0.1065</td></tr><tr><td align=\"left\" rowspan=\"2\">Memantine</td><td align=\"left\">n</td><td align=\"left\">71</td><td align=\"left\">73</td><td align=\"left\">144</td><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">380.8 ± 314.6</td><td align=\"left\">449.5 ± 348.1</td><td align=\"left\">415.6 ± 332.6</td><td align=\"left\">0.3086</td></tr><tr><td align=\"left\" rowspan=\"2\">Combination donepezil + memantine</td><td align=\"left\">n</td><td align=\"left\"/><td align=\"left\">68</td><td align=\"left\">68</td><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">—</td><td align=\"left\">723.7 ± 366.7</td><td align=\"left\">723.7 ± 366.7</td><td align=\"left\">—</td></tr></tbody></table></table-wrap>" ]
[ "<inline-formula id=\"IEq1\"><alternatives><tex-math id=\"M1\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\text{Medication Possession Ratio (MPR)} = \\frac{\\text{Actual number of days of taking medication*}}{\\text{Planned number of days of taking medication**}} \\times 100$$\\end{document}</tex-math><mml:math id=\"M2\"><mml:mrow><mml:mtext>Medication Possession Ratio (MPR)</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mtext>Actual number of days of taking medication*</mml:mtext></mml:mrow><mml:mrow><mml:mtext>Planned number of days of taking medication**</mml:mtext></mml:mrow></mml:mfrac><mml:mo>×</mml:mo><mml:mn>100</mml:mn></mml:mrow></mml:math></alternatives></inline-formula>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>*</sup>Chi-square tests except Wilcoxon rank-sum test for mean age</p></table-wrap-foot>", "<table-wrap-foot><p><sup>*</sup>Chi-square test</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>Medication persistence is defined as the proportion of time during the prescribed duration for which patients continued treatment, calculated as:</p><p>\n\n</p><p>*Treatment end date (end date of administration or end date of follow-up specified in the electronic medical record) - treatment start date (start date of administration)</p><p>**Number of prescribed days X times of prescription (in case the number of prescribed days were different, each number of prescribed days was added)</p><p><bold>†</bold>Wilcoxon rank-sum test</p></table-wrap-foot>", "<table-wrap-foot><p>Percentages shown are for the proportion of subjects in each cohort</p></table-wrap-foot>", "<table-wrap-foot><p><sup>*</sup>Log-rank test. Mean (± SD<bold>)</bold> time from initial treatment to diagnosis of depression or antidepressant prescription is shown</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<inline-graphic xlink:href=\"12889_2024_17671_Article_IEq1.gif\"/>", "<graphic xlink:href=\"12889_2024_17671_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12889_2024_17671_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"12889_2024_17671_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Supplementary Table 1.</bold> List of study sites and corresponding Institutional Review Boards (IRB) that reviewed and approved the study protocol.</p></caption></media>", "<media xlink:href=\"12889_2024_17671_MOESM2_ESM.docx\"><caption><p><bold>Additional file 2: Supplementary Table 2.</bold> Change in MMSE, treatment duration, discontinuation/changing treatment, medication persistence and time to diagnosis of depression/ prescription of antidepressants by severity of Alzheimer's disease (AD) at baseline.</p></caption></media>", "<media xlink:href=\"12889_2024_17671_MOESM3_ESM.docx\"><caption><p><bold>Additional file 3: Supplementary Table 3.</bold> Initial treatment medication in Cohort subgroups (analyzed by 12-month periods).</p></caption></media>", "<media xlink:href=\"12889_2024_17671_MOESM4_ESM.docx\"><caption><p><bold>Additional file 4: Supplementary Table 4.</bold> Reasons for discontinuation/interruption of initial treatment in Cohort subgroups (analyzed by 12-month periods).</p></caption></media>" ]
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{ "acronym": [], "definition": [] }
23
CC BY
no
2024-01-14 23:43:45
BMC Public Health. 2024 Jan 12; 24:168
oa_package/4f/6f/PMC10787419.tar.gz
PMC10787420
38216948
[ "<title>Background</title>", "<p id=\"Par17\">Non-small cell lung cancer (NSCLC) is one of the most common neoplasms, and the leading cause of cancer-related mortality in several countries, including South Korea [##REF##35313101##1##–##REF##23972814##3##]. Approximately 65% of patients with NSCLC are diagnosed with advanced status [##REF##23972814##3##], and the clinical outcome of advanced NSCLC with a median overall survival (OS) of 11–22 months remains unsatisfactory, despite advances of palliative chemotherapy [##REF##34273294##2##, ##REF##33894335##4##].</p>", "<p id=\"Par18\">Since NSCLC patients with epidermal growth factor receptor (EGFR)-activating mutations (exon 19 deletion and exon 21 L858R mutation), which are observed in 20–40% of Asian patients, demonstrated high response to EGFR tyrosine kinase inhibitors (TKIs) [##REF##19270482##5##, ##REF##15118073##6##], EGFR-TKIs have been considered as the standard first-line therapy of EGFR mutation-positive advanced NSCLC [##REF##34273294##2##, ##UREF##0##7##]. In the NCCN [##REF##35545176##8##] and ESMO guidelines [##UREF##1##9##], osimertinib, third-generation TKI, is recommended as a first-line treatment based on the results of FLAURA trial, which reported a significant prolongation of progression-free survival (PFS) compared to first-generation EGFR-TKIs (gefitinib, erlotinib) [##REF##29151359##10##]. However, the OS benefit of osimertinib was rather marginal (median OS: 38.6 vs. 31.8 months, <italic>P</italic> = 0.046), and there was no OS benefit for Asian patients and those with EGFR L858R mutation [##REF##31751012##11##]. Therefore, first and second-generation EGFR-TKIs are still recommended equally, especially for Asian patients. Although there are some real-world data on the comparison of outcomes between first- and second-generation EGFR-TKIs [##REF##33707140##12##–##REF##29898592##16##], only two trials have compared the efficacy of first-line first- and second-generation EGFR-TKIs, reporting conflicting results [##REF##27083334##17##–##REF##33331989##20##].</p>", "<p id=\"Par19\">The presence of differences in sensitivity to EGFR-TKIs among various types of EGFR mutation remains a subject of debate. Several studies demonstrated longer PFS and/or OS in patients with exon 19 deletion compared to those with L858R mutation [##REF##36817181##15##, ##REF##26967328##21##–##REF##26490356##29##]. On the other hand, no significantly different effect of EGFR-TKIs based on the types of EGFR mutation <bold>was</bold> observed in other retrospective studies and phase III trials [##REF##25034225##30##–##REF##34558665##36##]. In addition, many studies included patients who received EGFR-TKIs as variable lines [##REF##16818686##22##, ##REF##20552223##23##, ##REF##19692684##25##, ##REF##26490356##29##, ##REF##25034225##30##].</p>", "<p id=\"Par20\">Therefore, in the present study, the clinical outcomes of EGFR mutation-positive advanced NSCLC patients treated with first- and second-generation EGFR-TKIs as their first-line treatment were investigated in terms of the EGFR mutation subtypes as well as the agents.</p>" ]
[ "<title>Methods</title>", "<title>Study population</title>", "<p id=\"Par21\">All EGFR mutation-positive advanced NSCLC patients who started first-line first- or second-generation EGFR-TKIs therapy between July 2011 and June 2018 at our institution were retrospectively identified. The eligibility criteria were cytologically or histologically confirmed NSCLC, and either stage IV based on the 7th edition of the American Joint Committee on Cancer (AJCC) [##UREF##2##37##] or stage IIIB/recurrent disease unsuitable for definitive local treatment. Some patients and methods of this study cohort were included in previous retrospective studies on EGFR-TKIs in NSCLC [##REF##26967328##21##, ##REF##35167736##38##]. Nonetheless the criteria for eligibility criteria of this study were slightly different from those of the previous studies, with longer follow-up duration of patients.</p>", "<title>Clinical review</title>", "<p id=\"Par22\">The clinical information of eligible patients was retrospectively reviewed. Data collected on the patients included patient characteristics (age, gender, smoking history), performance status (PS) based on the Eastern Cooperative Oncology Group (ECOG) performance scale, histology, disease status at the start of EGFR-TKIs, presence of synchronous brain metastasis, second- or further-line of therapy, and information of survival status.</p>", "<title>EGFR mutation analysis</title>", "<p id=\"Par23\">A direct sequencing method was applied for detecting EGFR mutation without routine tumor enrichment. Retrieved Formalin-fixed, paraffin embedded (FFPE) tumor samples were used for genomic DNA extraction by the QIAmp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany). Polymerase chain reaction (PCR) amplification of EGFR exons 18 to 21, using intron-based primers was followed. Sequencing was performed in both the forward and reverse directions. Since September 2014, the peptide nucleic acid-locked nucleic acid (PNA-LNA) PCR clamp method has been applied in almost all cases. Genomic DNA of EGFR mutation hot-spots were amplified by PCR with a PNA clamp primer synthesized from a PNA with a wild-type sequence and detected by a fluorescent primer that incorporates locked nucleic acids. This method for preferential amplification of the mutant sequence can detect EGFR mutation in specimens containing 100 to 1000 excess copies of wild-type EGFR sequence [##UREF##3##39##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par24\">The Kaplan–Meier method was used for the calculation of OS and PFS. The time from the start day of the EGFR-TKI treatment to death and the time to disease progression or death by any cause were defined as OS and PFS, respectively. In case of surviving patients at the time of data cut-off with uncertain disease status, the data were censored on the last evaluation date at our institution for PFS. Data on the survivors were censored at the last follow-up for OS. The log-rank test <bold>was</bold> used for the analysis of the differences between the survival curves. Fisher’s exact test was applied to compare categorical variables among the different groups. The joint effects of several variables on survival were determined by the Cox proportional-hazards regression model, including factors with p-values &lt; 0.1 in the univariate analysis. All statistical analyses were performed two-sided using SPSS for Windows 20.0 software.</p>", "<title>Statement of ethics</title>", "<p id=\"Par25\">This research protocol was approved by the Institutional Review Board (IRB) of Ajou University Hospital, Suwon, Republic of Korea (AJOUIRB-MDB-2019-394) and all methods were performed in accordance with the relevant guidelines and regulations. The study was designed retrospectively. Written informed consent from patients was not required in accordance with guidelines of the IRB of Ajou University Hospital.</p>" ]
[ "<title>Results</title>", "<title>Patient characteristics</title>", "<p id=\"Par26\">A total of 237 EGFR-mutation-positive, advanced NSCLC patients, who received first- (gefitinib, erlotinib) or second-generation (afatinib) EGFR-TKIs as first-line palliative chemotherapy, were analyzed. Table ##TAB##0##1## describes the clinicopathological characteristics of patients. Almost all patients underwent EGFR-TKI treatment in the routine practice, except for four patients who received gefitinib in a clinical trial as a first-line TKI. The median age of all patients was 67 (23–91), and 138 (58.2%) patients were female. Primary metastatic and recurrent disease were diagnosed in 199 (84%) and 38 (16%) patients, respectively. The ECOG PS was 0 or 1 in 194 (81.9%) patients, 2 in 31 patients, 3 in 11 patients, and 4 in 1 patient. Synchronous brain metastasis was identified in 77 (32.5%) patients. Among the 220 patients with disease progression after first-line EGFR-TKI treatment, 37 (16.8%) patients received third-generation EGFR-TKIs (osimertinib: 28, olmutinib: 9 patients) as second- (27 patients) or further-lines (10 patients).\n</p>", "<p id=\"Par27\">Direct sequencing (82 patients), the PNA-LNA PCR clamp method (152 patients), and next-generation sequencing (3 patients) were used for detection of EGFR mutation subtypes. The most common type of EGFR mutation was the exon 19 deletion (130 patients, 54.9%), followed by L858R mutation in exon 21 (84 patients, 35.4%). Moreover, 18 patients had uncommon mutations (exon 18 mutation: 8, exon 18 with exon 20 mutation: 3, exon 20 mutation: 3, exon 21 mutation: 4 [L861Q: 3, other mutation: 1]), and five patients dual mutations (exon 19 deletion with L858R mutation: 1, L858R mutation with exon 18 mutation: 1, exon 19 deletion with exon 20 mutation: 1, and L858R and L861Q mutations: 2). The baseline characteristics were not statistically different based on the EGFR mutation subtype. However, the proportion of patients who received third-generation TKIs after progression was significantly higher in patients with exon 19 deletion compared to those with other mutations (L858R and uncommon or dual mutations) (Table ##TAB##0##1##).</p>", "<p id=\"Par28\">A total of 159 (67.1%), 18 (7.6%), and 60 (25.3%) patients were treated with gefitinib, erlotinib, and afatinib, respectively. The baseline characteristics of patients treated with afatinib in this cohort were significantly associated with younger age, male, smoker, better performance status, and exon 19 deletion (Table ##TAB##0##1##).</p>", "<title>Progression-free and overall survival</title>", "<p id=\"Par29\">The median follow-up duration was 43 (35–103) months for the survivors (42 patients) at the time of analysis. Only one patient was lost to follow-up for survival status after receiving a 14-day prescription of gefitinib and was excluded from the analysis for PFS and OS. The median PFS and OS from the start of EGFR-TKI treatment for all patients were 11 and 25 months, respectively, while those for the 214 patients with EGFR-activating mutation were 12 and 26 months. Patients with exon 19 deletion had significantly longer median OS compared to those with other mutations (30 vs. 22 months, <italic>p</italic>=0.047, Fig. ##FIG##0##1##B), without a difference in PFS (12 vs. 9 months, <italic>p</italic>=0.138, Fig. ##FIG##0##1##A). Patients treated with afatinib showed significantly longer median OS (30 vs. 23 months, <italic>p</italic>=0.037, Fig. ##FIG##1##2##B) compared to those treated with first-generation TKIs, without a difference in PFS (14 vs. 10 months, <italic>p</italic>=0.179, Fig. ##FIG##1##2##A). In the multivariate analysis, EGFR exon 19 deletion showed independent association with favorable OS (<italic>p</italic>=0.028), while age &gt;70 years (<italic>p</italic>=0.017), ECOG performance status ≥2 (<italic>p</italic>=0.001), primary metastatic disease (<italic>p</italic>=0.007), and synchronous brain metastasis (<italic>p</italic>=0.026) were independent prognostic factors for unfavorable OS (Table ##TAB##1##2##).</p>", "<p id=\"Par30\">In patients with EGFR exon 19 deletion, significant differences were not observed in median PFS (12 vs. 12 months, <italic>p</italic>=0.868) and OS (31 vs. 28 months, <italic>p</italic>=0.361) between patients treated with afatinib and those treated with first-generation TKIs. However, afatinib resulted in significantly better PFS (15 vs. 9 months, <italic>p</italic>=0.042) and OS trend (27 vs. 19 months, <italic>p</italic>=0.069) compared to first-generation TKIs in patients with other EGFR mutations (Table ##TAB##2##3##). In patients receiving first-generation EGFR-TKIs, EGFR exon 19 deletion was significantly associated with better median PFS (12 vs. 9 months, <italic>p</italic>=0.031) and OS (28 vs. 19 months, <italic>p</italic>=0.045) compared to other mutations, while there was no difference in median PFS and OS based on EGFR mutation subtypes in those treated with afatinib (Table ##TAB##2##3##).\n</p>", "<p id=\"Par31\">Of the patients who experienced disease progression after first-line EGFR-TKI treatment, those treated with third-generation TKIs demonstrated significantly longer median OS (44 months) from the start of first-line treatment compared to others (183 patients, 20 months, p&lt;0.0001) as well as those who received cytotoxic agents with or without first- or second-generation TKIs (96 patients, 24 months, <italic>p</italic>=0.006) (Fig. ##FIG##2##3##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par32\">In several retrospective/prospective studies and meta-analyses of those studies, first-generation EGFR-TKI therapy has revealed more favorable outcomes in patients with EGFR exon 19 deletion when compared to those with L858R mutation, especially in terms of PFS [##REF##26967328##21##, ##REF##23945384##24##, ##REF##20430469##26##, ##REF##25222496##28##]. Regarding second-generation EGFR-TKIs, an OS survival benefit of afatinib treatment was observed in patients with exon 19 deletion but not those with L858R mutation in a combined analysis of phase III studies (LUX-Lung 3, LUX-Lung 6) comparing cisplatin doublet chemotherapy with afatinib as a first-line setting [##REF##25589191##40##]. A few molecular mechanisms were suggested, including higher drug-binding affinity [##REF##17332364##41##, ##REF##16912195##42##], different downstream signaling after drug treatment, and lesser baseline combined T790M mutation in exon 19 deletion [##REF##25222496##28##], for the better efficacy of EGFR-TKIs in exon 19 deletion compared with L858R mutation [##REF##17332364##41##–##REF##28352061##43##]. However, subsequent retrospective studies and a metanalysis including afatinib and dacomitinib showed no significant differences in outcomes, especially OS, based on the type of EGFR mutation in first-line setting [##REF##33866796##27##, ##REF##26490356##29##, ##REF##34558665##36##]. Similarly, in our cohort, patients with EGFR exon 19 deletion did not show significantly better outcomes compared with those with other mutations when treated with afatinib, while EGFR exon 19 deletion showed longer PFS and OS in patients treated with first-generation EGFR-TKIs, with an independently favorable prognostic significance of exon 19 deletion in terms of OS for all patients. Although the difference in PFS and OS between patients with EGFR exon 19 deletion and other mutations treated with first-generation TKIs is rather small compared with that reported in a previous study on patients with first-line gefitinib treatment, probably due to the longer follow-up duration, which resulted in progression in the majority of patients, the trend toward favorable clinical outcomes in patients with EGFR exon 19 deletion has been observed consistently [##REF##26967328##21##]. The lack of improved PFS in patients with exon 19 deletion in the entire cohort may be explained by no significant difference in PFS based on mutation type in the afatinib group. Moreover, the significantly higher proportion of patients treated with third-generation TKIs after progression in exon 19 deletion compared with other mutations may be one of the possible explanations for favorable OS in patients with exon 19 deletion [##REF##29850136##44##]. However, this result should be validated in further trials including larger numbers of patients.</p>", "<p id=\"Par33\">Furthermore, in our study, patients with EGFR exon 19 deletion revealed almost similar median PFS and OS when they received either first-generation EGFR-TKIs or afatinib, while significantly longer median PFS and a better OS trend were observed in patients with other EGFR mutations receiving afatinib. It remains unclear whether the clinical efficacy of second-generation TKIs is superior to that of first-generation TKIs, as only dacomitinib has demonstrated an OS benefit compared to gefitinib [##REF##33331989##20##]. Moreover, with second-generation TKIs, even with dose modification, the incidence of overall and grade ≥ 3 adverse events resulting in negative effects on patients’ quality of life (e.g., skin toxicity and diarrhea) is usually higher than that with first-generation TKIs [##REF##29898592##16##–##REF##28958502##18##, ##REF##30783814##45##]. These concerns about the toxicity of afatinib may be reflected in the higher proportion of younger patients and the better performance status of patients treated with afatinib in the present study cohort. Because a proper agent must be selected based on the risk–benefit balance for each patient in clinical practice, the results of present study suggest that first-generation TKIs can be used more safely in poor performance status or elderly patients without compromising clinical efficacy compared to second-generation TKIs, especially those with exon 19 deletion.</p>", "<p id=\"Par34\">In the FLAURA trial, osimertinib resulted in significant prolongation of PFS with a marginal OS benefit compared to first-generation EGFR-TKIs [##REF##29151359##10##, ##REF##31751012##11##]. However, in Asian patients and those with EGFR L858R mutation, OS benefit of osimertinib was not observed [##REF##31751012##11##]. In the present study, patients treated with third-generation TKIs after first- or second-generation TKI failure showed a median OS of 44 months from the start of first-line therapy, comparable to that of osimertinib (38.6 months) in the FLAURA trial [##REF##31751012##11##]. Considering that prospective data directly comparing second- and third-generation EGFR-TKIs are not currently available, the results of a few studies including ours suggest that first-line second-generation TKIs and sequential third-generation EGFR-TKI treatment may be an effective therapeutic strategy, especially in patients with EGFR L868R mutation [##REF##33331989##20##, ##REF##35958320##46##]. Overall, first-line first- or second-generation EGFR-TKIs may still be a reasonable choice in routine practice due to its cost-effectiveness [##REF##36204237##47##] in countries where first-line osimertinib is not reimbursable, such as Korea.</p>", "<p id=\"Par35\">The current study demonstrated that EGFR exon 19 deletion was associated independently with favorable OS in advanced NSCLC patients treated with first-line EGFR-TKIs. To the best of our knowledge, current study is the first one showing a significantly favorable OS in patients with EGFR exon 19 deletion, when compared with other mutations in advanced NSCLC patients treated with either first- or second-generation EGFR-TKIs as first-line therapy. Moreover, as this study analyzed every EGFR mutation-positive patient who received first-line first- or second-generation EGFR-TKIs therapy during the defined period with a fairly long follow-up duration (minimum follow-up duration of survivors: 35 months), it reflected the patient outcomes of everyday clinical practice.</p>", "<p id=\"Par36\">However, several limitations were included in this study. First, it was retrospective and performed at a single institution. Second, the number of patients who received third-generation TKIs as second- or further-line therapy was small, as second- or further-line osimertinib treatment has been reimbursable by the Korean national health insurance system since late 2017. Finally, the collection of treatment-related adverse events was not planned considering the retrospective nature of this study.</p>", "<p id=\"Par37\">Nonetheless, several clinical implications can be suggested by the results of our study. First, first-generation EGFR-TKIs could still be recommended as a first-line palliative treatment for NSCLC with EGFR exon 19 deletion, especially in elderly and fragile patients. Second, patients and their families could receive more precise explanations regarding the outcomes and further treatment options after EGFR-TKI therapy based on the types of EGFR mutation. Finally, this study recommends that further clinical trials with EGFR-TKIs should still consider the types of EGFR mutation as a stratification factor.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par38\">The EGFR exon 19 deletion was correlated with favorable OS in advanced NSCLC treated with first-line EGFR-TKIs. Moreover, in patients with exon 19 deletion, first-generation TKIs seem to be a reasonable treatment option if osimertinib is unavailable.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Both first and second-generation EGFR-TKIs are recommended in advanced NSCLC with common EGFR mutations. However, there are few data on the difference in efficacy of EGFR-TKIs based on the type of EGFR mutation and agents.</p>", "<title>Methods</title>", "<p id=\"Par2\">This retrospective real-world study evaluated the outcomes and clinicopathologic characteristics, including the type of EGFR mutations, of 237 advanced NSCLC patients treated with first- or second-generation (afatinib) EGFR-TKIs as first-line therapy.</p>", "<title>Results</title>", "<p id=\"Par3\">The median progression-free survival (PFS) and overall survival (OS) of all patients were 11 months (M) and 25M, respectively. In the univariate analysis, patients with exon 19 deletion (del) (<italic>n</italic>=130) had significantly longer median OS compared to those with other mutations (L858R: 84, others: 23) (30 vs. 22 M, <italic>p</italic>=0.047), without a difference in PFS (<italic>p</italic>=0.138). Patients treated with afatinib (<italic>n</italic>=60) showed significantly longer median OS compared to those treated with first-generation TKIs (gefitinib: 159, erlotinib: 18) (30 vs. 23 M, <italic>p</italic>=0.037), without a difference in PFS (<italic>p</italic>=0.179). In patients with exon 19 del, there was no significant difference in median PFS (<italic>p</italic>=0.868) or OS (<italic>p</italic>=0.361) between patients treated with afatinib and those treated with first-generation TKIs, while significantly better PFS (<italic>p</italic>=0.042) and trend in OS (<italic>p</italic>=0.069) were observed in patients receiving afatinib in other mutations. Exon 19 del was independently associated with favorable OS (<italic>p</italic>=0.028), while age &gt;70 years (<italic>p</italic>=0.017), ECOG performance status ≥2 (<italic>p</italic>=0.001), primary metastatic disease (<italic>p</italic>=0.007), and synchronous brain metastasis (<italic>p</italic>=0.026) were independent prognostic factors of poor OS.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The EGFR exon 19 del was associated with favorable OS in advanced NSCLC patients receiving first-line EGFR-TKIs. Moreover, in patients with exon 19 del, first-generation TKIs seem to be a reasonable treatment option if osimertinib is unavailable.</p>", "<title>Keywords</title>" ]
[]
[ "<p>The authors are grateful to Geum Sook Jeong for administrative assistance in preparing and submitting the manuscript.</p>", "<p>This study was presented in part at the 2023 American Society of Clinical Oncology annual meeting (online publication), and 15th Annual Meeting of the Korean Society of Medical Oncology and 2022 International Conference (KSMO 2022, poster).</p>", "<title>Authors’ contributions</title>", "<p>T.-H.K., J.-H.C. and Y.W.C. designed and planned the study. T.-H.K., J.-H.C., M.S.A., H.W.L., S.Y.K., and Y.W.C. collected and analyzed clinical data, and Y.W.K. analyzed and confirmed pathologic data. T.-H.K. and J.-H.C. wrote the main manuscript and J.-H.C. and Y.W.C. edited the manuscript. T.-H.K., J.-H.C., and Y.W.C. performed statistical analysis and S.-S.S. reviewed the statistical analysis. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This work was supported in part by Samyang Biopharmaceuticals Corporation, Korea to J.-H.C., and by National Research Foundation of Korea and by the Korea Health Technology R&amp;D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health &amp; Welfare, Republic of Korea to Y.W.C. (NRF-2021R1C1C1012266, HR22C1734).</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated and/or analyzed during the current study are not publicly available due to the confidentiality of the data of patient but are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par39\">This research protocol was approved by the Institutional Review Board (IRB) of Ajou University Hospital, <italic>Suwon, Republic of Korea (AJOUIRB-MDB-2019-394)</italic> and all methods were performed in accordance with the relevant guidelines and regulations. The study was designed retrospectively. Written informed consent from patients was not required in accordance with guidelines of the IRB <italic>of Ajou University hospital</italic>.</p>", "<title>Consent for publication</title>", "<p id=\"Par40\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par41\">J.-H.C. received research grants from AstraZeneca, Roche, and Yuhan Corporation, Korea.</p>", "<p id=\"Par42\">T.-H.K., M.S.A., H.W.L., S.Y.K., Y.W.C., Y.W.K., and S.-S.S. declare no conflicts of interest. </p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p><bold>A</bold> Progression-free survival and (<bold>B</bold>) overall survival from the start of EGFR-TKI according to EGFR mutation subtypes. Exon 19 deletion: 130 patients, others: 106 patients (L858R: 83, uncommon mutations: 18, dual mutations: 5). Censoring was indicated by vertical lines</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p><bold>A</bold> Progression-free survival and (<bold>B</bold>) overall survival from the start of EGFR-TKI according to types of tyrosine kinase inhibitors. Exon 19 deletion: 130 patients, others: 106 patients (L858R: 83, uncommon mutations: 18, dual mutations: 5). Censoring was indicated by vertical lines</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Overall survival from the start of 1st line treatment according to the 2nd or further line agents in patients with progressive disease after EGFR TKI. <bold>A</bold> Exon 19 deletion: 124 patients, others: 96 patients (L858R: 74, uncommon mutations: 17, dual mutations: 5) and (<bold>B</bold>) Exon 19 deletion: 81 patients, others: 52 patients (L858R: 39, uncommon mutations: 12, dual mutation: 1). Censoring was indicated by vertical lines</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Patient characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"><bold>Clinical characteristics</bold></th><th align=\"left\"><bold>Exon 19 deletion (</bold><bold><italic>n</italic></bold><bold>=130)</bold></th><th align=\"left\"><bold>Others (</bold><bold><italic>n</italic></bold><bold>=107)</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>*</bold></th><th align=\"left\"><bold>1st generation TKI (</bold><bold><italic>n</italic></bold><bold>=177)</bold></th><th align=\"left\"><bold>Afatinib</bold><break/><bold>(</bold><bold><italic>n</italic></bold><bold>=60)</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>*</bold></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"7\">Age, years</td></tr><tr><td align=\"left\"> ≤70</td><td align=\"left\">86 (66.2%)</td><td align=\"left\">65 (60.7%)</td><td align=\"left\">0.417</td><td align=\"left\">101 (57.1%)</td><td align=\"left\">50 (83.3%)</td><td align=\"left\" rowspan=\"2\">&lt;0.0001</td></tr><tr><td align=\"left\"> &gt;70</td><td align=\"left\">44 (33.8%)</td><td align=\"left\">42 (39.3%)</td><td align=\"left\"/><td align=\"left\">76 (42.9%)</td><td align=\"left\">10 (16.7%)</td></tr><tr><td align=\"left\" colspan=\"7\">Gender</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">75 (57.7%)</td><td align=\"left\">63 (58.9%)</td><td align=\"left\">0.895</td><td align=\"left\">115 (65.0%)</td><td align=\"left\">23 (38.3%)</td><td align=\"left\" rowspan=\"2\">&lt;0.0001</td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">55 (42.3%)</td><td align=\"left\">44 (41.1%)</td><td align=\"left\"/><td align=\"left\">62 (35.0%)</td><td align=\"left\">37 (61.7%)</td></tr><tr><td align=\"left\" colspan=\"7\">Smoking</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">80 (61.5%)</td><td align=\"left\">59 (55.1%)</td><td align=\"left\">0.355</td><td align=\"left\">115 (65.0%)</td><td align=\"left\">24 (40.0%)</td><td align=\"left\" rowspan=\"2\">0.001</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">50 (38.5%)</td><td align=\"left\">48 (44.9%)</td><td align=\"left\"/><td align=\"left\">62 (35.0%)</td><td align=\"left\">36 (60.0%)</td></tr><tr><td align=\"left\" colspan=\"7\">ECOG PS</td></tr><tr><td align=\"left\"> 0/1</td><td align=\"left\">108 (83.1%)</td><td align=\"left\">86 (80.4%)</td><td align=\"left\">0.615</td><td align=\"left\">139 (78.5%)</td><td align=\"left\">55 (91.7%)</td><td align=\"left\" rowspan=\"2\">0.021</td></tr><tr><td align=\"left\"> ≥2</td><td align=\"left\">22 (16.9%)</td><td align=\"left\">21 (19.6%)</td><td align=\"left\"/><td align=\"left\">38 (21.5%)</td><td align=\"left\">5 (8.3%)</td></tr><tr><td align=\"left\" colspan=\"7\">Brain metastasis</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">88 (67.7%)</td><td align=\"left\">72 (67.3%)</td><td align=\"left\">1.000</td><td align=\"left\">120 (67.8%)</td><td align=\"left\">40 (66.7%)</td><td align=\"left\" rowspan=\"2\">0.874</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">42 (32.3%)</td><td align=\"left\">35 (32.7%)</td><td align=\"left\"/><td align=\"left\">57 (32.2%)</td><td align=\"left\">20 (33.3%)</td></tr><tr><td align=\"left\" colspan=\"7\">Disease status</td></tr><tr><td align=\"left\"> Recurrent</td><td align=\"left\">20 (15.4%)</td><td align=\"left\">18 (16.8%)</td><td align=\"left\">0.859</td><td align=\"left\">27 (15.3%)</td><td align=\"left\">11 (18.3%)</td><td align=\"left\" rowspan=\"2\">0.549</td></tr><tr><td align=\"left\"> Primary metastatic</td><td align=\"left\">110 (84.6%)</td><td align=\"left\">89 (83.2%)</td><td align=\"left\"/><td align=\"left\">150 (84.7%)</td><td align=\"left\">49 (81.7%)</td></tr><tr><td align=\"left\" colspan=\"7\">Type of EGFR mutation</td></tr><tr><td align=\"left\"> Exon 19 deletion</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">88 (49.7)</td><td align=\"left\">42 (70.0)</td><td align=\"left\" rowspan=\"2\">0.007</td></tr><tr><td align=\"left\"> Others</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">89 (50.3)</td><td align=\"left\">18 (30.0)</td></tr><tr><td align=\"left\" colspan=\"7\">3rd generation TKI after PD<sup>a</sup></td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">31 (25.0%)</td><td align=\"left\">6 (6.2%)</td><td align=\"left\">&lt;0.0001</td><td align=\"left\">23 (13.9%)</td><td align=\"left\">14 (25.9%)</td><td align=\"left\" rowspan=\"2\">0.058</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">93 (75.0%)</td><td align=\"left\">90 (93.8%)</td><td align=\"left\"/><td align=\"left\">143 (86.1%)</td><td align=\"left\">40 (74.1%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Univariate and multivariate analysis of progression-free and overall survival</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\" colspan=\"5\"><bold>PFS</bold></th><th align=\"left\" colspan=\"5\"><bold>OS</bold></th></tr><tr><th align=\"left\"><bold>Clinical characteristics</bold></th><th align=\"left\"><bold>M</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>*</bold></th><th align=\"left\"><bold>HR</bold></th><th align=\"left\"><bold>95%CI</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>†</bold></th><th align=\"left\"><bold>M</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>*</bold></th><th align=\"left\"><bold>HR</bold></th><th align=\"left\"><bold>95% CI</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>†</bold></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"11\">Age, years</td></tr><tr><td align=\"left\"> ≤70</td><td align=\"left\">10.0</td><td align=\"left\">0.270</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">28.0</td><td align=\"left\">0.004</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\" rowspan=\"2\">0.017</td></tr><tr><td align=\"left\"> &gt;70</td><td align=\"left\">14.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">22.0</td><td align=\"left\"/><td align=\"left\">1.47</td><td align=\"left\">1.07-2.01</td></tr><tr><td align=\"left\" colspan=\"11\">Gender</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">12.0</td><td align=\"left\">0.481</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">24.0</td><td align=\"left\">0.752</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\" rowspan=\"2\"/></tr><tr><td align=\"left\"> Male</td><td align=\"left\">11.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">25.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"11\">Smoking</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">12.0</td><td align=\"left\">0.365</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">27.0</td><td align=\"left\">0.359</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\" rowspan=\"2\"/></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">11.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">23.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"11\">ECOG PS</td></tr><tr><td align=\"left\"> 0/1</td><td align=\"left\">13.0</td><td align=\"left\">&lt;0.0001</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">0.001</td><td align=\"left\">29.0</td><td align=\"left\">&lt;0.0001</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\" rowspan=\"2\">0.001</td></tr><tr><td align=\"left\"> ≥2</td><td align=\"left\">7.0</td><td align=\"left\"/><td align=\"left\">1.80</td><td align=\"left\">1.26-2.56</td><td align=\"left\"/><td align=\"left\">12.0</td><td align=\"left\"/><td align=\"left\">1.88</td><td align=\"left\">1.28-2.75</td></tr><tr><td align=\"left\" colspan=\"11\">Brain metastasis</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">14.0</td><td align=\"left\">&lt;0.0001</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">0.001</td><td align=\"left\">30.0</td><td align=\"left\">&lt;0.0001</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\" rowspan=\"2\">0.026</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">9.0</td><td align=\"left\"/><td align=\"left\">1.65</td><td align=\"left\">1.22-2.23</td><td align=\"left\"/><td align=\"left\">19.0</td><td align=\"left\"/><td align=\"left\">1.46</td><td align=\"left\">1.05-2.02</td></tr><tr><td align=\"left\" colspan=\"11\">Disease status</td></tr><tr><td align=\"left\"> Recurrent</td><td align=\"left\">17.0</td><td align=\"left\">0.005</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">0.059</td><td align=\"left\">48.0</td><td align=\"left\">&lt;0.0001</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\" rowspan=\"2\">0.007</td></tr><tr><td align=\"left\"> Primary metastatic</td><td align=\"left\">11.0</td><td align=\"left\"/><td align=\"left\">1.46</td><td align=\"left\">0.99-2.15</td><td align=\"left\"/><td align=\"left\">23.0</td><td align=\"left\"/><td align=\"left\">1.86</td><td align=\"left\">1.18-2.92</td></tr><tr><td align=\"left\" colspan=\"11\">Type of TKI</td></tr><tr><td align=\"left\"> 1<sup>st</sup> generation</td><td align=\"left\">10.0</td><td align=\"left\">0.179</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">23.0</td><td align=\"left\">0.037</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\" rowspan=\"2\">0.595</td></tr><tr><td align=\"left\"> Afatinib</td><td align=\"left\">14.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">30.0</td><td align=\"left\"/><td align=\"left\">0.90</td><td align=\"left\">0.62-1.31</td></tr><tr><td align=\"left\" colspan=\"11\">Type of EGFR mutation</td></tr><tr><td align=\"left\"> Others</td><td align=\"left\">9.0</td><td align=\"left\">0.138</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">22.0</td><td align=\"left\">0.047</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\" rowspan=\"2\">0.028</td></tr><tr><td align=\"left\"> Exon 19 deletion</td><td align=\"left\">12.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">30.0</td><td align=\"left\"/><td align=\"left\">0.72</td><td align=\"left\">0.54-0.97</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Outcomes according to types of EGFR mutation and tyrosine kinase inhibitors</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"><bold>Type of EGFR mutation</bold></th><th align=\"left\"><bold>Type of TKI</bold></th><th align=\"left\"><bold>M</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>*</bold></th><th align=\"left\"><bold>Type of TKI</bold></th><th align=\"left\"><bold>Type of EGFR mutation</bold></th><th align=\"left\"><bold>M</bold></th><th align=\"left\"><bold><italic>p</italic></bold><bold>*</bold></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"4\">Median PFS</td><td align=\"left\" rowspan=\"2\">Exon 19 deletion</td><td align=\"left\">1<sup>st</sup> generation</td><td align=\"left\">12.0</td><td align=\"left\">0.868</td><td align=\"left\">1<sup>st</sup> generation</td><td align=\"left\">Exon 19 deletion</td><td align=\"left\">12.0</td><td align=\"left\" rowspan=\"2\">0.031</td></tr><tr><td align=\"left\">Afatinib</td><td align=\"left\">12.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Others</td><td align=\"left\">9.0</td></tr><tr><td align=\"left\" rowspan=\"2\">Others</td><td align=\"left\">1<sup>st</sup> generation</td><td align=\"left\">9.0</td><td align=\"left\">0.042</td><td align=\"left\">Afatinib</td><td align=\"left\">Exon 19 deletion</td><td align=\"left\">12.0</td><td align=\"left\" rowspan=\"2\">0.305</td></tr><tr><td align=\"left\">Afatinib</td><td align=\"left\">15.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Others</td><td align=\"left\">15.0</td></tr><tr><td align=\"left\" rowspan=\"4\">Median OS</td><td align=\"left\" rowspan=\"2\">Exon 19 deletion</td><td align=\"left\">1<sup>st</sup> generation</td><td align=\"left\">28.0</td><td align=\"left\">0.361</td><td align=\"left\">1<sup>st</sup> generation</td><td align=\"left\">Exon 19 deletion</td><td align=\"left\">28.0</td><td align=\"left\" rowspan=\"2\">0.045</td></tr><tr><td align=\"left\">Afatinib</td><td align=\"left\">31.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Others</td><td align=\"left\">19.0</td></tr><tr><td align=\"left\" rowspan=\"2\">Others</td><td align=\"left\">1<sup>st</sup> generation</td><td align=\"left\">19.0</td><td align=\"left\">0.069</td><td align=\"left\">Afatinib</td><td align=\"left\">Exon 19 deletion</td><td align=\"left\">31.0</td><td align=\"left\" rowspan=\"2\">0.604</td></tr><tr><td align=\"left\">Afatinib</td><td align=\"left\">27.0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Others</td><td align=\"left\">27.0</td></tr></tbody></table></table-wrap>" ]
[]
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[ "<table-wrap-foot><p><italic>ECOG</italic> Eastern Cooperative Oncology Group, <italic>PS</italic> Performance status, <italic>TKI</italic> Tyrosine kinase inhibitor, <italic>PD</italic> Progressive disease, <italic>M</italic> Months (median), <italic>p p</italic>-value</p><p>*Fisher’s exact test</p><p><sup>a</sup>Excluding 17 patients without documentation of PD</p></table-wrap-foot>", "<table-wrap-foot><p><italic>PFS</italic> Progression-free survival, <italic>OS</italic> Median overall survival, <italic>HR</italic> hazard ratio, <italic>CI</italic> Confidence interval, <italic>ECOG</italic> Eastern Cooperative Oncology Group, <italic>PS</italic> Performance status, <italic>TKI</italic> Tyrosine kinase inhibitor, <italic>EGFR</italic> Epidermal growth factor receptor; <italic>M</italic> Months (median), <italic>p p</italic>-value</p><p><sup>*</sup>Log-rank test †Cox proportional-hazards regression model</p></table-wrap-foot>", "<table-wrap-foot><p><italic>EGFR</italic> Epidermal growth factor receptor, <italic>TKI</italic> Tyrosine kinase inhibitor, <italic>M</italic> months (median), <italic>p p</italic>-value, <italic>OS</italic> Overall survival, <italic>PFS</italic> Progression-free survival</p><p><sup>*</sup>Log-rank test</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Tae-Hwan Kim and Jin-Hyuk Choi contributed equally.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12885_2023_11782_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12885_2023_11782_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12885_2023_11782_Fig3_HTML\" id=\"MO3\"/>" ]
[]
[{"label": ["7."], "mixed-citation": ["Reck M, Popat S, Reinmuth N, De Ruysscher D, Kerr KM, Peters S, Group EGW: Metastatic non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2014, 25 Suppl 3:iii27-39."]}, {"label": ["9."], "mixed-citation": ["Hendriks LE, Kerr KM, Menis J, Mok TS, Nestle U, Passaro A, Peters S, Planchard D, Smit EF, Solomon BJ et al: Oncogene-addicted metastatic non-small-cell lung cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol. 2023;34(4):358\u201376."]}, {"label": ["37."], "mixed-citation": ["Edge SB, American Joint Committee on Cancer.: AJCC cancer staging manual, 7th edn. New York: Springer; 2010."]}, {"label": ["39."], "mixed-citation": ["Nagai Y, Miyazawa H, Huqun, Tanaka T, Udagawa K, Kato M, Fukuyama S, Yokote A, Kobayashi K, Kanazawa M et al: Genetic heterogeneity of the epidermal growth factor receptor in non-small cell lung cancer cell lines revealed by a rapid and sensitive detection system, the peptide nucleic acid-locked nucleic acid PCR clamp. Cancer Res. 2005, 65(16):7276-7282."]}]
{ "acronym": [ "NSCLC", "OS", "EGFR", "TKIs", "PFS", "AJCC", "PS", "ECOG", "FFPE", "PCR", "PNA-LNA", "IRB" ], "definition": [ "Non-small cell lung cancer", "Overall survival", "Epidermal growth factor receptor", "Tyrosine kinase inhibitors", "Progression-free survival", "American Joint Committee on Cancer", "Performance status", "Eastern Cooperative Oncology Group", "Formalin-fixed, paraffin embedded", "Polymerase chain reaction", "Peptide nucleic acid-locked nucleic acid", "Institutional review board" ] }
47
CC BY
no
2024-01-14 23:43:45
BMC Cancer. 2024 Jan 12; 24:70
oa_package/dc/ca/PMC10787420.tar.gz
PMC10787421
38216865
[ "<title>Introduction</title>", "<p id=\"Par4\"><italic>Cromileptes altivelis</italic> (Serranidae: Cromileptes) and <italic>Epinephelus lanceolatus</italic> (Serranidae: Epinephelus) have been widely cultivated in China and Southeast Asian countries, possessing commercial importance fishing market species [##UREF##0##1##, ##REF##24372271##2##]. The appearance of <italic>C. altivelis</italic> is distinct from fish of the subfamily Epinephelinae, because it has a concave slope on the back of head, hump-like bulge on the back and dark gray-brown body with black spots, so it can also be called “humpback grouper” [##UREF##1##3##]. Juvenile <italic>C. altivelis</italic> is kept as ornamental fish, while the adult is important to commercial mariculture. <italic>E. lanceolatus</italic> (also named as giant grouper) is regarded as a high-value species in fish markets due to its fast growing, large size and high nutritional value [##UREF##2##4##]. It is distinguished by small eye, wide interorbital area, body with irregular whitish blotches and numerous small black spots, and fins slightly yellowish with irregular blackish and whitish marking [##UREF##3##5##]. Groupers are usually considered to be protogynous hermaphrodites, and their sex type changes from female to male as they mature. Mature males are hard to obtain because of their huge body size and long time to maturity, so it is quite difficult to artificially reproduce them [##UREF##4##6##]. Hybridization is the most effective and widely used technique in the artificial breeding of grouper, which can produce offspring with more desirable phenotypic characteristics than those of the parent [##REF##25041755##7##]. Many excellent offspring have been obtained using <italic>C. altivelis</italic> or <italic>E. lanceolatus</italic> as parent: <italic>C. altivelis</italic> (♀) × <italic>E. tukula</italic> (♂) [##UREF##5##8##], <italic>E. moara</italic> (♀) × <italic>E. lanceolatus</italic> (♂) [##UREF##6##9##], <italic>E. coioides</italic> (♀) × <italic>E. lanceolatus</italic> (♂) [##UREF##7##10##]. The hybrid grouper derived from the crossing of <italic>C. altivelis</italic> (♀) and <italic>E. lanceolatus</italic> (♂) exhibits the combined advantages of the parent species, with faster growth and improved taste when compared with wild groupers. However, the genetic traits in the hybrid grouper are poorly understood.</p>", "<p id=\"Par5\">Morphological research relies heavily on statistics and classification methods using measurable, countable, and partly descriptive traits in fish [##UREF##8##11##]. Where parents differ physically from one another, morphological analysis is a useful tool in revealing the genetic relationship between hybrid progenies and parents [##UREF##7##10##]. However, it cannot effectively identify the genetic relationship between offspring and parents only by phenotypic characteristics. When combined with morphological analysis, molecular markers can greatly improve the accuracy of hybrid identification. In eukaryotes, the ribosomal DNA multigene family is organized in coding regions and non-transcribed spacer (NTS) regions. Because concerted and birth-and-death evolution mechanisms act simultaneously in rDNA, the coding regions show high conservation, while the NTS regions exhibit different rates of variation within and between taxa. This trait of rDNA sequence structure makes it a good molecular marker for the investigation of rapid evolutionary events [##UREF##9##12##–##UREF##10##14##]. Intergenic spacers (IGS) can separate these rDNA repeats, and present between two successive genes [##REF##17200233##15##]. IGS transcripts play an important role in the epigenetic control of the rDNA locus [##UREF##11##16##]. DNA methylation, essentially the methylation of cytosine nucleotides, is the first identified epigenetic mechanism [##REF##2423876##17##] and has been extensively studied. Accumulated studies suggested that DNA methylation was closely correlated with the heterosis in animals. Ou et al<italic>.</italic> have reported that the association of DNA methylation with the growth heterosis in snakehead fish [##REF##30978477##18##]. Jiang et al<italic>.</italic> have found that DNA methylation can be involved in the heterosis formation in pig hybrids [##UREF##12##19##]. In the Pacific <italic>oyster Crassostrea gigas</italic>, the DNA methylation level is associated with the superior growth of the hybrid crosses [##UREF##13##20##].</p>", "<p id=\"Par6\">Mitochondria DNA (mtDNA) is also valued for tracking the ancestry of breeds back hundreds of generations [##REF##9465125##21##], because the organization in most fish mtDNA genomes is quite conserved [##UREF##14##22##]. Many researchers analyzed the mtDNA D-loop region and cytochrome oxidase subunit 1 (COI) to assess phylogenetic relationships and maternal origin of different fish populations [##UREF##15##23##–##REF##26187073##25##]. In this study, we investigated the phenotypic characteristics, chromosomal numbers, rDNA and mtDNA sequences, the DNA methylation level of 5S rDNA IGS sequences between the hybrid grouper and its parents. Based on our data, the genetic traits of the hybrid grouper (<italic>C. altivelis</italic> (♀) × <italic>E. lanceolatus</italic> (♂)) were explored.</p>" ]
[ "<title>Materials and methods</title>", "<title>Ethics statement</title>", "<p id=\"Par7\">All experiments were conducted in accordance with the guidelines statement of the Administration of Affairs Concerning Animal Experimentation of China. The health of the fish and environmental conditions were monitored daily.</p>", "<title>Collection of experimental fish</title>", "<p id=\"Par8\">The fry of <italic>E. lanceolatus</italic> were derived from Delin Chengxin Aquaculture Co., Ltd, Hainan Province, China. Two-month-old <italic>C. altivelis</italic> and two-month-old the hybrid groupers were collected from Hainan Chenhai Aquatic Co., Ltd, Hainan Province. All samples were raised up to two years old at Delin Chengxin Aquaculture Co., Ltd. Total genomic DNA was isolated from peripheral blood cells.</p>", "<title>Measurement of morphological data</title>", "<p id=\"Par9\">A total of 30 individuals aged 2 years of each from <italic>C. altivelis</italic>, <italic>E. lanceolatus</italic> and the hybrid grouper were selected at random. Fish were anaesthetized with 3-aminobenzoic acid ethyl ester methanesulfonate before measuring. The total length, standard length, body height, head length, caudal peduncle length and caudal peduncle height were measured. The average ratios of total length to standard length, head length to standard length, body height to standard length, caudal peduncle length to standard length and caudal peduncle height to standard length were recorded.</p>", "<title>Preparation of chromosome spreads</title>", "<p id=\"Par10\">The fin cells of <italic>C. altivelis</italic>, <italic>E. lanceolatus</italic> and the hybrid grouper were used for chromosome preparation. The method of fin cell culture and chromosome preparation described by Alvarez et al. was used with some modification [##UREF##17##26##]. Before collecting cells, concanavalin was added to the cells three times in one-hour intervals. The final concentration was 0.1 μg/mL. The collected cells underwent hypotonic treatment with 0.075 mol/L KCl at 37 °C for 15–20 min and were then fixed in methanol-acetic acid (3:1) for 20 min with two changes. Chromosome preparations were examined under an oil lens. Two-hundred metaphase spreads were examined for each fish sample.</p>", "<title>Analysis of the genetic traits of rDNA and mtDNA</title>", "<p id=\"Par11\">Thirty <italic>C. altivelis</italic>, thirty <italic>E. lanceolatus</italic> and fifty the hybrid grouper were selected at random. Genomic DNA was extracted from the blood and fin tissue. All PCR primers were listed in Table S##SUPPL##0##1##. The PCR amplification program was conducted for 30 cycles with an annealing temperature of 30 s at 57 °C for 5S rDNA, 35 s at 55 °C for COI gene and 30 s at 50 °C for D-loop region. All PCR products underwent a series of applications such as purification, cloning, and sequencing. Multiple sequence alignment analysis was conducted using BioEdit and Clustal W [##UREF##18##27##, ##UREF##19##28##]. The RepeatMasker program (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.repeatmasker.org/\">http://www.repeatmasker.org/</ext-link>) was used to search for 5S gene repeated elements inside spacers. All sequences were submitted to the NCBI.</p>", "<title>Methylation analysis of 5S rDNA IGS sequence</title>", "<p id=\"Par12\">The DNA methylation level in 1021 bp upstream sequence of coding region was tested and analyzed to investigate the DNA methylation patterns of IGS regions in the hybrid grouper and its parents (Supplementary Figure ##SUPPL##1##1##). Muscle tissues were applied to extract genomic DNA in <italic>C. altivelis</italic> (five individuals), <italic>E. lanceolatus</italic> (seven individuals) and the hybrid grouper (five individuals). MethPrimer software package (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.urogene.org/methprimer/index.html\">http://www.urogene.org/methprimer/index.html</ext-link>) was applied for designing PCR primers (Table S##SUPPL##0##1##). PCR amplification was conducted with an annealing temperature of 30 s at 50 ~ 60 °C by KAPA HiFi HotStart Uracil + ReadyMix PCR Kit (Kapa Biosystems, Wilmington, MA, USA). Steps of bisulfite modification and pyrosequencing were showed as follow: firstly, genomic DNA (1 μg) was converted (by the ZYMO EZ DNA Methylation-Gold Kit (Zymo Research, Irvine, CA, USA)) and one-tenth of the elution products were used as templates. Bisulfite sequencing PCR products of IGS sequences were pooled equally, 5'-phosphorylated, 3' -dA-tailed and ligated to barcoded adapter using T4 DNA ligase (NEB). Secondly, Barcoded libraries from all samples were sequenced on Illumina platform [##UREF##20##29##]. Thirdly, the raw reads needed to remove adapters and filter the low-quality sequences (Trimmomatic-0.36). Finally, clear reads were obtained. The methylation levels of individual cytosines were calculated as the ratio of the total number of methylated CpG cytosines to the number of sequenced clones. A two-tailed Fisher’s Exact Test was used to test the methylated and unmethylated counts for each cytosine between two groups [##REF##25163507##30##].</p>", "<title>Phylogenetic analysis and genetic distances</title>", "<p id=\"Par13\">Mitochondrial genome sequences were obtained from the NCBI GenBank. All accession numbers of the sequences were listed in Table S##SUPPL##0##2##. Phylogenetic trees were constructed by a maximum-likelihood approach (ML) in the program PhyML 3.0 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.atgc-montpellier.fr/phyml/\">http://www.atgc-montpellier.fr/phyml/</ext-link>) and Bayesian inference (BI) using MrBayes 3.1.2 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://mrbayes.sourceforge.net/\">http://mrbayes.sourceforge.net/</ext-link>). A generalized time reversible (GTR) model with a proportion of invariable sites (I) and a gamma distribution (G) was selected for the concatenated dataset in ML. Nodal robustness was estimated by bootstrap percentage values (BP). The BP values of nodes of the subtree were obtained after 1000 replicates. MrBayes used Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution of model parameters. Convergence occurred when average standard deviation of split frequencies fell below 0.01. Posterior probability (PP) values were applied to estimate branch support. The phylogenetic trees were shown using the Figtree program v.1.4.4 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://tree.bio.ed.ac.uk/software/figtree/\">http://tree.bio.ed.ac.uk/software/figtree/</ext-link>).</p>", "<p id=\"Par14\">Between-group mean distances were calculated using MEGA 7 with a p-distance model.</p>" ]
[ "<title>Results</title>", "<title>Morphological traits</title>", "<p id=\"Par15\">There were obvious phenotypic differences between the hybrid grouper and its parents (<italic>C. altivelis</italic> and <italic>E. lanceolatus</italic>) (Fig. ##FIG##0##1##). Regarding body color, <italic>C. altivelis</italic> is white with scattered black dots and <italic>E. lanceolatus</italic> is dark brown with scattered black spots. The hybrid grouper is dark brown without any obvious black spots, which differed visibly from both parents.</p>", "<p id=\"Par16\">The measurable traits in <italic>C. altivelis</italic>, <italic>E. lanceolatus,</italic> and the hybrid grouper are presented in Table ##TAB##0##1##. The values of total length, standard length, head length, body height, and caudal peduncle height for <italic>E. lanceolatus</italic> were greater than in <italic>C. altivelis</italic>. However, the caudal peduncle length was greater for <italic>C. altivelis</italic> than for <italic>E. lanceolatus.</italic> All measurable traits differed significantly between <italic>E. lanceolatus</italic> and <italic>C. altivelis</italic> (<italic>p</italic> &lt; 0.05)<italic>.</italic> For the hybrid grouper, all measurable traits had values higher than those of <italic>C. altivelis</italic> and lower than those of <italic>E. lanceolatus</italic> (excepting for caudal peduncle length). All measurable traits with the exception of head length and body height showed significant differences between the hybrid and <italic>C. altivelis</italic> (<italic>p</italic> &lt; 0.05)<italic>.</italic>\n</p>", "<p id=\"Par17\">To control for differences in growth rate between species, the ratios of the measurable traits were recorded in the hybrid grouper and its parents. The ratios of measurable traits did not differ significantly between the hybrid grouper, <italic>C. altivelis,</italic> and <italic>E. lanceolatus</italic> (<italic>p</italic> &gt; 0.05), which indicates that all three groupers show similar morphological characteristics in terms of total length, head length, standard length, caudal peduncle length, body height, and caudal peduncle height.</p>", "<title>Examination of chromosome number</title>", "<p id=\"Par18\">The distribution of chromosome numbers in <italic>C. altivelis</italic>, <italic>E. lanceolatus</italic>, and the hybrid grouper is illustrated in Fig. ##FIG##1##2##. Among <italic>C. altivelis</italic>, 92% of the chromosomal metaphases had 48 chromosomes. Among <italic>E. lanceolatus</italic>, 90% of the chromosomal metaphases had 48 chromosomes. Among the hybrid grouper, 89% of the chromosomal metaphases had 48 chromosomes.</p>", "<title>Sequence organization and analysis of rDNA and mtDNA</title>", "<p id=\"Par19\">A single band of 5S rDNA was observed in the genomes of <italic>C. altivelis</italic> (403 bp, accession numbers: OM289959), <italic>E. lanceolatus</italic> (402 bp, accession numbers: OM289957) and the hybrid grouper. Based on the nucleotide compositions of NTS, 5S sequences in the hybrid grouper were divided into two categories (type I: 402 bp, accession numbers: OM289958; type II: 404 bp, accession numbers: OP244353). All 5S clones in samples had the same coding region sequences (Fig. ##FIG##2##3##a). The internal control regions (ICRs, i.e., the promoters for transcription)-Box A (positions 48–62), Box B (positions 65–70), and Box C (positions 78–95)-were detected in the 5S coding region. In 5S NTS region, several base substitutions or insertions/deletions were found in the hybrids and their parents. Sequence alignments of the NTS region with BLASTn showed 96.2% similarity between the hybrid grouper (type I) and <italic>C. altivelis,</italic> and 99.0% similarity between the hybrid grouper (type I) and <italic>E. lanceolatus.</italic> Type II of the hybrid grouper displayed higher conservation with <italic>C. altivelis</italic> (99.2%) compared with <italic>E. lanceolatus</italic> (95.0%) (Table ##TAB##1##2##). The TATA control element that regulates 5S gene transcription was generally located from -25 to -30 from the 5S, was also identifiable in the hybrid and parents (at -29 in all NTS sequences, where it was modified to TAAA) (Fig. ##FIG##2##3##b). In addition, long terminal repeat (LTR) retrotransposons were identified by the RepeatMasker program in the NTS regions of <italic>C. altivelis</italic> (pos. 18–122) and the hybrid grouper (type I: pos. 51–122; type II: pos. 117–223), and the (T)n simple repeat was identified in that of <italic>E. lanceolatus</italic> (pos. 88–122) (Fig. ##FIG##3##4##).</p>", "<p id=\"Par20\">The length of COI gene sequences was 1545 bp in <italic>C. altivelis</italic>, <italic>E. lanceolatus</italic>, and the hybrid grouper (Supplementary Figure ##SUPPL##2##2##). Sequence alignments with BLASTn showed that the COI gene sequences of <italic>C. altivelis</italic> and <italic>E. lanceolatus</italic> in this study was identical with the sequences in NCBI database (<italic>Cromileptes altivelis</italic>: NC_021614.1, <italic>Epinephelus lanceolatus</italic>: KM386619.1). The similarity between the hybrid grouper and <italic>C. altivelis</italic> was 99.8% (Table ##TAB##2##3##). Partial D-loop region sequences (-800 bp) were obtained in <italic>C. altivelis</italic>, <italic>E. lanceolatus</italic>, and the hybrid grouper (Supplementary Figure ##SUPPL##3##3##). The similarity between the hybrid grouper and <italic>C. altivelis</italic> was 99.0% (Table ##TAB##2##3##).\n</p>", "<title>DNA methylation analysis of 5S rDNA IGS sequence</title>", "<p id=\"Par21\">Seven CpG sites were found in the 1021 bp upstream sequence of coding region between the hybrid grouper and its parents (Fig. ##FIG##4##5##). Only two CpG sites (the position of 107 and 178 in the sequence) exhibited the significant differences between the hybrid grouper and its parents (Fig. ##FIG##4##5##A, B). In site 107, the DNA methylation level of the hybrid grouper (9.66%) was higher than that of <italic>E. lanceolatus</italic> (7.59%). There was no significant difference between the hybrid grouper and <italic>C. altivelis</italic> (Fig. ##FIG##4##5##C). In site 178, the DNA methylation level of the hybrid grouper (14.60%) was higher than that of <italic>E. lanceolatus</italic> (6.31%), but lower than that of <italic>C. altivelis</italic> (27.06%) (Fig. ##FIG##4##5##D).</p>", "<title>Genetic distances and phylogenetic analysis</title>", "<p id=\"Par22\">Genetic distances were estimated between <italic>C. altivelis, E. lanceolatus</italic> and the hybrid grouper in mtDNA and rDNA (Tables ##TAB##1##2## and ##TAB##2##3##). The hybrids and <italic>C. altivelis</italic> had the minimal genetic distance (COI gene: 0.002; D-loop region: 0.010). In 5S rDNA, the genetic distance between the hybrids and <italic>C. altivelis</italic> ranged from 0.007 to 0.050 (average value = 0.0285) and was less than the distance between the hybrids and <italic>E. lanceolatus</italic>, which ranged from 0.014 to 0.057 (average value = 0.0355).</p>", "<p id=\"Par23\">Phylogenetic analyses generated similar tree topologies in ML (Fig. ##FIG##5##6##) and BI (Fig. ##FIG##6##7##). In the phylogenetic tree, the hybrid grouper and <italic>C. altivelis</italic> were closely clustered together (COI gene: BP = 100%, PP = 1; D-loop region: BP = 100%, PP = 1). <italic>E. lanceolatus</italic> and other Epinephelus species were clustered together.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par24\">Geometric morphometrics is considered to be one of the most powerful tools in fish shape analysis [##UREF##21##31##, ##UREF##22##32##], and can most intuitively express germplasm characteristics. In our results, obvious differences in the body color and blot shape were visible between the hybrid offspring and its parents (<italic>Cromileptes altivelis</italic> and <italic>Epinephelus lanceolatus</italic>) at 2 years of age. The hybrid grouper displayed intermediate morphology compared with the parents’ measurable characteristics. In total length, standard length, caudal peduncle length, and caudal peduncle height, there were significant differences between the offspring and <italic>C. altivelis.</italic> These observations indicated that the offspring's phenotypic traits exhibited the hybridity, and supported the viewpoint that the hybrid offspring exhibits faster growth than its female parent (<italic>C. altivelis</italic>) [##UREF##23##33##].</p>", "<p id=\"Par25\">The chromosome number determines the characteristics of the species, and alterations in the chromosome number can reflect changes in genetic material during species evolution. Previous studies have shown that the ploidy level of <italic>C. altivelis</italic> and <italic>E. lanceolatus</italic> is diploid (2n = 48, [##UREF##24##34##, ##UREF##25##35##]). The ploidy level of the hybrid grouper has not been reported yet. In the present study, the hybrid grouper (2n = 48) was confirmed to be diploid by chromosome count. Such diploid offspring have previously been observed in other crosses between members of Epinephelinae: (<italic>Epinephelus fuscoguttatus</italic>, ♀ × <italic>Epinephelus lanceolatus</italic>, ♂), (<italic>Epinephelus moara</italic>, ♀ × <italic>Epinephelus lanceolatus</italic>, ♂), and <italic>Epinephelus awoara</italic>, ♀ × <italic>Epinephelus tukula</italic>, ♂) [##UREF##25##35##, ##UREF##26##36##].</p>", "<p id=\"Par26\">To further analyze genetic characteristics, rDNA and mtDNA sequences were compared between the hybrid grouper and its parents. In rDNA coding region sequences, a low intra-specific and a high rate of homogenization were observed between the hybrid grouper, the female parent (<italic>C. altivelis</italic>), and the male parent (<italic>E. lanceolatus</italic>), in which the sequence similarity of 5S was 100%, indicating the presence of concerted evolution in the rDNA of these species. In the concerted evolution model, all the members of a multi-gene family evolve in concert. Variation in the repeat unit extends to all the member genes through gene conversion and unequal crossing over, which leads to homogenization in the units of the multigene family [##REF##16285855##37##, ##UREF##27##38##].</p>", "<p id=\"Par27\">Different 5S rDNA types have been reported in freshwater fish and several plants [##REF##11681615##39##–##REF##28114894##42##]. In the bony fish, there are often two 5S gene fragments [##REF##11841188##43##], such as in <italic>Carassius auratus</italic> (2n = 100) and <italic>Cyprinus carpio</italic> (2n = 100). In our study, only one 5S gene band was found in the hybrid (2n = 48), <italic>C. altivelis</italic> (2n = 48), and <italic>E. lanceolatus</italic> (2n = 48). This result was previously observed in the genome of <italic>Megalobrama amblycephala</italic> (2n = 48)<italic>.</italic> Researchers [##UREF##27##38##] have proposed that the genomes of diploid <italic>Carassius auratus</italic> and <italic>Cyprinus carpio</italic> with 100 chromosomes likely experienced a polyploidization process and are ancient polyploidy fish. During the process, the variations and reorganizations of the genomes may have resulted in the appearance of new 5S rDNA. There was no evidence to suggest that <italic>C. altivelis</italic> and <italic>E. lanceolatus</italic> with 48 chromosomes went through the polyploidization process, and it seems reasonable to observe only one 5S gene type in their genome. In this study, all 5S gene sequences contained essential internal control regions (Box A, Box B, Box C, and TATA control element) for correct gene expression; thus, these 5S genes were likely to correspond to functional genes [##REF##28114894##42##, ##REF##10810091##44##].</p>", "<p id=\"Par28\">In the 5S NTS region, nucleotide variations (including base substitutions or insertions/deletions) discovered in the hybrids, <italic>C. altivelis</italic> and <italic>E. lanceolatus</italic> demonstrate the divergence exerted in this region, as predicated by a birth-and-death evolution model [##REF##24080995##45##]. Birth-and-death evolution leads to heterogeneity and pseudogenes in an rDNA multigene family [##REF##29253608##46##, ##REF##30055309##47##]. A mixed-mediated model between concerted evolution and birth-and-death has been described for the fish species <italic>Diplodus sargus </italic>[##UREF##28##48##], and <italic>Halobatrachus didactylus </italic>[##REF##22545758##49##]. LTR retrotransposons were identified in the NTS regions of <italic>C. altivelis</italic> and the hybrid grouper. The presence of LTR retrotransposons has been associated with genome expansion because it can potentially give rise to numerous daughter copies [##REF##19144100##50##].</p>", "<p id=\"Par29\">Phylogenetic analysis revealed that all fish species were well clustered according to their taxonomic level. Matrilineal inheritance of mtDNA was observed in <italic>C. altivelis</italic> × <italic>E. lanceolatus</italic> and other hybrids (<italic>E. fuscoguttatus</italic> × <italic>E. lanceolatus</italic>, <italic>E. moara</italic> × <italic>E. lanceolatus</italic> and <italic>E. coioides</italic> × <italic>E. lanceolatus</italic>). All hybrids were closely clustered with their female parent. The genetic distance between the hybrid grouper and female parent (<italic>C. altivelis)</italic> was lower than those between the hybrid grouper and male parent (<italic>E. lanceolatus</italic>) in 5S rDNA and mtDNA. These results indicate that the hybrid grouper had a closer genetic relationship with female parent. The genetic distance of 5S rDNA between type I of the hybrids and type II of the hybrids was 0.043. Type I and <italic>E. lanceolatus</italic> had the minimum genetic distance (0.014), type II and <italic>C. altivelis</italic> had the minimum genetic distance (0.007). These observations have suggested the presence of genetic material from both parents in the hybrid grouper.</p>", "<p id=\"Par30\">The synthesis of rRNA genes is closely related to the complex process of ribosome biogenesis, and can be regulated by changes of the transcription rate and the number of gene copies that are transcribed [##UREF##29##51##]. DNA methylation of rRNA gene promoter is an epigenetic switch, which can regulate rRNA transcription by controlling the number of rRNA genes in the on or off state [##REF##15190210##52##]. It is widely known that hypomethylation of rRNA genes promoter can facilitates the binding of transcription factor on chromatin templates and drive the synthesis of rRNA in order for ribosomes biogenesis [##UREF##29##51##, ##REF##21576262##53##]. In our results, methylation level of sites 107 and 178 presented the significant difference between the hybrid grouper and its parents. Among them, the methylation level of the hybrid grouper was in the middle compared with that of parents<italic>.</italic> Hybridization often results in dramatic genome reconfigurations including epigenetic changes [##REF##21914783##54##]. Scholars have proposed that genome epigenetic regulation is an important factor for the formation of heterosis [##UREF##30##55##, ##UREF##31##56##]. In this study, results of geometric morphometrics indicated that the growth rate of 2-year-old the hybrid grouper was higher than that of <italic>C. altivelis</italic>, exhibiting the growth advantage. As it is known, grouper generally reaches sexual maturity at 3—5 years. Before reaching sexual maturity, the demand for energy is mainly used for growth and development. The protein synthesis is indispensable in the process of growth and development. Therefore, we infer that DNA methylation of 5S rDNA IGS sequences may indirectly affect the growth and development of grouper by regulating the rate of protein synthesis, but it still requires extensive evidences to support this viewpoint.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par31\">The work in this study firstly confirmed the existence of diploid the hybrid grouper with 48 chromosomes. The molecular and phylogenetic analysis of rDNA and mtDNA recovered that the hybrid grouper has inherited the genetic materials from both of parents. The morphological trait data showed the hybrid grouper exhibits improved growth compared with <italic>C. altivelis</italic>. The DNA methylation of 5S rDNA IGS sequences in the hybrid grouper was also lower than that of <italic>C. altivelis,</italic> which provided a clue to understanding the growth advantage in the hybrid grouper.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Hybridization is a useful strategy to produce offspring with more desirable phenotypic characteristics than those of parents. The hybrid grouper derived from the cross of <italic>Cromileptes altivelis</italic> (♀, 2n = 48) with <italic>Epinephelus lanceolatus</italic> (♂, 2n = 48) exhibits improved growth compared with its female parent, which makes it valuable to aquaculture. However, the genetic traits of the hybrid grouper are poorly understood.</p>", "<title>Results</title>", "<p id=\"Par2\">The observations showed that the hybrid grouper was diploid (2n = 48) and displayed intermediate morphology with the parent's measurable characteristics. The ribosomal DNA (rDNA) and mitochondria DNA (mtDNA) were characterized at molecular and phylogenetic level. High similarity and low genetic distance of 5S rDNA and mtDNA sequences between the hybrid grouper and <italic>C. altivelis</italic> showed that the hybrid grouper had a closer genetic relationship with female parents. The reconstructed phylogenetic tree based on COI gene and D-loop region of mtDNA recovered that mtDNA was maternally inherited in the hybrid grouper. Additionally, the DNA methylation level of 5S rDNA intergenic spacers (IGS) sequence was tested in here. The results showed that the DNA methylation status of the hybrid grouper was significantly lower than that of <italic>C. altivelis</italic>.</p>", "<title>Conclusion</title>", "<p id=\"Par3\">Results of this study provide important data on the genetic characteristics of the hybrid derived from the cross of <italic>C. altivelis</italic> and <italic>E. lanceolatus</italic>, and contribute the knowledge of both evolution and marine fish breeding.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12863-023-01188-5.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We would like to sincerely thank many researchers who help to complete this manuscript.</p>", "<title>Authors’ contributions</title>", "<p>H.H contributed to the conception and designed the study, L.C. carried out the experimental work, participated in rafted the manuscript. Y.L. analyzed sequences and P.C., X.H., J.M. and N.Y. participated in interpretation and discussion of the results. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>The research was supported by the specific research fund of National Natural Science Foundation of China (32160861), Hainan Provincial Natural Science Foundation of China (321QN263), The Major Science and Technology plan of Hainan Province (ZDKJ2021017), the Youth Project of Yazhou Bay Innovation Institute of Hainan Tropical Ocean University (2022CXYQNXM06), State Key Laboratory of Developmental Biology of Freshwater Fish (2020KF001), National Natural Science Foundation of China (32002389) and Scientific Research Foundation of Hainan Tropical Ocean University (RHDRC202010).</p>", "<title>Availability of data and materials</title>", "<p>All raw data of bisulfite sequencing in <italic>Cromileptes altivelis</italic> × <italic>Epinephelus lanceolatus</italic> and parents have been uploaded to GenBank database (BioProject ID: PRJNA1009716, <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1009716/\">https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1009716/</ext-link>). All 5S rDNA sequences generated during the current study are available in the NCBI (accession number: OM289957-OM289959, OP244353).</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par32\">This study was approved by Animal Ethical and Welfare Committee of Hainan Tropical Ocean University (HTOU) and followed the guidelines statement of the Administration of Affairs Concerning Animal Experimentation of China. This study does not involve the use of any human data or tissue. The animals used in the study were obtained from Delin Chengxin Aquaculture Co., Ltd, and Hainan Chenhai Aquatic Co., Ltd from which we have obtained consent to use these animals in our research.</p>", "<title>Consent for publication</title>", "<p id=\"Par33\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par34\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The appearances of <italic>Cromileptes altivelis, Epinephelus lanceolatus</italic> and the hybrid grouper</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Chromosome spreads at metaphase in <italic>Cromileptes altivelis, Epinephelus lanceolatus</italic> and the hybrid grouper. <bold>a</bold>. The 48 chromosomes of <italic>Cromileptes altivelis</italic>. <bold>b</bold>. The 48 chromosomes of <italic>Epinephelus lanceolatus</italic>. <bold>c</bold>. The 48 chromosomes of the hybrid grouper</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Representative sequences of 5S rDNA. <bold>a</bold>. Complete 5S coding regions from <italic>Cromileptes altivelis, Epinephelus lanceolatus</italic> and the hybrid grouper. Internal control regions of the coding region are shaded. <bold>b</bold>. Comparison of the NTS sequences from <italic>Cromileptes altivelis, Epinephelus lanceolatus</italic> and the hybrid grouper, the NTS upstream TATA elements are shaded; asterisks mark variable sites in the NTS</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Schematic representation of the 5S rDNA sequences showing the different types of elements found in the NTS of <italic>Cromileptes altivelis, Epinephelus lanceolatus</italic> and the hybrid grouper</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>DNA methylation of 5S rDNA intergenic spacers (IGS) sequence in <italic>Cromileptes altivelis</italic>, <italic>Epinephelus lanceolatus</italic>, the hybrid grouper. <bold>a</bold>. Schematic representation of the DNA methylation level in CpG sites. The box indicates methylation level of CpG sites with significant difference between the hybrid grouper and parents. <bold>b</bold>. The partial sequence of IGS. The red lines indicate CpG sites. <bold>c</bold>. The DNA methylation level in site 107. <bold>d</bold>. The DNA methylation level in site 178. The symbol * indicates significant differences</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Maximum likelihood phylogenetic tree reconstructed based on COI gene (<bold>a</bold>) and D-loop region (<bold>b</bold>)</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Bayesian phylogenetic tree reconstructed based on COI gene (<bold>a</bold>) and D-loop region (<bold>b</bold>)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Comparison of the measurable traits between <italic>Cromileptes altivelis</italic>, <italic>Epinephelus lanceolatus</italic> and the hybrid grouper</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">measurable traits</th><th align=\"left\"><italic>Cromileptes altivelis</italic></th><th align=\"left\"><italic>Epinephelus lanceolatus</italic></th><th align=\"left\">The hybrid grouper</th></tr></thead><tbody><tr><td align=\"left\">Total length (cm)</td><td align=\"left\">33.07 ± 2.19<sup>a,b</sup></td><td align=\"left\">43.03 ± 3.20</td><td align=\"left\">36.51 ± 1.78</td></tr><tr><td align=\"left\">Standard length (cm)</td><td align=\"left\">27.55 ± 1.87<sup>a,b</sup></td><td align=\"left\">35.80 ± 2.93</td><td align=\"left\">30.32 ± 2.08</td></tr><tr><td align=\"left\">Head length (cm)</td><td align=\"left\">11.09 ± 0.81<sup>a</sup></td><td align=\"left\">14.43 ± 1.08</td><td align=\"left\">11.24 ± 0.25</td></tr><tr><td align=\"left\">Caudal peduncle length (cm)</td><td align=\"left\">2.96 ± 0.28<sup>a,b</sup></td><td align=\"left\">2.65 ± 0.48</td><td align=\"left\">3.18 ± 0.30</td></tr><tr><td align=\"left\">Body height (cm)</td><td align=\"left\">9.52 ± 0.91<sup>a</sup></td><td align=\"left\">12.92 ± 1.42</td><td align=\"left\">9.81 ± 0.60</td></tr><tr><td align=\"left\">Caudal peduncle height (cm)</td><td align=\"left\">3.11 ± 0.20<sup>a,b</sup></td><td align=\"left\">4.65 ± 0.40</td><td align=\"left\">3.37 ± 0.24</td></tr><tr><td align=\"left\"><p>Total length/</p><p>Standard length</p></td><td align=\"left\">1.20 ± 0.01</td><td align=\"left\">1.20 ± 0.01</td><td align=\"left\">1.21 ± 0.03</td></tr><tr><td align=\"left\"><p>Head length/</p><p>Standard length</p></td><td align=\"left\">0.40 ± 0.01</td><td align=\"left\">0.40 ± 0.02</td><td align=\"left\">0.37 ± 0.03</td></tr><tr><td align=\"left\"><p>Body height/</p><p>Standard length</p></td><td align=\"left\">2.90 ± 0.14</td><td align=\"left\">2.78 ± 0.16</td><td align=\"left\">3.10 ± 0.21</td></tr><tr><td align=\"left\">Caudal peduncle length/ Standard length</td><td align=\"left\">0.11 ± 0.01</td><td align=\"left\">0.07 ± 0.01</td><td align=\"left\">0.10 ± 0.01</td></tr><tr><td align=\"left\">Caudal peduncle height/ Standard length</td><td align=\"left\">0.11 ± 0.01</td><td align=\"left\">0.13 ± 0.01</td><td align=\"left\">0.11 ± 0.01</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>The similarity and genetic distance between <italic>Cromileptes altivelis</italic>, <italic>Epinephelus lanceolatus</italic> and the hybrid grouper in 5S rDNA</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Genetic distance<break/>Similarity</th><th align=\"left\"><italic>Cromileptes altivelis</italic></th><th align=\"left\"><italic>Epinephelu lanceolatus</italic></th><th align=\"left\">The hybrid grouper<break/>(Type I)</th><th align=\"left\">The hybrid grouper<break/>(Type II)</th></tr></thead><tbody><tr><td align=\"left\"><italic>Cromileptes altivelis</italic></td><td align=\"left\"/><td align=\"left\">0.064</td><td align=\"left\">0.050</td><td align=\"left\">0.007</td></tr><tr><td align=\"left\"><italic>Epinephelu lanceolatus</italic></td><td align=\"left\">0.952</td><td align=\"left\"/><td align=\"left\">0.014</td><td align=\"left\">0.057</td></tr><tr><td align=\"left\"><p>The hybrid grouper</p><p>(Type I)</p></td><td align=\"left\">0.962</td><td align=\"left\">0.990</td><td align=\"left\"/><td align=\"left\">0.043</td></tr><tr><td align=\"left\"><p>The hybrid grouper</p><p>(Type II)</p></td><td align=\"left\">0.992</td><td align=\"left\">0.95</td><td align=\"left\">0.96</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>The similarity and genetic distance between <italic>Cromileptes altivelis</italic>, <italic>Epinephelus lanceolatus</italic> and the hybrid grouper in COI gene and D-loop region</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Genetic distance<break/>Similarity</th><th align=\"left\"><italic>Cromileptes altivelis</italic></th><th align=\"left\"><italic>Epinephelu lanceolatus</italic></th><th align=\"left\">The hybrid grouper</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">COI gene</td><td align=\"left\"><italic>Cromileptes altivelis</italic></td><td align=\"left\"/><td align=\"left\">0.122</td><td align=\"left\">0.002</td></tr><tr><td align=\"left\"><italic>Epinephelu lanceolatus</italic></td><td align=\"left\">0.878</td><td align=\"left\"/><td align=\"left\">0.124</td></tr><tr><td align=\"left\">The hybrid grouper</td><td align=\"left\">0.998</td><td align=\"left\">0.876</td><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"3\">D-loop region</td><td align=\"left\"><italic>Cromileptes altivelis</italic></td><td align=\"left\"/><td align=\"left\">0.370</td><td align=\"left\">0.010</td></tr><tr><td align=\"left\"><italic>Epinephelu lanceolatus</italic></td><td align=\"left\">0.649</td><td align=\"left\"/><td align=\"left\">0.369</td></tr><tr><td align=\"left\">The hybrid grouper</td><td align=\"left\">0.99</td><td align=\"left\">0.645</td><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup> there is a significant difference between <italic>Cromileptes altivelis</italic> and <italic>Epinephelus lanceolatus</italic> (<italic>p</italic> &lt; 0.05)</p><p><sup>b</sup> there is a significant difference between <italic>Cromileptes altivelis</italic> and the hybrid grouper (<italic>p</italic> &lt; 0.05)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12863_2023_1188_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1:</bold>\n<bold>Table S1.</bold> The primers used for PCR and BSP-PCR. <bold>Table S2.</bold> GenBank accession numbers for mitochondrial genome sequences.</p></caption></media>", "<media xlink:href=\"12863_2023_1188_MOESM2_ESM.tif\"><caption><p><bold>Additional file 2:</bold>\n<bold>Supplementary Figure 1.</bold> Representative sequences of 5S rDNA intergenic spacers (IGS) sequence.</p></caption></media>", "<media xlink:href=\"12863_2023_1188_MOESM3_ESM.tif\"><caption><p><bold>Additional file 3:</bold>\n<bold>Supplementary Figure 2.</bold> Representative sequences of COI gene from <italic>Cromileptes altivelis</italic>, <italic>Epinephelus lanceolatus</italic>, the hybrid grouper.</p></caption></media>", "<media xlink:href=\"12863_2023_1188_MOESM4_ESM.tif\"><caption><p><bold>Additional file 4:</bold>\n<bold>Supplementary Figure 3.</bold> Representative partial sequences of D-loop region from <italic>Cromileptes altivelis</italic>, <italic>Epinephelus lanceolatus</italic>, the hybrid grouper.</p></caption></media>" ]
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{ "acronym": [], "definition": [] }
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2024-01-14 23:43:45
BMC Genom Data. 2024 Jan 12; 25:5
oa_package/3d/ef/PMC10787421.tar.gz
PMC10787422
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[ "<title>Background</title>", "<p id=\"Par5\">Type 2 diabetes mellitus (T2DM) and its preceding states, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), are a growing epidemic worldwide [##REF##34879977##1##]. Moreover, patients with T2DM and IGT have a higher risk for future cardiovascular disease (CVD), including coronary artery disease (CAD), than those with normal glucose tolerance (NGT) [##REF##20609967##2##].</p>", "<p id=\"Par6\">T2DM affects cardiovascular (CV) risk differently in females and males. CV events and mortality are usually delayed by approximately ten years in females, presumably due to hormonal differences. On the other hand, females with T2DM have a higher relative risk for fatal and non-fatal CVD than males [##REF##24613026##3##–##REF##16371403##7##]. These differences are possibly due to a more pronounced dysglycaemia, with females progressing earlier from NGT to IGT, a greater accumulation of CV risk factors, and a less efficient management of CV risk factors in females than in males [##REF##33573665##8##, ##REF##17259507##9##]. A possible reason for this deteriorating glucose tolerance may be sex disparities in body composition and insulin resistance (IR). IR is indeed a key factor linking several elements of cardiometabolic dysfunction together [##REF##35700159##10##]. There is some evidence suggesting that the more rapid deterioration of glucose homeostasis in females than in males may be associated with worsening IR due to the greater accumulation of body fat in females [##REF##36442546##11##]. IR can be expressed by various indexes, traditionally derived from measures of plasma glucose and insulin, but few of them are routinely used because of impracticalities [##REF##10902785##12##–##REF##3899825##15##]. Indexes derived from routinely assessed laboratory and anthropometric parameters may be more appropriate in females [##REF##11289468##13##, ##REF##20067971##16##–##REF##16054467##18##].</p>", "<p id=\"Par7\">This study aims to investigate sex differences in the association between IR indexes and a first non-fatal myocardial infarction (MI) across glycaemic states.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study design and population</title>", "<p id=\"Par8\">The present investigation is a post-hoc analysis based on the population from the Periodontitis and its relation to coronary artery disease (PAROKRANK) study, a multicentre case-control study that recruited subjects with and without a first non-fatal MI from May 2010 to February 2014 at 17 Swedish hospitals. A detailed description of the study has been given previously [##REF##26762521##19##]. Thus, only data of importance for the present investigation is repeated here. Individuals &lt; 75 years old were enrolled during their hospitalization for a first non-fatal acute MI, defined according to international criteria [##REF##22958960##20##]. They were scheduled for follow-up visits 6–10 weeks later at the local department of cardiology. Subjects with previous heart valve replacement, and any condition that could limit their ability to follow the study protocol were excluded. The national population registry was used to identify controls free from prior MI and heart valve replacement but of the same sex, age, and from the same postal code area as the corresponding case.</p>", "<p id=\"Par9\">At the visit casesand controls had been fasting and abstained from smoking for at least 12 h. They were subjected to a physical examination where data about heart rate, blood pressure following five minutes of rest in a sitting position, height, body weight, body mass index (BMI), and waist circumference (WC) were collected. At the same time, a venous blood sample was drawn to analyse the following laboratory values: complete blood count, total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), creatinine, fasting plasma glucose (FPG) and glycated haemoglobin A1c (HbA1c) while high-sensitivity C-reactive protein (hsCRP) was analysed on stored samples. Subjects without known T2DM underwent a 2-hour oral glucose tolerance test (OGTT) during which FPG, 30 and 120 min post-load venous-plasma glucose were measured through the point-of-care HemoCue 201 System (HemoCue AB, Ängelholm, Sweden). Plasma was stored for subsequent analysis of fasting plasma insulin using an electro-chemiluminescence immune assay on a COBAS e411 instrument (Roche, Indianapolis, IN, USA) at Pisa’s Metabolism laboratory, in Italy.</p>", "<p id=\"Par10\">Smoking habits were defined as current, previous (stopped more than one month before the visit), or never. Information on previous medical history was based on self-reported data from standardized questionnaires.</p>", "<p id=\"Par11\">For the present analyses, only individualswho underwent an OGTT were included while those with known diabetes were excluded.</p>", "<title>Definitions</title>", "<p id=\"Par12\">Multiple surrogate indexes of IR were calculated according to the formulas derived from glucose, insulin, lipid metabolites, and participants’ anthropometric characteristics.</p>", "<p id=\"Par13\">The <italic>Homeostatic Model Assessment</italic> of IR (HOMA-IR) was defined as fasting insulin (mU/L) × fasting glucose (mmol/L)/22.5 [##REF##3899825##15##].</p>", "<p id=\"Par14\">The <italic>Visceral adiposity index (VAI)</italic> was evaluated with different formulas in females and males [##REF##20067971##16##]:</p>", "<p id=\"Par1005\">\n\n</p>", "<p id=\"Par15\">\n\n</p>", "<p id=\"Par16\">The <italic>triglycerides/HDL-C (TG/HDL-C)</italic> index was determined as the ratio between triglycerides (mmol/L) and HDL-C (mmol/L) [##REF##16054467##18##, ##REF##20484475##21##].</p>", "<p id=\"Par17\">The TyG index was calculated by the following formula:</p>", "<p id=\"Par18\">Glucose levels obtained during the OGTT were used to classify study participants according to the World Health Organization criteria [##UREF##1##22##] as having NGT, IFG, IGT, or newly diagnosed T2DM.</p>", "<p id=\"Par19\">Estimated glomerular filtration rate (eGFR) was calculated by using the CKD-EPI equation [##REF##19414839##23##]: eGFR = 141 × min(Scr/k, 1)α × max(Scr/k, 1)-1.209 × 0.993Age × 1.018 [if female], where Scr is serum creatinine, k is 0.7 for females and 0.9 for males, α is -0.329 for females and − 0.411 for males, min indicates the minimum of Scr/k or 1, and max indicates the maximum of Scr/k or 1.</p>", "<title>Statistical analyses</title>", "<p id=\"Par20\">Continuous variables are expressed as median and interquartile range (IQR) and compared by the Mann-Whitney test while categorical variables are reported as numbers and proportions and compared by chi-square statistics.</p>", "<p id=\"Par21\">Age, BMI, hsCRP, total cholesterol, TG, HDL-C, HOMA-IR, VAI, and TG/HDL-C were natural log-transformed for statistical analyses.</p>", "<p id=\"Par22\">The independent association between sex, IR indexes, a first non-fatal MI, and the following CV risk factors: age, BMI, hsCRP, known family history of CVD, smoking habit, glycaemic status, and blood lipids were investigated by fitting a multivariable regression model. An interaction term between sex and the investigated IR index was inserted to assess whether there was any effect modification of these associations according to sex. The multivariable models were run separately in females and males for indexes where the interaction term was significant (p ≤ 0.05).</p>", "<p id=\"Par23\">Variables that are incorporated into the formulas of each index were not computed in the regression models due to potential collinearity. Multicollinearity between variables comprised in the multiple logistic regression models was assessed by the variance inflection factor.</p>", "<p id=\"Par24\">A two-sided p-value ≤ 0.05 was considered statistically significant. All statistical analyses were performed by SPSS software program version 27 for Windows (IBM CORP, Armonk, NY, USA).</p>" ]
[ "<title>Results</title>", "<p id=\"Par25\">The study population comprises 1403 participants of whom 268 (19%) were females and 1135 (81%) males. A total of 126 (47%) females and 570 (50%) males had a first non-fatal MI, respectively (Fig. ##FIG##0##1##). The baseline anthropometric and metabolic characteristics of the population are shown in Table ##TAB##0##1##. Compared with males, females were older, less often smokers, with a lower BMI and WC, and had lower triglycerides, fasting plasma glucose, and insulin concentrations, but higher levels of total cholesterol and HDL-C. Generally, females were less insulin resistant than males, as they had statistically significant lower HOMA-IR, VAI, TG/HDL-C and TyG levels (Table ##TAB##0##1##). No differences between the two sexes were observed in the proportion of different glycaemic states (p = 0.06). These differences in anthropometric and metabolic characteristics between the two sexes were maintained even within the different glycaemic states (Supplemental Table ##SUPPL##0##1##).</p>", "<p id=\"Par28\">\n\n</p>", "<p id=\"Par30\">\n\n</p>", "<p id=\"Par26\">Table ##TAB##1##2## shows the IR indexes in casesand controls according to sex, in the whole population, and within each glycaemic state. In the overall population, among both cases and controls, females were less insulin resistant than males. These sex difference persisted in the NGT group, with VAI, TG/HDL-C index and TyG remaining significantly different between females and males in both cases and controls. In the IFG subgroups, VAI and TG/HDL-C index were significantly different between females and males in casesonly, whereas in the IGT class this difference persisted also in controls. In individuals with newly diagnosed T2DM there were no sex differences in VAI, TG/HDL-C and TyG but higher HOMA-IR in male cases.</p>", "<p id=\"Par34\">\n\n</p>", "<p id=\"Par27\">At multivariable logistic regression analysis, the interaction term between the IR indexes and sex was statistically significant for VAI and TG/HDL-C index (Supplemental Table ##SUPPL##0##2##), thus multivariable logistic regression models were run separately in females and males (Table ##TAB##2##3##). The univariate association between HOMA-IR, VAI and TG/HDL-C and a first non-fatal acute MI, separately, was significant both in females and males. In the multivariate models the associations between VAI and TG/HDL-C index, separately, and a first non-fatal acute MI was significant in females (VAI: OR 1.7, 95% CI 1.0-2.9; TG/HDL-C index: OR 1.9, 95% CI 1.1–3.4) but not in males (VAI: OR 1.2, 95% CI 0.9–1.5; TG/HDL-C index: OR 1.2, 95% CI 0.9–1.5). Vice versa, the association between HOMA-IR, TyG and a first non-fatal MI was significant in males (HOMA-IR: OR 1.4, 95% CI 1.0-1.9; TyG: OR 0.5, 95% CI 0.3–0.6) but not in females (HOMA-IR: OR 1.5, 95% CI 0.8–2.9; TyG: OR 0.7, 95% CI 0.3–1.4).</p>", "<p id=\"Par37\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par49\">In this post-hoc analysis two surrogate indexes of IR, containing metabolic and anthropometric parameters, namely VAI and TG/HDL-C index, were significantly associated with a first MI in females, but not in males, independently of traditional CV risk factors and glycaemic state, the latter characterized by OGTT.</p>", "<p id=\"Par50\">In the present population, there were sex differences in anthropometric and metabolic characteristics. Females displayed a better cardio-metabolic risk profile than males since they were less often smokers, had lower BMI, WC and triglycerides levels, and were less insulin resistant than males. In general, female sex is characterized by the storage of adipose tissue in subcutaneous sites as compared with preferential visceral deposition in males [##REF##22651247##24##]. Previous studies have shown that in a population with normal blood glucose levels females are more insulin sensitive than males [##UREF##2##25##], although this sex advantage disappears in females with diabetes [##REF##30287229##26##]. Additionally, the VIRGO study found that young females with MI only had a slightly more favourable lipid panel compared with males, suggesting that the sex difference in outcomes after MI cannot be explained by dyslipidaemia only [##REF##27979045##27##]. Several clamp studies, investigating how sex can affect insulin sensitivity in individuals with NGT, showed higher insulin-stimulated glucose disposal in females than in males [##REF##19056613##28##–##REF##26635731##36##]. In our comparison, females displayed lower fasting plasma glucose and insulin levels, and consequently, lower HOMA-IR than their male counterparts. This is in accordance with previous work showing a higher prevalence of IFG in males than in females [##REF##33573665##8##]. However, HOMA-IR might not be the most accurate way to express IR in females, considering that it mainly represents hepatic IR, whereas females would be more exposed to peripheral IR [##REF##14747216##37##]. Using indexes that include anthropometric characteristics and lipids could help clarify the mechanisms underlying the sex differences across glycaemic states.</p>", "<p id=\"Par51\">Another important finding is that, in both sexes, individuals with a first MI had consistently higher values of all IR indexes compared with controls, not only in the general study population but also in the subgroup with NGT. This is remarkable, as we classified NGT quite strictly, excluding not only subjectswith IGT and T2DM but also those with IFG. This, together with the fact that cases, all surviving a first MI, were relatively healthy, further supports the hypothesis that a certain degree of metabolic derangement exists in CAD, even without glycaemic perturbations [##REF##35974709##38##].</p>", "<p id=\"Par52\">Thus, even if VAI and TG/HDL-C index were lower in females than in males, they might capture an early stage of metabolic disturbance that is not pictured by the glycaemic state but is still clinically important and they could be better predictors of MI. This is in line with a recent study highlighting that VAI is associated with CV events in normal weight and over-weight subjects, but not in those who had obesity [##REF##36513453##39##], suggesting that indexes derived from multiple parameters, both anthropometric and laboratory, are more able to identify CV risk in healthier populations.</p>", "<p id=\"Par53\">Additionally, a Chinese study shows that VAI is significantly associated with intracranial atherosclerotic stenosis in middle-aged and elderly females [##REF##28801558##40##]. Accordingly, in a recent clamp-based study in subjectswithout diabetes, there was greater deterioration of insulin sensitivity and greater fat accumulation in females than in males [##REF##36442546##11##]. Therefore, we hypothesized that VAI and TG/HDL-C index could have a better performance than OGTT-derived glycaemic status and HOMA-IR in identifying clinically meaningful IR, with the advantage that they are more practical than OGTT or clamps. Indeed, both VAI and TG/HDL-C index are based on anthropometrics and lipid profiles, (and do not at all include insulin levels), which are routinely assessed, and they are quite well validated.</p>", "<p id=\"Par54\">Assessing VAI and TG/HDL index in females could contribute to the early identification of metabolic deterioration and to instituting preventive measures, such as lifestyle modifications, that could prevent them from developing T2DM and hence losing advantages in terms of CV risk. Indeed, with CV risk stratification being widely based on the limited number of traditional risk factors derived from the Framingham study, our findings provide a rationale for further exploring the possibility of finding risk factors that are more specific for CV risk in females.</p>", "<p id=\"Par55\">The INTERHEART study tried to widen the view on CV risk factors but confirmed that the two most important ones were smoking and increased lipids, followed by hypertension and diabetes, and the importance of all CV risk factors was similar in both sexes, regardless of age and geographical region [##REF##15364185##41##]. Although females remain less represented in CV clinical trials than men, recent years have brought a better understanding of the sex differences in the biological processes accounting for CV risk factors, allowing for an expansion of the number of factors that might play a key role in CV risk. The main challenge in the following years will be to more equitably include both sexes in trials, aiming at adopting efficient preventive measures in females and males, separately.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par57\">IR might be of special importance as a CV risk factor in females. In particular, IR indexes based on anthropometrics and a lipid panel, i.e., VAI and TG/HDL-C index, may contribute to CV risk stratification in females, independently of their glycaemic state. Further studies are needed to assess the prognostic value of these indexes.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Females are generally less prone to cardiovascular (CV) events than males, but this protection is trumped by diabetes. The mechanism behind the increased relative risk in females with diabetes is not fully understood. Insulin resistance (IR) is suggested to be a more important contributor to CV morbidity in females than in males. We aim to investigate differences in the association between IR indexes (Homeostatic Model Assessment of IR - HOMA-IR, visceral adiposity index – VAI, and triglycerides/high-density lipoprotein-cholesterol - TG/HDL-C index), and a first non-fatal myocardial infarction (MI) across different glycaemic states.</p>", "<title>Methods</title>", "<p id=\"Par2\">IR indexes were calculated in a population with (n = 696) and without (n = 707) a first non-fatal MI, free from known diabetes. MI cases were investigated at least six weeks after the event. All participants were categorized by an oral glucose tolerance test as having normal glucose tolerance, impaired fasting glucose, impaired glucose tolerance, or newly diagnosed diabetes. Comparison of proportion of glycaemic states by sex was tested by chi-square test. The associations between sex, a first non-fatal MI, IR indexes, and traditional CV risk factors were analysed by multivariate logistic regression models. Continuous variables were logarithmically transformed.</p>", "<title>Results</title>", "<p id=\"Par3\">Of the total population 19% were females and 81% males, out of whom 47% and 50% had a first non-fatal MI, respectively. Compared with males, females were older, less often smokers, with lower body mass index and higher total cholesterol and high-density lipoprotein cholesterol levels. The proportion of glycaemic states did not differ between the sexes (p = 0.06). Females were less insulin resistant than males, especially among cases and with normal glucose tolerance. In logistic regression models adjusted for major CV risk factors including sex, the associations between VAI and TG/HDL-C index and a first non-fatal MI remained significant only in females (odds ratios and 95% confidence intervals: 1.7, 1.0-2.9, and 1.9, 1.1–3.4 respectively).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">These results support the assumption that IR indexes based on anthropometrics and lipid panel, i.e., VAI and TG/HDL-C, could be a better measure of IR and CV-predictor for non-fatal MI in females, even without glycaemic perturbations.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02093-y.</p>", "<title>Keywords</title>" ]
[ "<title>Strengths and limitations</title>", "<p id=\"Par56\">The present study has several strengths. Firstly, the study cohort was recruited from 17 Swedish hospitals, covering a nationwide geographical area and various educational and socioeconomic states. The whole population is well characterised and relatively young and healthy, as it includes only cases with a first MI and a well-matched control population. Some limitations should be underlined. As a post-hoc investigation it can only be hypothesis-generating and the present findings need further confirmation. The proportion of females in the complete population (19%) was relatively low and might restrict the power of the analyses. However, this proportion is in line with epidemiological data for a MI population with an upper age limit of 75 years reported in SWEDEHEART during the time of the recruitment, further considering two aspects: we excluded individuals in the first six to ten weeks after the acute event, when females have worse outcomes compared with males, and those with known diabetes, where the proportion of females is higher. Additionally, IR was not evaluated with the gold standard method, the Euglycaemic Hyperinsulinemic Clamp, but with surrogate indexes, however validated and more clinically practical.</p>", "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>A.R.: concept, data managing, analyses, manuscript drafting and revision. E.F.: data managing, manuscript revision. L.M.: manuscript revision, supervision. A.N.: collection of study participants, concept, manuscript revision, supervision. P.N.: data managing, data analysis, manuscript revision. L.R.: collection of study participants, concept, manuscript revision, supervision. G.S.: manuscript revision, supervision. G.F.: concept, data managing, analyses, manuscript revision, supervision.</p>", "<title>Funding</title>", "<p>The PAROKRANK study was supported by grants from AFA Insurance, Swedish Heart-Lung Foundation, Swedish Research Council, Swedish Society of Medicine, and Stockholm County Council (ALF project and Steering committee KI/SLL for odontological research), The Eklund foundation.</p>", "<title>Data availability</title>", "<p>The datasets used during the current study are available from L.R. or G.F. on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par77\">The PAROKRANK study was approved by the Regional Ethics Committee at Stockholm (Dnr: 2008/152 − 31/2). PAROKRANK was conducted according to the principles delineated in the Helsinki Declaration. All participants provided their written informed consent before inclusion in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par78\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par76\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow chart of study population divided by sex, presence of first non-fatal myocardial infarction, and glycaemic states defined according to OGTT. IFG = impaired fasting glucose; IGT = impaired glucose tolerance; NGT = normal glucose tolerance; OGTT = oral glucose tolerance test; T2DM = type 2 diabetes mellitus</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics of the whole population, reported as number (%) or median (interquartile range)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Females<break/>268 (19)</th><th align=\"left\">Males<break/>1135 (81)</th><th align=\"left\">P value<break/>(F vs. M)</th></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"left\">65 (60–69)</td><td align=\"left\">63 (57–67)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Smoking, yes</td><td align=\"left\">126 (48)</td><td align=\"left\">559 (50)</td><td align=\"left\">0.005</td></tr><tr><td align=\"left\">Index MI, yes</td><td align=\"left\">126 (47)</td><td align=\"left\">570 (50)</td><td align=\"left\">0.35</td></tr><tr><td align=\"left\">Glycaemic states</td><td align=\"left\">-</td><td align=\"left\">-</td><td align=\"left\">0.06</td></tr><tr><td align=\"left\"> NGT</td><td align=\"left\">183 (68)</td><td align=\"left\">715 (63)</td><td align=\"left\">0.77</td></tr><tr><td align=\"left\"> IFG</td><td align=\"left\">16 (6)</td><td align=\"left\">131 (12)</td><td align=\"left\">5.20</td></tr><tr><td align=\"left\"> IGT</td><td align=\"left\">49 (18)</td><td align=\"left\">197 (17)</td><td align=\"left\">0.09</td></tr><tr><td align=\"left\"> Newly detected T2DM</td><td align=\"left\">20 (8)</td><td align=\"left\">92 (8)</td><td align=\"left\">0.09</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Medical History</bold>\n</td></tr><tr><td align=\"left\">Hypertension, yes</td><td align=\"left\">84 (32)</td><td align=\"left\">343 (30)</td><td align=\"left\">0.66</td></tr><tr><td align=\"left\">Known family history of CVD*, yes</td><td align=\"left\">95 (35)</td><td align=\"left\">336 (30)</td><td align=\"left\">0.18</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Anthropometrics - vitals</bold>\n</td></tr><tr><td align=\"left\">BMI (kg/m<sup>2</sup>)</td><td align=\"left\">25.7 (23–29)</td><td align=\"left\">26.6 (24.5–28.9)</td><td align=\"left\">0.001</td></tr><tr><td align=\"left\">Obesity, yes</td><td align=\"left\">52 (20)</td><td align=\"left\">194 (17)</td><td align=\"left\">0.36</td></tr><tr><td align=\"left\">Waist circumference (cm)</td><td align=\"left\">90 (83–100)</td><td align=\"left\">100 (93–106)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Systolic blood pressure (mmHg)</td><td align=\"left\">133 (120–145)</td><td align=\"left\">130 (120–140)</td><td align=\"left\">0.20</td></tr><tr><td align=\"left\">Diastolic blood pressure (mmHg)</td><td align=\"left\">80 (70–86)</td><td align=\"left\">80 (74–87)</td><td align=\"left\">0.05</td></tr><tr><td align=\"left\">Heart rate (bpm)</td><td align=\"left\">72 (60–83)</td><td align=\"left\">72 (63–85)</td><td align=\"left\">0.21</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Laboratory</bold>\n</td></tr><tr><td align=\"left\">Total cholesterol (mmol/L)</td><td align=\"left\">5 (4–6)</td><td align=\"left\">4.6 (3.7–5.6)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">HDL-C (mmol/L)</td><td align=\"left\">1.6 (1.3–1.9)</td><td align=\"left\">1.2 (1.1–1.5)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Triglycerides (mmol/L)</td><td align=\"left\">1.1 (0.8–1.4)</td><td align=\"left\">1.2 (0.9–1.6)</td><td align=\"left\">0.005</td></tr><tr><td align=\"left\">hsCRP (mg/L)</td><td align=\"left\">1.4 (0.7-3)</td><td align=\"left\">1.3 (0.7–2.4)</td><td align=\"left\">0.07</td></tr><tr><td align=\"left\">Creatinine (µmol/L)</td><td align=\"left\">68 (60–74)</td><td align=\"left\">83 (76–92)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">eGFR (mL/min/1.73m<sup>2</sup>)</td><td align=\"left\">82.9 (73.6–93.2)</td><td align=\"left\">86.7 (76.3–94.2)</td><td align=\"left\">0.009</td></tr><tr><td align=\"left\">Fasting plasma glucose (mmol/L)</td><td align=\"left\">5.3 (4.9–5.8)</td><td align=\"left\">5.6 (5.1–6.1)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">2 h post-load glucose (mmol/L)</td><td align=\"left\">6 (4.9–7.8)</td><td align=\"left\">6.2 (5-7.6)</td><td align=\"left\">0.72</td></tr><tr><td align=\"left\">HbA1c (mmol/mol)</td><td align=\"left\">38 (35.5–41)</td><td align=\"left\">38 (35–41)</td><td align=\"left\">0.28</td></tr><tr><td align=\"left\">Fasting plasma insulin (mU/L)</td><td align=\"left\">9.8 (7.1–13.5)</td><td align=\"left\">11 (7.6–16.6)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Insulin resistance indexes</bold>\n</td></tr><tr><td align=\"left\">HOMA-IR</td><td align=\"left\">2.3 (1.6–3.3)</td><td align=\"left\">2.7 (1.8–4.3)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">VAI</td><td align=\"left\">0.9 (0.6–1.4)</td><td align=\"left\">1.3 (0.9–1.9)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">TG/HDL-C</td><td align=\"left\">1.5 (1.1–2.4)</td><td align=\"left\">2.1 (1.4–3.2)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">TyG</td><td align=\"left\">8.4 (8.1–8.7)</td><td align=\"left\">8.5 (8.2–8.9)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Pharmacological treatment</bold>\n</td></tr><tr><td align=\"left\">Beta-blockers, yes</td><td align=\"left\">131 (49)</td><td align=\"left\">576 (51)</td><td align=\"left\">0.58</td></tr><tr><td align=\"left\">Renin-angiotensin inhibitors, yes</td><td align=\"left\">125 (47)</td><td align=\"left\">613 (55)</td><td align=\"left\">0.03</td></tr><tr><td align=\"left\">Calcium-antagonist, yes</td><td align=\"left\">30 (11)</td><td align=\"left\">124 (11)</td><td align=\"left\">0.90</td></tr><tr><td align=\"left\">Diuretics, yes</td><td align=\"left\">24 (9)</td><td align=\"left\">85 (8)</td><td align=\"left\">0.42</td></tr><tr><td align=\"left\">Statins, yes</td><td align=\"left\">137 (51)</td><td align=\"left\">621 (55)</td><td align=\"left\">0.28</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Insulin resistance indexes in patients and controls in the whole population and among the glycaemic states</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\"/><td align=\"left\" colspan=\"3\">\n<bold>Females</bold>\n</td><td align=\"left\" colspan=\"3\">\n<bold>Males</bold>\n</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>126 (47)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>142 (53)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\">\n<bold>Cases 570 (50)</bold>\n</td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>565 (50)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>P value</bold>\n</p><p>\n<bold>cases F vs M</bold>\n</p></td><td align=\"left\"><p>\n<bold>P value controls</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td></tr><tr><td align=\"left\">HOMA-IR</td><td align=\"left\"><p>2.59</p><p>(1.87–3.51)</p></td><td align=\"left\"><p>2.06</p><p>(1.43–3.04)</p></td><td align=\"left\">0.001</td><td align=\"left\"><p>3.03</p><p>(2.09–4.53)</p></td><td align=\"left\"><p>2.54</p><p>(1.60–3.87)</p></td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.002</td><td align=\"left\">0.001</td></tr><tr><td align=\"left\">VAI</td><td align=\"left\"><p>0.91</p><p>(0.69–1.47)</p></td><td align=\"left\"><p>0.82</p><p>(0.53–1.26)</p></td><td align=\"left\">0.01</td><td align=\"left\"><p>1.41</p><p>(0.98–1.98)</p></td><td align=\"left\"><p>1.25</p><p>(0.79–1.95)</p></td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">TG/HDL-C</td><td align=\"left\"><p>1.66</p><p>(1.20–2.63)</p></td><td align=\"left\"><p>1.39</p><p>(0.93–2.12)</p></td><td align=\"left\">0.009</td><td align=\"left\"><p>2.28</p><p>(1.59–3.23)</p></td><td align=\"left\"><p>2.00</p><p>(1.28–3.11)</p></td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">TyG</td><td align=\"left\"><p>8.44</p><p>(8.19–8.72)</p></td><td align=\"left\"><p>8.38</p><p>(8.09–8.76)</p></td><td align=\"left\">0.15</td><td align=\"left\"><p>8.54</p><p>(8.28–8.86)</p></td><td align=\"left\"><p>8.53</p><p>(8.23–8.92)</p></td><td align=\"left\">0.63</td><td align=\"left\">0.02</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"9\">\n<bold>NGT</bold>\n</td></tr><tr><td align=\"left\"/><td align=\"left\" colspan=\"3\">\n<bold>Females</bold>\n</td><td align=\"left\" colspan=\"3\">\n<bold>Males</bold>\n</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>70 (38)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>113 (62)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>308 (43)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>407 (57)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>P value</bold>\n</p><p>\n<bold>cases</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td><td align=\"left\"><p>\n<bold>P value controls</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td></tr><tr><td align=\"left\">HOMA-IR</td><td align=\"left\"><p>2.37</p><p>(1.68–3.12)</p></td><td align=\"left\"><p>1.94</p><p>(1.33–2.53)</p></td><td align=\"left\">0.004</td><td align=\"left\"><p>2.54</p><p>(1.82–3.87)</p></td><td align=\"left\"><p>2.04</p><p>(1.41–3.12)</p></td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.11</td><td align=\"left\">0.02</td></tr><tr><td align=\"left\">VAI</td><td align=\"left\"><p>0.86</p><p>(0.62–1.26)</p></td><td align=\"left\"><p>0.73</p><p>(0.51–1.21)</p></td><td align=\"left\">0.04</td><td align=\"left\"><p>1.36</p><p>(0.94–1.89)</p></td><td align=\"left\"><p>1.15</p><p>(0.73–1.86)</p></td><td align=\"left\">0.002</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">TG/HDL-C</td><td align=\"left\"><p>1.62</p><p>(1.11–2.28)</p></td><td align=\"left\"><p>1.25</p><p>(0.90–2.11)</p></td><td align=\"left\">0.03</td><td align=\"left\"><p>2.17</p><p>(1.56–3.04)</p></td><td align=\"left\"><p>1.90</p><p>(1.21–2.95)</p></td><td align=\"left\">0.002</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">TyG</td><td align=\"left\"><p>8.38</p><p>(8.08–8.61)</p></td><td align=\"left\"><p>8.33</p><p>(8.06–8.67)</p></td><td align=\"left\">0.59</td><td align=\"left\"><p>8.51</p><p>(8.21–8.77)</p></td><td align=\"left\"><p>8.45</p><p>(8.15–8.80)</p></td><td align=\"left\">0.47</td><td align=\"left\">0.05</td><td align=\"left\">0.02</td></tr><tr><td align=\"left\" colspan=\"9\">\n<bold>IFG</bold>\n</td></tr><tr><td align=\"left\"/><td align=\"left\" colspan=\"3\">\n<bold>Females</bold>\n</td><td align=\"left\" colspan=\"3\">\n<bold>Males</bold>\n</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>10 (63)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>6 (37)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>83 (63)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>48 (37)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>P value</bold>\n</p><p>\n<bold>cases</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td><td align=\"left\"><p>\n<bold>P value controls</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td></tr><tr><td align=\"left\">HOMA-IR</td><td align=\"left\"><p>3.73</p><p>(2.36–4.69)</p></td><td align=\"left\"><p>3.35</p><p>(1.88–5.09)</p></td><td align=\"left\">0.71</td><td align=\"left\"><p>3.63</p><p>(2.67–4.85)</p></td><td align=\"left\"><p>3.75</p><p>(2.63–5.89)</p></td><td align=\"left\">0.48</td><td align=\"left\">0.82</td><td align=\"left\">0.48</td></tr><tr><td align=\"left\">VAI</td><td align=\"left\"><p>0.82</p><p>(0.50–1.27)</p></td><td align=\"left\"><p>0.92</p><p>(0.36–1.53)</p></td><td align=\"left\">0.79</td><td align=\"left\"><p>1.29</p><p>(0.92–1.89)</p></td><td align=\"left\"><p>1.41</p><p>(0.98–1.87)</p></td><td align=\"left\">0.62</td><td align=\"left\">0.02</td><td align=\"left\">0.08</td></tr><tr><td align=\"left\">TG/HDL-C</td><td align=\"left\"><p>1.37</p><p>(0.88–2.13)</p></td><td align=\"left\"><p>1.53</p><p>(0.69–2.67)</p></td><td align=\"left\">0.88</td><td align=\"left\"><p>2.09</p><p>(1.54–3.09)</p></td><td align=\"left\"><p>2.28</p><p>(1.63–2.97)</p></td><td align=\"left\">0.60</td><td align=\"left\">0.04</td><td align=\"left\">0.10</td></tr><tr><td align=\"left\">TyG</td><td align=\"left\"><p>8.33</p><p>(8.22–8.75)</p></td><td align=\"left\"><p>8.60</p><p>(7.96–8.94)</p></td><td align=\"left\">0.79</td><td align=\"left\"><p>8.54</p><p>(8.30–8.87)</p></td><td align=\"left\"><p>8.76</p><p>(8.51–9.05)</p></td><td align=\"left\">0.02</td><td align=\"left\">0.29</td><td align=\"left\">0.22</td></tr><tr><td align=\"left\" colspan=\"9\">\n<bold>IGT</bold>\n</td></tr><tr><td align=\"left\"/><td align=\"left\" colspan=\"3\">\n<bold>Females</bold>\n</td><td align=\"left\" colspan=\"3\">\n<bold>Males</bold>\n</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>33 (67)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>16 (33)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>120 (61)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>77 (39)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>P value</bold>\n</p><p>\n<bold>cases</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td><td align=\"left\"><p>\n<bold>P value controls</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td></tr><tr><td align=\"left\">HOMA-IR</td><td align=\"left\"><p>3.00</p><p>(2.14–3.65)</p></td><td align=\"left\"><p>3.33</p><p>(2.38–4.44)</p></td><td align=\"left\">0.22</td><td align=\"left\"><p>3.41</p><p>(2.33–5.03)</p></td><td align=\"left\"><p>3.82</p><p>(2.43–5.38)</p></td><td align=\"left\">0.26</td><td align=\"left\">0.06</td><td align=\"left\">0.43</td></tr><tr><td align=\"left\">VAI</td><td align=\"left\"><p>1.03</p><p>(0.75–1.53)</p></td><td align=\"left\"><p>1.01</p><p>(0.63–1.17)</p></td><td align=\"left\">0.35</td><td align=\"left\"><p>1.55</p><p>(1.11–2.54)</p></td><td align=\"left\"><p>1.45</p><p>(0.95–2.58)</p></td><td align=\"left\">0.67</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.005</td></tr><tr><td align=\"left\">TG/HDL-C</td><td align=\"left\"><p>1.82</p><p>(1.35–2.75)</p></td><td align=\"left\"><p>1.69</p><p>(1.04–2.04)</p></td><td align=\"left\">0.23</td><td align=\"left\"><p>2.51</p><p>(1.81–3.99)</p></td><td align=\"left\"><p>2.28</p><p>(1.54–4.27)</p></td><td align=\"left\">0.63</td><td align=\"left\">0.01</td><td align=\"left\">0.01</td></tr><tr><td align=\"left\">TyG</td><td align=\"left\"><p>8.51</p><p>(8.29–8.79)</p></td><td align=\"left\"><p>8.46</p><p>(8.24–8.85)</p></td><td align=\"left\">0.57</td><td align=\"left\"><p>8.63</p><p>(8.38–8.96)</p></td><td align=\"left\"><p>8.69</p><p>(8.44–9.21)</p></td><td align=\"left\">0.17</td><td align=\"left\">0.14</td><td align=\"left\">0.03</td></tr><tr><td align=\"left\" colspan=\"9\">\n<bold>Newly diagnosed T2DM</bold>\n</td></tr><tr><td align=\"left\"/><td align=\"left\" colspan=\"3\">\n<bold>Females</bold>\n</td><td align=\"left\" colspan=\"3\">\n<bold>Males</bold>\n</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>13 (65)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>7 (35)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>Cases</bold>\n</p><p>\n<bold>59 (64)</bold>\n</p></td><td align=\"left\"><p>\n<bold>Controls</bold>\n</p><p>\n<bold>33 (36)</bold>\n</p></td><td align=\"left\">\n<bold>P value</bold>\n</td><td align=\"left\"><p>\n<bold>P value</bold>\n</p><p>\n<bold>cases</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td><td align=\"left\"><p>\n<bold>P value controls</bold>\n</p><p>\n<bold>F vs M</bold>\n</p></td></tr><tr><td align=\"left\">HOMA-IR</td><td align=\"left\"><p>2.70</p><p>(2.12–4.25)</p></td><td align=\"left\"><p>4.51</p><p>(2.49–5.55)</p></td><td align=\"left\">0.14</td><td align=\"left\"><p>5.12</p><p>(2.83–7.57)</p></td><td align=\"left\"><p>5.79</p><p>(3.43–7.53)</p></td><td align=\"left\">0.50</td><td align=\"left\">0.02</td><td align=\"left\">0.53</td></tr><tr><td align=\"left\">VAI</td><td align=\"left\"><p>0.99</p><p>(0.73–1.92)</p></td><td align=\"left\"><p>1.26</p><p>(0.96–1.98)</p></td><td align=\"left\">0.37</td><td align=\"left\"><p>1.49</p><p>(1.01–2.01)</p></td><td align=\"left\"><p>1.28</p><p>(0.86–2.31)</p></td><td align=\"left\">0.91</td><td align=\"left\">0.17</td><td align=\"left\">0.89</td></tr><tr><td align=\"left\">TG/HDL-C</td><td align=\"left\"><p>1.75</p><p>(1.28–3.22)</p></td><td align=\"left\"><p>2.22</p><p>(1.77–3.27)</p></td><td align=\"left\">0.39</td><td align=\"left\"><p>2.47</p><p>(1.57–3.26)</p></td><td align=\"left\"><p>2.11</p><p>(1.37–3.63)</p></td><td align=\"left\">0.86</td><td align=\"left\">0.32</td><td align=\"left\">0.94</td></tr><tr><td align=\"left\">TyG</td><td align=\"left\"><p>8.76</p><p>(8.49–9.11)</p></td><td align=\"left\"><p>8.84</p><p>(8.72–8.95)</p></td><td align=\"left\">0.54</td><td align=\"left\"><p>8.68</p><p>(8.39-9.00)</p></td><td align=\"left\"><p>8.92</p><p>(8.53–9.43)</p></td><td align=\"left\">0.08</td><td align=\"left\">0.87</td><td align=\"left\">0.55</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>\n<bold>Multivariate analysis between non-fatal acute myocardial infarction and several risk factors for cardiovascular disease in females and males</bold>\n</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\" colspan=\"3\">Dependent variable: non-fatal acute MI</th></tr><tr><th align=\"left\"/><th align=\"left\">IR index</th><th align=\"left\">OR (95% CI) in females</th><th align=\"left\">OR (95% CI) in males</th></tr></thead><tbody><tr><td align=\"left\"/><td align=\"left\">HOMA-IR</td><td align=\"left\">1.8 (1.2–2.8)</td><td align=\"left\">1.7 (1.4–2.1)</td></tr><tr><td align=\"left\"><bold>Model 1</bold> includes age, BMI, smoking habit, known family history of CVD, hsCRP, glycaemic state, triglycerides, HDL-cholesterol and <bold>HOMA-IR</bold></td><td align=\"left\"/><td align=\"left\">1.5 (0.8–2.9)</td><td align=\"left\">1.4 (1.0-1.9)</td></tr><tr><td align=\"left\"/><td align=\"left\">VAI</td><td align=\"left\">1.8 (1.2–2.7)</td><td align=\"left\">1.3 (1.1–1.5)</td></tr><tr><td align=\"left\"><bold>Model 2</bold> includes age, smoking habit, known family history of CVD, hsCRP, glycaemic states and <bold>VAI</bold></td><td align=\"left\"/><td align=\"left\">1.7 (1.0-2.9)</td><td align=\"left\">1.2 (0.9–1.5)</td></tr><tr><td align=\"left\"/><td align=\"left\">TG/HDL-C index</td><td align=\"left\">1.9 (1.2–2.9)</td><td align=\"left\">1.3 (1.1–1.5)</td></tr><tr><td align=\"left\"><bold>Model 3</bold> includes age, BMI, smoking habit, known family history of CVD, hsCRP, glycaemic states and <bold>TG/HDL-C index</bold></td><td align=\"left\"/><td align=\"left\">1.9 (1.1–3.4)</td><td align=\"left\">1.2 (0.9–1.5)</td></tr><tr><td align=\"left\"/><td align=\"left\">TyG</td><td align=\"left\">1.6 (0.9–2.8)</td><td align=\"left\">0.9 (0.8–1.3)</td></tr><tr><td align=\"left\"><bold>Model 4</bold> includes age, BMI, smoking habit, known family history of CVD, hsCRP, glycaemic states, HDL-choleserol and <bold>TyG</bold></td><td align=\"left\"/><td align=\"left\">0.7 (0.3–1.4)</td><td align=\"left\">0.5 (0.3–0.6)</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Continuous variables were expressed as median (IQR) and compared by Mann-Whitney test; categorical variables were reported as numbers and proportions and compared by chi-square test</p><p>*Close relative with CVD at &lt; 60 years of age</p><p>BMI = body mass index; CVD = cardiovascular disease; eGFR = estimated glomerular filtration rate; HbA1c = glycol-haemoglobin A1c; HDL-C = high-density lipoprotein cholesterol; HOMA-IR = homeostasis model assessment-insulin resistance; hsCRP = high-density C-reactive protein; IFG = impaired fasting glucose; IGT = impaired glucose tolerance; MI = myocardial infarction; NGT = normal glucose tolerance; T2DM = type 2 diabetes mellitus; TG = triglycerides; TyG = triglycerides x fasting glucose; VAI = visceral adiposity index</p></table-wrap-foot>", "<table-wrap-foot><p>Insulin resistance indexes were expressed as median (IQR) and compared by the Mann-Whitney test</p><p>HDL-C = high-density lipoprotein cholesterol; HOMA-IR = homeostasis model assessment-insulin resistance; IFG = impaired fasting glucose; IGT = impaired glucose tolerance; NGT = normal glucose tolerance; T2DM = type 2 diabetes mellitus; TG = triglycerides; TyG = triglycerides x fasting glucose; VAI = visceral adiposity index</p></table-wrap-foot>", "<table-wrap-foot><p>Continuous variables were natural log transformed</p><p>BMI = body mass index; CI = confidence interval; CVD = cardiovascular disease; HOMA-IR = homeostasis model assessment-insulin resistance; hsCRP = high sensitivity C-reactive protein; IR = insulin resistance; MI = myocardial infarction; OR = odds ratio; TG/HDL-C = triglycerides/high-density lipoprotein; TyG = triglycerides x fasting glucose; VAI = visceral adiposity index</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2093_Article_Equ1.gif\" position=\"anchor\"/>", "<graphic xlink:href=\"12933_2023_2093_Article_Equ2.gif\" position=\"anchor\"/>", "<graphic xlink:href=\"12933_2023_2093_Article_Equ3.gif\" position=\"anchor\"/>", "<graphic xlink:href=\"12933_2023_2093_Fig1_HTML\" id=\"d32e563\"/>" ]
[ "<media xlink:href=\"12933_2023_2093_MOESM1_ESM.docx\"><caption><p><bold>Supplementary Material 1:</bold> Supplemental Table 1. Main baseline characteristics within glycaemic states</p></caption></media>", "<media xlink:href=\"12933_2023_2093_MOESM2_ESM.docx\"><caption><p><bold>Supplementary Material 2:</bold> Supplemental Table 2. Multivariate analysis between sex and several risk factors for cardiovascular disease</p></caption></media>" ]
[{"label": ["5."], "mixed-citation": ["Dong X, Cai R, Sun J, Huang R, Wang P, Sun H et al. Diabetes as a risk factor for acute coronary syndrome in women compared with men: a meta-analysis, including 10 856 279 individuals and 106 703 acute coronary syndrome events. Diabetes Metab Res Rev. 2017;33(5)."]}, {"label": ["22."], "surname": ["Organization"], "given-names": ["WH"], "source": ["Definition and diagnosis of Diabetes Mellitus and Intermediate Hyperglycaemia: report of a WHO/IDF Consultation"], "year": ["2006"], "publisher-loc": ["Geneva"], "publisher-name": ["World Health Organization"]}, {"label": ["25."], "surname": ["Kautzky-Willer", "Brazzale", "Moro", "Vrb\u00edkov\u00e1", "Bendlova", "Sbrignadello"], "given-names": ["A", "AR", "E", "J", "B", "S"], "article-title": ["Influence of increasing BMI on insulin sensitivity and secretion in normotolerant men and women of a wide age span"], "source": ["Obes (Silver Spring)"], "year": ["2012"], "volume": ["20"], "issue": ["10"], "fpage": ["1966"], "lpage": ["73"], "pub-id": ["10.1038/oby.2011.384"]}]
{ "acronym": [ "BMI", "CAD", "CI", "CV", "CVD", "eGFR", "FPG", "HbA1c", "HDL-C", "HOMA-IR", "hsCRP", "IFG", "IGT", "IQR", "IR", "MI", "NGT", "OGTT", "OR", "PAROKRANK", "Scr", "T2DM", "TG", "TG/HDL-C", "TyG", "VAI", "WC" ], "definition": [ "body mass index", "coronary artery disease", "confidence interval", "cardiovascular", "cardiovascular disease", "estimated glomerular filtration rate", "fasting plasma glucose", "glycated haemoglobin A1c", "high-density lipoprotein-cholesterol", "Homeostatic Model Assessment of insulin resistance", "high-sensitivity C-reactive protein", "impaired fasting glucose", "impaired glucose tolerance", "interquartile range", "insulin resistance", "myocardial infarction", "normal glucose tolerance", "oral glucose tolerance test", "Odds ratio", "Periodontitis and its relation to coronary artery disease", "serum creatinine", "type 2 diabetes mellitus", "triglycerides", "triglycerides/high-density lipoprotein-cholesterol", "triglycerides x fasting glucose", "visceral adiposity index", "waist circumference" ] }
41
CC BY
no
2024-01-14 23:43:46
Cardiovasc Diabetol. 2024 Jan 13; 23:25
oa_package/8e/e2/PMC10787422.tar.gz
PMC10787423
0
[ "<title>Introduction</title>", "<p id=\"Par13\">Type 1 diabetes (T1D) is a chronic disease associated with poor cardiac outcomes and an increased risk of premature mortality [##REF##11742409##1##–##REF##28358037##3##]. It accounts for approximately 5–15% of diabetes cases in high-income countries and about 2% in low- and middle-income countries [##REF##34599655##4##]. The prevalence of T1D is increasing worldwide, showing variations across different countries and areas, potentially influenced by environmental variables [##REF##34427600##5##–##REF##23733895##8##].</p>", "<p id=\"Par14\">Cardiovascular diseases are the leading cause of mortality in individuals with T1D [##REF##10391392##9##]. Previous cohort studies have also suggested that T1D can increase the risk of cardiovascular diseases [##REF##15326070##10##–##REF##36419118##12##]. For example, a recently published Mendelian randomized(MR) study indicated that T1D increases the risk of atherosclerosis [##REF##37659996##13##]. Furthermore, Marcus Lind et al. showed that heart failure (HF) is a common complication in T1D patients [##UREF##2##14##]. However, there is an ongoing debate regarding the specific phenotype of HF associated with T1D. Most studies have suggested that T1D mainly affects the diastolic function, while effects on systolic function remain controversial [##REF##7924771##15##–##REF##17196468##19##]. Most cases in these studies were accompanied by confounding factors such as coronary artery disease and hypertension. According to the research on T1D conducted by Konduracka et al., it was found that the occurrence of HF and myocardial dysfunction was observed only in those who developed hypertension or coronary heart disease [##REF##23358920##20##]. In a recent study, no significant differences in echocardiographic findings were observed between patients with T1D and healthy individuals, despite the presence of microvascular damage [##UREF##3##21##]. Therefore, the influence of T1D on HF, especially non-ischemic cardiomyopathy (NICM), remains incompletely understood based on human studies. Diabetic cardiomyopathy has been proposed as an explanation for the residual risk of HF in diabetic patients after accounting for coronary heart disease, hypertension and other factors [##REF##430798##11##]. However, most of the studies on T1D-induced diabetic cardiomyopathy have focused mainly on animal and cellular experiments [##REF##21421556##22##–##UREF##4##25##]. Although diabetic cardiomyopathy is classified as a NICM resulting from diabetes mellitus, it is noteworthy that the myocardial pathologic phenotypes of T1D and type 2 diabetes (T2D) cardiomyopathy differ. Additionally, conducting real-world studies on T1D-induced NICM presents challenges in controlling for confounding factors. To address these gaps, it is essential to assess the causal relationship between T1D and NICM by MR method. In addition, another noteworthy consideration pertains to identify factors that mediate T1D-induced NICM. Previous observational studies have identified several inflammatory factors, such as interleukin-6, tumor necrosis factor α, and C-reactive protein (CRP), that are associated with HF [##REF##37495278##26##, ##REF##36882679##27##]. However, conflicting results have also been reported in some studies [##REF##36166332##28##, ##REF##16566827##29##]. Additionally, a observational study has shown that factors like renal disease and anemia are associated with the risk of HF [##REF##25539945##30##]. Thus, we aim to investigate whether inflammatory cytokines and certain diseases have mediating roles in the development of T1D-induced NICM.</p>", "<p id=\"Par15\">Conventional observational studies are susceptible to confounding factors and reverse causation bias. To overcome these limitations, MR utilizes genetic variants as instrumental variables (IVs) to infer causal relationships [##REF##32760811##31##]. MR can not only overcome the limitations of observational studies by mimicking a randomized controlled trial but also provide evidence beyond clinical studies to establish the causal association between T1D and NICM. In this study, we performed two-sample MR analyses and multivariable MR (MVMR) to investigate the independent causal effect of T1D and its complications on NCIM. Furthermore, we conducted mediation analysis to explore the mediators in the association between T1D and NICM.</p>" ]
[ "<title>Methods</title>", "<title>Two sample MR and MVMR</title>", "<p id=\"Par16\">Figure ##FIG##0##1## presents the study design. We used two-sample MR to investigate the causal effects of T1D and its complications on NICM [##REF##34936225##32##]. To obtain the necessary data, we collected summary statistics from publicly available databases, as outlined in Table ##TAB##0##1##. Our single nucleotide polymorphisms (SNPs) selection process focused on SNPs strongly associated with T1D and randomly allocated at conception, ensuring minimal influence from environmental factors [##UREF##5##33##]. We followed three assumptions for MR analysis: (1) the selected IVs must be strongly associated with T1D; (2) the selected IVs should not be associated with potential confounders; (3) the selected IVs could only influence the NICM through T1D, but not other pathways. In the primary analysis, we conducted MR analysis using data from two T1D datasets and used the conventional random effect inverse variance weighted (IVW) method to estimate the causal effect of T1D on NICM. In addition, we also performed four complementary methods, including the weighted median method, the weighted mode method, simple mode, MR Egger. To ensure the robustness of the outcomes, we performed a meta-analysis of the results from two T1D datasets. We also conducted MVMR to mitigate potential pleiotropy by accounting for confounding factors such as body mass index (BMI) and hypertension. The analytic process adhered to the STROBE-MR guidelines [##REF##34702754##34##].</p>", "<p id=\"Par17\">\n\n</p>", "<p id=\"Par18\">\n\n</p>", "<title>Mediation MR/Two-step MR analysis</title>", "<p id=\"Par19\">In the mediation analysis, we included glomerular disease, anemia, BMI, and hypertension. Furthermore, we included glycated hemoglobin, HOMA-IR, fasting insulin, blood lipids, CRP, and 41 other inflammatory factors in the mediation analysis. The three-step method provides evidence of a mediating role for a variable in the exposure-outcome effect. The indirect effect of each mediator was derived using the two-step MR method [##REF##22422451##35##]. In the first step, we estimated the causal impact of T1D on a hypothesized mediator using IVs for T1D. In the second step, we established the causal impact of the mediators on NICM using IVs for the mediator. For all mediators individually, we quantified the proportion mediated by dividing the indirect effect by the total effect. Confidence intervals were estimated using the delta method [##REF##32760811##31##].</p>", "<title>The data source and the selection of instrumental variables</title>", "<p id=\"Par20\">We extracted summary-level data for the associations of SNPs with T1D from two Genome-Wide Association Studies (GWASs). One is a meta-analysis including 9,266 T1D cases and 15,574 non-cases from 12 European cohorts [##REF##32005708##36##]. The other dataset is derived from the Finnish database and UKB data, consisting of 6,447 cases and 451,248 controls [##REF##34594039##37##]. T1D with complications dataset obtained from Finnish database [##REF##36653562##38##]. The NICM dataset comes from a Finnish database and contains 11,400 cases and 175,752 controls. For inflammatory cytokines, the data was from the study providing genome variant associations with 41 cytokines and growth factors in 8,293 individuals. This study combined the results from The Cardiovascular Risk in Young Finns Study (YFS) and FINRISK surveys [##UREF##6##39##]. The average participant ages are 37 years for YFS study and 60 years for FINRISK survey. Diseases in the Finnish database were diagnosed using ICD coding. The age distribution of patients and the inclusion process in the Finnish database can be accessed online through the link <ext-link ext-link-type=\"uri\" xlink:href=\"https://r9.risteys.finngen.fi/endpoints/+ID\">https://r9.risteys.finngen.fi/endpoints/+ID</ext-link>, such as ID E4_DM1PERIPH. Detailed information about the data sources can be found in Table ##TAB##0##1## and Table ##SUPPL##2##S1##. Table ##SUPPL##2##S1## includes information on all datasets and the available diagnostic codes.</p>", "<p id=\"Par21\">We used strict selection criteria to select valid and reliable IVs for T1D. First, we searched for the largest GWAS summary statistics for the genetic proxies of T1D. We extracted SNPs strongly associated with T1D as candidate IVs (<italic>p</italic> &lt; 5e-8). Second, we eliminated SNPs that were in linkage disequilibrium (r<sup>2</sup> &lt; 0.01) or palindromic with intermediate allele frequencies. Third, we excluded SNPs that were not available in the outcome GWAS or had proxy SNPs. In this study, we identified BMI and hypertension as confounding factors for NICM. We calculated the F statistics to measure the strength between IVs and T1D. We only considered SNPs with an F statistic &gt; 10 as valid and reliable IVs for T1D. Finally, we included the 50 qualified SNPs as IVs to conduct the MR analysis. We extracted IVs of complications of T1D using the same method. Detailed information on those IVs is shown in Supplementary Excel ##SUPPL##0##1##. Since only few SNPs were identified for part of mediators when they were as the exposure, a higher cutoff (<italic>p</italic> &lt; 5e-6) was chosen (<italic>p</italic> &lt; 5e-6, Supplementary Excel ##SUPPL##1##2##).</p>", "<title>Statistical analysis</title>", "<p id=\"Par22\">The MR estimates were represented by odds ratios (OR) with 95% confidence intervals (CIs). We performed the MR-Egger regression method, the leave-one-out method, and the MR-PRESSO method as sensitivity analysis. We used the MR-egger regression and MR-PRESSO method to test and correct the potential horizontal pleiotropy of the selected IVs. The MR-egger intercept and zero difference could indicate directional pleiotropy. The MR-PRESSO could detect and remove outliers in the IVs. We employed Cochrane’s Q statistic to evaluate the variability of SNPs estimates within each MR association. We used the p-value of the intercept test from MR-Egger regression to assess the horizontal pleiotropy [##REF##26050253##40##]. By using MVMR analysis to adjust for confounding risk factors, we reduced the impact of confounding factors on the causal relationship. We performed all tests using the Two Sample MR [##REF##29846171##41##], MR-PRESSO [##REF##29686387##42##] and Mendelian Randomization [##REF##28398548##43##] packages in the R software (version 4.0.2).</p>" ]
[ "<title>Result</title>", "<p id=\"Par23\">Univariable MR analysis supported a causal role for liability to T1D in the development of NICM. (IVW: GCST010681: OR 1.02; 95% CI 1.01–1.04; <italic>p</italic> = 1.17e-4; GCST90018925: OR 1.06; 95% CI 1.03–1.09; <italic>p</italic> = 0.02; Meta-analysis: OR 1.03; 95% CI 1.01–1.04; p&lt;1e-4). Additionally, under sensitivity analyses, the other three methods, including MR-Egger, weighted median, and weighted mode, also revealed significant associations between T1D and NICM in GCST010681 and meta-analysis. Only the simple mode was attenuated (GCST010681: OR 1.02; 95% CI 0.99–1.06; <italic>p</italic> = 0.17; GCST90018925: OR 0.99; 95% CI 0.92–1.06; <italic>p</italic> = 0.68; Meta-analysis: OR 1.02; 95% CI 0.99–1.05; <italic>p</italic> = 0.29).</p>", "<p id=\"Par24\">No heterogeneity or pleiotropy was observed in the associations between T1D (GCST010681) and NICM (<italic>p</italic> for heterogeneity = 0.35, <italic>p</italic> for pleiotropy = 0.28, respectively). For GCST90018925, heterogeneity exists but there is no evidence of pleiotropy (p for heterogeneity = 0.01, p for pleiotropy = 0.34, respectively). The results were robust in the leave-one-out and MR-PRESSO tests. To further rule out the influence of confounding factor level pleiotropy, we conducted MVMR. After matching for BMI, hypertension or both, statistical significance remained between T1D and NICM (Fig. ##FIG##2##3##). For additional information and visual representations of the data analysis, please refer to Supplementary Fig. ##SUPPL##0##1##, which includes scatter plots for the pleiotropy analysis, forest plots using the leave-one-out method, and funnel plots.</p>", "<p id=\"Par26\">To understand the relationship between different subgroups of T1D and NICM, we analyzed data from the Finnish database, which is the most comprehensive for T1D complications. Both T1D without complications and T1D with complications showed causal correlations with NICM (IVW: OR 1.02; 95% CI 1.004–1.04; <italic>p</italic> = 1.42e-02; OR 1.03; 95% CI 1.01–1.05; <italic>p</italic> = 3.15e-3, respectively). T1D with complications encompasses a range of diseases. These subgroup analyses also revealed significant causal correlations with NICM. The ORs of NICM were 1.02 (95% CI 1.01–1.03; <italic>p</italic> = 7.90e-03) for T1D with renal complications, 1.01 (95% CI 1.00-1.02; <italic>p</italic> = 8.75e-02) for T1D with ketoacidosis, 1.02 (95% CI 1.02–1.03; <italic>p</italic> = 4.17e-03) for T1D with coma, 1.03 (95% CI 1.01–1.05; <italic>p</italic> = 1.39e-02) for T1D with ophthalmic complications, 1.03 (95% CI 1.01–1.05; <italic>p</italic> = 5.19e-03) for T1D with peripheral circulatory complications, 1.02 (95% CI 1.01–1.04; <italic>p</italic> = 9.61e-03) for T1D with coma. Except for the analysis for T1D without complications, where heterogeneity was observed, all other subgroup analyses showed no significant heterogeneity or pleiotropy (Fig. ##FIG##1##2##). The results were robust in the leave-one-out and MR-PRESSO tests. We also conducted MVMR for T1D with complications. After matching for BMI, statistical significance remained (OR1.03, 95% CI 1.002–1.06, <italic>p</italic> = 3.66e-02) (Fig. ##FIG##2##3##). However, after adjusting for hypertension, the statistical correlation disappeared. In the subgroup analysis, the exposure and outcome datasets were from the same database. Therefore, there is a significant overlap in the control group. We used <ext-link ext-link-type=\"uri\" xlink:href=\"https://sb452.shinyapps.io/overlap\">https://sb452.shinyapps.io/overlap</ext-link> to estimate the potential for Type I errors. After evaluation, even if the samples completely overlapped, the type I errors rate still be maintained at 0.05 in all subgroup analyses.</p>", "<p id=\"Par27\">\n\n</p>", "<p id=\"Par25\">\n\n</p>", "<p id=\"Par29\">We then performed mediation analysis involving potential mediators, including anemia, glomerular disease, BMI, hypertension, glycated hemoglobin, HOMA-IR, fasting insulin, low-density lipoprotein cholesterol, triglyceride, intermediate-density lipoprotein and very-low-density lipoprotein. However, none of these factors demonstrated a mediating effect (Supplementary Excel.##SUPPL##1##2##). Among analyzed CRP and 41 inflammatory cytokines, a causal relationship with NICM was only found for Nerve Growth Factor and MIG. As Nerve Growth Factor had only 4 SNP instrumental variables, thus further analysis was not performed. Conversely, MIG mediated the relationship between T1D and NICM with an OR of 1.005 (95% CI 1.001–1.01) and accounted for 20% of the mediation effect (See Fig. ##FIG##3##4##). During the MR process, multiple tests were performed, hence the p-value was adjusted using false discovery rate (FDR) correction. The significance of the p-value for MIG disappears after correction (Supplementary Excel. ##SUPPL##0##1##).</p>", "<p id=\"Par28\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par30\">The study provided genetic evidence supporting the causal association between NICM and T1D in univariable MR and MVMR analyses. Furthermore, the study demonstrated the causal relationship between T1D complications and NICM. Notably, there was no significant difference in the OR of NICM between T1D alone and T1D with complications.</p>", "<p id=\"Par31\">Clinical observational studies have suggested an association between diabetes mellitus and HF [##UREF##3##21##, ##UREF##7##44##–##REF##12556246##46##]. However, these studies primarily focus on T2D and are influenced by numerous confounding factors. For most diabetic patients who develop HF, their HF is related to coronary artery disease [##REF##9857929##18##]. Therefore, it is necessary to elucidate the isolated impact of T1D on NICM. The impact of T1D on the myocardium is primarily focused on animal studies. In recent studies, it has been suggested that factors such as oxidative stress, inflammatory response, calcium ion imbalance, and energy dysregulation are involved in the impact of diabetes mellitus on the myocardium [##UREF##8##47##, ##REF##21498129##48##]. Our previous study demonstrated impaired diastolic function in T1D SD rats [##REF##31363380##49##]. Clinical research on the relationship between T1D and NICM is limited due to challenges in conducting prospective clinical studies, including cost and confounding biases. To address these challenges, we used an MR study to establish a causal connection between T1D and NICM, providing valuable evidence.</p>", "<p id=\"Par32\">Anemia and nephropathy are relatively common concurrent diseases in patients with HF. Both of these conditions increase the risk factors for poor prognosis in patients with HF [##REF##15864227##50##, ##REF##11583864##51##]. Additionally, iron deficiency anemia and chronic kidney disease have been identified as risk factors for HF [##REF##25539945##30##, ##REF##36104509##52##]. However, it is worth noting that most research findings in the existing literature are derived from developed countries and largely focus on cases of ischemic cardiomyopathy. In a study from a developing country, the authors observed a significantly lower prevalence of anemia and nephropathy in individuals with NICM compared to studies conducted in Western countries [##REF##17251058##53##]. An MR study suggested bidirectional causality between anemia and chronic HF [##REF##37301769##54##]. Glomerular disease is a common complication of T1D. The correlation between T1D and anemia is unclear, but its complication, diabetic nephropathy, can cause anemia. The current study confirmed a causal association between genetically predicted T1D and genetically predicted glomerular disease as well as anemia. However, the causal relationship between anemia and NICM showed pleiotropy in the MR analysis. Although there is a causal relationship between glomerular disease and NICM, the mediating effect did not reach statistical significance. Therefore, further research is needed to analyze this potential mediating effect.</p>", "<p id=\"Par33\">The association between inflammation and HF is currently a topic of great interest. An observational study conducted in 1990 found that patients with HF had elevated level of pro-inflammatory cytokines compared to healthy individuals [##REF##2195340##55##]. Subsequent experimental and clinical research has highlighted the activation of the innate and adaptive immune systems as important factors in acute and chronic HF, leading to the exploration of potential immunotherapy for HF [##REF##31969688##56##]. However, the outcomes of immunotherapy for HF have been less than satisfactory [##REF##25814686##57##–##REF##12796126##59##]. The CANTOS trial, a double-blind, randomized, placebo-controlled outcomes trial involving 10,061 patients with myocardial infarction and inflammatory atherosclerosis characterized by high-sensitivity CRP levels ≥ 2 mg/l, demonstrated a 15% reduction in the risk of the composite endpoint of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death compared to placebo [##REF##28845751##60##]. Further exploration of this study revealed that patients with evidence of clonal hematopoiesis of indeterminate potential owing to mutations in TET2 had an improved response to canakinumab treatment compared with patients without the mutations [##REF##35385050##61##]. This study provides inspiration that immunotherapy may not be universally effective for all cases of HF, and thus, it is important to explore which specific types of HF may respond positively to immunization. In an MR study, it was proposed that genetically predicted 10 inflammatory biomarkers (not including MIG) did not show a significant association with HF [##REF##36166332##28##]. In current study, we investigated the causal relationship between 42 inflammatory biomarkers and discovered that MIG has a suggestive causal relationship with NICM and may plays a mediating role in the process of T1D causing NICM. Previous studies have also found that MIG is involved in immune checkpoint inhibitor myocarditis and chronic rejection after heart transplantation [##UREF##9##62##, ##REF##12368204##63##]. Further exploration is warranted to determine the role of MIG in NICM.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par34\">To our knowledge, this is the first study to investigate the causal associations between T1D and NICM using univariable MR and MVMR analysis. The study fills a gap in the current human-level research on the causal relationship between T1D and NICM. Additionally, by investigating potential mediators, we can improve our understanding of the potential mechanisms underlying NICM, paving the way toward the development of preventative and therapeutic solutions. The application of the MR method helped to reduce confounding biases and derive robust causal effect estimates. Multiple sensitivity analyses and IV strength evaluations were conducted to ensure the reliability of the results. However, this study has certain limitations. Firstly, most of the data used in this study comes from individuals of European ancestry, which may limit the generalizability of our findings. Secondly, while subgroup MR analysis of T1D with complications can offer us a comprehensive insight into the association between various complications and NICM, it is important to acknowledge the considerable sample overlap between participants in the exposure and outcome datasets. In fact, these are single-sample analysis. This might increase the risk of type I errors, so caution should be exercised when interpreting the results in this section. We used <ext-link ext-link-type=\"uri\" xlink:href=\"https://sb452.shinyapps.io/overlap\">https://sb452.shinyapps.io/overlap</ext-link> to estimate the potential for Type I errors. After evaluation, even if the samples completely overlapped, the type I error rate could be maintained at 0.05 in all subgroup analyses. Thirdly, even with the assurance of F statistic &gt; 10, the explanatory power of IVs on potential mediating variables is limited. Therefore, even though many inflammatory cytokines have not been found to have a mediating effect, further research is still warranted in this area. In addition, the correlation p-value of MIG becomes non-significant after FDR correction. This suggests that it may play a mediating role, but more evidence is needed to confirm this.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par35\">In conclusion, the study suggests that genetically predicted T1D and its complications play an independent causal role in the development of NICM. MIG may mediate the progression from T1D to NICM.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Type 1 diabetes (T1D) is a significant risk factor for a range of cardiovascular diseases. Nonetheless, the causal relationship between T1D and non-ischemic cardiomyopathy (NICM) remains to be elucidated. Furthermore, the mechanisms responsible for the progression from T1D to NICM have not been definitively characterized.</p>", "<title>Objective</title>", "<p id=\"Par2\">The aim of this study was to conduct a Mendelian randomization (MR) study to investigate the causal effects of T1D and its complications on the development of NICM. Additionally, this study aimed to conduct a mediation analysis to identify potential mediators within this correlation.</p>", "<title>Methods</title>", "<p id=\"Par3\">Genetic variants were used as instrumental variables for T1D. The summary data for T1D were obtained from two genome-wide association study datasets. The summary data for T1D with complications and NICM were obtained from the Finnish database. Two-sample MR, multivariable MR and mediation MR were conducted in this study.</p>", "<title>Results</title>", "<p id=\"Par4\">The study revealed a causal association between T1D, T1D with complications, and NICM (with odds ratios of 1.02, 95% CI 1.01–1.04, <italic>p</italic> = 1.17e-04 and 1.03, 95% CI 1.01–1.05, <italic>p</italic> = 3.15e-3). Even after adjusting for confounding factors such as body mass index and hypertension, T1D remained statistically significant (with odds ratio of 1.02, 95% CI 1.01–1.04, <italic>p</italic> = 1.35e-4). Mediation analysis indicated that monokine induced by gamma interferon may play a mediating role in the pathogenesis of T1D-NICM (mediation effect indicated by odds ratio of 1.005, 95% CI 1.001–1.01, <italic>p</italic> = 4.9e-2).</p>", "<title>Conclusion</title>", "<p id=\"Par5\">The study demonstrates a causal relationship between T1D, its complications, and NICM. Additionally, monokine induced by gamma interferon may act as a potential mediator in the pathogenesis of T1D-NICM.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02117-7.</p>", "<title>Key points</title>", "<p id=\"Par7\">\n<bold>Question:</bold> 1 Does type 1 diabetes(T1D) have an independent causal relationship with non-ischemic cardiomyopathy (NICM)?</p>", "<p id=\"Par8\">2 Which inflammatory factors or diseases mediate the development of NICM in T1D?</p>", "<p id=\"Par9\">\n<bold>The following findings were identified in a Mendelian randomization study:</bold></p>", "<p id=\"Par10\">\n<bold>Primary findings:</bold> 1 There is an independent causal relationship between T1D and NICM. Additionally, the causal relationship between T1D with complications and NICM is demonstrated. 2 Monokine induced by IFN-γ (MIG) mediates the progression from T1D to NICM.</p>", "<p id=\"Par11\">\n<bold>Secondary findings:</bold> BMI, hypertension, glomerular diseases, and MIG are causally associated with NICM.</p>", "<p id=\"Par12\">\n<bold>Meaning:</bold> All the findings are first-time discoveries in Mendelian randomization studies. The study confirms the causal relationship between T1D and NICM, while accounting for confounding factors. The MIG serves as a potential target for new preventive measure and therapy.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02117-7.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We want to acknowledge the participants and investigators of the FinnGen study, UK Biobank, and other GWASs included in this study. Without the dedication of these organizations and their members, this article would have been difficult to complete.</p>", "<title>Author contributions</title>", "<p>The concept for the project was developed by H C and YT C. And， YY Z designed this study and revised the manuscript. T Z, ZS H, YT L, L P, SH L and Jl L collected data from the public database. YY Z and EX Q wrote the manuscript. All authors contributed to the article and approved the submitted version.</p>", "<title>Funding</title>", "<p>This study was supported by the Science and Technology Program of Guangzhou, China (grant nos 202103000060).</p>", "<title>Declarations</title>", "<title>Competing interests</title>", "<p id=\"Par38\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Study design</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Genetically predicted type 1 diabetes and its complications: associations with the non-ischemic cardiomyopathy. IVW (Inverse Variance Weighted), H (Heterogeneity), P (Pleiotropy), CI (Confidence Interval), OR (Odds Ratio), <italic>p</italic> &lt; 0.05 was considered statistically significant. The FDR-corrected results of the p-values (IVW) in each sub-group remained consistent with the uncorrected results</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Genetically predicted association of T1D and its complications: associations with the non-ischemic cardiomyopathy after adjusting for confounders. CI (Confidence Interval), OR (Odds Ratio), <italic>p</italic> &lt; 0.05 was considered statistically significant</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Mediation analysis. CI (Confidence Interval), OR (Odds Ratio), <italic>p</italic> &lt; 0.05 was considered statistically significant. After applying FDR correction, the p-value for the correlation between MIG and NICM was determined to be 0.25</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Information on data included in the study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Phenotypes/ID</th><th align=\"left\">Data source</th><th align=\"left\">Study information/PMID</th><th align=\"left\">Cases/controls</th><th align=\"left\">Author/Year</th></tr></thead><tbody><tr><td align=\"left\"><p>T1D:</p><p>ebi-a-GCST010681</p></td><td align=\"left\">12 cohorts<sup>#</sup></td><td align=\"left\">European /32,005,708</td><td align=\"left\">9266/15,574</td><td align=\"left\">Forgetta V/2020</td></tr><tr><td align=\"left\"><p>T1D:</p><p>ebi-a-GCST90018925</p></td><td align=\"left\">UKB, Finnish database</td><td align=\"left\">European/34,594,039</td><td align=\"left\">6447/451,248</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D with complications:</p><p>DM1NASCOMP</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">6234/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D without complications:</p><p>E4_DM1NOCOMP</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">4918/183,185</td><td align=\"left\">NA/2021</td></tr><tr><td align=\"left\"><p>T1D with renal complications:</p><p>E4_DM1REN</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">1579/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D with ketoacidosis:</p><p>E4_DM1KETO</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">2102/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D with coma:</p><p>E4_DM1COMA</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">2050/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D with neurological complications:</p><p>E4_DM1NEU</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">1077/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D with peripheral circulatory complications:</p><p>E4_DM1PERIPH</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">669/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>T1D with ophthalmic complications:</p><p>E4_DM1OPTH</p></td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">5202/308,280</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\">Non-ischemic cardiomyopathy: finn-b-I9_NONISCHCARDMYOP</td><td align=\"left\">Finnish database</td><td align=\"left\">European</td><td align=\"left\">11,400/175,752</td><td align=\"left\">NA/2022</td></tr><tr><td align=\"left\"><p>Hypertension:</p><p>ukb-b-12,493</p></td><td align=\"left\">UKB</td><td align=\"left\">European</td><td align=\"left\">54,358/408,652</td><td align=\"left\">2018/Ben Elsworth</td></tr><tr><td align=\"left\"><p>Body mass index:</p><p>ukb-b-19,953</p></td><td align=\"left\">UKB</td><td align=\"left\">European</td><td align=\"left\">461,460</td><td align=\"left\">2018/Ben Elsworth</td></tr><tr><td align=\"left\">Monokine Induced by Gamma Interferon</td><td align=\"left\">YFS and FINRISK 1997 and 2002</td><td align=\"left\">European/33,491,305</td><td align=\"left\">8293</td><td align=\"left\">2020/Vanessa Tan</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>" ]
[ "<table-wrap-foot><p>#, See Table ##SUPPL##2##S1## for more details. UKB (UK BioBank), YFS (Young Finns Study), FINRISK (Finland’s National FINRISK Study)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Yunyue Zhao, Enxi Quan and Tao Zeng contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2117_Fig1_HTML\" id=\"d32e390\"/>", "<graphic xlink:href=\"12933_2023_2117_Fig2_HTML\" id=\"d32e756\"/>", "<graphic xlink:href=\"12933_2023_2117_Fig3_HTML\" id=\"d32e770\"/>", "<graphic xlink:href=\"12933_2023_2117_Fig4_HTML\" id=\"d32e795\"/>" ]
[ "<media xlink:href=\"12933_2023_2117_MOESM1_ESM.xls\"><caption><p><bold>Supplementary Material 1:</bold><bold> Supplemental Excel 1</bold>. Detailed data for univariate and multivariate mendelian randomization</p></caption></media>", "<media xlink:href=\"12933_2023_2117_MOESM2_ESM.docx\"><caption><p><bold>Supplementary Material 2:</bold><bold> Table S1</bold>. Descriptive information for all the datasets included and their corresponding diagnostic codes</p></caption></media>", "<media xlink:href=\"12933_2023_2117_MOESM3_ESM.xlsx\"><caption><p><bold>Supplementary Material 3:</bold><bold> Supplemental Excel 2</bold>. Detailed data for mediation mendelian randomization</p></caption></media>", "<media xlink:href=\"12933_2023_2117_MOESM4_ESM.pdf\"><caption><p><bold>Supplementary Material 4:</bold><bold>Supplemental Figure 1</bold>. Visualization of Mendelian Randomization for T1D and T1D with Complications: A) Pleiotropy Analysis; B) Stability Analysis Utilizing the Leave-One-Out Method; C) Forest Plot Showing MR Effect Sizes Using MR-Egger and IVW; D) Funnel Plot</p></caption></media>" ]
[{"label": ["2."], "surname": ["Chen", "Magliano", "Zimmet"], "given-names": ["L", "DJ", "PZ"], "article-title": ["The worldwide epidemiology of type 2 diabetes mellitus\u2014present and future perspectives"], "source": ["Nat Rev Endocrinol"], "year": ["2012"], "volume": ["8"], "fpage": ["228"], "lpage": ["36"]}, {"label": ["7."], "mixed-citation": ["Luk AOY, Ke C, Lau ESH, Wu H, Goggins W, Ma RCW et al. Secular trends in incidence of type 1 and type 2 diabetes in Hong Kong: A retrospective cohort study. Basu S, editor. PLoS Med. 2020;17:e1003052."]}, {"label": ["14."], "surname": ["Lind", "Bounias", "Olsson", "Gudbj\u00f6rnsdottir", "Svensson", "Rosengren"], "given-names": ["M", "I", "M", "S", "A-M", "A"], "article-title": ["Glycaemic control and incidence of heart failure in 20 985 patients with type 1 diabetes: an observational study"], "source": ["The Lancet"], "year": ["2011"], "volume": ["378"], "fpage": ["140"], "lpage": ["6"]}, {"label": ["21."], "surname": ["Brunvand", "Fugelseth", "Stensaeth", "Dahl-J\u00f8rgensen", "Margeirsdottir"], "given-names": ["L", "D", "KH", "K", "HD"], "article-title": ["Early reduced myocardial diastolic function in children and adolescents with type 1 diabetes mellitus a population-based study"], "source": ["Bmc Cardiovasc Disor"], "year": ["2016"], "volume": ["16"], "fpage": ["103"]}, {"label": ["25."], "surname": ["Fang", "Wang", "Wang", "Zhang", "Yin", "Li"], "given-names": ["Q", "J", "L", "Y", "H", "Y"], "article-title": ["Attenuation of inflammatory response by a novel chalcone protects kidney and heart from hyperglycemia-induced injuries in type 1 diabetic mice"], "source": ["Toxicol Appl Pharm"], "year": ["2015"], "volume": ["288"], "fpage": ["179"], "lpage": ["91"]}, {"label": ["33."], "surname": ["Hingorani", "Humphries"], "given-names": ["A", "S"], "article-title": ["Nature\u2019s randomised trials"], "source": ["The Lancet"], "year": ["2005"], "volume": ["366"], "fpage": ["1906"], "lpage": ["8"]}, {"label": ["39."], "mixed-citation": ["Ahola-Olli AV, W\u00fcrtz P, Havulinna AS, Aalto K, Pitk\u00e4nen N, Lehtim\u00e4ki T, et al. Genome-wide association study identifies 27 loci influencing concentrations of circulating cytokines and growth factors. Am J Hum Genet. 2017;100:40\u201350."]}, {"label": ["44."], "surname": ["Rawshani", "Sattar", "Franz\u00e9n", "Rawshani", "Hattersley", "Svensson"], "given-names": ["A", "N", "S", "A", "AT", "A-M"], "article-title": ["Excess mortality and cardiovascular disease in young adults with type 1 diabetes in relation to age at onset: a nationwide, register-based cohort study"], "source": ["The Lancet"], "year": ["2018"], "volume": ["392"], "fpage": ["477"], "lpage": ["86"]}, {"label": ["47."], "mixed-citation": ["Dillmann WH. Diabetic Cardiomyopathy. Circ Res. 2019;124(8):1160\u20131162."]}, {"label": ["62."], "mixed-citation": ["Ma P, Liu J, Qin J, Lai L, Heo GS, Luehmann H et al. Expansion of pathogenic Cardiac macrophages in Immune checkpoint inhibitor myocarditis. Circulation. 2023."]}]
{ "acronym": [ "IVW", "IVs", "SNPs", "FDR", "MVMR", "T1D", "T2D", "NICM", "HF", "OR", "MIG", "HOMA-IR", "GWAS", "CRP", "UKB" ], "definition": [ "Inverse variance weighted", "Instrumental variables", "Single Nucleotide Polymorphisms", "False Discovery Rate", "Multivariable MR", "Type 1 diabetes", "Type 2 diabetic", "Non-ischemic cardiomyopathy", "Heart failure", "Odds ratio", "Monokine Induced by Gamma Interferon", "Homeostatic Model Assessment of Insulin Resistance", "Genome-Wide Association Study", "C-reactive protein", "UK Biobank" ] }
63
CC BY
no
2024-01-14 23:43:46
Cardiovasc Diabetol. 2024 Jan 13; 23:31
oa_package/95/84/PMC10787423.tar.gz
PMC10787424
0
[ "<title>Introduction</title>", "<p id=\"Par23\">Today people tend to live for longer, however, the rate of aging of the population as a whole has accelerated [##UREF##0##1##]. The World Health Organization estimates that between 2015 and 2050, the percentage of the world’s population aged over 60 years will double from 12 to 22%; and that by 2030, one in six people in the world will be aged 60 or over [##UREF##0##1##]. A healthy old age is related with maintaining quality of life, allowing people to carry out their everyday activities normally [##UREF##1##2##].</p>", "<p id=\"Par24\">Older adults present a wide variety of oral problems, such as caries, periodontal disease, tooth loss, non-functional dentures, lesions in the oral mucosa, and xerostomia, which directly affect their eating and nutrition habits [##REF##9766107##3##, ##REF##15725170##4##]. Extensive tooth loss may affect their speech, and chewing together with aesthetic implications, leading to problems with self-esteem and social interaction [##UREF##2##5##–##UREF##3##8##]<italic>.</italic> All the diseases and conditions mentioned above, in addition to co-morbidities and limited access to dental care in older adult populations, could significantly impact their quality of life [##REF##27401382##9##, ##REF##28792274##10##].</p>", "<p id=\"Par25\">The concept of Oral Health-Related Quality of Life (OHRQoL) is conceived of as a multi-dimensional, self-reported evaluation to measure the impact of oral health on everyday activities [##REF##21422477##11##]. In response to this need, various generic (Geriatric Oral Health Assessment Index-GOHAI, Oral Health Impact Profile-OHIP) and condition-specific instruments (Prosthetic Quality of Life-PQL, Oral Aesthetic-related quality of life-QoLDAS) have been developed to measure OHRQoL, however, according to our knowledge, there is no comparative evaluation of psychometric properties and applicability of OHRQoL instruments developed and validated for older adults. A comparative evaluation that identifies the strengths and weaknesses would facilitate the choice of the most suitable tool for clinical or research purposes to determine the expectations and perceptions about OHRQoL in this population. Therefore, unsuitable OHRQoL instruments for specific purposes or with deficient psychometric properties can introduce bias through unreliable effect estimates, leading to wrong clinical decisions. In addition, identifying suitable instruments to measure OHRQoL in older adults could contribute to formulating public policies that consider the user’s perspectives to improve their quality of life. Nevertheless, the absence of a valid and reliable OHRQoL measure could hinder this purpose.</p>", "<p id=\"Par26\">This study aimed to identify OHRQoL instruments available for older adults and summarize the evidence on the conceptual and measurement model, psychometric properties, interpretability, and administration issues of OHRQoL instruments available for older adults through a systematic review.</p>" ]
[ "<title>Material and methods</title>", "<title>Protocol</title>", "<p id=\"Par27\">For this study, we used the methodology published previously [##REF##18194398##12##]. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis ##SUPPL##0##(PRISMA) guidelines## to report this systematic review [##REF##36911350##13##–##REF##33388080##15##] (Online Resource ##SUPPL##0##1##). This study was registered in PROSPERO (CRD42019133875).</p>", "<title>Eligibility criteria</title>", "<p id=\"Par28\">Qualitative, observational and experimental studies reporting information on the conceptual and measurement model, the psychometric properties (reliability, validity and responsiveness), interpretability, and the administration (administration burden and alternative modes of administration) of OHRQoL instruments in older adults (&gt; 60 years old or average age over 60 years) were included. Development studies for instruments that were not initially identified in the search were also included, regardless of the population’s age included. Articles written in English, Spanish, Portuguese, French, German and Italian were eligible, including studies both of original instruments and of versions validated for other countries.</p>", "<p id=\"Par29\">Studies that did not evaluate the conceptual and measurement model, psychometric properties or administration of OHRQoL questionnaires, studies that evaluated instruments measuring patient-reported outcomes (PRO) other than the quality of life, and studies without information on the age of the participants were excluded.</p>", "<title>Information sources and search</title>", "<p id=\"Par30\">A systematic search was conducted from inception to February 2023 in the following databases: MEDLINE, EMBASE, LILACS, and CENTRAL. The search strategy used in Medline is listed in the supplementary material (Online Resource ##SUPPL##1##2##).</p>", "<p id=\"Par31\">It was complemented by a manual review of the references of the articles included and by online databases of PRO instruments: PROQOLID (<ext-link ext-link-type=\"uri\" xlink:href=\"https://eprovide.mapi-trust.org\">https://eprovide.mapi-trust.org</ext-link>) and BiblioPRO (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.bibliopro.org\">www.bibliopro.org</ext-link>).</p>", "<title>Study selection</title>", "<p id=\"Par32\">Pairs of reviewers (CAA-GEE, PMM-CZ) in duplicate selected titles, abstracts, and full text. Any disagreement between the two review authors over the eligibility of a study was resolved through a third reviewer (YP).</p>", "<title>Data collection process</title>", "<p id=\"Par33\">Each oral health-related quality of life instrument was evaluated independently by two reviewers with training and experience in measuring PRO (AP, CAA, CZ, GEE, MF, NFD, PMM, OG, or YP). The instruments were evaluated in the EMPRO online platform (<ext-link ext-link-type=\"uri\" xlink:href=\"https://empro.imim.es/es/principal\">https://empro.imim.es/es/principal</ext-link>). Disagreements on the criteria analysed were resolved by consensus between the evaluators.</p>", "<title>Evaluating measures of patient-reported outcomes</title>", "<p id=\"Par34\">The EMPRO tool consists of 39 criteria assessing both the methodological quality of the included studies (11 criteria) and the results regarding their psychometric properties (13–16 criteria, since 3 could be assessed as not applicable), considering 8 attributes: 1.Conceptual and measurement model; 2.Reliability; 3.Validity; 4.Responsiveness; 5.Interpretability; 6.Burden (time, effort, and other demands on administrators and respondents); 7.Alternative modes of administration; 8.Cross-cultural and linguistic adaptation. The latter attribute was not completed in our case, because it was outside the scope of this study.</p>", "<p id=\"Par35\">Agreement with each item is answered on a four-point Likert scale, from 4 (strongly agree) to 1 (strongly disagree), and there is also a “no information” option. Five items allow a reply of “not applicable”. Items for which the response option is “no information” are assigned a score of 1 (lowest possible score).</p>", "<p id=\"Par36\">The overall score is constructed from the first five attributes. These attributes assess both the methodological quality of the included studies (11 criteria) and the results regarding their psychometric properties (13–16 criteria, since three could be assessed as not applicable) [##REF##18194398##12##].</p>", "<title>Strategy for data synthesis</title>", "<p id=\"Par37\">Attribute-specific scores and an overall score were calculated for each instrument. The mean score of the items was calculated for each attribute when at least 50% of the attributes were rated. Mean scores were linearly transformed into a range from 0 (worst possible score) to 100 (best possible score). Separate sub-scores for the Reliability and Burden attributes were calculated, as they are composed of two components each: “internal consistency” and “reproducibility” for Reliability and “respondent” and “administrative” for Burden. For Reliability, as the two components represent different approaches to examine the same attribute, the higher sub-score was chosen. For Burden, the final score was calculated as their mean as the two components assess different aspects of the same attribute.</p>", "<p id=\"Par38\">The overall score was computed by calculating the mean of the five metric-related attributes: Conceptual and measurement model, Reliability, Validity, Responsiveness, and Interpretability. The overall score was only calculated when at least three of these five attributes had a score. EMPRO scores were considered acceptable if they reached at least 50 points (half the theoretical maximum of 100 points) [##REF##18194398##12##, ##REF##23681849##16##].</p>" ]
[ "<title>Results</title>", "<title>Search results</title>", "<p id=\"Par39\">The search identified 5319 references (Fig. ##FIG##0##1##). After excluding 1005 duplicates and reviewing the titles, abstracts and full-text, 297 articles were selected. Of these, 211 were excluded, and 86 studies were selected as potentially relevant for data extraction. Twelve further articles were identified by manual search and from online databases of PRO. Thus, a total of 97 full-text articles assessed 14 instruments were considered in the EMPRO evaluation (see characteristics of included in Online Resource ##SUPPL##2##3##). The number of articles found per instrument ranged from 1 to 43, with five articles providing information for more than one instrument.</p>", "<title>Characteristics of instruments</title>", "<p id=\"Par40\">Table ##TAB##0##1## shows the characteristics of the instruments identified. The instruments identified were developed between 1993 and 2020. Seven instruments were developed in English, three in Spanish, and one in different languages (British, English, Dutch, French, German, Greek, Hebrew, Italian, Polish, Swedish, and Norwegian). The Geriatric Oral Health Assessment Index (GOHAI), The Oral Health Impact Profile (OHIP), and The Oral Hygiene Assessment Instrument (OHAI) were the only instruments adapted to other languages. The European Organization of Research and Treatment of Cancer, Oral Health Module (EORTC QLQ-OH-15) was developed in different countries and languages. Most instruments are self-administered (9/14), while five were developed for administration in an interview. Seven instruments were developed exclusively for an older adult population (DSQ, GOHAI, IPQ-RDE, OHAI, OHIDL, OHQoL-UK-W, OHIP); three for adult and older adult populations (EORTC QLQ-OH15, QoLDAS-9: Oral Aesthetic-related quality of life, PQL: Prosthetic Quality of Life, QoLIP-10:The Quality of Life with Implant-Protheses); and three were developed for an adult population but were subsequently validated for older adult populations (LORQ: Liverpool Oral Rehabilitation Questionnaire, OIDP: Oral Impacts on Daily Performance, OHRQL: Oral Health-Related Quality of Life). The majority of the instruments (8/14) were generic for measuring OHRQoL, and only six were designed to assess specific treatments and health conditions related with oral health. Within the specific instruments, DSQ was designed to measure patient satisfaction before and after prosthesis treatment. EORTC QLQ-OH15 focused on oral health and related QoL issues in all cancer diagnoses. LORQ is a specific questionnaire for head and neck cancer. PQL evaluates OHRQoL in individuals who use a removable prosthesis. QoLDAS-9 evaluates the quality of life-related with oral aesthetics in patients with restoration by prosthesis. Finally, QoLIP-10 evaluates the OHRQoL of patients who have received oral rehabilitation with Implant-Prostheses.\n</p>", "<title>Results of the EMPRO ratings</title>", "<p id=\"Par41\">The attribute Conceptual and measurement model presented the best performance, with 10/14 instruments obtaining a score higher than 50.0. The thresholds for this attribute varied between 17.9 and 97.6, with 3/14 instruments obtaining a score higher than 90 (EORTC QLQ-OH15, GOHAI, and QOLDAS-9). The OHAI obtained a score of 63.1 and the DSQ could not be evaluated as there was insufficient information for most aspects analysed in this attribute (Fig. ##FIG##1##2##). The OHAI and the DSQ were not included in the figures since they had insufficient information for an overall evaluation.</p>", "<p id=\"Par42\">The thresholds for Reliability varied between 12.5 and 87.5. Five instruments had a score equal to or higher than 50.0; IPQ-RDE obtained the highest score, followed by GOHAI, OHIP, EORTC-OH15 and OHIDL. EMPRO score could not be obtained for DSQ, LORQ, and OHAI due to the lack of enough evidence identified (Fig. ##FIG##1##2##).</p>", "<p id=\"Par43\">Validity was the attribute with the second-best performance in the instruments, with 9/14 instruments obtaining a score higher than 50.0. The thresholds varied between 13.9 for LORQ and 94.4 for QOLIP-10. DSQ and OHAI did not present sufficient information to assess this attribute (Fig. ##FIG##1##2##).</p>", "<p id=\"Par44\">Interpretability presented the worst performance. Only four instruments presented sufficient information for evaluation, with scores of 77.8 for EORTC QLQ-OH15, 38.9 for IPQ-RDE and 33.3 for OHIDL and QOLIP-10 (Fig. ##FIG##1##2##).</p>", "<p id=\"Par45\">Only five instruments presented sufficient information for evaluation of Responsiveness, all with scores over 50.0: OHIP rated the maximum score (100.0), GOHAI and OHIDL 66.7, OIDP 61.2, and EORTC QLQ-OH15 rated 50.0.</p>", "<p id=\"Par46\">In evaluating the ease of use of the instruments, QoLDAS-9, OHAI and GOHAI obtained the highest scores for Respondent burden (88.9, 83.3 and 83.3). These instruments described the skills and time needed to complete the instrument, its acceptability, and the circumstances in which it is unsuitable for the respondent. The instruments which obtained the highest scores for questionnaire administration and scoring were QoLDAS-9 and OHIP, with 100.0 each. The high scores were because the instrument details the resources needed for the administration, the score calculation method is well described, and the associated burden is acceptable.</p>", "<p id=\"Par47\">OHIP was the only instrument with alternative administration forms, in this case, application by an interview. Abbreviated versions of the original format of the instrument (OHIP-49) were also evaluated, namely OHIP-14 and OHIP-7. A specific version for edentulous patients has also been created (OHIP-Edent).</p>", "<p id=\"Par48\">The instrument with the highest overall score was EORTC QLQ-OH15 with 73.7, followed by OHIP with 66.9, GOHAI with 65.5, and OHIDL with 65.2. The instruments with the lowest scores were OHRQL with 24.7 and LORQ, with 8.9. Six instruments obtained an overall score lower than 50.0 (LORQ, OIDP, OHQOL-UK-W, OHRQoL, PQL, QOLDAS-9). The overall scores for DSQ and OHAI were not analysed as they did not present information for at least 4 attributes evaluated by EMPRO (Fig. ##FIG##1##2##).</p>", "<p id=\"Par49\">The detailed results of EMPRO for any specific criterion and attribute are shown in Table ##TAB##1##2##.\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par50\">Evaluation of OHRQoL plays an important role in clinical practice. As a result, several instruments have been developed to evaluate functional, social and psychological aspects of oral diseases or conditions disorder [##REF##11553110##17##]. In this study, we identified and evaluated 14 instruments designed to measure OHRQoL in older adults. Of these, only six overcame the minimum score in EMPRO (50.0) for their administration in older patients to be recommended (EORTC QLQ-OH-15, GOHAI, IPQ-RDE, OHIDL, OHIP, QOLIP-10). EORTC QLQ-OH-15 was the instrument that obtained the best evaluation by the experts, followed by OHIP, GOHAI, and OHIDL.</p>", "<p id=\"Par51\">EORTC QLQ-OH-15 is a supplementary module of the EORTC QLQ-C30 for assessing OHRQOL in cancer patients, addressing aspects such as pain, sensitivity to food and drink, saliva, information received, and use of dentures [##UREF##5##18##, ##REF##22572480##19##]. It was developed for the adult and older adult populations, and it has been validated for different populations and languages.</p>", "<p id=\"Par52\">OHIP, GOHAI, and OHIDL are generic instruments for evaluating OHRQoL in patients with oral diseases [##UREF##1##2##, ##REF##11553110##17##]. Applying OHIP may involve a greater respondent burden than GOHAI, so a shorter version of the instrument, such as OHIP-14 or OHIP-EDENT, is a possible option. However, shorter versions of OHIP place more weight on psychological or behavioural aspects, while GOHAI prioritises aspects related to functional limitations and pain [##REF##11553110##17##]. Previous studies have compared the psychometric properties of GOHAI and OHIP-14 for the older adult population. It was found that both instruments are suitable for evaluating the impact of oral pathologies on OHRQoL; however, GOHAI is better than the short forms of OHIP at detecting problems in oral function [##REF##11553110##17##, ##REF##23110518##20##].</p>", "<p id=\"Par53\">El IPQ-RDE, a generic instrument for detecting single and multiple dental conditions in older adults [##REF##30970021##21##]. It measures different aspects from those measured in EORTC QLQ-OH15, OHIDL, GOHAI and OHIP, such as the chronology of the disease, control of the symptoms, treatment burden and prioritisation of the disease. IPQ-RDE is a promising instrument, and it is probable that when new evidence is available, with more studies and improvements in some of its attributes, this instrument will prove to be an excellent option for measuring OHRQoL in older adults.</p>", "<p id=\"Par54\">The majority of the instruments for evaluating OHRQoL in older adults are not suitable for detecting changes in oral health since Responsiveness was measured by five instruments (EORTC QLQ-OH-15, GOHAI, OHIDL, OHIP and OIDP). OHIP showed the best performance for Responsiveness, followed by GOHAI and OHIDL, making them recommended for longitudinal studies and clinical trials. Responsiveness is essential for ensuring that the changes reported are real and not the result of measurement errors. OIDP also obtained a good score for Responsiveness; however, it had poor internal consistency and inadequate coefficients of Reproducibility, which may affect the data in instruments used for longitudinal studies. OIDP is a generic, self-administered instrument translated into five languages other than the original. It evaluates serious oral impacts on daily performance [##UREF##6##22##]. The evaluation of OIDP could only be improved by developing strategies to make score interpretation easier, to describe the burden (respondent and administrative) and to increase internal consistency and reproducibility.</p>", "<p id=\"Par55\">A generic instrument can detect the impact of oral or orofacial diseases, allowing comparisons of diseases and conditions [##REF##11553110##17##]. On the other hand, generic instruments may be less sensitive, specific or useful for evaluating a specific disease [##REF##11553110##17##]. Previous studies have shown that the EMPRO score is higher for generic than for specific instruments [##REF##29569021##23##], very similar to what was found in our study. Evaluation by experts showed that only two (EORTC QLQ-OH-15 and QoLIP-10) of the six specific instruments obtained a score higher than 50.0. The EORTC QLQ-OH-15 showed the highest overall score and good performance in most domains; however, generic instruments such as the GOHAI, OHIDL and OHIP showed better performance in domains such as reliability and validity.</p>", "<p id=\"Par56\">Evaluation by the EMPRO tool is based on the quantity and quality of the evidence published for each instrument. The absence of information for some attributes in EMPRO evaluation penalises the scores since the missing information is given the lowest possible score [##REF##29569021##23##]. One factor which could have affected the performance of these instruments is the fact that only one or two studies per instrument were evaluated, with poor or missing information for some attributes.</p>", "<p id=\"Par57\">The overall score was not calculated for DSQ and OHAI, as information was missing for at least half of the attributes evaluated by EMPRO. In the case of DSQ, not only was there no information for many attributes, but those evaluated obtained very low scores. All aspects of this instrument need to be improved. OHAI obtained a good score for Conceptual and measurement model (score = 63.1) and ease of use (respondent burden: 83.3; administrative burden: 75.0); however, there were insufficient data for evaluation of Reliability, Validity, Interpretability and Responsiveness.</p>", "<p id=\"Par58\">Apart from EORTC QLQ-OH15, IPQ-RDE, OHAI and OHQoL-UK-W, all the instruments were developed for self-administration. The mode of administration may influence the quality of the data, and the way in which older adults answer the instrument. Self-administered instruments may require greater physical and cognitive capabilities in the respondents [##UREF##7##24##]. This reflects the need for the clinician/investigator to consider the patient’s condition before selecting the most appropriate instrument for evaluating OHRQoL in the older adult population.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par59\">The main strength of this study is that we also include instruments not explicitly developed for older adults but are currently used by clinicians and researchers in this population. Not including them would introduce a selection bias excluding valuable information on the validity, reliability and responsiveness of these instruments currently in use in this population.</p>", "<p id=\"Par60\">The use of EMPRO is another strength of our study since it is designed to evaluate the performance of an instrument based on what is reported by all the studies that assessed a specific health problem. EMPRO has been shown to have high internal consistency, inter-rater agreement, and positive associations consistent with a priori hypotheses between EMPRO attribute scores and bibliometric quality indicators. In addition, according to the FDA (US Food and Drug Administration) guideline for patient-reported outcome measures [25], it is essential that the reliability, validity, sensitivity to change and the choice of interpretation method of an instrument be evaluated before use in the measurement of treatment benefit or risk in medical product clinical trials; all these properties are assessed attributes in EMPRO.</p>", "<p id=\"Par61\">Our study presents certain limitations attributable to a variety of reasons. First, it is possible that we did not identify all the instruments of OHRQoL in older adults. To minimise this risk, we used a sensitive search strategy complemented by a manual search of the references and two online databases of PRO, as well as a duplicated review process. In addition, our systematic review has a limitation regarding language restrictions. We attempted to include research in various languages, including English, Spanish, Portuguese, French, German, and Italian. However, it is possible that some studies in other languages were not included in our inclusion criteria, introducing selection bias. Furthermore, the development instruments were included regardless of the age range of the participants in order to identify all the available information. Second, the cut-off point established as the threshold for considering EMPRO scores acceptable is questionable. This threshold was obtained with data from the first two EMPRO studies [##REF##18194398##12##, ##REF##23681849##16##]: the area under the receiver operating characteristic (ROC) curve evaluating the agreement between EMPRO attribute scores and the reviewers’ global recommendations was of 0.87 (data not shown but available upon request) and should be used only as a guideline for identifying gaps in the instruments. Third, the EMPRO evaluations may be biased by the individual experience of the evaluators; however, the evaluations were carried out by researchers with experience in the evaluation of PROMs, and at least one of the two evaluators belonged to the team that manages the EMPRO tool, minimizing this bias. Fourth, it is also important to bear in mind that the EMPRO criteria assess both the methodological quality of the studies and the results of the instrument metric properties, so there could be a risk that studies with adequate methodologies and poor results may obtain EMPRO scores above 50. However, to mitigate this potential risk, there are more EMPRO criteria focused on results than on methodological characteristics: 5 vs 2 in the conceptual and measurement model, 2–3 vs 1 for internal consistency, 2 vs 2 for reproducibility, 2–4 vs 2 for validity, 2 vs 1 for responsiveness, and 2 vs 1 for interpretability. Furthermore, in our EMPRO evaluation, all instruments with scores over 50 also have a good rating in the results criteria. Fifth, EMPRO global score is a summary of the five metric attributes assessed that facilitates a synthesis, but it is recommended to consider scores of each of these five attributes separately according to the purpose for applying the instrument. Sixth, because the EMPRO tool is based on the quantity and quality of the evidence published for each instrument, instruments developed recently, for which little evidence is available, may have been penalised. On the other hand, no overall score was calculated for instruments which did not present information for at least half of the attributes, in order not to penalise them too heavily for lack of information. Finally, we didn’t perform a meta-analysis since EMPRO makes a qualitative evaluation by experts with a consensus process of each OHRQoL instrument considering the variability of the data reported in the different studies to make a judgment and not just the average as would be the case with meta-analysis. In addition, the variability between studies related to the characteristics of the population and methods used to measure the different psychometric properties could generate a significant heterogeneity affecting the certainty estimate obtained with meta-analysis.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par62\">The evidence supports using EORTC QLQ-OH15, as a specific instrument to assess OHRQoL in cancer patients and the OHIP-49, GOHAI, or OHIDL, as generic instruments to assess OHRQoL either for cross-sectional or longitudinal studies in older adults. Future studies of the other instruments should focus on attributes such as Burden, Interpretability and Responsiveness, in order to re-evaluate their usefulness in this population. Our results will facilitate decision-making by clinicians and investigators in choosing the best instrument according to the needs and requirements of older adults.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Older adults present a variety of oral diseases and conditions, in addition to co-morbidities and limited access to dental care, which significantly impact their oral health-related quality of life (OHRQoL). There are many instruments published to measure OHRQoL. However, it is challenging for clinicians and researchers to choose the best instrument for a given purpose.</p>", "<title>Purpose</title>", "<p id=\"Par2\">To identify OHRQoL instruments available for older adults and summarize the evidence on the conceptual and measurement model, psychometric properties, interpretability, and administration issues of OHRQoL instruments available for older adults through a systematic review.</p>", "<title>Methods</title>", "<p id=\"Par3\">A systematic search was conducted in MEDLINE, EMBASE, LILACS, and CENTRAL up to February 2023. Articles reporting information on the concept model measurement, psychometric properties, and administration issues of an instrument measuring OHRQoL in older adults were included. Two researchers independently evaluated each instrument using the Evaluating Measures of Patient-Reported Outcomes (EMPRO) tool. The overall score and seven attribute-specific scores were calculated (range 0–100): Conceptual and measurement model, Reliability, Validity, Responsiveness, Interpretability, Burden, and Alternative forms.</p>", "<title>Results</title>", "<p id=\"Par4\">We identified 14 instruments evaluated in 97 articles. The overall score varied between 73.7 and 8.9, with only six questionnaires over the threshold score 50.0. EORTC QLQ OH-15 (cancer-specific questionnaire) achieved the highest score (73.7), followed by OHIP (generic OHRQoL questionnaire) (66.9), GOHAI (generic OHRQoL questionnaire) (65.5), and OHIDL (generic OHRQoL questionnaire) (65.2). Overall, the Conceptual and measurement model and Validity showed the best performance, while Responsiveness and Interpretability showed the worst. Insufficient information was presented for an overall evaluation of DSQ and OHAI.</p>", "<title>Conclusion</title>", "<p id=\"Par5\">The evidence supports using EORTC QLQ-OH15 as a specific instrument to assess OHRQoL in cancer patients and the OHIP-49, GOHAI, or OHIDL as generic instruments to assess OHRQoL either for cross-sectional or longitudinal studies in older adults.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12955-023-02218-7.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>ANID-Subdirección de Capital Humano/Doctorado Nacional/2021 [FOLIO21210983].</p>", "<title>Authors’ contributions</title>", "<p>Conceptualization: CZ, MC, MF, YP; Methodology: CZ, MC, MF, OG, YP; Formal analysis and investigation: AP, CZ, CAA, GEE, NFD, OG, PMM, YP; Writing - original draft preparation: CZ, MF, NFD; Writing - review and editing: CA, CZ, MF, NFD, OG, YP; Funding acquisition: CZ, NFD; Supervision: CZ, MF, YP.</p>", "<title>Funding</title>", "<p>This work was supported by the Dirección de Investigación, Universidad de La Frontera [grant numbers DI20–0054 and IAF18–0008].</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par63\">This article does not contain any studies with human participants or animals performed by any of the authors.</p>", "<title>Consent to participate</title>", "<p id=\"Par64\">For this type of study, formal consent is not required.</p>", "<title>Competing interests</title>", "<p id=\"Par65\">The authors MF, YP, AP, OG were responsible for the development of the EMPRO instrument and currently participate in the EMPRO platform. Carlos Zaror is an Editorial Board Member of BMC Oral Health. The other authors declare no conflict of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow-chart of the studies and reports included</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Overall EMPRO ranking and attribute-specific scores of instruments designed for the elderly (age &gt; 65 years). The grey line on 50 (half of the theoretical maximum of 100 points) represents the reasonably acceptable cut-off defined for EMPRO scores. EORTC QLQ-OH-15: European organization of Research and Treatment of Cancer, Oral Health Module; GOHAI: Geriatric Oral Health Assessment Index; IPQ-RDE: Illness Perception Questionnaire Revised for Dental Use in Older/Elder Adults; LORQ: Liverpool Oral Rehabilitation Questionnaire; OIDP: Oral Impacts on Daily Performance; OHIDL: Oral Health Impact on Daily Living; OHIP: Oral Health Impact Profile; OHRQL: Oral Health Related of Quality of Life; OHQoL-UK-W: Oral Health Related of Quality of Life – UK; PQL: Prosthetic Quality of Life; QoLDAS-9: Oral Aesthetic-related quality of life; QoLIP-10: The Quality of Life with Implant-Protheses</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Summarized characteristics of instruments designed or validated for old adults, in alphabetical order</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th>Instrument</th><th>Country of development</th><th>Purpose of development<break/>(type of instrument)</th><th>Administration mode</th><th>Dimensions (no. of items)</th><th>Response options</th><th>Score (range)</th><th>Original and adopted languages</th><th>Number of studies evaluated</th></tr></thead><tbody><tr><td>DSQ</td><td>NI</td><td><p>Edentulous patient</p><p>(Specific)</p></td><td>Self-administered</td><td>General satisfaction,  retention, comfort, stability, appearance, ability  to speak, and occlusion (12)</td><td>Likert-scale</td><td>NI</td><td>Maltese</td><td>1</td></tr><tr><td>EORTC QLQ-OH15</td><td>10 countries: France, Germany, Greece, Israel, Italy, Netherlands, Norway, Poland, Sweden, UK</td><td>Oral health in cancer patients (Specific)</td><td>Interview administered</td><td>OH-QoL scale (8), 3 single items (sticky saliva/mouth soreness/ sensitivity to food/drink), 2 two-item contingency scales regarding use (yes/no) and problems with dentures and reception of (yes/no) and satisfaction with information</td><td>4-point Likert scale</td><td>Global score (0–100)</td><td><p>Dutch</p><p>English</p><p>French</p><p>German</p><p>Greek</p><p>Hebrew</p><p>Norwegian</p><p>Polish</p><p>Sinhalese</p><p>Swedish</p></td><td>3</td></tr><tr><td>GOHAI</td><td>United States</td><td><p>Oral Health</p><p>(Generic)</p></td><td>Self-administered</td><td><p>Physical function (4);</p><p>Psychosocial function (5);</p><p>pain or discomfort (3)</p></td><td>5-point Likert scale</td><td><p>Global score</p><p>(12 to 60)</p></td><td><p>English</p><p>Arabic</p><p>Chinese</p><p>Dutch</p><p>German</p><p>Greek</p><p>Hindi</p><p>Japanese</p><p>Lebanese</p><p>Malay</p><p>Maltese</p><p>Mexican</p><p>Mandarin Chinese</p><p>Nepalese</p><p>Persian</p><p>Portuguese</p><p>Serbian</p><p>Swedish</p><p>Turkish</p><p>Urdu</p></td><td>33</td></tr><tr><td>IPQ-RDE</td><td>US</td><td><p>Oral Health</p><p>(Generic)</p></td><td>Interview administered</td><td>Identity (2); Timeline (5); Consequences (6); Control (6); Illness coherence (2); Treatment burden (5), Prioritization (3); Causal relationship (3); Activity restriction (3); Emotional representation (5)</td><td>5-points Likert scale</td><td>NI</td><td>English</td><td>1</td></tr><tr><td>LORQ</td><td>England</td><td><p>Head and neck cancer</p><p>(Specific)</p></td><td>Self-administered</td><td><p>Oral function (12)</p><p>denture satisfaction (13)</p></td><td>4-point Likert-scale</td><td><p>Global score</p><p>(25 to 100)</p></td><td>English</td><td>2</td></tr><tr><td>OIDP</td><td>Thailand</td><td><p>Oral health</p><p>(Generic)</p></td><td>Self-administered</td><td><p>Eating and enjoying food (1)</p><p>Speaking and pronouncing clearly (1);</p><p>Cleaning teeth (1);</p><p>Sleeping and relaxing (1);</p><p>Smiling, laughing and showing teeth without embarrassment (1);</p><p>Maintain usual emotional state without being irritable (1);</p><p>Carrying out major work or social role (1);</p><p>Enjoying contact with people (1)</p></td><td><p>Frequency Score (0–5);</p><p>Severity score (0–5)</p></td><td><p>Global Score</p><p>(0 to 200)</p></td><td><p>Thai</p><p>English</p><p>Greek</p><p>Japanese</p><p>Mangalese</p><p>Portuguese</p></td><td>10</td></tr><tr><td>OHAI</td><td>Sweden</td><td><p>Oral Health</p><p>(Generic)</p></td><td>Interview administered</td><td><p>Background, social context (8) (Part I);</p><p>Dental care and xerostomia (10) (Part I);</p><p>Clinical examination (6) (Part II);</p><p>Observation ADL (8) (Part III)</p></td><td><p>Qualitative evaluation (Parts I and II);</p><p>Observational ADL part (part III) three response alternatives</p></td><td>Global Score Observational ADL part (11 to 33)</td><td>Sweden</td><td>1</td></tr><tr><td>OHIDL</td><td>Hong Kong</td><td><p>Oral health</p><p>(Generic)</p></td><td>Semi-structured interviews administered</td><td><p>Part I: checklist of oral health problems and symptoms;</p><p>Part II: Cleasing (1)</p><p>Eating (6)</p><p>Speaking (1)</p><p>Appearance (2)</p><p>Social (2)</p><p>Psychological (2)</p><p>Health (2)</p><p>Finance (1):</p><p>Part III: five global questions</p></td><td>Part II: 5-point Likert Scale</td><td>NI</td><td>Chinese</td><td>3</td></tr><tr><td>OHIP</td><td>United States</td><td><p>Oral health</p><p>(Generic)</p></td><td>Self-administered</td><td><p>Functional limitation (9),</p><p>Physical pain/discomfort (9),</p><p>Psychological discomfort (5);</p><p>Physical disability (9);</p><p>Psychological disability (6);</p><p>Social disability (5),</p><p>Handicap (6)</p></td><td>5-point Likert scale</td><td><p>Global score</p><p>(0 to 245)</p></td><td><p>English</p><p>Albanian</p><p>Arabic</p><p>Australian</p><p>Chinese</p><p>Croatian</p><p>Czech</p><p>German</p><p>Greek</p><p>Hungarian</p><p>Italian</p><p>Japanese</p><p>Korean</p><p>Lebanese</p><p>Maltese</p><p>Mexican</p><p>Nepalese</p><p>Persian</p><p>Polish</p><p>Portuguese</p><p>Romanian</p><p>Serbian</p><p>Sinhalese</p><p>Spanish</p><p>Swedish</p></td><td>44</td></tr><tr><td>OHQoL-UK-W</td><td>United Kingdon</td><td><p>Oral health</p><p>(Generic)</p></td><td>Interview administered</td><td><p>Physical aspects (6)</p><p>Social aspects (5)</p><p>Psychological aspects (5)</p></td><td>Scale from 1 to 9</td><td><p>Global score</p><p>(16 to 144)</p></td><td>English</td><td>1</td></tr><tr><td>OHRQL</td><td>United States</td><td><p>Oral health</p><p>(Generic)</p></td><td>Self-administered</td><td><p>Symptom status: Pain (6);</p><p>Dry mouth symptom (3).</p><p>Function status: Eating/Chewing Function (3);</p><p>Speech function (3);</p><p>Social function (4);</p><p>Psychological function (5).</p><p>Health perceptions: Oral health perception (2)</p></td><td>5-point Likert-scale</td><td>NI</td><td>English</td><td>1</td></tr><tr><td>PQL</td><td>Spain</td><td><p>Total or partial removable prostheses</p><p>(Specific)</p></td><td>Self-administered</td><td><p>Prosthetic fit (1),</p><p>Chewing (1),</p><p>Foreign body (1),</p><p>Aesthetics (1),</p><p>Communication (1),</p><p>Realism of prosthesis (1),</p><p>Unnoticeability (1),</p><p>Hygiene (1),</p><p>Food impaction (1),</p><p>Functional comfort (1),</p><p>Self-confidence (1)</p></td><td>5-point Likert-scale</td><td><p>Global score</p><p>(11 to 55)</p></td><td>Spanish</td><td>1</td></tr><tr><td>QoLDAS-9</td><td>Spain</td><td><p>Dental aesthetics - prosthetically restored patients</p><p>(Specific)</p></td><td>Self-administered</td><td><p>Psychofacial aesthetic (3)</p><p>Interactive aesthetic (3)</p><p>Socio-dental aesthetic (3)</p></td><td>Likert scale: −2 to + 2</td><td><p>- Global score</p><p>(−18 to + 18)</p></td><td>Spanish</td><td>1</td></tr><tr><td>QoLIP-10</td><td>Spain</td><td><p>Patients wearing implant overdentures and hybrid prostheses</p><p>(Specific)</p></td><td>Self-administered</td><td><p>Biopsychosocial dimension (5)</p><p>Dental–facial aesthetics dimension (3)</p><p>Performance dimension (2)</p></td><td>Likert scale: −2 to + 2</td><td><p>Global score</p><p>(− 20 to + 20)</p></td><td>Spanish</td><td>2</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Rating of each EMPRO items and attribute for OHRQoL in Elderly</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>ATTRIBUTES</th><th>DSQ</th><th>EORTC QLQ-OH15</th><th>GOHAI</th><th>IPQ-RDE</th><th>LORQ</th><th>OIDP</th><th>OHAI</th><th>OHIDL</th><th>OHIP</th><th>OHQoL-UK-W</th><th>ORHQL</th><th>PQL</th><th>QoLDAS-9</th><th>QoLIP-10</th></tr></thead><tbody><tr><td/><td><bold>CONCEPT AND MEASUREMENT MODE</bold>L</td><td>NI</td><td>97.6</td><td>92.9</td><td>85.7</td><td>17.9</td><td>69.0</td><td>63.1</td><td>86.9</td><td>85.7</td><td><bold>52.4</bold></td><td><bold>47.6</bold></td><td><bold>66.7</bold></td><td><bold>90.5</bold></td><td><bold>85.7</bold></td></tr><tr><td>1</td><td>concept of measurement stated</td><td>+</td><td>++++</td><td>++++</td><td>++++</td><td>++</td><td>++++</td><td>++++</td><td>++++</td><td>++++</td><td>+++</td><td>++++</td><td>++++</td><td>++++</td><td>++++</td></tr><tr><td>2</td><td>obtaining and combining items described</td><td>–</td><td>++++</td><td>++++</td><td>++++</td><td>+</td><td>++++</td><td>++++</td><td>++++</td><td>+++</td><td>+++</td><td>+++</td><td>++++</td><td>++++</td><td>++++</td></tr><tr><td>3</td><td>rationality for dimensionality and scales</td><td>–</td><td>++++</td><td>+++</td><td>++++</td><td>+</td><td>++</td><td>++++</td><td>++++</td><td>++</td><td>++</td><td>+++</td><td>+++</td><td>++++</td><td>+++</td></tr><tr><td>4</td><td>involvement of target population</td><td>–</td><td>++++</td><td>+++</td><td>+++</td><td>+</td><td>++++</td><td>+++</td><td>+++</td><td>+++</td><td>++++</td><td>+++</td><td>++++</td><td>++++</td><td>+++</td></tr><tr><td>5</td><td>scale variability described and adequate</td><td>+</td><td>++++</td><td>+++</td><td>++</td><td>++</td><td>+</td><td>–</td><td>+++</td><td>++++</td><td>++</td><td>–</td><td>+</td><td>++</td><td>+++</td></tr><tr><td>6</td><td>level of measurement described</td><td>+</td><td>++++</td><td>++++</td><td>+++</td><td>++</td><td>++</td><td>++</td><td>+++</td><td>++++</td><td>++</td><td>+</td><td>–</td><td>++++</td><td>++++</td></tr><tr><td>7</td><td>procedures for deriving scores</td><td>–</td><td>+++</td><td>++++</td><td>++++</td><td>–</td><td>++++</td><td>–</td><td>++++</td><td>++++</td><td>++</td><td>–</td><td>+++</td><td>++++</td><td>+++</td></tr><tr><td/><td><bold>RELIABILITY - total score</bold></td><td><bold>–</bold></td><td><bold>62.5</bold></td><td><bold>79.2</bold></td><td><bold>87.5</bold></td><td><bold>12.5</bold></td><td><bold>41.7</bold></td><td><bold>–</bold></td><td><bold>55.6</bold></td><td><bold>62.5</bold></td><td><bold>47.2</bold></td><td><bold>29.2</bold></td><td><bold>22.2</bold></td><td><bold>44.4</bold></td><td><bold>38.9</bold></td></tr><tr><td/><td><italic>Reliability: internal consistency</italic></td><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td>8</td><td>data collection methods described</td><td>+</td><td>++++</td><td>++++</td><td>++++</td><td>+</td><td>++</td><td>–</td><td>++++</td><td>++++</td><td>++</td><td>++</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>9</td><td>Cronbach’s alpha adequate</td><td>+</td><td>+++</td><td>+++</td><td>+++</td><td>+</td><td>++</td><td>–</td><td>+++</td><td>+++</td><td>++++</td><td>+++</td><td>++</td><td>+++</td><td>++</td></tr><tr><td>10</td><td>IRT estimates provided</td><td>–</td><td>–</td><td>+++</td><td>+++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>11</td><td>testing in different populations</td><td>n.a.</td><td>–</td><td>++++</td><td>++++</td><td>+</td><td>n.a.</td><td>–</td><td>n.a.</td><td>+++</td><td>n.a.</td><td>–</td><td>n.a.</td><td>n.a.</td><td>n.a.</td></tr><tr><td/><td><italic>Reliability: reproducibility</italic></td><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td>–</td><td/><td/><td/></tr><tr><td>12</td><td>data collection methods described</td><td>+</td><td>+++</td><td>+++</td><td>–</td><td>+</td><td>++</td><td>–</td><td>–</td><td>+++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>13</td><td>test-retest and time interval adequate</td><td>+</td><td>++++</td><td>++++</td><td>–</td><td>+</td><td>+++</td><td>–</td><td>–</td><td>+++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>14</td><td>reproducibility coefficients adequate</td><td>+</td><td>+++</td><td>+++</td><td>–</td><td>+</td><td>++</td><td>–</td><td>–</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>15</td><td>IRT estimates provided</td><td>+</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td/><td><bold>VALIDITY</bold></td><td><bold>–</bold></td><td><bold>80.6</bold></td><td><bold>88.9</bold></td><td><bold>75.0</bold></td><td><bold>13.9</bold></td><td><bold>63.9</bold></td><td><bold>–</bold></td><td><bold>83.3</bold></td><td><bold>86.2</bold></td><td><bold>40.3</bold></td><td><bold>46.7</bold></td><td><bold>52.8</bold></td><td><bold>86.7</bold></td><td><bold>94.4</bold></td></tr><tr><td>16</td><td>content validity adequate</td><td>–</td><td>++++</td><td>++++</td><td>+++</td><td>–</td><td>+++</td><td>++++</td><td>+++</td><td>+++</td><td>++</td><td>++</td><td>++++</td><td>++++</td><td>++++</td></tr><tr><td>17</td><td>construct/criterion validity adequate</td><td>–</td><td>+++</td><td>+++</td><td>++++</td><td>++</td><td>++++</td><td>–</td><td>++++</td><td>+++</td><td>+++</td><td>++</td><td>++</td><td>+++</td><td>+++</td></tr><tr><td>18</td><td>sample composition described</td><td>–</td><td>++++</td><td>++++</td><td>+++</td><td>+</td><td>–</td><td>–</td><td>++++</td><td>++++</td><td>+++</td><td>+++</td><td>++++</td><td>++++</td><td>++++</td></tr><tr><td>19</td><td>prior hypothesis stated</td><td>–</td><td>+++</td><td>++++</td><td>+++</td><td>+</td><td>+++</td><td>–</td><td>++</td><td>+++</td><td>+++</td><td>+</td><td>++</td><td>+++</td><td>++++</td></tr><tr><td>20</td><td>rational for criterion validity</td><td>n.a.</td><td>++</td><td>+++</td><td>–</td><td>+</td><td>++++</td><td>–</td><td>n.a.</td><td>++++</td><td>–</td><td>n.a.</td><td>++</td><td>++++</td><td>++++</td></tr><tr><td>21</td><td>tested in different populations</td><td>–</td><td>++++</td><td>++++</td><td>++++</td><td>++</td><td>++</td><td>n.a.</td><td>n.a.</td><td>++++</td><td>–</td><td>+++</td><td>+</td><td>n.a.</td><td>++++</td></tr><tr><td/><td><bold>RESPONSIVENESS</bold></td><td><bold>–</bold></td><td><bold>50.0</bold></td><td><bold>66.7</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>61.2</bold></td><td><bold>–</bold></td><td><bold>66.7</bold></td><td><bold>100</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td></tr><tr><td>22</td><td>adequacy of methods</td><td>–</td><td>+++</td><td>+++</td><td>–</td><td>–</td><td>+</td><td>–</td><td>++++</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>23</td><td>description of estimated magnitude of change</td><td>–</td><td>+++</td><td>+++</td><td>–</td><td>–</td><td>+++</td><td>–</td><td>++++</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>24</td><td>comparison of stable and unstable groups</td><td>–</td><td>+</td><td>+++</td><td>–</td><td>–</td><td>++++</td><td>–</td><td>–</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td/><td><bold>INTERPRETABILITY</bold></td><td><bold>–</bold></td><td><bold>77.8</bold></td><td><bold>–</bold></td><td><bold>38.9</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>33.3</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>–</bold></td><td><bold>33.3</bold></td></tr><tr><td>25</td><td>rational of external criteria</td><td>–</td><td>++++</td><td>–</td><td>+++</td><td>–</td><td>–</td><td>–</td><td>+++</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>26</td><td>description of interpretation strategies</td><td>–</td><td>++</td><td>–</td><td>++</td><td>–</td><td>–</td><td>–</td><td>++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>++</td></tr><tr><td>27</td><td>how data should be reported stated</td><td>–</td><td>++++</td><td>–</td><td>+</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>+++</td></tr><tr><td/><td><bold>OVERALL SCORE</bold></td><td><bold>–</bold></td><td><bold>73.7</bold></td><td><bold>65.5</bold></td><td><bold>57.4</bold></td><td><bold>8.9</bold></td><td><bold>47.1</bold></td><td><bold>–</bold></td><td><bold>65.2</bold></td><td><bold>66.9</bold></td><td><bold>28.0</bold></td><td><bold>24.7</bold></td><td><bold>28.3</bold></td><td><bold>44.3</bold></td><td><bold>50.5</bold></td></tr><tr><td/><td><bold>BURDEN</bold></td><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/><td/></tr><tr><td/><td><bold><italic>Burden: respondent</italic></bold></td><td><bold>–</bold></td><td><bold>72.2</bold></td><td><bold>83.3</bold></td><td><bold>11.1</bold></td><td><bold>16.7</bold></td><td><bold>–</bold></td><td><bold>83.3</bold></td><td><bold>–</bold></td><td><bold>33.3</bold></td><td><bold>22.2</bold></td><td><bold>11.1</bold></td><td><bold>–</bold></td><td><bold>88.9</bold></td><td><bold>33.3</bold></td></tr><tr><td>28</td><td>skills and time needed</td><td>–</td><td>+++</td><td>+++</td><td>++</td><td>+</td><td>–</td><td>++++</td><td>++</td><td>+++</td><td>+++</td><td>–</td><td>–</td><td>+++</td><td>++</td></tr><tr><td>29</td><td>impact on respondents</td><td>+++</td><td>+++</td><td>+++</td><td>+</td><td>+</td><td>+</td><td>+++</td><td>–</td><td>++++</td><td>+</td><td>++</td><td>+</td><td>++++</td><td>++++</td></tr><tr><td>30</td><td>not suitable circumstances</td><td>++</td><td>+++</td><td>++++</td><td>+</td><td>+</td><td>–</td><td>+++</td><td>–</td><td>–</td><td>+</td><td>+</td><td>–</td><td>++++</td><td>–</td></tr><tr><td/><td><bold><italic>Burden: administrative</italic></bold></td><td><bold>–</bold></td><td><bold>75.0</bold></td><td><bold>75.0</bold></td><td><bold>20.8</bold></td><td><bold>33.3</bold></td><td><bold>–</bold></td><td><bold>75.0</bold></td><td><bold>50.0</bold></td><td><bold>100.0</bold></td><td><bold>18.7</bold></td><td><bold>–</bold></td><td><bold>83.3</bold></td><td><bold>100.0</bold></td><td><bold>66.7</bold></td></tr><tr><td>31</td><td>resources required</td><td>–</td><td>+++</td><td>++++</td><td>+</td><td>+++</td><td>–</td><td>++++</td><td>++++</td><td>++++</td><td>+</td><td>–</td><td>+++</td><td>++++</td><td>++++</td></tr><tr><td>32</td><td>time required</td><td>n.a.</td><td>++++</td><td>++</td><td>+++</td><td>n.a.</td><td>–</td><td>++++</td><td>–</td><td>n.a.</td><td>+</td><td>n.a.</td><td>n.a.</td><td>n.a.</td><td>+++</td></tr><tr><td>33</td><td>training and expertise needed</td><td>n.a.</td><td>++</td><td>+++</td><td>+</td><td>n.a.</td><td>–</td><td>++</td><td>–</td><td>n.a.</td><td>++</td><td>n.a.</td><td>n.a.</td><td>n.a.</td><td>–</td></tr><tr><td>34</td><td>burden of score calculation</td><td>–</td><td>+++</td><td>++++</td><td>+</td><td>–</td><td>++</td><td>+++</td><td>++++</td><td>++++</td><td>++</td><td>–</td><td>++++</td><td>++++</td><td>++++</td></tr><tr><td/><td><bold>ALTERNATIVE MODES OF ADMINISTRATION</bold></td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td><bold>100.00</bold></td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>35</td><td>metric characteristics</td><td>–</td><td/><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>36</td><td>comparability</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td><td>++++</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>ADL</italic> Activities of daily living, <italic>NI </italic>No information, <italic>DSQ </italic>Denture Satisfaction Questionnaire, <italic>EORTC QLQ OH-15 </italic>European organization of Research and Treatment of Cancer, Oral Health Module, <italic>GOHAI</italic> Geriatric Oral Health Assessment Index, <italic>IPQ-RDE </italic>Illness Perception Questionnaire Revised for Dental Use in Older/Elder Adults, <italic>LORQ </italic>Liverpool Oral Rehabilitation Questionnaire, <italic>OIDP </italic>Oral Impacts on Daily Performance, <italic>OHAI </italic>The Oral Hygiene Assessment Instrument, <italic>OHIDL </italic>Oral Health Impact on Daily Living, <italic>OHIP </italic>Oral Health Impact Profile, <italic>OHRQL </italic>Oral Health Related of Quality of Life, <italic>OHQoL-UK-W </italic>Oral Health Related of Quality of Life - UK, <italic>PQL </italic>Prosthetic Quality of Life, <italic>QoLDAS-9</italic> Oral Aesthetic-related quality of life, <italic>QoLIP-10</italic> The Quality of Life with Implant-Protheses</p></table-wrap-foot>", "<table-wrap-foot><p>Explanation: ++++ 4 (strongly agree); +++ 3; ++ 2; + 1 (strongly disagree); − no information; n.a. not applicable. The higher the agreement the better the rating. Rows in white show EMPRO criteria assessing the results of the corresponding metric property, while rows in grey show EMPRO criteria assessing the methods applied to evaluate the corresponding metric property</p><p><italic>DSQ</italic> Denture Satisfaction Questionnaire, <italic>EORTC QLQ OH-15 </italic>European organization for Research and Treatment of Cancer, Oral Health Module, <italic>GOHAI </italic>Geriatric Oral Health Assessment Index, <italic>IPQ-RDE </italic>Illness Perception Questionnaire Revised for Dental Use in Older/Elder Adults, <italic>LORQ </italic>Liverpool Oral Rehabilitation Questionnaire, <italic>OIDP </italic>Oral Impacts on Daily Performance, <italic>OHAI </italic>The Oral Hygiene Assessment Instrument, <italic>OHIDL </italic>Oral Health Impact on Daily Living, <italic>OHIP </italic>Oral Health Impact Profile, <italic>ORHQL </italic>Oral Health Related of Quality of Life, <italic>OHQoL-UK-W </italic>Oral Health Related of Quality of Life - UK, <italic>PQL </italic>Prosthetic Quality of Life, <italic>QoLDAS-9 </italic>Oral Aesthetic-related quality of life, <italic>QoLIP-10</italic> The Quality of Life with Implant-Protheses</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12955_2023_2218_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12955_2023_2218_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"12955_2023_2218_MOESM1_ESM.pdf\"><caption><p><bold>Additional file 1.</bold>\n</p></caption></media>", "<media xlink:href=\"12955_2023_2218_MOESM2_ESM.docx\"><caption><p><bold>Additional file 2.</bold>\n</p></caption></media>", "<media xlink:href=\"12955_2023_2218_MOESM3_ESM.xlsx\"><caption><p><bold>Additional file 3.</bold>\n</p></caption></media>" ]
[{"label": ["1."], "mixed-citation": ["World Health Organization (WHO). Ageing and health. 2022. "], "ext-link": ["https://www.who.int/news-room/fact-sheets/detail/ageing-and-health"]}, {"label": ["2."], "surname": ["Hebling", "Pereira"], "given-names": ["E", "AC"], "article-title": ["Oral health-related quality of life: a critical appraisalof assessment tools used in elderly people"], "source": ["Gerodontol."], "year": ["2007"], "volume": ["24"], "issue": ["3"], "fpage": ["151"], "lpage": ["161"], "pub-id": ["10.1111/j.1741-2358.2007.00178.x"]}, {"label": ["5."], "mixed-citation": ["BaHammam FA, Akhil J, Stewart M, Abdulmohsen B, Durham J, McCracken GI, et al. Establishing an empirical conceptual model of oral health in dependent adults: systematic review. Spec Care Dentist. 2023; 10.1111/scd.12842."]}, {"label": ["8."], "mixed-citation": ["Cooray U, Tsakos G, Heilmann A, Watt R, Takeuchi K, Kondo K, et al. Impact of teeth on social participation: modified treatment policy approach. J Dent Res. 2023;00220345231164106"]}, {"label": ["14."], "surname": ["Higgins", "Thomas", "Chandler"], "given-names": ["JP", "J", "J"], "source": ["Cochrane handbook for systematic reviews of interventions"], "year": ["2019"], "publisher-name": ["John Wiley & Sons"]}, {"label": ["18."], "surname": ["Hjermstad", "Bergenmar", "Bjordal", "Fisher", "Hofmeister", "Montel"], "given-names": ["MJ", "M", "K", "SE", "D", "S"], "article-title": ["International field testing of the psychometric properties of an EORTC quality of life module for oral health: the EORTC QLQ-OH15"], "source": ["Supp Care Cancer."], "year": ["2016"], "volume": ["24"], "issue": ["9"], "fpage": ["3915"], "lpage": ["3924"], "pub-id": ["10.1007/s00520-016-3216-0"]}, {"label": ["22."], "mixed-citation": ["Adulyanon S, Sheiham A. Oral impacts on daily performances. In: Slade GD, editor. Measuring oral health and quality of life. North Carolina. 1996. p. 151\u2013160."]}, {"label": ["24."], "surname": ["Halvorsrud", "Kalfoss"], "given-names": ["L", "M"], "article-title": ["Quality of life data in older adults: self-assessment vs interview"], "source": ["Brit J Nur."], "year": ["2014"], "volume": ["23"], "issue": ["13"], "fpage": ["712"], "lpage": ["721"], "pub-id": ["10.12968/bjon.2014.23.13.712"]}]
{ "acronym": [ "OHRQoL", "OHRQL", "EMPRO", "EORTC QLQ OH-15", "OHIP", "GOHAI", "OHIDL", "DSQ", "OHAI", "OIDP", "LORQ", "QoLDAS-9", "PQL", "PRISMA", "PRO", "PROQOLID", "IPQ-RDE" ], "definition": [ "oral health-related quality of life", "Oral Health-Related Quality of Life", "Evaluating Measures of Patient-Reported Outcomes", "European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Oral Health Module", "Oral Health Impact Profile", "Geriatric Oral Health Assessment Index", "Oral Health Impact on Daily Living", "Dental Satisfaction Questionnaire", "Oral Hygiene Assessment Instrument", "Oral Impacts on Daily Performance", "Liverpool Oral Rehabilitation Questionnaire", "Oral Aesthetic-related quality of life", "Prosthetic Quality of Life", "Preferred Reporting Items for Systematic Reviews and Meta-analysis", "patient-reported outcomes", "Patient-Reported Outcome and Quality of Life Instruments Database", "Illness Perception Questionnaire Revised for Dental Use in Older/Elder Adults" ] }
24
CC BY
no
2024-01-14 23:43:46
Health Qual Life Outcomes. 2024 Jan 13; 22:5
oa_package/c6/13/PMC10787424.tar.gz
PMC10787425
38217049
[ "<title>Introduction</title>", "<p id=\"Par27\">Hepatocellular carcinoma (HCC) is the most common primary liver cancer and usually develops in patients with liver cirrhosis or an underlying chronic liver disease [##REF##33538338##1##–##REF##29628281##3##]. Macrovascular tumour invasion into portal or hepatic veins is a common complication of advanced or progressing HCC and associated with a poor prognosis [##REF##9862851##4##–##REF##33755196##6##]. Given the critical implications for management, portal vein tumour thrombosis needs to be distinguished from non-tumorous portal vein thrombosis – a well-known complication in patients with liver cirrhosis [##REF##33930474##7##]. This can be done by contrast-enhanced imaging with relatively high accuracy [##REF##20440775##8##, ##REF##20032150##9##]. Patients with HCC who developed macrovascular tumour invasion become candidates for systemic therapy. While immune checkpoint inhibitor (ICI)-based combination therapies have replaced tyrosine kinase inhibitors (TKIs) as preferred standard of care in systemic front-line, TKIs are frequently used in the second-line setting [##REF##34801630##10##].</p>", "<p id=\"Par28\">Macrovascular tumour invasion, particularly in case of main portal vein involvement, is one of the most important negative prognostic factors [##REF##30972935##11##] and may complicate the course of the disease by aggravating portal hypertension and its complications [##REF##36631021##12##]. Indeed, portal vein tumour thrombosis is associated with an increased risk of high-risk varices and variceal bleeding in patients with HCC [##REF##33402105##13##]. Moreover, invasion of hepatic veins or the vena cava may increase the risk for venous thromboembolism [##REF##36444235##14##, ##REF##35944830##15##].</p>", "<p id=\"Par29\">Current recommendations on the prevention of variceal bleeding in individuals with liver cirrhosis also apply to patients with cirrhosis and HCC [##REF##36631021##12##, ##REF##35120736##16##, ##REF##35526788##17##]. However, the value of adequate bleeding prophylaxis, particularly that of non-selective beta blockers (NSBB), in patients with clinically significant portal hypertension secondary to portal vein tumour thrombosis is unclear [##REF##36631021##12##].</p>", "<p id=\"Par30\">Moreover, data on anticoagulation to prevent or treat non-malignant thrombus apposition in HCC patients with macrovascular tumour invasion are lacking. While therapeutic anticoagulation is recommended in selected patients with liver cirrhosis and non-tumorous portal vein thrombosis [##REF##33930474##7##, ##REF##33219529##18##], no recommendations exist for HCC patients with portal vein tumour thrombosis.</p>", "<p id=\"Par31\">To address some of these knowledge gaps, we conducted a retrospective study in patients with advanced HCC and well-preserved liver function who were diagnosed with macrovascular tumour invasion. We investigated the impact of anticoagulation on thrombosis progression, bleeding events, and all-cause mortality, and assessed the efficacy of adequate management of varices as recommended for patients with cirrhosis.</p>" ]
[ "<title>Methods</title>", "<title>Study design and patients</title>", "<p id=\"Par32\">Patients with histologically or radiologically diagnosed HCC and suspected macrovascular tumour invasion were considered for this retrospective study. Since patients with decompensated liver disease should receive best supportive care [##REF##29628281##3##], we only included patients with Child-Turcotte-Pugh (CTP) score A or B7. Individuals with Barcelona-Clinic Liver Cancer (BCLC) stage D or unconfirmed macrovascular tumour invasion (i.e., only non-tumorous thrombosis), as well as patients treated with surgery or locoregional therapies (i.e., transarterial chemoembolization [TACE], selective internal radiation therapy [SIRT], or ablation, as these therapies are not recommended for HCC with macrovascular tumour invasion [##REF##29628281##3##]) were excluded. Furthermore, we excluded individuals who were lost to follow-up within 30 days. Only patients with available images of the scans (i.e., computed tomography [CT] or magnetic resonance imaging [MRI]) at diagnosis of macrovascular tumour invasion were eligible. Patients were included between Q4/2002 and Q2/2022 at the Medical University of Vienna/General Hospital Vienna. Data including patient history and laboratory results were collected retrospectively. The date of diagnosis of macrovascular tumour invasion was defined as the baseline of this study. The retrospective analysis was approved by the Ethics Committee of the Medical University of Vienna.</p>", "<title>Radiological assessments</title>", "<p id=\"Par33\">Contrast-enhanced CT and/or MRI scans were performed at baseline and approximately every 3 months thereafter. Images were read in consensus by two radiologists (A.M., and D.T.) who were blinded regarding medical treatment. The following characteristics of the tumour thrombus were described at baseline: location and extension of macrovascular tumour invasion, grade of occlusion of affected vessel (total/partial), type of thrombus (tumour thrombus or non-tumorous thrombus apposition), and presence of venous congestion.</p>", "<p id=\"Par34\">Differentiation between tumour and non-tumorous thrombus was performed according to the following criteria: According to the current Liver Imaging and Data System (LI-RADS), the presence of unequivocal enhancing soft tissue in a vein, regardless of visualisation of parenchymal mass was considered a feature diagnostic of tumorous thrombus. Further features indicating tumorous thrombus were occluded vein with restricted diffusion, occluded or obscured vein in contiguity with malignant parenchymal mass and heterogeneous vein appearance not attributable to an artifact, leading to further assessment whether an enhancing component in the thrombus was to be observed [##REF##30251931##19##].</p>", "<p id=\"Par35\">In patients with available follow-up imaging, changes in thrombus size or degree of occlusion were assessed by direct comparison with the last imaging performed immediately before, and evaluated according to Baveno VII recommendations [##REF##35120736##16##]: i) regression – thrombus decreased in size or degree of occlusion; ii) stabilization – no appreciable change in size or occlusion; iii) progression – thrombus increased in size or degree of occlusion. Best radiological response of the thrombus was evaluated at 3–6 months, as recommended in patients with liver cirrhosis and portal vein thrombosis undergoing anticoagulation [##REF##33930474##7##].</p>", "<title>Management of macrovascular tumour invasion and varices</title>", "<p id=\"Par36\">Patient data was obtained from medical records. Start and stop date of anticoagulation and systemic anti-tumour therapy was recorded for time-dependent analyses. The following therapies were regarded as ‘effective systemic therapies’, as these are recommended in advanced HCC with macrovascular tumour invasion [##REF##34256065##20##, ##REF##33197225##21##]: immune checkpoint inhibitor (ICI)-based therapies, sorafenib, lenvatinib, regorafenib, cabozantinib, and ramucirumab. Non-effective treatment included any other systemic therapy (i.e., experimental or with unproven efficacy in HCC, including octreotide, sirolimus, crizotinib, thalidomide, nintedanib, tivantinib, imatinib), or no specific anti-tumour therapy.</p>", "<p id=\"Par37\">The decision on whether to initiate anticoagulation as well as the type of anticoagulation were solely at the discretion of the treating physician, as international or local guidelines on anticoagulation in patients with HCC and macrovascular tumour invasion are lacking. For main analyses, anticoagulation was considered adequate if therapeutic doses were used, and only these were included in the ‘therapeutic anticoagulation’ group, whereas patients receiving reduced/prophylactic doses were excluded. However, for sensitivity analysis, we also calculated Cox regression models including patients who received any dose of anticoagulation.</p>", "<p id=\"Par38\">Management of varices was evaluated in patients with known variceal status. Accordingly, the following clinical scenarios were considered as adequate management of varices [##REF##35120736##16##, ##REF##26047908##22##]: i) low-risk varices – no endoscopic treatment, NSBB optionally, ii) high-risk varices – either NSBB or endoscopic treatment (or both), and iii) history of variceal bleeding – NSBB plus endoscopic treatment.</p>", "<p id=\"Par39\">Portal hypertension-related complications (i.e., variceal bleeding, ascites, hepatorenal syndrome-type acute kidney injury, spontaneous bacterial peritonitis, overt hepatic encephalopathy) during follow-up were obtained from medical records.</p>", "<title>Statistical analysis</title>", "<p id=\"Par40\">Statistical analyses were performed using IBM SPSS Statistics version 27 (SPSS Inc., Chicago, IL), R 4.1.2 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria) and GraphPad Prism 8 (GraphPad Software, Inc., San Diego, CA). As this is a retrospective study, no formal sample size calculation was performed, instead, all available patients fulfilling inclusion but not exclusion criteria were considered for this study. Data on baseline patient and tumour characteristics as well as radiographic features were summarised using descriptive statistics. Categorical variables were reported as absolute (n) and relative frequencies (%), whereas continuous variables as mean ± standard deviation (SD) or median (interquartile range [IQR]), as appropriate. Student’s t-test was used for group comparisons of normally distributed variables and Mann-Whitney-U-test for non-normally distributed variables. Group comparisons of categorical variables were performed using either Chi-squared or Fisher’s exact test, as appropriate. Logistic regression analyses were calculated with variceal bleeding as outcome of interest using backward elimination for variable selection in patients with known endoscopy status at study inclusion.</p>", "<p id=\"Par41\">Overall survival was defined as the time from radiological diagnosis of macrovascular tumour invasion until death, and patients who were still alive were censored at the date of last contact. Variceal bleeding-free survival was defined as time from radiological diagnosis of macrovascular tumour invasion until variceal bleeding or death from any cause, whatever came first; patients who were still alive without variceal bleeding were censored at the date of last contact. Time on treatment (e.g., systemic anti-tumour therapy, anticoagulation, NSBB) was defined as the time from treatment start until end of treatment (e.g., including time on 1st and further lines of systemic anti-tumour therapy); patients who were alive or lost to follow-up with ongoing treatment were censored at the date of last contact. Median overall survival was calculated by the Kaplan-Meier method. Median estimated follow-up was calculated using the reverse Kaplan-Meier method [##REF##8889347##23##].</p>", "<p id=\"Par42\">Univariable and multivariable analyses were conducted using Cox regression analyses, and included time-dependent variables (i.e., anticoagulation, effective systemic therapy, NSBB; <ext-link ext-link-type=\"uri\" xlink:href=\"https://cran.r-project.org/web/packages/survival/vignettes/timedep.pdf\">https://cran.r-project.org/web/packages/survival/vignettes/timedep.pdf</ext-link>). Data was put into long-format using the tmerge package (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.rdocumentation.org/packages/survival/versions/2.43-3/topics/tmerge\">https://www.rdocumentation.org/packages/survival/versions/2.43-3/topics/tmerge</ext-link>). Variable selection was based on backward elimination, eliminating variables with <italic>p</italic>-values &gt; 0.157 [##REF##27896874##24##]. For graphical depiction, a Simon-Makuch plot was created [##REF##12459796##25##, ##REF##6729287##26##]. The Sankey plot was created using SankeyMATIC (<ext-link ext-link-type=\"uri\" xlink:href=\"https://sankeymatic.com\">https://sankeymatic.com</ext-link>). The level of significance was set at a 2-sided <italic>p</italic>-value &lt; 0.05.</p>" ]
[ "<title>Results</title>", "<title>Study population and patient characteristics</title>", "<p id=\"Par43\">Overall, 508 consecutive patients with HCC and suspected macrovascular tumour invasion were screened for study inclusion from Q4/2002 until Q2/2022 at the study centre (Supplementary Figure ##SUPPL##0##1##). After applying in- and exclusion criteria, 124 patients were finally included in this study (Fig. ##FIG##0##1##A).</p>", "<p id=\"Par44\">Mean age was 65 ± 10 years and most patients were male (<italic>n</italic> = 110, 89%). The main aetiologies of liver disease were alcohol-related liver disease (<italic>n</italic> = 51, 41%) and viral hepatitis (<italic>n</italic> = 46, 37%), and most patients had liver cirrhosis (<italic>n</italic> = 110, 89%). Of 80 patients (65%) with known variceal status, 50 patients (63%) had gastroesophageal varices (low-risk <italic>n</italic> = 18, 36%; high-risk <italic>n</italic> = 32, 64%). According to the study inclusion criteria, all patients had preserved liver function (CTP class A-B7), with a mean Albumin-to-Bilirubin score (ALBI) of − 2.5 ± 0.4 (stage 1: <italic>n</italic> = 48, 39%; stage 2: <italic>n</italic> = 76, 61%). Overall, 21 patients (17%) had prior surgery/local therapies, 36 individuals had extrahepatic metastases (29%), and more than half of patients had an Eastern Cooperative Oncology Group Performance Status (ECOG-PS) of 0 (<italic>n</italic> = 72, 58%). Baseline radiological assessment was performed in 96 patients (77%) by a CT and in 28 (23%) by an MRI scan. Detailed patient characteristics are displayed in Table ##TAB##0##1##.\n</p>", "<title>Localization of macrovascular tumour thrombosis at diagnosis</title>", "<p id=\"Par45\">The main portal vein was involved in 47 patients (38%). Invasion of the left and/or right portal branch alone was diagnosed in 53 patients (43%), and 17 individuals (14%) had additional involvement of other splanchnic veins (i.e., hepatic veins, splenic vein, vena cava inferior, superior mesenteric vein). Selective invasion of splanchnic veins without invasion of the main portal vein or its right and left branches was seen in 7 patients (6%) (Table ##TAB##1##2## and Fig. ##FIG##0##1##B). Forty-nine subjects (40%) had non-tumorous thrombus apposition. The number of patients with main portal vein involvement was higher in patients receiving therapeutic doses of anticoagulation compared to all other patients (<italic>n</italic> = 14, 58% vs. <italic>n</italic> = 33, 33%; <italic>p</italic> = 0.022) (Table ##TAB##1##2##).\n</p>", "<title>Description of systemic anti-tumour therapy and anticoagulation</title>", "<p id=\"Par46\">Median estimated follow-up time was 59.0 months (95% confidence interval [95%CI]: 20.2–97.9) and median overall survival was 9.7 months (95%CI: 6.9–12.6). Ninety-eight patients (79%) died during follow-up. Ninety-four patients (76%) were treated with effective systemic therapies, and 19 (15%) and 11 (9%) individuals received either experimental systemic therapy or no systemic therapy, respectively. Most common systemic first-line therapy was sorafenib (<italic>n</italic> = 72, 78%) followed by ICI-based therapy (<italic>n</italic> = 14, 15%). Detailed information on systemic first- and further line treatments are displayed in Supplementary Table ##SUPPL##0##1##.</p>", "<p id=\"Par47\">Median time from diagnosis of macrovascular tumour invasion to effective systemic therapy was 1.4 months (95%CI: 1.1–1.7), and median time on effective systemic therapy was 7.9 months (95%CI: 4.5–11.2). Thirty-two patients (26%) were treated with anticoagulation (<italic>n</italic> = 24 with therapeutic and <italic>n</italic> = 8 with reduced/prophylactic doses). Anticoagulation was started in most patients right after diagnosis of macrovascular tumour invasion and some patients were already on anticoagulation for other indications. Median time on therapeutic anticoagulation was 7.7 months (95%CI: 2.2–13.2). Of patients receiving therapeutic doses of anticoagulation, 2 patients (8%) were treated with low molecular weight heparin (LMWH), 5 patients (21%) were treated with vitamin K antagonists (VKA), and 17 patients (71%) received direct oral anticoagulants (DOACs, rivaroxaban <italic>n</italic> = 6, edoxaban <italic>n</italic> = 1, apixaban <italic>n</italic> = 10). Of all 24 patients receiving therapeutic anticoagulation, 12 (50%) were anticoagulated because of an existing non-tumorous thrombus apposition, 3 (13%) individuals without non-tumorous thrombus apposition at baseline received anticoagulation to prevent thrombus apposition, and 9 (38%) patients had another indication for anticoagulation (e.g., atrial fibrillation, history of pulmonary embolism/deep vein thrombosis).</p>", "<title>Impact of systemic anti-tumour therapy and therapeutic anticoagulation on all-cause mortality</title>", "<p id=\"Par48\">In univariable Cox regression analysis, effective systemic therapy (HR: 0.26 [95%CI: 0.16–0.41]; <italic>p</italic> &lt; 0.001) but not therapeutic anticoagulation (HR: 0.71 [95%CI: 0.42–1.19]; <italic>p</italic> = 0.190) was associated with significantly reduced all-cause mortality (Table ##TAB##2##3##). After adjusting for possible confounding co-factors, effective systemic therapy remained an independent predictor of reduced all-cause mortality (adjusted HR [aHR]: 0.26 [95%CI: 0.16–0.40]; p &lt; 0.001), along with ECOG PS, ALBI score and degree of thrombus-induced vessel occlusion (Table ##TAB##2##3##). Survival curves according to systemic anti-tumour therapy and anticoagulation status using the Simon and Makuch method are shown in Fig. ##FIG##1##2##. Importantly, results were similar when including any anticoagulation (therapeutic and reduced/prophylactic doses) in Cox regression analyses (Supplementary Table ##SUPPL##0##2##).\n</p>", "<title>Changes of macrovascular tumour thrombosis during follow-up</title>", "<p id=\"Par49\">Best response of the thrombus at 3–6 months (median time to best response, 3.4 months [95%CI: 3.1–3.7]) was evaluated in patients who had at least one follow-up imaging (<italic>n</italic> = 83, 66%). Of these, 17 patients (20%) received therapeutic anticoagulation (Table ##TAB##1##2##). There was no difference in the rate of regression (<italic>n</italic> = 3, 18% vs. <italic>n</italic> = 11, 17%), stabilization (<italic>n</italic> = 7, 41% vs. <italic>n</italic> = 25, 38%), and progression (<italic>n</italic> = 7, 41% vs. <italic>n</italic> = 30, 45%) between patients with and without therapeutic anticoagulation (<italic>p</italic> = 0.951) (Table ##TAB##1##2##, Supplementary Figure ##SUPPL##0##2##A).</p>", "<p id=\"Par50\">Similar results were observed, when only patients with non-tumorous thrombus apposition at baseline were analysed (<italic>p</italic> = 0.772), even though the percentage of patients with a thrombus regression was numerically higher in individuals receiving anticoagulation (<italic>n</italic> = 2/7, 29% vs. <italic>n</italic> = 5/26, 19%) (Supplementary Figure ##SUPPL##0##2##B).</p>", "<title>Management of varices and portal hypertension-related complications</title>", "<p id=\"Par51\">There was no difference in the number of portal-hypertension-related complications between patients with and without therapeutic anticoagulation, and particularly the proportion of patients with variceal bleeding events was not different between both groups (<italic>n</italic> = 3, 13% vs. <italic>n</italic> = 13, 13%) (Supplementary Table ##SUPPL##0##3##). The variceal status was known in 80 patients (65%). This number was higher in patients receiving therapeutic anticoagulation (<italic>n</italic> = 21, 88% vs. <italic>n</italic> = 59, 59%), as was the number of individuals receiving adequate management of varices among those with known variceal status (<italic>n</italic> = 21/21, 100% vs. <italic>n</italic> = 48/59, 81%) (Supplementary Table ##SUPPL##0##3##).</p>", "<p id=\"Par52\">Overall, sixty-nine individuals (86%) received adequate management of varices. Variceal bleeding events were observed significantly more often in patients without vs. with adequate management of varices (<italic>n</italic> = 5, 46% vs. <italic>n</italic> = 8, 12%; <italic>p</italic> = 0.014), while there was no difference between both groups regarding other portal hypertension-related complications (Supplemental Table ##SUPPL##0##4##). In multivariable logistic regression analysis, adequate management of varices was independently associated with a reduced risk of variceal bleeding (aHR: 0.12 [95%CI: 0.02–0.71]; <italic>p</italic> = 0.019), while no association was observed with degree of thrombus-induced vessel occlusion, involvement of main portal vein, and therapeutic anticoagulation (Table ##TAB##3##4##). Adequate management of varices was associated with reduced risk of variceal bleeding or death from any cause in univariable Cox regression analysis (HR: 0.46 [95%CI: 0.25–0.84]; <italic>p</italic> = 0.011) but not in multivariable analyses (Supplementary Table ##SUPPL##0##5##). However, when only including patients with involvement of the main portal vein and/or both portal branches who have the highest bleeding risk, adequate management of varices was independently associated with reduced risk of variceal bleeding or death from any cause (aHR: 0.29 [95%CI: 0.13–0.66]; <italic>p</italic> = 0.003) (Supplementary Table ##SUPPL##0##6##).\n</p>", "<p id=\"Par53\">In the whole cohort (<italic>n</italic> = 124), the use of NSBB was independently associated with reduced risk of variceal bleeding or death from any cause (aHR: 0.69 [95%CI: 0.50–0.96]; <italic>p</italic> = 0.027), along with effective anti-tumour therapy, partial vessel occlusion, lower ALBI score, and better performance status (Supplementary Table ##SUPPL##0##7##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par54\">In this retrospective study including 124 patients with HCC and macrovascular tumour invasion, therapeutic anticoagulation was not associated with an increased bleeding rate but failed to reduce thrombosis progression and mortality risk. Adequate management of varices was associated with a lower rate and risk of variceal bleedings, especially in patients with involvement of the main portal vein and/or both portal branches, where it also reduced the risk of variceal bleeding or death from any cause.</p>", "<p id=\"Par55\">In patients with cirrhosis and non-tumorous portal vein thrombosis, therapeutic anticoagulation is recommended in candidates for liver transplantation as well as in selected non-transplant candidates (i.e., recent &gt; 50% occlusion of main portal vein or both main branches or involvement of mesenteric veins), with the aim to ‘recanalize’ the portal venous tract to prevent complications or facilitate liver transplantation. Evaluation of treatment efficacy by imaging is recommended after 3–6 months [##REF##33930474##7##, ##REF##33219529##18##, ##REF##26516032##27##].</p>", "<p id=\"Par56\">No recommendations on anticoagulation exist for patients with HCC and macrovascular tumour invasion. Regression of a tumour thrombus, as seen with systemic anti-tumour therapy in some cases [##REF##34414120##28##], seems unlikely to be achievable by anticoagulation. However, anticoagulation may prevent occurrence or progression of non-malignant thrombus apposition that could worsen portal hypertension or cause thromboembolic complications, providing a clinical rationale for the use of anticoagulation in this setting.</p>", "<p id=\"Par57\">In patients with at least one follow-up imaging, the regression rate at 3–6 months was similar between patients with and without therapeutic anticoagulation (18% vs. 17%), as was the rate of progression (41% vs. 45%). Results were similar when only patients with thrombus apposition at baseline were analysed. Not surprisingly, this contrasts with cirrhotic patients with non-tumorous portal vein thrombosis, in whom the ‘recanalization rate’ was significantly higher with anticoagulation; however, the progression rate in our study was comparable to that observed in cirrhotic individuals with untreated portal vein thrombosis [##REF##22891357##29##–##REF##28479379##31##].</p>", "<p id=\"Par58\">The rate of portal hypertension-related complications was also similar between patients with and without therapeutic anticoagulation. In particular, we did not observe a reduced or increased number of variceal bleeding events in patients receiving anticoagulation, which is in line with previous reports of cirrhotic patients receiving anticoagulation [##REF##28479379##31##–##REF##34152697##33##].</p>", "<p id=\"Par59\">Like non-tumorous portal vein thrombosis, macrovascular tumour invasion, especially in case of main portal vein involvement, may aggravate portal hypertension by increasing resistance to portal blood flow [##REF##33930474##7##, ##REF##36631021##12##]. In line, portal vein tumour thrombosis is associated with an increased risk of high-risk varices and variceal bleeding in patients with HCC, particularly in individuals receiving vascular endothelial growth factor (VEGF)-targeted agents [##REF##33402105##13##]. Although the management of portal hypertension in cirrhotic patients with HCC should follow recommendations for individuals with liver cirrhosis, there are several uncertainties, including the value of NSBBs in patients with varices secondary to portal vein tumour thrombosis [##REF##36631021##12##, ##REF##35944830##15##–##REF##35526788##17##].</p>", "<p id=\"Par60\">In our study, variceal status was known in two-thirds of patients (anticoagulation vs. no anticoagulation, 88% vs. 59%). This is higher compared to two previous reports on advanced HCC patients treated with atezolizumab plus bevacizumab (53% in both) [##REF##35313048##34##]. In patients with known variceal status, 86% of individuals received adequate bleeding prophylaxis in our cohort. This proportion was higher in patients receiving anticoagulation (100%) than in those without anticoagulation (81%), suggesting that treating physicians were more cautious and diligent in adhering to guidelines when initiating anticoagulation. Overall, these data call for measures to raise the awareness for adequate screening and management of portal hypertension in patients with HCC.</p>", "<p id=\"Par61\">Only little is known about the efficacy of bleeding prophylaxis in patients with HCC. In a large Korean cohort of HCC patients without a history of variceal bleeding, primary prophylaxis was associated with a lower cumulative incidence rate of variceal haemorrhage at one year; however, only overall mortality but not the risk of variceal bleeding was significantly reduced with primary prophylaxis [##REF##35944830##15##, ##REF##27435325##35##]. In our cohort, the number of variceal bleeding events was significantly lower in individuals with adequate management of varices, as was the risk for variceal bleeding or death from any cause in patients with involvement of the main portal vein and/or both portal branches after multivariable adjustment.</p>", "<p id=\"Par62\">We want to acknowledge some limitations of our study. These include the retrospective nature with all its inevitable, potential confounders. To account for a potential selection bias due to lack of randomisation, main analyses were adjusted for relevant co-factors in multivariable models. Furthermore, the variceal status was only known in 80 of 124 patients; therefore, only these were available to evaluate the efficacy of variceal management. Different types of anticoagulation (i.e., LMWH, VKA, DOAC) were used in our cohort, but the sample size was not large enough to analyse the effects of each type separately. Finally, follow-up imaging in patients with advanced HCC is usually performed every 3 months at our institution; nevertheless, imaging was done by different modalities (i.e., CT or MRI) and not performed at predefined intervals based on a specific protocol.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par63\">In conclusion, therapeutic anticoagulation had no clinical benefit in patients with HCC and macrovascular tumour invasion, but adequate management of varices (i.e., NSBB and/or endoscopic treatment of varices) was associated with reduced risk of variceal bleeding events. Hence, our data support the use of variceal bleeding prophylaxis as recommended for patients with liver cirrhosis in HCC patients with macrovascular tumour invasion, but do not argue for therapeutic anticoagulation in this setting. Prospective trials are warranted to confirm these findings.</p>" ]
[ "<title>Background &amp; aims</title>", "<p id=\"Par1\">The value of bleeding prophylaxis and anticoagulation in patients with hepatocellular carcinoma (HCC) and macrovascular tumour invasion (MVI) is unclear. We evaluated the impact of anticoagulation on thrombosis progression, bleeding events, and overall mortality, and assessed the efficacy of adequate management of varices as recommended for patients with cirrhosis.</p>", "<title>Methods</title>", "<p id=\"Par2\">HCC patients with MVI who had Child-Turcotte-Pugh A-B7 were included between Q4/2002 and Q2/2022. Localization of the tumour thrombus and changes at 3–6 months were evaluated by two radiologists. Univariable and multivariable logistic/Cox regression analyses included time-dependent variables (i.e., anticoagulation, systemic therapy, non-selective beta blocker treatment).</p>", "<title>Results</title>", "<p id=\"Par3\">Of 124 patients included (male: <italic>n</italic> = 110, 89%), MVI involved the main portal vein in 47 patients (38%), and 49 individuals (40%) had additional non-tumorous thrombus apposition. Fifty of 80 patients (63%) with available endoscopy had varices. Twenty-four individuals (19%) received therapeutic anticoagulation and 94 patients (76%) were treated with effective systemic therapies. The use of therapeutic anticoagulation did not significantly affect the course of the malignant thrombosis at 3–6 months. Systemic therapy (aHR: 0.26 [95%CI: 0.16–0.40]) but not anticoagulation was independently associated with reduced all-cause mortality. In patients with known variceal status, adequate management of varices was independently associated with reduced risk of variceal bleeding (aHR: 0.12 [95%CI: 0.02–0.71]). In the whole cohort, non-selective beta blockers were independently associated with reduced risk of variceal bleeding or death from any cause (aHR: 0.69 [95%CI: 0.50–0.96]).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Adequate bleeding prophylaxis and systemic anti-tumour therapy but not anticoagulation were associated with improved outcomes in patients with HCC and MVI.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s40644-024-00657-z.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<p>N/A</p>", "<title>Authors’ contributions</title>", "<p>Concept of the study (L.B., A.M., D.T., M.P.), data collection (L.B., A.M. D.T., M.P.), statistical analysis (L.B., M.P.), drafting of the manuscript (L.B., A.M., D.T., M.P.), revision for important intellectual content and approval of the final manuscript (all authors).</p>", "<title>Funding</title>", "<p>No financial support specific to this study was received.</p>", "<title>Availability of data and materials</title>", "<p>The data that support the findings of this study are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par64\">The retrospective analysis was approved by the Ethics Committee of the Medical University of Vienna.</p>", "<title>Consent for publication</title>", "<p id=\"Par65\">N/A</p>", "<title>Competing interests</title>", "<p id=\"Par66\">The authors have nothing to disclose regarding the work under consideration for publication. The following authors disclose conflicts of interests outside the submitted work:</p>", "<p id=\"Par67\">L.B., A.M., and K.P. have nothing to disclose.</p>", "<p id=\"Par68\">B.S. received travel support from AbbVie, Ipsen, and Gilead.</p>", "<p id=\"Par69\">T.M. received travel support from Chiesi and Janssen-Cilag; and travel support from CSL Behring, Chiesi, Jazz Pharmaceuticals and Janssen-Cilag.</p>", "<p id=\"Par70\">M.M. served as a speaker and/or consultant and/or advisory board member for AbbVie, Collective Acumen, Gilead, Takeda, and W. L. Gore &amp; Associates and received travel support from AbbVie and Gilead.</p>", "<p id=\"Par71\">T.R. served as a speaker and/or consultant and/or advisory board member for AbbVie, Bayer, Boehringer Ingelheim, Gilead, Intercept, MSD, Siemens, and W. L. Gore &amp; Associates and received grants/research support from AbbVie, Boehringer Ingelheim, Gilead, Intercept, MSD, Myr Pharmaceuticals, Pliant, Philips, Siemens, and W. L. Gore &amp; Associates as well as travel support from AbbVie, Boehringer Ingelheim, Gilead and Roche.</p>", "<p id=\"Par72\">M.T. served as a speaker and/or consultant and/or advisory board member for Albireo, BiomX, Falk, Boehringer Ingelheim, Bristol-Myers Squibb, Falk, Genfit, Gilead, Hightide, Intercept, Janssen, MSD, Novartis, Phenex, Pliant, Regulus, and Shire, and received travel support from AbbVie, Falk, Gilead, and Intercept, as well as grants/research support from Albireo, Alnylam, Cymabay, Falk, Gilead, Intercept, MSD, Takeda, and UltraGenyx. He is also co-inventor of patents on the medical use of 24-norursodeoxycholic acid.</p>", "<p id=\"Par73\">D.T. served as a speaker and/or consultant and/or advisory board member for Siemens, Roche, Sanova, Bristol-Myers Squibb and received travel support from Bayer and Siemens.</p>", "<p id=\"Par74\">M.P. served as a speaker and/or consultant and/or advisory board member for Astra Zeneca, Bayer, Bristol-Myers Squibb, Eisai, Ipsen, Lilly, MSD, and Roche, and received travel support from Bayer, Bristol-Myers Squibb, and Roche.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Patient flow chart and location of macrovascular tumour invasion. <bold>A</bold> A total of 508 patients diagnosed with hepatocellular carcinoma and suspected macrovascular tumour invasion between Q4/2002 and Q2/2022 were screened. <bold>B</bold> Localization of macrovascular tumour invasion and degree of vessel occlusion. <italic>Abbreviations: CTP Child-Turcotte-Pugh score; FU follow-up; MVI macrovascular tumour invasion</italic></p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Survival curves for anticoagulation and systemic therapy (time-dependent covariates) using the Simon and Makuch method</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline patient characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th><italic>Patient characteristics</italic></th><th>Study cohort,<break/><italic>n</italic> = 124</th></tr></thead><tbody><tr><td>Age, years, mean ± SD</td><td>65.3 ± 9.7</td></tr><tr><td colspan=\"2\">Sex, n (%)</td></tr><tr><td> Male</td><td>110 (89%)</td></tr><tr><td> Female</td><td>14 (11%)</td></tr><tr><td colspan=\"2\">Aetiology, n (%)</td></tr><tr><td> ARLD</td><td>51 (41%)</td></tr><tr><td> Viral</td><td>46 (37%)</td></tr><tr><td> Other/Unknown</td><td>15 (12%)</td></tr><tr><td> MASLD</td><td>12 (10%)</td></tr><tr><td>Cirrhosis, n (%)</td><td>110 (89%)</td></tr><tr><td>Varices, n (%)<sup>a</sup></td><td>50/80 (63%)</td></tr><tr><td> Low-risk varices<sup>b</sup></td><td>18/50 (36%)</td></tr><tr><td> High-risk varices</td><td>32/50 (64%)</td></tr><tr><td>Non-selective beta blocker treatment, n (%)</td><td>42 (34%)</td></tr><tr><td>Endoscopic treatment of varices, n (%)</td><td>14 (11%)</td></tr><tr><td>CTP score, points, median (IQR)</td><td>5 (5–6)</td></tr><tr><td> A, n (%)</td><td>108 (87%)</td></tr><tr><td> B7, n (%)</td><td>16 (13%)</td></tr><tr><td>ALBI score, mean ± SD</td><td>−2.5 ± 0.4</td></tr><tr><td> Stage 1, n (%)</td><td>48 (39%)</td></tr><tr><td> Stage 2, n (%)</td><td>76 (61%)</td></tr><tr><td>Prior surgery/local therapy, n (%)</td><td>21 (17%)</td></tr><tr><td>Extrahepatic spread, n (%)</td><td>36 (29%)</td></tr><tr><td colspan=\"2\">ECOG PS, n (%)</td></tr><tr><td> 0</td><td>72 (58%)</td></tr><tr><td> 1</td><td>52 (42%)</td></tr><tr><td colspan=\"2\">Baseline imaging modality, n (%)</td></tr><tr><td> Computed tomography</td><td>96 (77%)</td></tr><tr><td> Magnetic resonance imaging</td><td>28 (23%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Localization of macrovascular tumour invasion (<italic>n</italic> = 124) and changes during follow-up (<italic>n</italic> = 83) according to therapeutic anticoagulation</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td><italic>Patient characteristics</italic></td><td><p><bold>Study cohort,</bold></p><p><bold><italic>n</italic></bold> <bold>= 124 (100%)</bold></p></td><td><p>Anticoagulation,</p><p><bold><italic>n</italic></bold> <bold>= 24 (19%)</bold></p></td><td><p>No anticoagulation,</p><p><bold><italic>n</italic></bold> <bold>= 100 (81%)</bold></p></td><td><bold><italic>p</italic></bold><bold>-value</bold></td></tr><tr><td colspan=\"5\">Localization and degree of occlusion, n (%)</td></tr><tr><td> Main portal vein involved</td><td>47 (38%)</td><td>14 (58%)</td><td>33 (33%)</td><td><bold>0.022</bold></td></tr><tr><td>  Total</td><td>19 (15%)</td><td>6 (25%)</td><td>13 (13%)</td><td rowspan=\"2\">0.069</td></tr><tr><td>  Partial</td><td>28 (23%)</td><td>8 (33%)</td><td>20 (20%)</td></tr><tr><td> Left and/or right portal branch</td><td>53 (43%)</td><td>8 (33%)</td><td>45 (45%)</td><td>0.299</td></tr><tr><td>  Total</td><td>25 (20%)</td><td>2 (8%)</td><td>23 (23%)</td><td rowspan=\"2\">0.272</td></tr><tr><td>  Partial</td><td>28 (23%)</td><td>6 (25%)</td><td>22 (22%)</td></tr><tr><td> Left and/or right portal branch and other veins (hepatic veins, splenic vein, VCI, SMV)</td><td>17 (14%)</td><td>2 (8%)</td><td>15 (15%)</td><td>0.522</td></tr><tr><td>  Total</td><td>7 (6%)</td><td>2 (8%)</td><td>5 (5%)</td><td rowspan=\"2\">0.237</td></tr><tr><td>  Partial</td><td>10 (8%)</td><td>–</td><td>10 (10%)</td></tr><tr><td> Other veins (hepatic veins, splenic vein, VCI, SMV)</td><td>7 (6%)</td><td>–</td><td>7 (7%)</td><td rowspan=\"2\">0.344</td></tr><tr><td>  Total</td><td>7 (6%)</td><td>–</td><td>7 (7%)</td></tr><tr><td>  Apposition thrombus</td><td>49 (40%)</td><td>12 (50%)</td><td>37 (37%)</td><td>0.242</td></tr><tr><td>  Venous congestion</td><td>22 (18%)</td><td>5 (21%)</td><td>17 (17%)</td><td>0.766</td></tr><tr><td><italic>Best radiological response of macrovascular tumour invasion at 3–6 months, n (%)</italic></td><td><p><bold>All patients with available FU imaging,</bold></p><p><bold><italic>n</italic></bold> <bold>= 83 (100%)</bold></p></td><td><p>Anticoagulation,</p><p><bold><italic>n</italic></bold> <bold>= 17 (20%)</bold></p></td><td><p>No anticoagulation,</p><p><bold><italic>n</italic></bold> <bold>= 66 (80%)</bold></p></td><td><bold><italic>p</italic></bold><bold>-value</bold></td></tr><tr><td> Regression</td><td>14 (17%)</td><td>3 (18%)</td><td>11 (17%)</td><td rowspan=\"3\">0.951</td></tr><tr><td> Stabilization</td><td>32 (39%)</td><td>7 (41%)</td><td>25 (38%)</td></tr><tr><td> Progression</td><td>37 (45%)</td><td>7 (41%)</td><td>30 (45%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Uni- and multivariable Cox regression analyses of factors associated with all-cause mortality using backward elimination in all patients (<italic>n</italic> = 124, <italic>n</italic> = 98 events)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th rowspan=\"2\"><italic>Patient characteristics</italic></th><th colspan=\"2\">Univariable</th><th colspan=\"2\">Multivariable first step</th><th colspan=\"2\">Multivariable last step</th></tr><tr><th>HR (95%CI)</th><th><italic>p</italic>-value</th><th>aHR (95%CI)</th><th><italic>p</italic>-value</th><th>aHR (95%CI)</th><th><italic>p</italic>-value</th></tr></thead><tbody><tr><td>Age, per year</td><td>1.00 (0.98–1.03)</td><td>0.767</td><td>1.00 (0.98–1.02)</td><td>1.000</td><td>–</td><td>–</td></tr><tr><td>Sex, male vs. female</td><td>1.03 (0.54–1.97)</td><td>0.931</td><td>0.99 (0.51–1.91)</td><td>0.969</td><td>–</td><td>–</td></tr><tr><td>Cirrhosis</td><td>1.52 (0.84–2.73)</td><td>0.164</td><td>1.13 (0.58–2.23)</td><td>0.714</td><td>–</td><td>–</td></tr><tr><td>EHS</td><td>1.69 (1.17–2.43)</td><td><bold>0.005</bold></td><td>1.21 (0.82–1.79)</td><td>0.328</td><td>–</td><td>–</td></tr><tr><td>ECOG PS, 1 vs. 0</td><td>1.79 (1.26–2.55)</td><td><bold>0.001</bold></td><td>1.66 (1.15–2.40)</td><td><bold>0.007</bold></td><td>1.73 (1.24–2.42)</td><td><bold>0.001</bold></td></tr><tr><td>CTP score, per point</td><td>1.41 (1.09–1.84)</td><td><bold>0.010</bold></td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>ALBI score, per point</td><td>2.15 (1.40–3.30)</td><td><bold>&lt; 0.001</bold></td><td>1.82 (1.11–2.98)</td><td><bold>0.017</bold></td><td>2.04 (1.30–3.21)</td><td><bold>0.035</bold></td></tr><tr><td colspan=\"7\">Degree of thrombus-induced vessel occlusion</td></tr><tr><td> Partial</td><td>1</td><td>–</td><td>1</td><td>–</td><td>1</td><td>–</td></tr><tr><td> Total</td><td>1.60 (1.11–2.31)</td><td><bold>0.012</bold></td><td>1.47 (1.04–2.07)</td><td><bold>0.027</bold></td><td>1.44 (1.03–2.02)</td><td><bold>0.035</bold></td></tr><tr><td colspan=\"7\">Thrombus localization</td></tr><tr><td> MPV not involved</td><td>1</td><td>–</td><td>1</td><td>–</td><td>–</td><td>–</td></tr><tr><td> MPV involved</td><td>0.96 (0.66–1.40)</td><td>0.824</td><td>1.26 (0.87–1.82)</td><td>0.214</td><td>–</td><td>–</td></tr><tr><td>Effective systemic therapy</td><td>0.26 (0.16–0.41)</td><td><bold>&lt; 0.001</bold></td><td>0.26 (0.16–0.41)</td><td><bold>&lt; 0.001</bold></td><td>0.26 (0.16–0.40)</td><td><bold>&lt; 0.001</bold></td></tr><tr><td>Non-selective beta blocker therapy</td><td>0.81 (0.57–1.14)</td><td>0.227</td><td>0.71 (0.50–1.00)</td><td>0.052</td><td>0.75 (0.54–1.05)</td><td>0.098</td></tr><tr><td>Therapeutic anticoagulation</td><td>0.71 (0.42–1.19)</td><td>0.190</td><td>0.88 (0.55–1.41)</td><td>0.596</td><td>–</td><td>–</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Uni- and multivariable logistic regression analyses of factors associated with variceal bleeding using backward elimination in patients with known variceal status at study inclusion (<italic>n</italic> = 80, <italic>n</italic> = 13 events)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th rowspan=\"2\"><italic>Patient characteristics</italic></th><th colspan=\"2\">Univariable</th><th colspan=\"2\">Multivariable first step</th><th colspan=\"2\">Multivariable last step</th></tr><tr><th>HR (95%CI)</th><th>p-value</th><th>aHR (95%CI)</th><th>p-value</th><th>aHR (95%CI)</th><th>p-value</th></tr></thead><tbody><tr><td>Age, per year</td><td>0.90 (0.84–0.98)</td><td><bold>0.008</bold></td><td>0.88 (0.80–0.97)</td><td><bold>0.013</bold></td><td>0.90 (0.82–0.98)</td><td><bold>0.022</bold></td></tr><tr><td>EHS</td><td>0.37 (0.08–1.83)</td><td>0.223</td><td>0.09 (0.01–1.14)</td><td>0.063</td><td>0.20 (0.03–1.22)</td><td>0.081</td></tr><tr><td>ECOG PS, 1 vs. 0</td><td>2.23 (0.67–7.42)</td><td>0.190</td><td>9.02 (1.36–59.87)</td><td><bold>0.023</bold></td><td>5.91 (1.22–28.73)</td><td><bold>0.028</bold></td></tr><tr><td>CTP score, per point</td><td>0.64 (0.26–1.55)</td><td>0.323</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>ALBI score, per point</td><td>1.33 (0.34–5.29)</td><td>0.685</td><td>0.31 (0.03–2.94)</td><td>0.308</td><td>–</td><td>–</td></tr><tr><td colspan=\"7\">Degree of thrombus-induced vessel occlusion</td></tr><tr><td> Partial</td><td>1</td><td>–</td><td>1</td><td>–</td><td>–</td><td>–</td></tr><tr><td> Total</td><td>1.07 (0.32–3.51)</td><td>0.915</td><td>2.79 (0.45–17.44)</td><td>0.274</td><td>–</td><td>–</td></tr><tr><td colspan=\"7\">Thrombus localization</td></tr><tr><td> MPV not involved</td><td>1</td><td>–</td><td>1</td><td>–</td><td>–</td><td>–</td></tr><tr><td> MPV involved</td><td>0.58 (0.18–1.91)</td><td>0.369</td><td>3.44 (0.59–20.09)</td><td>0.171</td><td>–</td><td>–</td></tr><tr><td>Effective systemic therapy</td><td>0.54 (0.14–2.04)</td><td>0.364</td><td>0.36 (0.04–3.04)</td><td>0.347</td><td>–</td><td>–</td></tr><tr><td>Adequate management of varices</td><td>0.16 (0.04–0.64)</td><td><bold>0.009</bold></td><td>0.03 (0.00–0.38)</td><td><bold>0.006</bold></td><td>0.12 (0.02–0.71)</td><td><bold>0.019</bold></td></tr><tr><td>Therapeutic anticoagulation</td><td>0.82 (0.20–3.31)</td><td>0.777</td><td>1.73 (0.26–11.62)</td><td>0.574</td><td>–</td><td>–</td></tr></tbody></table></table-wrap>" ]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>Abbreviations: ALBI</italic> score albumin-to-bilirubin score, <italic>ARLD</italic> alcohol-related liver disease, <italic>BCLC</italic> Barcelona Clinic Liver Cancer, <italic>BMI</italic> body mass index, <italic>CTP</italic> Child-Turcotte-Pugh score, <italic>ECOG PS</italic> Eastern Cooperative Oncology Group Performance Status, <italic>IQR</italic> interquartile range, MASLD metabolic-dysfunction associated steatotic liver disease, <italic>SD</italic> standard deviation</p><p><sup>a</sup>Data available in 80 patients (65%)</p><p><sup>b</sup>One patient with non-cirrhotic portal hypertension with low-risk varices</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Abbreviations: FU</italic> follow-up, <italic>SMV</italic> superior mesenteric vein, <italic>VCI vena cava inferior</italic></p></table-wrap-foot>", "<table-wrap-foot><p><italic>Abbreviations: ALBI</italic> albumin-to-bilirubin score, <italic>(a)HR</italic> (adjusted) hazard ratio, <italic>CTP</italic> Child-Turcotte-Pugh score, <italic>ECOG PS</italic> Eastern Cooperative Oncology Group Performance Status, <italic>EHS</italic> extrahepatic spread, <italic>MPV main portal vein</italic></p></table-wrap-foot>", "<table-wrap-foot><p><italic>Abbreviations: ALBI</italic> albumin-to-bilirubin score, <italic>(a)HR</italic> (adjusted) hazard ratio, <italic>CTP</italic> Child-Turcotte-Pugh score, <italic>ECOG PS</italic> Eastern Cooperative Oncology Group Performance Status, <italic>EHS</italic> extrahepatic spread, <italic>MPV</italic> main portal vein</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Lorenz Balcar and Arpad Mrekva shared the first authorship and Dietmar Tamandl and Matthias Pinter shared the last authorship.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"40644_2024_657_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"40644_2024_657_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"40644_2024_657_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1:</bold><bold> Supplementary Figure 1. </bold>Illustration of inclusion and follow-up time. <bold>Supplementary Figure 2.</bold> Changes of macrovascular tumour invasion during follow-up. <bold>Supplementary Table 1.</bold> Description of systemic anti-tumour therapy and anticoagulation. <bold>Supplementary Table 2.</bold> Uni- and multivariable Cox regression analyses of factors associated with all-cause mortality using backward elimination considering all types of anticoagulation in all patients (<italic>n</italic>=124, <italic>n</italic>=98 events). <bold>Supplementary Table 3.</bold> Management of varices and portal hypertension-related complications according to therapeutic anticoagulation status. <bold>Supplementary Table 4.</bold> Decompensation events according to adequate management of varices. <bold>Supplementary Table 5.</bold> Uni- and multivariable Cox regression analyses of factors associated with risk of variceal bleeding or death from any-cause using backward elimination in patients with known variceal status at study inclusion (<italic>n</italic>=80, <italic>n</italic>=61 events). <bold>Supplementary Table 6.</bold> Uni- and multivariable Cox regression analyses of factors associated with risk of variceal bleeding or death from any cause using backward elimination in patients with known variceal status and involvement of the main portal vein and/or both portal branches at study inclusion (<italic>n</italic>=63, <italic>n</italic>=35 events). <bold>Supplementary Table 7.</bold> Uni- and multivariable Cox regression analyses of factors associated with risk of variceal bleeding or death from any-cause using backward elimination in all patients (<italic>n</italic>=124, <italic>n</italic>=99 events).</p></caption></media>" ]
[]
{ "acronym": [ "(a)HR", "ALBI", "BCLC", "CI", "CT", "CTP", "DOAC", "ECOG-PS", "HCC", "ICI", "IQR", "LI-RADS", "LMWH", "MRI", "MVI", "NSBB", "SD", "SIRT", "TACE", "TKI", "VEGF", "VKA" ], "definition": [ "(adjusted) hazard ratio", "Albumin-to-Bilirubin score", "Barcelona-Clinic Liver Cancer", "confidence interval", "computed tomography", "Child-Turcotte-Pugh score", "direct oral anticoagulants", "Eastern Cooperative Oncology Group Performance Status", "hepatocellular carcinoma", "immune checkpoint inhibitor", "interquartile range", "Liver Imaging and Data System", "low molecular weight heparin", "magnetic resonance imaging", "macrovascular tumour invasion", "non-selective beta blocker", "standard deviation", "selective internal radiation therapy", "transarterial chemoembolization", "tyrosine kinase inhibitors", "vascular endothelial growth factor", "vitamin K antagonist" ] }
35
CC BY
no
2024-01-14 23:43:46
Cancer Imaging. 2024 Jan 13; 24:9
oa_package/c7/2c/PMC10787425.tar.gz
PMC10787426
38216990
[ "<title>Introduction</title>", "<p id=\"Par5\">Cornelia de Lange Syndrome (CdLS), also known as Brachmann-de Lange Syndrome, is a genetically and clinically heterogeneous disorder that affects multiple aspects of development and has a wide clinical variability [##REF##19154515##1##, ##REF##19793304##2##]. Over time, different diagnostic criteria have been proposed, and the disease has been classified as a spectrum (CdLS) based on a detailed diagnostic algorithm that combines “cardinal” and “suggestive” features. CdLS belongs to a broader group of conditions called cohesinopathies, which include patients carrying variants in one of the different genes belonging to the cohesin complex. The natural history of the disease includes multiple chronic medical problems, and several behavioral comorbidities have also been described [##REF##29995837##3##]. CdLS is a rare condition, with an estimated incidence ranging from 1 in 10,000 to 1 in 30,000 newborns [##REF##29995837##3##].</p>", "<p id=\"Par6\">While the majority of CdLS cases appear to be sporadic, a few familial cases have been reported. Pedigree analyses of several families indicate autosomal dominant inheritance, with transmission observed from both parents in some cases [##REF##15318302##4##]; however, given autosomal dominant inheritance, cases of apparently normal parents who have multiple children with CdLS were hypothesized to be the result of germline mosaicism that is one of the critical areas of medical genetics [##REF##7554368##5##].</p>", "<p id=\"Par7\">CdLS is associated with mutations in six genes of the cohesin complex, including <italic>NIPBL</italic>, <italic>SMC1A</italic>, <italic>SMC3</italic>, <italic>RAD21</italic>, <italic>BRD4</italic>, and <italic>HDAC8</italic> [##REF##33478103##6##]. Most CdLS patients exhibit <italic>de novo</italic> pathogenic variants in one of these genes, with <italic>NIPBL</italic> being the most commonly affected gene [##REF##29995837##3##]. The proteins encoded by these genes serve as structural or regulatory components of the cohesin complex, which is a multimeric system that regulates sister chromatid cohesion and gene expression. The core of the cohesin complex is composed of <italic>SMC1A</italic>, <italic>SMC3</italic>, <italic>RAD21</italic>, and <italic>STAG</italic>, and is involved in sister chromatid cohesion and gene expression regulation [##REF##15383284##7##, ##REF##31721174##8##].</p>", "<p id=\"Par8\">The objective of this study is to present two novel heterozygous mutations identified in two patients with CdLS symptoms from unrelated families. These mutations contribute to the growing body of knowledge surrounding the genetic landscape of CdLS. Additionally, the study aims to underscore the importance of investigating mosaicism in patients exhibiting CdLS phenotypes. By identifying these mutations and highlighting the role of mosaicism, this research has implications for genetic counseling and clinical management of CdLS patients and their families.</p>" ]
[ "<title>Methods</title>", "<title>Sample collection and genomic analysis</title>", "<p id=\"Par12\">The genomic DNA was isolated from the peripheral blood of probands and their parent utilizing the salting-out procedure. The concentration and purity of DNA were ascertained using a NanoDrop 1000 (Thermo Fisher Scientific, Inc., Wilmington, DE, USA). Whole-Exome Sequencing <bold>(</bold>WES) was performed on an Illumina HiSeq4000 system with paired-end reads of 101 bp and 100X coverage, using genomic DNA from probands. Exonic and surrounding exon-intron border regions were enriched using SureSelectXT2 V6 kits.</p>", "<p id=\"Par13\">Subsequent to the removal of low-quality reads, the reads were mapped to the human genome reference (hg19 build) with the aid of the Burrows-Wheeler Aligner (BWA). Duplicates were marked and removed using SAM tools. Following that, recalibration and SNP/indel calling were carried out. Variant calling and filtering were performed using the Genome Analysis Toolkit (GATK). Finally, the called variants were annotated, filtered, and prioritized using ANNOVAR software and an in-house workflow. The 3D protein structural model of mutations in <italic>NIPBL</italic> and <italic>SMC1A</italic> was modeled and visualized using PyMol software (The PyMOL Molecular Graphics System, Version 1.2r3pre, Schrödinger, LLC).</p>" ]
[ "<title>Results</title>", "<p id=\"Par14\">The homozygous variants identified in this study, which encompassed splicing regions, stop gain, and frameshift mutations, were primarily evaluated based on their degree of pathogenicity. Subsequently, the pathogenicity of nonsynonymous mutations was assessed using multiple amino acid change predictions. Emphasis was placed on prioritizing mutations in genes known to be associated with diseases exhibiting reported phenotypes.</p>", "<p id=\"Par15\">During the WES analysis of case 1’s blood sample, no clinically significant variants related to the proband’s symptoms were found. However, the coding regions of <italic>NIPBL</italic>, <italic>SMC1A</italic>, <italic>SMC3</italic>, <italic>HDAC8</italic>, and <italic>RAD21</italic> genes related to CdLS received extra scrutiny due to a high clinical suspicion of the genetic syndrome. Therefore, WES of the skin sample was conducted, resulting in the detection of a heterozygous variant (NM_133433.4:c.6534_6535del (p.Met2178Ilefs*8) in the <italic>NIPBL</italic> found in 38% of reads. This mutation is novel and appears to exhibit a mosaic pattern in the proband as it was not detected in the previous analysis of blood-derived DNA. The variant entails a two-base pair deletion causing a frameshift in exon 38 and is absent from population databases such as Iranome and gnomAD [##REF##27535533##9##, ##UREF##0##10##]. Based on the American College of Medical Genetics (ACMG) guidelines [##UREF##1##11##], this variant has been classified as a likely pathogenic variant.</p>", "<p id=\"Par16\">Furthermore, a heterozygous variant in the <italic>SMC1A</italic> gene with dominant X-linked inheritance was primarily identified through WES in case 2. Subsequent confirmation was conducted using Sanger sequencing of genomic DNA. The analysis revealed that case 2 was heterozygous for the variant NM_006306.4: c.2320G &gt; A (p.Asp774Asn), while both parents exhibited normal homozygosity. Similar to the <italic>NIPBL</italic> variant, the <italic>SMC1A</italic> variant was classified as a likely pathogenic variant in accordance with the guidelines provided by the American College of Medical Genetics (ACMG). This novel mutation, NM_006306.4: c.2320G &gt; A, has not been documented in population databases, including gnomAD and Iranome. Furthermore, various prediction methods, such as MutationTaster, SIFT, polyphen, and UMD-predictor, have indicated its potential harmfulness [##REF##20676075##12##, ##REF##12824425##13##].</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par17\">In this study, we performed a comprehensive narrative review of the literature on CdLS, with a focus on genotype-phenotype correlations. We also identified novel heterozygous mutations in two patients exhibiting CdLS manifestations, further expanding the genetic landscape of the disorder. Our analysis revealed that the mutations affect genes involved in chromatin regulation within the cohesin complex, which is consistent with previous research. Moreover, we underscored the importance of investigating mosaicism in CdLS cases, as one patient displayed mosaicism for a <italic>NIPBL</italic> mutation detected only in skin-derived DNA, but not in blood-derived DNA. Our findings demonstrate the value of genotype-phenotype correlations in understanding the clinical presentation of CdLS and improving diagnosis and management of affected individuals. By combining our novel findings with a comprehensive literature review, we provide valuable insights into the genetic basis of CdLS and its clinical manifestations.</p>", "<p id=\"Par18\">The first description of CdLS was made by a Dutch pediatrician, Cornelia de Lange, in 1933 [##UREF##2##14##]. Over time, several authors have attempted to define diagnostic criteria, resulting in the identification of three clinical subtypes: classic, mild, and phenocopies [##REF##34356091##15##]. The variability of clinical expression led in the past to clinical diagnosis only, but with the discovery of the complex and heterogeneous biological basis of the disease, molecular confirmation analysis became necessary. In 2018, a consensus statement was published, classifying CdLS as a spectrum (CdLSp) and providing a detailed diagnostic algorithm based on “cardinal” and “suggestive” features. The algorithm distinguishes between classic and non-classic CdLS, which do not overlap with the old definitions [##REF##29995837##3##].</p>", "<p id=\"Par19\">The natural history of the disease includes multiple chronic medical problems, pivotal for properly planning and addressing the follow-up of the affected patients. Several behavioral comorbidities have also been described. Additional cohesin- or chromatin-associated factors have also been identified, which are genetically different from cohesin but whose variants have been found in CdLS patients. The cohesin complex, in conjunction with the chromosome loader <italic>NIPBL</italic> and the sequence-specific DNA binding protein CTCF, organizes the genome into topologically associated domains (TADs), chromatin loops, and contact domains, which helps to orchestrate gene expression. Although CdLS cell lines do not display abnormalities in sister chromatid cohesion, they exhibit dysregulated genes and protein expression, suggesting that the disorder is due to altered transcriptional regulation resulting from an impaired function of the cohesin complex in 3D chromatin organization. Additionally, many genes have been found to be weakly transcriptionally dysregulated in CdLS animal models.</p>", "<p id=\"Par20\">CdLS is classified into six types (MIM #300,590, #614,701, #300,882, #610,759, and #122,470) based on the specific genes involved in the cohesin complex, including <italic>NIPBL, SMC1A, SMC3, RAD21, BRD4</italic> and <italic>HDAC8</italic>. Additionally, mutations in <italic>ANKRD11</italic> genes have also been associated with CdLS [##REF##29995837##3##]. The phenotypic spectrum of CdLS varies, with classic and non-classic forms observed. Classic CdLS is easily recognizable at birth due to distinctive craniofacial features, growth patterns, and limb defects. However, non-classic CdLS can present with different degrees of facial and limb involvement, making diagnosis more challenging [##REF##29995837##3##].</p>", "<p id=\"Par21\">CdLSp1, caused by mutations in the <italic>NIPBL</italic> gene, accounts for 70% of the cases and has been shown to cause both mild and severe forms of the syndrome. CdLSp2, associated with the <italic>SMC1A</italic> gene mutations, accounts for about 5% of cases. CdLSp3, CdLSp4, and CdLSp5 are caused by mutations in <italic>SMC3</italic>, <italic>RAD21</italic>, and <italic>HDAC8</italic>, respectively, and encompass the remaining CdLS cases. Most CdLSp1 patients with <italic>NIPBL</italic> mutations exhibit characteristic facial and skeletal changes, along with prenatal growth retardation, moderate to severe psychomotor deficiency, and major malformations leading to severe disability or death. However, it is important to note that individuals with variants in other causative CdLS genes can also meet the criteria for classic CdLS. Loss-of-function variants tend to result in more severe clinical features compared to missense variants, which are associated with a milder phenotype [##REF##15318302##4##, ##REF##16236812##16##–##REF##25125236##18##].</p>", "<p id=\"Par22\">Case 1 of this study also harbors a frameshift mutation, which is classified as a loss-of-function variant. This finding is consistent with previous reports indicating that severe clinical features are commonly associated with such mutations. Somatic mosaicism has been previously documented in CdLSp1 cases. Huisman et al. reported the detection of pathogenic <italic>NIPBL</italic> mutations in buccal cell-derived DNA from ten CdLSp1 patients whose blood-derived DNA analyses yielded negative results. Even upon resequencing of the <italic>NIPBL</italic> in the blood sample of those ten patients, the mutations could not be identified [##REF##23505322##19##]. Along with previous studies, literature findings suggest that 15–20% of patients with classic CdLS phenotypes exhibit mosaicism with <italic>NIPBL</italic> mutations that are not detectable in blood-derived DNA [##REF##29995837##3##]. Case 1 in this study presents characteristic clinical features, including a long philtrum, synophrys, depressed nasal bridge, thin upper lip, small hand, developmental delay, and microcephaly, which align with the established diagnostic criteria for classic CdLS as proposed by Kline et al. However, the epilepsy observed in Case 1 deviated from the reported cases of epilepsy in CdLS patients. Typically, partial epilepsy is the most prevalent type, with an age of onset typically before two years. In most reported instances, affected individuals respond favorably to standard medical therapy and can be successfully weaned off medication after a few years [##REF##29995837##3##]. In contrast to these established patterns, the epilepsy in our reported case persisted as uncontrolled seizures despite the administration of various drugs. This departure from the expected form of epilepsy adds a distinctive aspect to our case and broaden the spectrum of epilepsy in the context of CdLS and necessitate further investigations. The consensus molecular diagnostic pathways for CdLS recommend initial screening using next-generation sequencing (NGS) for patients displaying classic phenotypes. If no variants in CdLS genes are identified, further investigation of mosaicism should be pursued by sequencing cells derived from tissues other than lymphocytes. In cases where such analysis yields no results, it is advisable to assess for deletions and duplications in the <italic>NIPBL</italic> [##REF##29995837##3##]. In Case 1, the findings are consistent with previous reports where blood-derived DNA analysis failed to detect any CdLS-related mutations. However, a frameshift mutation was identified in the <italic>NIPBL</italic> when analyzing DNA derived from skin tissue. These observations highlight the prominence of mosaicism, particularly in patients exhibiting classical phenotypes of CdLS, and emphasize the importance of exploring alternative tissue sources if blood-derived DNA testing yields negative results. Mosaicism can occur due to various reasons, such as a mutation happening after fertilization, leading to some cells having the mutation while others do not. It can also occur during early embryonic development when cells divide and differentiate. The presence of mosaicism in CdLS patients with <italic>NIPBL</italic> mutations suggests that the mutation may have occurred at a later stage of development, resulting in a subset of cells having the mutation while others remain unaffected. This can lead to variation in the severity and presentation of CdLS symptoms among affected individuals. It is important to note that the exact reasons for mosaicism in CdLS patients with <italic>NIPBL</italic> mutations are still not fully understood and further research is needed to fully comprehend its implications on the disorder.</p>", "<p id=\"Par23\">CdLSp2, characterized by mutations in the <italic>SMC1A</italic> gene, is the second most common type of CdLS, accounting for approximately 5% of cases after CdLSp1 [##REF##28548707##20##]. It has been observed that most CdLSp2 patients with <italic>SMC1A</italic> mutations are female, and the manifestations in females are attributed to the dominant-negative effect of the mutated <italic>SMC1A</italic> that escapes chromosome X-inactivation [##UREF##3##21##]. In contrast, males with <italic>SMC1A</italic> mutations typically exhibit a more severe phenotype compared to females. Initially, CdLSp2 was believed to be present with milder dysmorphic facial features, less affected growth patterns, and milder limb involvement compared to CdLSp1. However, there is variability in the phenotypic spectrum of <italic>SMC1A</italic>-related CdLS, and some cases have shown atypical features [##REF##28548707##22##]. In this study, a patient (case 2) presented with several characteristic features of CdLS, such as a long philtrum, upturned nasal tip, thick eyebrows, microcephaly, and developmental delay. However, these features were classified as a non-classic phenotype based on the consensus clinical diagnostic criteria [##REF##29995837##3##]. This finding is consistent with previous reports on CdLSp2 cases, which predominantly exhibit a non-classic phenotype. Based on the non-classic CdLS phenotypes observed in case 1, it is necessary to perform next-generation sequencing (NGS)-based screening of CdLS genes for accurate diagnosis of the patient. The WES analysis revealed the presence of the <italic>SMCA1</italic>:c.2320G &gt; A (p.Asp774Asn) mutation, confirming the diagnosis of CdLS in the patient. In this mutation, the wild-type residue, Asp774, carries a negative charge, whereas the mutant residue, Asn774, carries a neutral charge. Consequently, the mutation results in the loss of charge in the wild-type residue, which may disrupt its interactions with other molecules or residues (Fig. ##FIG##0##1##). The wild-type residue is highly conserved, and the mutated residue is located within a domain crucial for binding other molecules (Fig. ##FIG##1##2##). Therefore, the mutation of this residue may interfere with its normal function. Numerous missense mutations in the <italic>SMCA1</italic> gene have been reported in association with CdLSp2, suggesting that missense mutations may represent a common disease mechanism. However, the <italic>SMC1A</italic>:c.2320G &gt; A (p.Asp774Asn) mutation has not been reported in any previous cases. Future functional studies are necessary to elucidate the precise impact of the p. Asp774Asn mutation on SMCA1 function.</p>", "<p id=\"Par24\">\n\n</p>", "<p id=\"Par25\">\n\n</p>", "<p id=\"Par26\">Furthermore, this study provides valuable insights into the phenotypic spectrum and diagnostic criteria of CdLS. It is characterized by a wide range of phenotypes, from classic to non-classic forms, which can complicate the diagnosis of the disease. The consensus criteria for CdLS diagnosis include cardinal and suggestive features, with a clinical score equal to or greater than 11 and three cardinal features confirming the diagnosis of classic CdLS. It is worth noting that different types of CdLS are associated with mutations in specific genes, such as CdLSp1 with <italic>NIPBL</italic> mutations and CdLSp2 with <italic>SMC1A</italic> mutations. However, there is variability in the phenotypic spectrum of CdLS, with some cases exhibiting milder dysmorphic features and less affected growth patterns. This study also emphasizes the importance of genetic testing, particularly NGS-based screening, for accurate diagnosis and management of CdLS patients, and highlights the need for further research to understand the functional consequences of novel variations in CdLS-associated genes.</p>", "<p id=\"Par27\">Researchers have been attempting to identify correlations between molecular data and clinical phenotypes in CdLS since the discovery of new genes. However, the small number of patients with variants in genes other than <italic>NIPBL</italic> limits this effort. Variants in the <italic>NIPBL</italic> are responsible for the majority of classical and severe CdLS cases. Patients with missense variants have a better prognosis than those with loss of function variants. Variants in the <italic>SMC1A</italic>, <italic>SMC3</italic>, <italic>RAD21</italic>, <italic>BRD4</italic>, <italic>ANKRD11</italic> and <italic>HDAC8</italic> genes are rarer and have different phenotypic characteristics. Somatic mosaicism may contribute to less severe phenotypes, but further study is needed to determine its prevalence and consequences. CdLS-like phenotypes have also been observed in patients with variants in other genes associated with CdLS overlapping phenotypes.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par28\">The study, conducted on CdLS, highlights the effectiveness of WES in identifying genetic defects that underlie unexplained neurological symptoms in affected individuals. The research expands upon the mutational spectrum of CdLSp1 and CdLSp2, emphasizing the importance of genetic testing for accurate diagnosis and management of patients. Furthermore, the study underscores the importance of mosaicism testing in patients with classic CdLS, whose blood-derived WES analysis may yield negative results for CdLS-related genes. These findings have important implications for genetic counseling and clinical management of CdLS patients and their families. By identifying these mutations and recognizing the role of mosaicism, healthcare professionals can provide more accurate diagnoses and appropriate treatment plans for CdLS patients. Further research is required to determine the functional consequences of the novel mutations identified in this study, which could provide additional insights into the relationship between mutation type and disease severity in CdLS. Overall, this study contributes valuable knowledge to the growing body of research on the genetic basis and clinical manifestation of CdLS, providing important insights for future research and clinical practice.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Cornelia de Lange Syndrome (CdLS) is a rare genetic disorder characterized by a range of physical, cognitive, and behavioral abnormalities. This study aimed to perform a comprehensive review of the literature on CdLS and investigate two cases of CdLS with distinct phenotypes that underwent WES to aid in their diagnosis.</p>", "<title>Methods</title>", "<p id=\"Par2\">We conducted a comprehensive review of the literature on CdLS along with performing whole-exome sequencing on two CdLS patients with distinct phenotypes, followed by Sanger sequencing validation and in-silico analysis.</p>", "<title>Results</title>", "<p id=\"Par3\">The first case exhibited a classic CdLS phenotype, but the initial WES analysis of blood-derived DNA failed to identify any mutations in CdLS-related genes. However, a subsequent WES analysis of skin-derived DNA revealed a novel heterozygous mutation in the <italic>NIPBL</italic> gene (NM_133433.4:c.6534_6535del, p.Met2178Ilefs*8). The second case was presented with a non-classic CdLS phenotype, and WES analysis of blood-derived DNA identified a heterozygous missense variant in the <italic>SMC1A</italic> gene (NM_006306.4:c.2320G&gt;A, p.Asp774Asn).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The study shows the importance of considering mosaicism in classic CdLS cases and the value of WES for identifying genetic defects. These findings contribute to our understanding of CdLS genetics and underscore the need for comprehensive genetic testing to enhance the diagnosis and management of CdLS patients.</p>", "<title>Keywords</title>" ]
[ "<title>Case presentation</title>", "<title>Case 1</title>", "<p id=\"Par9\">The research subject in question is a thirteen-year-old female, born to non-consanguineous parents. Her birth occurred at 37 weeks of gestational age via cesarean section, with recorded measurements of 2950 g in weight, 48 cm in height, and a head circumference of 32 cm (Table ##TAB##0##1##). No evidence indicating maternal infection or exposure during gestation has been identified in parental interviews or documents pertaining to the pregnancy period. Both parents displayed no clinical symptoms and had no notable family history. The patient exhibited various physical characteristics at birth, including a cleft palate, long philtrum, anteverted nares, low-set ears, long curly eyelashes, a short neck, and microcephaly. At the age of three and a half, she experienced her first seizure, which persisted as uncontrolled seizures for a duration of approximately ten years. As a result, her medication regimen underwent multiple changes, with her current treatment consisting of phenobarbital and sodium valproate. Furthermore, the patient received a diagnosis of intellectual disability and displayed developmental delays, rendering her unable to walk independently even at the age of thirteen, as she could only crawl. Since birth, she has faced challenges with feeding, constipation, and severe gastroesophageal reflux. Notably, her physical examination did not reveal any abnormalities in the extremities, ruling out upper limb reduction defects. Additionally, her speech development was delayed, and she could only articulate simple words at the age of thirteen. Laboratory analysis, including complete blood count, biochemical parameters, and urinalysis, yielded normal results. A transthoracic echocardiography examination identified a mild ventricular septal defect. Chromosome analysis confirmed a normal karyotype of 46, XX.</p>", "<p id=\"Par10\">\n\n</p>", "<title>Case 2</title>", "<p id=\"Par11\">Patient 2 was a nine-year-old girl born to parents who were not closely related. The pregnancy lasted approximately 36 weeks, resulting in a birth weight of 2300 g and a head circumference of 29 cm (Table ##TAB##0##1##). The delivery was performed via cesarean section. Throughout the pregnancy, no medications were administered, and there was no exposure to cigarettes or alcohol. The patient exhibited classic craniofacial features, including micrognathia, synophrys, microcephaly, low hairline, long curly eyelashes, thin upper lips, long philtrum, depressed nasal bridge, and high arched palate. Additionally, she presented with syndactyly of the second and third toes, small hands with the thumb positioned closer to the body, and a simian crease. A transthoracic echocardiography examination revealed a mild ventricular septal defect, but no abnormalities were found in her gastroesophageal function. An electroencephalogram showed no abnormalities, and she had no history of seizures. The patient experienced failure to thrive and developmental delay. She did not begin walking until the age of four, with the assistance of occupational therapy. Her speech development was delayed, and at the age of nine, she could only articulate simple words. Chromosome analysis revealed a normal karyotype of 46, XX.</p>" ]
[ "<title>Acknowledgements</title>", "<p>Sincere gratitude to the families for their participation in this study.</p>", "<title>Author contributions</title>", "<p>STF, NM, M-RG, PM, SS, and MM were responsible for participant recruitment and clinical confirmation. STF, M-RG, FH-G, and MM conducted molecular experiments such as DNA extraction and analyzed the results derived from whole-exome sequencing (WES). The bioinformatic analyses were carried out by STF, M-RG, and FH-G. NM and STF wrote the manuscript, while M-RG, FH-G, AO, HS, RM, SK, SM, and MM contributed to the revision process. The final revision has been confirmed and essential ideas for the revision of the manuscript have been provided by all authors.</p>", "<title>Funding</title>", "<p>No external funding was used for this study.</p>", "<title>Data availability</title>", "<p>The data and materials that support the findings of this study are available from the corresponding authors, upon request.</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to participate</title>", "<p id=\"Par29\">This study It was approved by the Research Ethics Committee of Faculty of Medicine, Shahid Beheshti University of Medical Sciences (Approval Number: IR.SBMU.MSP.REC.1398.575), and was conducted in accordance with the tenets of the Declaration of Helsinki. Informed consent was obtained from adult participants to participate in the study. Written informed consent was obtained from parents of kin next of kin for all participants aged under 18.</p>", "<title>Consent for publication</title>", "<p id=\"Par30\">Informed consent for publication of identifiable information/ images in open access journal was obtained from all study participants.</p>", "<title>Competing interests</title>", "<p id=\"Par31\">The authors declare no competing interests.</p>", "<title>ClinVar Accession</title>", "<p id=\"Par32\">SCV001251685.1(<italic>SMC1A</italic>), SCV004099297(<italic>NIPBL</italic>).</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Overview of cohesin-NIPBL<sup>C</sup> -DNA complex base on PDB 6WGE. The protein is coloured by protein. SMC1, SMC3, RAD21, NIPBL, and DNA are colored Blue, yellow, purple, green, and cyan, respectively. Left arrows show structure of normal human cohesin bound to the NIPBL<sup>C</sup> and left arrows shows the structure of NIPBL<sup>C</sup> with p.Met2178Ilefs*8 mutation in the complex. NIPBL<sup>C=</sup> C-terminal HEAT repeat domain of NIPBL</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>(<bold>A</bold>) Close-up of the wild type Asp(D) and mutated Asn(N) amino acid residues at position 774 in SMC1A. The side chain of the wild-type and the mutant residue are shown and coloured green and red respectively. (<bold>B</bold>) predicted score for D774N by polyphen-2 (<bold>C</bold>) Conservation of D774 among different species</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Signs and symptoms CdLS and clinical finding of patients in this study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"3\">Signs and symptoms CdLS</th><th align=\"left\">Case 1</th><th align=\"left\">Case 2</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Growth</td><td align=\"left\">IUGR</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Short stature</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Microcephaly</td><td align=\"left\">Suggestive</td><td align=\"left\">+</td><td align=\"left\">+</td></tr><tr><td align=\"left\" rowspan=\"15\">Craniofacial features</td><td align=\"left\">Brachycephaly</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Low anterior hairline</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Arched, thick eyebrows</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Synophrys</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Long eyelashes</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">+</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Depressed nasal bridge</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Anteverted nostrils</td><td align=\"left\">Cardinal</td><td align=\"left\">+</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Broad nasal tip</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Long, smooth philtrum</td><td align=\"left\">Cardinal</td><td align=\"left\">+</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Thin upper vermilion</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Downturned corners of the mouth</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Highly arched palate</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Widely spaced teeth</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Micrognathia</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Low-set and malformed ears</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">+</td><td align=\"left\">−</td></tr><tr><td align=\"left\" rowspan=\"9\">Trunk and limbs</td><td align=\"left\">Oligodactyly and adactyly (hands)</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Small hands</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Proximally placed thumbs</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Clinodactyly or short fifth finger</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Small feet</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Hirsutism</td><td align=\"left\">Suggestive</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Cardiovascular anomalies</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">+</td><td align=\"left\">+</td></tr><tr><td align=\"left\">Vertebral anomalies</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Congenital diaphragmatic hernia</td><td align=\"left\">Cardinal</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\" rowspan=\"4\">Cognition and behaviour</td><td align=\"left\">Intellectual disability (any degree)</td><td align=\"left\">Suggestive</td><td align=\"left\">+</td><td align=\"left\">−</td></tr><tr><td align=\"left\">ASD</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Self-injurious behavior</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">−</td></tr><tr><td align=\"left\">Stereotypic movements</td><td align=\"left\">Other clinical Findings</td><td align=\"left\">−</td><td align=\"left\">−</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>ASD, autism spectrum disorder; IUGR, intrauterine growth retardation</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Sahand Tehrani Fateh and Nadia Mohammad Zadeh are equal contributors to this work and designated as co-first authors.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12920_2024_1798_Fig1_HTML\" id=\"d32e929\"/>", "<graphic xlink:href=\"12920_2024_1798_Fig2_HTML\" id=\"d32e949\"/>" ]
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[{"label": ["10."], "mixed-citation": ["Chen S, Francioli LC, Goodrich JK, Collins RL, Kanai M, Wang Q et al. A genome-wide mutational constraint map quantified from variation in 76,156 human genomes. bioRxiv. 2022:2022.03. 20.485034."]}, {"label": ["11."], "surname": ["Green", "Berg", "Grody", "Kalia", "Korf", "Martin"], "given-names": ["RC", "JS", "WW", "SS", "BR", "CL"], "article-title": ["ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing"], "source": ["Genet Sci"], "year": ["2013"], "volume": ["15"], "issue": ["7"], "fpage": ["565"], "lpage": ["74"]}, {"label": ["14."], "surname": ["De Lange"], "given-names": ["C"], "article-title": ["Surun type nouveau degeneration (typus amestelodamensis)"], "source": ["Arch Med Enfants"], "year": ["1933"], "volume": ["36"], "fpage": ["713"], "lpage": ["9"]}, {"label": ["21."], "surname": ["Hoppman-Chaney", "Jang", "Jen", "Babovic\u2010Vuksanovic", "Hodge"], "given-names": ["N", "JS", "J", "D", "JC"], "article-title": ["In\u2010frame multi\u2010exon deletion of SMC1A in a severely affected female with Cornelia De Lange Syndrome"], "source": ["Am J Med Genet Part A"], "year": ["2012"], "volume": ["158"], "issue": ["1"], "fpage": ["193"], "lpage": ["8"], "pub-id": ["10.1002/ajmg.a.34360"]}]
{ "acronym": [ "CdLS", "BWA", "GATK", "ACMG", "TADs", "NGS" ], "definition": [ "Cornelia de Lange Syndrome", "Burrows-Wheeler Aligner", "Genome Analysis Toolkit", "American College of Medical Genetics", "topologically associated domains", "next-generation sequencing" ] }
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2024-01-14 23:43:46
BMC Med Genomics. 2024 Jan 12; 17:20
oa_package/12/9c/PMC10787426.tar.gz
PMC10787427
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[ "<p id=\"Par1\">\n<bold>Correction: Arthritis Res Ther 25, 249 (2023)</bold>\n</p>", "<p id=\"Par2\">\n<bold>https://doi.org/10.1186/s13075-023-03230-4</bold>\n</p>", "<p id=\"Par3\">Following publication of the original article [##REF##38124066##1##], the authors reported that the following Equal Contribution note was missing in the article “Changchuan Li, Zhuji Ouyang and Yuhsi Huang contributed equally to this paper and should be listed as co-first authors”.</p>", "<p id=\"Par4\">The original article [##REF##38124066##1##] has been updated.</p>" ]
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[ "<fn-group><fn><p>Changchuan Li, Zhuji Ouyang and Yuhsi Huang contributed equally to this paper and should be listed as co-first authors.</p></fn></fn-group>" ]
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{ "acronym": [], "definition": [] }
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CC BY
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2024-01-14 23:43:46
Arthritis Res Ther. 2024 Jan 13; 26:22
oa_package/28/04/PMC10787427.tar.gz
PMC10787428
0
[ "<title>Background</title>", "<p id=\"Par5\">Lumbar Herniated Intervertebral Disc (HIVD) is among the most prevalent types of spinal degenerative disorders causing low back pain accompanied by radiculopathy, accounting for approximately two-thirds of spinal pain diagnoses [##REF##33414495##1##–##REF##28660102##3##]. The intervertebral disc is composed of the inner nucleus pulposus (NP) and the outer annulus fibrosus (AF), with HIVD referring to the displacement of the inner disc material NP beyond the disc space limits and the rupture of AF [##REF##20421859##4##]. Two main treatment approaches are surgical and conservative, with surgery often favored for better short- and medium-term outcomes in pain reduction and functional disability improvement [##REF##28980275##5##], due to which an increasing number of patients with HIVD receive surgery [##REF##23023591##6##, ##REF##31408926##7##].</p>", "<p id=\"Par6\">Lumbar spine surgery types include open discectomy (OD), laminectomy, percutaneous endoscopic lumbar discectomy (PELD), spinal fusion, and nucleolysis [##REF##28715939##8##]. In a previous study, OD was the most common procedure followed by endoscopic discectomy [##REF##23023591##6##], known for its effectiveness in pain relief and neurological function restoration. However, it can cause muscle damage, scarring, and spinal instability from nerve retraction [##REF##27001138##9##, ##REF##27260312##10##]. PELD, on the other hand, offers advantages such as shorter operation times, reduced hospital stays, and less hemorrhage [##REF##27260312##10##, ##REF##24583364##11##]. For these reasons, some studies recommend PELD as an alternative to OD [##UREF##0##12##, ##REF##11923665##13##]. Laminectomy and spinal fusion are also used, but they carry risks of multiple sclerosis, chronic low back pain, and nerve damage [##UREF##1##14##, ##REF##26555839##15##].</p>", "<p id=\"Par7\">Despite surgical advancements, postoperative pain remains a significant concern, with many patients experiencing moderate pain 6 months after surgery. There is yet no established standard for prescribing analgesics following spinal surgery [##REF##35528286##16##]. Morphine was previously commonly used in clinical practice for pain management [##REF##27673505##17##, ##REF##7643992##18##]; however due to complications like nausea, vomiting, pruritus, and hypotension, efforts have been made to reduce morphine consumption [##REF##23711600##19##, ##UREF##2##20##]. The type and dose of analgesics vary, with PELD showing promise in short-term preoperative back pain relief [##UREF##3##21##]. Apart from medical outcomes, surgery also incurs various social costs such as productivity loss and reduced quality of life of patients. Minimizing surgery-induced hospital stays can contribute to patients’ improved psychological well-being and quality of life [##UREF##4##22##].</p>", "<p id=\"Par8\">Previous study focused on the incidence of OD and PELD [##REF##31408926##7##], but few studies have investigated postoperative medication trends and the duration of the recovery period. This study aims to fill this gap by analyzing 10-year claims data (2010–2019) from the Health Insurance Review and Assessment Service (HIRA) to examine type of lumbar surgery for HIVD, changes in opioid analgesic prescriptions, and postoperative hospital stay durations by surgery type.</p>" ]
[ "<title>Methods</title>", "<title>Data collection</title>", "<p id=\"Par9\">This study analyzed claims data provided by the Health Insurance Review and Assessment Service (HIRA), specifically the HIRA-National Patient Sample (HIRA-NPS) data spanning from January 2010 to December 2019. The HIRA-NPS is a 2% sample (approximately 1,000,000 individuals) annually selected through sex-stratified (two categories) and age-stratified (16 categories) random sampling from the 98% of the Korean population enrolled in the National Health Insurance (NHI) program. The provided data de-identified any personally identifiable information and include treatment and prescription data based on NHI claims.</p>", "<title>Study design and population</title>", "<p id=\"Par10\">This retrospective cross-sectional study examined patients who made one or more NHI claims with HIVD (ICD-10 code: M511, M518, M519) as the primary or secondary diagnosis over a 10-year period (2010–2019). From this sample, we selected adult patients, aged 20 years or older, who sought care at various medical institutions, including tertiary hospitals, general hospitals, clinics, Korean medicine (KM) hospitals, and KM clinics. Only those with complete data for the study variables were included. Moreover, those who did not require reoperation within 30 days following the initial lumbar surgery were selected. Ultimately, the patients who underwent only one type of surgery among the surgical options considered in this study were finally selected for the study.</p>", "<title>Study outcomes</title>", "<p id=\"Par11\">In this study, we analyzed the baseline characteristics of patients, including age, sex, and payer type (Table ##TAB##0##1##). The age category was stratified into six groups, each representing a 10-year increment for adults aged 20 years or older. The surgical treatment type (“Surgery type”) for HIVD was classified into OD, laminectomy, PELD, and spinal fusion, and we examined the annual trends in the number and percentage of each surgery type. We categorized prescribed medications during inpatient and outpatient care, including the day of surgery, according to the Anatomical Therapeutic Chemical (ATC) classification system, and investigated the yearly trends of the number and percentage of patients prescribed each medication (Additional Table ##SUPPL##1##1##). Among the different medications, opioid analgesics were further divided into strong opioids, weak opioids, and tramadol, and the usage rate for each category was calculated by surgery type. Finally, we also examined trends in hospital stay duration, considered as the recovery period from surgery completion to return to daily routine, by surgery type.</p>", "<p id=\"Par12\">\n\n</p>", "<title>Statistical analysis</title>", "<p id=\"Par13\">We employed descriptive statistical analysis for data examination in this study. To present the data for baseline patient characteristics, number of patients by lumbar spine surgery type, number of patients by medication category, and the number of patients prescribed each category of opioid analgesics according to surgery type, we used the applicable number of patients and percentages relative to the total patient number. The yearly trends in lumbar surgery types, use of prescribed medications, and opioids prescription by surgery type were illustrated using graphs. The length of hospital stay by surgery type was presented using mean and standard deviation (SD). Furthermore, subgroup analyses were conducted by sex and age groups (Younger adults below 40 years of age vs. Older adults more than 40 years of age). Calculations and graph creation were performed using the statistical software suite SAS (version 9.4, SAS Institute, Cary, NC, USA).</p>", "<title>Ethical considerations</title>", "<p id=\"Par14\">This study protocol received approval from the public data provision deliberation committee in the HIRA and adhered to relevant guidelines and regulations. The current study was reviewed by the Institutional Review Board of Jaseng Hospital of Korean Medicine, Seoul, Korea (IRB file No. JASENG 2022-12-008), and the need for consent was waived. As the study analyzed publicly available data, no consent was obtained from the individuals whose data was included; all personal information had been de-identified by the NHIS prior to public release. All analyses performed adhered to the principles outlined in the Declaration of Helsinki.</p>" ]
[ "<title>Results</title>", "<title>Characteristic of patients</title>", "<p id=\"Par15\">After the patient selection process, 7741 patients were included in this study (Fig. ##FIG##0##1##). Regarding the demographic characteristics of the study sample, the age group 40–49 years accounted for highest proportion of patients, followed by the groups 50–59 and 30–39 years. Overall, more male patients were observed compared to female patients, with men making up 56.67% of the total sample. In terms of payer type, almost all patients were covered by the NHI program, accounting for 96.62%. There was no specific noticeable pattens in the yearly trends in the number of patients during the study period. In relation to the surgical treatments received by the patients in this study, OD had the highest ratio, constituting 84.33% of the surgeries. This was followed by laminectomy at 9.66% and PELD at 5.09%. Spinal fusion was rarely performed alone, accounting for only 0.92% over the study period. Regarding the trends in the type of medical institutions, surgery for HIVD was most commonly carried out in hospital-level medical institutions (79.77%), followed by general hospitals, tertiary hospitals, and clinic-level institutions (Table ##TAB##0##1##).</p>", "<p id=\"Par34\">\n\n</p>", "<title>Trends in surgical treatment</title>", "<p id=\"Par16\">Figure ##FIG##1##2## illustrates a 10-year trend in the proportion of patients who underwent each of the four types of lumbar spine surgery considered in this study. OD was the most common surgery performed throughout the studied decade. However, its proportion started to decline from 2017, reaching its lowest point in 2018 at 69.9%. Laminectomy’s proportion remained stable from 2010 to 2017, but slightly increased to 15.6% in 2018. PELD accounted for a small percentage of approximately 1–3%, but the ratio gradually increased from 3.5% in 2016 to 12.6% in 2019, similar to that of laminectomy. Without much change, spinal fusion remained low at around 0.01% (Additional Table ##SUPPL##0##2##).</p>", "<p id=\"Par35\">\n\n</p>", "<title>Opioid prescription</title>", "<p id=\"Par18\">The majority of medications prescribed for 1 month (including the day of surgery) for patients who underwent surgery after the diagnosis of HIVD did not show any particular trend over the 10-year period. However, opioid prescriptions saw a steady increase, from about 78% in 2010 to 94% in 2019 (Additional Table ##SUPPL##2##3##). Among the types of opioid analgesics, strong opioids and tramadol were predominantly prescribed with a similar trend. The proportion of patients prescribed strong opioids decreased slightly from 50.7% in 2010 to 49.3% in 2011, but subsequently increased to 77.8% in 2019. Tramadol prescriptions also saw an overall increase from 50.9% in 2010 to 76.8% in 2019. In contrast, weak opioids represented less than 1% of total prescriptions over the decade (2010–2019) (Fig. ##FIG##2##3##).</p>", "<p id=\"Par36\">\n\n</p>", "<p id=\"Par20\">Considering the trends in opioid prescriptions (including the day of surgery) by surgery type, the prescription rates were similar across laminectomy, OD, and PELD. Among these, strong opioids were prescribed for 64.8% of those who underwent laminectomy, 65.6% for OD, and 61.9% for PELD. Tramadol was prescribed for 66.3% of laminectomy patients, 68% for OD, and 66.5% for PELD. Weak opioids were prescribed for 6.6% of laminectomy patients, 6% for OD, and 8.6% for PELD. However, for spinal fusion, strong opioids were prescribed for 80.3% of patients, weak opioids for 19.7%, and tramadol for 78.9%, showing a comparatively high overall prescription of opioids compared to that for other three surgery types (Table ##TAB##1##2##). Subgroup analysis did not show differences in the prescription rates by sex (Additional Table ##SUPPL##4##4##) or age group (Additional Table ##SUPPL##3##5##).</p>", "<p id=\"Par17\">\n\n</p>", "<title>Hospital stay</title>", "<p id=\"Par21\">A 10-year trend analysis of the length of hospital stay by surgery type revealed that the average duration of hospital stay for all 6528 surgeries was roughly 13.6 days (SD = 8.95 days). Laminectomy, the second most performed surgery with 748 cases, had an average hospital stay of about 13.0 days (SD = 8.40 days), without a significant difference compared to OD. PELD, a relatively less invasive surgery, had the shortest average hospital stay of 7.04 days (SD = 6.78 days) for a total of 394 surgeries. In contrast, spinal fusion, which involves inserting metallic hardware into the body, had the longest average hospital stay of 20.14 days (SD = 12.18 days) for a total of 71 surgeries (Table ##TAB##2##3##). Subgroup analysis showed that females stayed slightly longer compared to male in all types of surgery (Additional Table ##SUPPL##5##6##), and differences in the duration of hospital stay by age group was not observed (Additional Table ##SUPPL##6##7##).</p>", "<p id=\"Par19\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par22\">In this study, we used claims data from 2010 to 2019 provided by HIRA to explore the recent 10-year trends in the types of lumbar surgeries performed on patients diagnosed with HIVD. We also examined changes in the prescription of opioid analgesics and the length of postoperative hospital stay according to surgery type. During the 10-year period, OD accounted for the highest proportion of lumbar surgeries, with PELD showing an increasing trend in more recent 4 years. The prescription of strong opioids and tramadol demonstrated an overall upward trend. Spinal fusion had a higher opioid prescription rate compared to other surgery types. Moreover, the postoperative length of hospital stay varied by surgery type, with spinal fusion requiring the longest hospital stay.</p>", "<p id=\"Par23\">In the United States, the number of spinal surgeries for lumbar degenerative disc disease increased 2.4 times between 2000 and 2009. However, the number of lumbar spine surgeries began to decline after 2010. From 2003 to 2013, the number of lumbar discectomies and laminectomies decreased by 19.8% and 26.1%, respectively, while spinal fusion increased by 56.4% [##REF##28660102##3##]. In Korea, from 2003 to 2008, OD was the most common surgery type for patients with lumbar disc herniation, and its proportion increased from 71.21 to 84.12% during this period. On the other hand, PELD decreased from about 16.68–4.57% during the same period. Spinal fusion saw an increase from 3.97 to 6.61% during the same period [##REF##29095409##23##]. In the present study, which is based on the analysis of relatively recent data, OD was the most common type of lumbar surgery for the 10-year study period but began to decrease from 2017.</p>", "<p id=\"Par24\">PELD, showing the most discrepancy between this study and previous studies, has shown the most advancement in terms of technique over the last 10 years as of 2020 [##REF##32013278##24##]. Compared to OD, PELD offers shorter recovery time, faster back pain improvement, and generally fewer complications [##REF##32683107##25##]. However, the learning curve for PELD is steep, and surgeons with insufficient training are likely to face incomplete decompression [##REF##32683107##25##, ##REF##33989822##26##]. Therefore, with technical advancement and skill improvement over time, it is expected that PELD will be more frequently performed among the surgery types, as demonstrated by the present results. However, despite the aforementioned advantages of PELD, there are still conflicting reports that OD yields superior clinical results [##UREF##5##27##]. In this study, spinal fusion accounted for only a very small proportion of approximately 1% among the surgery types. The considerable difference in proportion of spinal fusion performed in this study and previous studies is believed to be due to the difference in how the surgery is performed in practice; in many cases, spinal fusion is performed along with laminectomy or OD, but in this study, we only included cases where one type of surgery was performed.</p>", "<p id=\"Par25\">According to Jarebi, M. et al., the PELD group had a shorter hospital stay (2.55 ± 1.78 days) compared to the open lumbar microdiscectomy (OLMD) group (3.21 ± 1.26 days; <italic>p</italic> &lt; 0.037) [##REF##32683107##25##]. Moreover, Ahn.S.S et al. reported a shorter hospital stay in the PELD group (7.50 ± 2.63) than in the OLMD group (15.65 ± 4.80, <italic>p</italic> &lt; 0.001). Compared to OLMD, PELD is considered superior in terms of duration of hospital stay and work resumption because PELD has a shorter operation time and causes less intraoperative tissue damage than OLMD [##REF##27260312##10##]. Despite the overall duration of hospital stay in this study being longer compared with that in previous studies due to healthcare service environment differences, the patients who underwent PELD in our study had a relatively shorter hospital stay than those who underwent OD.</p>", "<p id=\"Par26\">In a past study using MarketScan claims data in the US, approximately 23% of patients who underwent lumbar discectomy from 2010 to 2015 used opioids. However, it is noteworthy that in 2010, about 27% of the patients used opioids, but this proportion decreased considerably to about 17% in 2015. Additionally, the use of high-dose opioids decreased from 59% in 2010 to 43% in 2015, and that of very high-dose opioids decreased from 26% in 2010 to 19% in 2015 [##REF##33401866##28##]. Although there is no comparable study on opioid prescription after lumbar surgery in Korea, the total number of opioid prescriptions in Korea displayed a consistent increasing trend, from approximately 17 million cases in 2009 to 27 million cases in 2019. The rate per 1,000 persons of total opioid prescriptions also continued to increase over the last 11 years, from 347.5 in 2009 to 531.3 in 2019 [##REF##33979378##29##]. In this study based on NHI claims data from Korea, the rates of prescribing strong opioids and tramadol during and after surgery increased with similar trend from 50.7% to 50.9% in 2010 to 77.8% and 76.8% in 2019, respectively.</p>", "<p id=\"Par27\">The analysis of opioid prescription rates across different types of surgery revealed that patients undergoing laminectomy, OD, and PELD were prescribed opioids in comparable patterns. In contrast, those receiving spinal fusion exhibited significantly higher prescription rates for strong opioids, weak opioids, and tramadol. Gender-based examination indicated that male patients consistently had higher opioid prescription rates across all categories. Age-wise, younger patients undergoing spinal fusion were notably prescribed more strong opioids, weak opioids, and tramadol. It is important to note that the subset of patients undergoing only spinal fusion was relatively small. Consequently, generalizing these findings requires caution, and additional research is imperative to better understand the influence of spinal fusion surgery types on opioid prescription trends.</p>", "<p id=\"Par28\">The escalating opioid crisis in the United States, which is increasingly gaining global attention [##UREF##6##30##, ##REF##35639699##31##], underscores the importance of this study. Prior research has indicated an elevated risk of chronic opioid use among post-surgical patients [##REF##29049117##32##, ##REF##31073685##33##]. In this context, our study aimed to evaluate the patterns of opioid prescriptions, including strong and weak opioids as well as tramadol, in patients post-lumbar disc herniation surgery, providing insights into their overall exposure to these medications. However, the cross-sectional nature of the data limits the ability to investigate the relationship between opioid prescription patterns and the duration of hospital stays. Thus, further research is essential to explore this aspect more comprehensively.</p>", "<p id=\"Par29\">In Korea, a more detailed treatment strategy for opioid prescription is needed. Currently, opioid use in Korea is governed by the Standards for Safe Use of Narcotic Analgesics issued by the Ministry of Food and Drug Safety; however, strategies for different treatment types have not been established yet. Moreover, these standards do not include tramadol, which should be addressed in future updates. Conversely, in the United States, where opioid prescriptions kept increasing until the early- and mid-2010s, efforts have been made to reduce opioid consumption through the development of the SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects) model, prescription drug monitoring programs (PDMPs), and various regulations [##UREF##6##30##, ##REF##35639699##31##]. Similarly, in Korea, where opioid prescriptions have shown an overall increasing trend, there is an urgent need for active discussions on the development of a more specific model for opioid prescription strategy for postoperative pain management.</p>", "<title>Strength &amp; limitation</title>", "<p id=\"Par30\">In the present study, the sample utilized is representative as it used the claims data (HIRA-NPS) sampled from the national population of Korea. The study’s strength lies in examining the recent 10-year trends and healthcare utilization by the type of lumbar surgery performed on patients diagnosed with lumbar HIVD, encompassing patients across all adult age groups over 20 years of age based on age strata provided by the data source. However, this study has several limitations. First, among patients diagnosed with HIVD and those who underwent surgical treatment, all cases that underwent reoperation or required two or more types of lumbar surgeries were excluded based on NHI claims of the applicable year. This could have led to underestimation of the number of patients, prescription of pain medications, or the length of hospital stay. Second, retrieving previous treatment history of the patients was difficult in the study sample as data sources divided by year were used, and follow-up monitoring for long-term use of opioids after surgery was not possible. Third, this study’s data source comprised NHI claims; thus, surgeries not covered by NHI were not included in the analysis. Furthermore, the categorization of certain surgery codes, such as open discectomy, which encompassed both open microdiscectomy and tubular retractor assisted microdiscectomy, was too broad to capture the potential differences that clinicians would have been interested in. Additionally, since there was no information on patient-reported pain scores or quality-of-life, it was not possible to compare the prognosis of surgery in a practical sense. Fourth, only patients who underwent one type of surgery were selected for analysis. However, lumbar fusion is often performed along with OD or laminectomy, but such cases were not considered in this study. Therefore, careful interpretation is required for further generalization of results obtained in this study.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par31\">This comprehensive study, utilizing claims data from HIRA spanning 2010 to 2019, has provided valuable insights into the evolving trends in lumbar surgery types and opioid prescription patterns for patients diagnosed with HIVD in Korea. Our findings indicate that OD remained the most prevalent surgery type throughout the decade, although its frequency began to decline from 2017 onwards. In contrast, PELD showed a notable increase in recent years, likely due to advancements in surgical techniques and its benefits in terms of recovery time and complications. The study highlighted a significant increase in the prescription of strong opioids and tramadol, particularly in spinal fusion cases, which also necessitated longer hospital stays. This trend was more pronounced in younger patients and males, suggesting demographic variations in postoperative pain management strategies. These findings are particularly relevant in the context of the global opioid crisis and the increasing focus on post-surgical pain management. Comparisons with international data, particularly from the United States, reveal some differences in surgical practices and opioid prescription patterns. These differences underscore the need for a more tailored approach to opioid prescription in postoperative pain management in Korea, considering the rising trend in opioid prescriptions. While this study sheds light on important trends in lumbar surgery and opioid prescription in Korea, it also highlights the need for ongoing research and the development of more nuanced strategies for opioid prescription and pain management in post-surgical care. With the global focus on the opioid crisis, such research is crucial for informing healthcare policies and clinical practices that prioritize patient safety and effective pain management.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">This study, utilizing the claims data from the Health Insurance Review and Assessment Service of Korea, aimed to examine the 10-year (2010–2019) trends in various types of lumbar spine surgeries performed on patients diagnosed with lumbar herniated intervertebral disc (HIVD), and the current status of opioid prescriptions, as well as the duration of postoperative hospital stays based on the type of surgery performed.</p>", "<title>Method</title>", "<p id=\"Par2\">This retrospective cross-sectional study examined patients with one or more national health insurance claims carrying a primary or secondary diagnosis of HIVD (ICD-10 codes: M511, M518, M519) over a 10-year period (2010–2019). From the patients undergoing lumbar spine surgery, we selected those who did not require reoperation within 30 days following the initial lumbar surgery. Our final study sample comprised patients who underwent only one type of surgery.</p>", "<title>Results</title>", "<p id=\"Par3\">Among the patients diagnosed with HIVD and subsequently undergoing lumbar surgery between 2010 and 2019, a slight downward trend was observed in those undergoing open discectomy (OD); however, OD persistently accounted for the highest proportion over the 10 years. Percutaneous endoscopic lumbar discectomy (PELD) demonstrated a consistent upward trend from 2016 to 2018. When inspecting trends, we noted a consistent escalation over the decade in the postoperative opioid prescription rates of strong opioids (50.7% in 2010 to 77.8% in 2019) and tramadol (50.9% in 2010 to 76.8% in 2019). Analyzing these trends by surgery type, spinal fusion exhibited a slightly higher rate of opioid prescriptions than other lumbar surgeries. Regarding the length of postoperative hospital stays, patients undergoing PELD recorded the shortest stay (7.04 ± 6.78 days), while spinal fusion necessitated the longest (20.14 ± 12.18 days).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">This study analyzed the trends in types of lumbar spine surgeries, opioid analgesic prescriptions, and length of hospital stays over 10 years (2010–2019) among patients with HIVD in Korea. Our data and findings provide valuable evidence that may prove beneficial for clinicians and researchers involved in HIVD-related practices.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12891-024-07167-w.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>Study design, conception: S.Y.K., Y.-C.L., Y.-S.L, and Y.J.L; Analysis: Y.-C.L.; Editing and critical revision: B.-K.S., D.N., I.-H.H., Y.-S.L, and Y.J.L; interpretation of data: S.Y.K.; Literature search and drafting of manuscript: S.Y.K.; All authors read and approved the final version of the manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by the Korea Health Technology R&amp;D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health and Welfare, Republic of Korea (grant no. HF21C0111). The funders had no role in any part of this study.</p>", "<title>Data availability</title>", "<p>The datasets analyzed in the current study are available upon authorization by the inquiry committee of research support within HIRA. The Patient Samples are provided in a DVD (text file) format, and a fee is charged for the samples. <ext-link ext-link-type=\"uri\" xlink:href=\"https://opendata.hira.or.kr/home.do\">https://opendata.hira.or.kr/home.do</ext-link> (accessed on 10 July 2023). The contact person for inquiries regarding this data is Ye-Seul Lee.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par41\">This study protocol received approval from the public data provision deliberation committee in the HIRA and adhered to relevant guidelines and regulations. The current study was reviewed by the Institutional Review Board of Jaseng Hospital of Korean Medicine, Seoul, Korea (IRB file No. JASENG 2022-12-008) and the need for consent was waived. As the study analyzed publicly available data, no consent was obtained from the individuals whose data was included; all personal information had been de-identified by the NHIS prior to public release. All analyses performed adhered to the principles outlined in the Declaration of Helsinki.</p>", "<title>Consent for publication</title>", "<p id=\"Par42\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par40\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Study patients selection</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Trends of lumbar surgeries</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Trends of prescribed opioid analgesics after lumbar surgery. <bold>A</bold>: Number of patients prescribed opioid analgesics (by categories); <bold>B</bold>: Percentage of patients prescribed opioid analgesics (by categories)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"2\">Category</th><th align=\"left\" colspan=\"2\">Total (<italic>n</italic> = 7,741)</th></tr><tr><th align=\"left\">N</th><th align=\"left\">Percentage</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"6\">Age (years)</td><td align=\"left\">20–29</td><td align=\"left\">861</td><td align=\"left\">11.12</td></tr><tr><td align=\"left\">30–39</td><td align=\"left\">1491</td><td align=\"left\">19.26</td></tr><tr><td align=\"left\">40–49</td><td align=\"left\">1828</td><td align=\"left\">23.61</td></tr><tr><td align=\"left\">50–59</td><td align=\"left\">1755</td><td align=\"left\">22.67</td></tr><tr><td align=\"left\">60–69</td><td align=\"left\">1298</td><td align=\"left\">16.77</td></tr><tr><td align=\"left\">70–</td><td align=\"left\">508</td><td align=\"left\">6.56</td></tr><tr><td align=\"left\" rowspan=\"2\">Gender</td><td align=\"left\">Male</td><td align=\"left\">4387</td><td align=\"left\">56.67</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">3354</td><td align=\"left\">43.33</td></tr><tr><td align=\"left\" rowspan=\"3\">Payer type</td><td align=\"left\">NHI</td><td align=\"left\">7479</td><td align=\"left\">96.62</td></tr><tr><td align=\"left\">Medicaid</td><td align=\"left\">257</td><td align=\"left\">3.32</td></tr><tr><td align=\"left\">Others</td><td align=\"left\">5</td><td align=\"left\">0.06</td></tr><tr><td align=\"left\" rowspan=\"4\">Surgery type</td><td align=\"left\">OD</td><td align=\"left\">6528</td><td align=\"left\">84.33</td></tr><tr><td align=\"left\">Laminectomy</td><td align=\"left\">748</td><td align=\"left\">9.66</td></tr><tr><td align=\"left\">PELD</td><td align=\"left\">394</td><td align=\"left\">5.09</td></tr><tr><td align=\"left\">Spinal fusion</td><td align=\"left\">71</td><td align=\"left\">0.92</td></tr><tr><td align=\"left\" rowspan=\"4\">Surgery medical institution</td><td align=\"left\">Tertiary hospital</td><td align=\"left\">214</td><td align=\"left\">2.76</td></tr><tr><td align=\"left\">General hospital</td><td align=\"left\">1180</td><td align=\"left\">15.24</td></tr><tr><td align=\"left\">Hospital</td><td align=\"left\">6175</td><td align=\"left\">79.77</td></tr><tr><td align=\"left\">Clinic</td><td align=\"left\">172</td><td align=\"left\">2.22</td></tr><tr><td align=\"left\" rowspan=\"10\">Year of surgery</td><td align=\"left\">2010</td><td align=\"left\">802</td><td align=\"left\">10.36</td></tr><tr><td align=\"left\">2011</td><td align=\"left\">747</td><td align=\"left\">9.65</td></tr><tr><td align=\"left\">2012</td><td align=\"left\">890</td><td align=\"left\">11.50</td></tr><tr><td align=\"left\">2013</td><td align=\"left\">815</td><td align=\"left\">10.53</td></tr><tr><td align=\"left\">2014</td><td align=\"left\">794</td><td align=\"left\">10.26</td></tr><tr><td align=\"left\">2015</td><td align=\"left\">702</td><td align=\"left\">9.07</td></tr><tr><td align=\"left\">2016</td><td align=\"left\">684</td><td align=\"left\">8.84</td></tr><tr><td align=\"left\">2017</td><td align=\"left\">733</td><td align=\"left\">9.47</td></tr><tr><td align=\"left\">2018</td><td align=\"left\">790</td><td align=\"left\">10.21</td></tr><tr><td align=\"left\">2019</td><td align=\"left\">784</td><td align=\"left\">10.13</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Prescribed opioid analgesics after lumbar surgery</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Category</th><th align=\"left\">Laminectomy <break/><italic>n</italic> = 748</th><th align=\"left\">OD <break/><italic>n</italic> = 6528</th><th align=\"left\">PELD <break/><italic>n</italic> = 394</th><th align=\"left\">Spinal fusion<break/><italic>n</italic> = 71</th></tr></thead><tbody><tr><td align=\"left\">Strong opioids, n (%)</td><td align=\"left\">485 (64.84)</td><td align=\"left\">4280 (65.56)</td><td align=\"left\">244 (61.93)</td><td align=\"left\">57 (80.28)</td></tr><tr><td align=\"left\">Weak opioids, n (%)</td><td align=\"left\">49 (6.55)</td><td align=\"left\">390 (5.97)</td><td align=\"left\">34 (8.63)</td><td align=\"left\">14 (19.72)</td></tr><tr><td align=\"left\">Tramadol, n (%)</td><td align=\"left\">496 (66.31)</td><td align=\"left\">4438 (67.98)</td><td align=\"left\">262 (66.50)</td><td align=\"left\">56 (78.87)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Duration of hospital stay after lumbar surgery</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Inpatient days (day)</th><th align=\"left\">Laminectomy</th><th align=\"left\">OD</th><th align=\"left\">PELD</th><th align=\"left\">Spinal fusion</th></tr></thead><tbody><tr><td align=\"left\">Mean (SD)</td><td align=\"left\">13.03 (8.40)</td><td align=\"left\">13.61 (8.96)</td><td align=\"left\">7.04 (6.78)</td><td align=\"left\">20.14 (12.18)</td></tr><tr><td align=\"left\">1–5, n (%)</td><td align=\"left\">104 (13.90)</td><td align=\"left\">603 (9.24)</td><td align=\"left\">219 (55.58)</td><td align=\"left\">00 (0.00)</td></tr><tr><td align=\"left\">6–10</td><td align=\"left\">244 (32.62)</td><td align=\"left\">2332 (35.72)</td><td align=\"left\">109 (27.66)</td><td align=\"left\">10 (14.08)</td></tr><tr><td align=\"left\">11–15</td><td align=\"left\">194 (25.94)</td><td align=\"left\">1731 (26.52)</td><td align=\"left\">29 (7.36)</td><td align=\"left\">18 (25.35)</td></tr><tr><td align=\"left\">16–20</td><td align=\"left\">95 (12.70)</td><td align=\"left\">901 (13.80)</td><td align=\"left\">17 (4.31)</td><td align=\"left\">22 (30.99)</td></tr><tr><td align=\"left\">21–</td><td align=\"left\">111 (14.84)</td><td align=\"left\">961 (14.72)</td><td align=\"left\">20 (5.08)</td><td align=\"left\">21 (29.58)</td></tr></tbody></table></table-wrap>" ]
[]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM5\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM6\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM7\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12891_2024_7167_Fig1_HTML\" id=\"d32e689\"/>", "<graphic xlink:href=\"12891_2024_7167_Fig2_HTML\" id=\"d32e709\"/>", "<graphic xlink:href=\"12891_2024_7167_Fig3_HTML\" id=\"d32e736\"/>" ]
[ "<media xlink:href=\"12891_2024_7167_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>", "<media xlink:href=\"12891_2024_7167_MOESM2_ESM.docx\"><caption><p>Supplementary Material 2</p></caption></media>", "<media xlink:href=\"12891_2024_7167_MOESM3_ESM.docx\"><caption><p>Supplementary Material 3</p></caption></media>", "<media xlink:href=\"12891_2024_7167_MOESM4_ESM.docx\"><caption><p>Supplementary Material 4</p></caption></media>", "<media xlink:href=\"12891_2024_7167_MOESM5_ESM.docx\"><caption><p>Supplementary Material 5</p></caption></media>", "<media xlink:href=\"12891_2024_7167_MOESM6_ESM.docx\"><caption><p>Supplementary Material 6</p></caption></media>", "<media xlink:href=\"12891_2024_7167_MOESM7_ESM.docx\"><caption><p>Supplementary Material 7</p></caption></media>" ]
[{"label": ["12."], "surname": ["Kambin", "Savitz"], "given-names": ["P", "MH"], "italic": ["Arthroscopic microdiscectomy: an alternative to open disc surgery"], "source": ["New York"], "year": ["2000"], "volume": ["67"], "issue": ["4"], "fpage": ["283"], "lpage": ["7"]}, {"label": ["14."], "surname": ["Eck", "Hodges", "Humphreys"], "given-names": ["JC", "S", "SC"], "article-title": ["Minimally invasive lumbar spinal fusion"], "source": ["JAAOS-Journal of the American Academy of Orthopaedic Surgeons"], "year": ["2007"], "volume": ["15"], "issue": ["6"], "fpage": ["321"], "lpage": ["9"], "pub-id": ["10.5435/00124635-200706000-00001"]}, {"label": ["20."], "mixed-citation": ["Peng C et al. "], "italic": ["Gabapentin can decrease acute pain and morphine consumption in spinal surgery patients: a meta-analysis of randomized controlled trials"]}, {"label": ["21."], "mixed-citation": ["Zhu W et al. "], "italic": ["Short-Term Postoperative Pain and Function of Unilateral Biportal Endoscopic Discectomy versus Percutaneous Endoscopic Lumbar Discectomy for Single-Segment Lumbar Disc Herniation: A Systematic Review and Meta-analysis"]}, {"label": ["22."], "surname": ["Damiani"], "given-names": ["G"], "article-title": ["The short stay unit as a new option for hospitals: a review of the scientific literature"], "source": ["Med Sci Monitor: Int Med J Experimental Clin Res"], "year": ["2011"], "volume": ["17"], "issue": ["6"], "fpage": ["SR15"], "pub-id": ["10.12659/MSM.881791"]}, {"label": ["27."], "mixed-citation": ["Kim M et al. "], "italic": ["A comparison of percutaneous endoscopic lumbar discectomy and open lumbar microdiscectomy for lumbar disc herniation in the Korean: a meta-analysis"]}, {"label": ["30."], "surname": ["Chisholm-Burns"], "given-names": ["MA"], "article-title": ["The opioid crisis: origins, trends, policies, and the roles of pharmacists"], "source": ["Am J health-system Pharm"], "year": ["2019"], "volume": ["76"], "issue": ["7"], "fpage": ["424"], "lpage": ["35"], "pub-id": ["10.1093/ajhp/zxy089"]}]
{ "acronym": [ "HIVD", "ICD", "OD", "PELD", "SD", "NP", "AF", "HIRA", "NPS", "NHI", "OLMD", "SOURCE", "PDMPs" ], "definition": [ "Lumbar Herniated Intervertebral Disc", "10-International Classification of Diseases, 10th Revision", "Open Discectomy", "Percutaneous Endoscopic Lumbar Discectomy", "Standard Deviation", "Nucleus Pulposus", "Annulus Fibrosus", "Health Insurance Review and Assessment Service", "National Patient Sample", "National Health Insurance", "Open Lumbar Microdiscectomy", "Simulation of Opioid Use, Response, Consequences, and Effects", "Prescription Drug Monitoring Programs" ] }
33
CC BY
no
2024-01-14 23:43:46
BMC Musculoskelet Disord. 2024 Jan 13; 25:65
oa_package/5d/eb/PMC10787428.tar.gz
PMC10787429
0
[ "<title>Background</title>", "<p id=\"Par5\">With the development of society, sitting posture has become the primary position for human learning, living, and working. sitting posture exerts greater pressure on the lumbar spine, making it more susceptible to degenerative changes and subsequently leading to lower back pain [##REF##37447741##1##–##REF##31513435##5##]. Studying the movement patterns of lumbar spine during sitting can further enhance our understanding of the characteristics of lumbar spine motion. The facet joints, as a structures located at the posterior aspect of the lumbar spine, play an important role in load-bearing and maintaining stability. Abnormal movement patterns of the facet joints may lead to joint damage and degeneration, ultimately causing lower back pain. Therefore, investigating the movement patterns of the lumbar facet joints can guide proper movement patterns and also contribute to guiding treatment strategies for related conditions.</p>", "<p id=\"Par6\">Currently, research on the motion patterns of small joints is often limited to 2D methods, such as commonly used X-ray, CT, MRI, etc. However, the motion of lumbar small joints is three-dimensional, not only limited to a specific plane but also involving changes in the entire spatial structure. Therefore, the currently applied research methods are unable to effectively measure the three-dimensional motion of small joints. At the same time, most methods that can be used for 3D motion measurement, such as tracking measurement, often have low accuracy and disadvantages such as invasive operations, making them more suitable for overall spinal motion measurement rather than fine motion structures like small joints. Therefore, we chose the dual fluoroscopic image system that combines 2D and 3D for the measurement of small joints. This method not only has high accuracy but also accurately reproduces the motion of lumbar facet joints in vivo.</p>", "<p id=\"Par7\">In this study, we hypothesize that: 1. The motion pattern of lumbar facet joints will change after loading during sitting posture; 2. There is an asymmetry in the motion pattern of lumbar facet joints between the left and right sides, which exists regardless of loading or non-loading conditions.</p>" ]
[ "<title>Methods</title>", "<title>Time and place</title>", "<p id=\"Par8\">Ten normal healthy people (5 males and 5 females) aged 25–39 years with an average of 32 ± 4.29 years were recruited for this study. Inclusion criteria: 1. Without heart disease, cerebrovascular disease, liver and kidney disease; 2. BMI between 18.5 and 23.9; 3. <italic>T</italic> value in bone mineral density between − 1 and 1, patients do not have bone metabolic disease. Exclusion criteria: 1. History of lumbar surgery or lumbar trauma; 2. There are spinal diseases, such as idiopathic scoliosis, Humen disease and other diseases that cause lumbar deformities; 3. Pregnancy; 4. Severe osteoporosis and other diseases that may affect the test results.</p>", "<p id=\"Par9\">The study was conducted according to the Declaration of Helsinki (revised 2013). The study was explained to all subjects and informed consent was signed. This study was approved by Tianjin Hospital Tianjin University Research Ethics Committee.</p>", "<title>Reconstruction of 3D model of lumbar vertebra</title>", "<p id=\"Par10\">The subjects completed thin-slice CT scanning in supine position with CT equipment (Sensation16, Siemens, Germany), tube voltage 120 kV, tube current 280 mAs, scanning angle 0°, slice thickness 0.625 mm, resolution 512*512 pixels, window level 50, window width 360. Subjects were scanned in the supine position for 45 s, including the range L1-S1, and the resulting data were stored in DICOM format. The obtained image data were imported into Mimics 21.0 software, and 3D model reconstruction of the lumbar spine was performed by selecting a special bone threshold and extracting the bone model (Fig. ##FIG##0##1##).</p>", "<title>Establishment of dual fluoroscopic image system (DFIS)</title>", "<p id=\"Par11\">The DFIS consists of two mobile X-ray units: the mobile C-arm X-ray machines used are produced by General Electric Healthcare Group, with both C-arm models being GEOECFluorostar7900. The two C-arms are identical in terms of specifications. The C-arms are designated as F1 and F2 respectively. During the experiment, the planes in which the two C-arms are located are perpendicular to each other, and the line formed by extending the two planes is close to the lumbar vertebrae L3-S1 of the subjects.</p>", "<p id=\"Par12\">The subjects sit on an adjustable-height chair, adjusted according to their individual height. The subjects' pelvis is fixed, maintaining the position of the thighs parallel to the ground and the lower legs perpendicular to the ground. Both upper limbs are placed on the shoulders to ensure that the lumbar vertebrae are at the center of the collimator field and within the imaging acquisition area. The subjects perform three movements: left lateral bending, neutral position, and right lateral bending, with each movement being held at maximum range. X-ray fluoroscopy (30 frames per second, 8 ms pulse width) was performed at each position for 1 s to obtain clear lumbar X-ray images. The subjects carried a specially designed 10 kg load for 30 min and then underwent X-ray imaging of the same movements again. The image acquisition process was supervised by two spine surgeons to ensure the accuracy of the movements (Fig. ##FIG##1##2##). The obtained X-ray images were saved in DICOM format and then underwent diffraction removal image processing.</p>", "<title>Establish coordinate system</title>", "<p id=\"Par13\">Rhinoceros 5 (64-bit) software was used to establish a coordinate system. Select the center point of the vertebra to establish a Cartesian coordinate system, with the center point as the origin. Three axis lines are established based on the origin: <italic>X</italic>, <italic>Y</italic>, and <italic>Z</italic>. The <italic>X</italic>-axis (red) is a horizontal line pointing to the left on the coronal plane. The <italic>Y</italic>-axis (green) is a horizontal line pointing backwards on the sagittal plane. The <italic>Z</italic>-axis (blue) is a vertical line pointing towards the head on the sagittal plane. The displacements along each axis are denoted as <italic>x</italic>, <italic>y</italic>, and <italic>z</italic>, respectively. The rotation angles around the <italic>X</italic>, <italic>Y</italic>, and <italic>Z</italic> axes are denoted as <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic>, respectively. Positive displacements are in the same direction as the arrow, while negative displacements are in the opposite direction. Clockwise rotation is denoted as positive, while counterclockwise rotation is denoted as negative. Displacements are noted in millimeters (mm), while rotation are noted in degrees (°). Copy the established coordinate system with the origin located at the midpoint between the articular processes below the cranial vertebral body and above the caudal vertebral body. At this point, the coordinate system for the articular process joint is established, which can be used to measure the displacement distance and rotational angle of the articular process joint.</p>", "<title>Reproduction of lumbar facet joint kinematics in different seated positions:</title>", "<p id=\"Par14\">Import the X-ray images with diffraction removed into Rhinoceros 5 (64-bit) and simulate the X-ray emission and receiving devices in the software according to the method proposed by LI et al. [##REF##19301040##6##]. The X-ray images serve as background images in the software, and the anatomical contours of the vertebral body, facet joints, spinous processes, etc. are delineated using the relevant tools in the software, completing the 2D modeling of the lumbar spine model. Import the CT 3D model into the modeling software. Adjust the position of each vertebral body based on the anatomical structure of the lumbar spine, ensuring complete overlap with the anatomical contours of the background image, thereby achieving the 2D-3D matching of vertebral body positions during different movements. The restored lumbar spine motion states in different positions (left bending, neutral position, right bending) can be obtained (Fig. ##FIG##2##3##).</p>", "<title>Measurement of three-dimensional lumbar spine model data</title>", "<p id=\"Par15\">By measuring the relative position changes of the lumbar zygapophyseal joints, data on the corresponding motion changes can be obtained. Specifically, the position comparison is made between the L4 superior articular process and the L3 inferior articular process, the L5 superior articular process and the L4 inferior articular process, and the S1 superior articular process and the L5 inferior articular process. The motion characteristics of the lumbar zygapophyseal joints during sitting position are studied by comparing the data of left bending-right bending without load and left bending-right bending with a load of 10 kg.</p>", "<title>Data statistics and analysis</title>", "<p id=\"Par16\">Statistical analysis was performed using SPSS 26.0 (IBM, Armonk, NY, USA). The dependent variable was the movement change, while the independent variables were the load and vertebral level. The data were found to follow a normal distribution based on the Kolmogorov–Smirnov test. The paired <italic>t</italic>-test was used to compare the displacement and rotational angles of the facet joints at L3/4, L4/5, and L5/S1 under 0 kg and 10 kg load conditions. A significance level of <italic>P</italic> &lt; 0.05 was considered statistically significant, and continuous variables were expressed as ±S.</p>" ]
[ "<title>Results</title>", "<title>Left–right bending movements at the L3-4 segment</title>", "<p id=\"Par17\">When there is no load, the displacement on the left side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 1.68 ± 0.85 mm, − 0.78 ± 1.10 mm, and − 1.34 ± 2.84 mm, respectively.The displacement on the right side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 1.45 ± 0.88 mm, 0.52 ± 0.47 mm, and 0.49 ± 2.07 mm, respectively. The rotation degrees along the <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic> axes on both sides are − 1.41 ± 3.55°, 5.66 ± 2.70°, and − 2.56 ± 2.05°, respectively. When there is a load of 10 kg, the displacement on the left side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 0.40 ± 0.74 mm, − 0.30 ± 0.65 mm, and − 0.97 ± 1.02 mm, respectively. The displacement on the right side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 0.69 ± 0.53 mm, 0.05 ± 0.40 mm, and 0.05 ± 1.75 mm, respectively. The rotation degrees along the <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic> axes are − 1.01 ± 2.64°, 2.22 ± 3.70°, and − 0.57 ± 1.43°, respectively.</p>", "<title>Left–right bending movements at the L4-5 segment</title>", "<p id=\"Par18\">When there is no load, the displacement on the left side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 0.91 ± 1.39 mm,  − 0.35 ± 1.77 mm, and − 2.11 ± 0.88 mm, respectively. The displacement on the right side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 0.62 ± 1.14 mm, 0.53 ± 0.87 mm, and 1.61 ± 1.00 mm, respectively. The rotation degrees along the <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic> axes on both sides are − 0.39 ± 1.52°, 7.89 ± 2.59°, and − 0.84 ± 3.65°, respectively. When there is a load of 10 kg, the displacement on the left side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 0.74 ± 1.67 mm, 0.28 ± 0.53 mm, and − 1.72 ± 2.30 mm, respectively. The displacement on the right side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is − 0.36 ± 1.09 mm, − 0.13 ± 0.91 mm, and 1.17 ± 1.02 mm, respectively. The rotation degrees along the <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic> axes are − 1.25 ± 2.58°, 3.67 ± 5.79°, and 0.21 ± 2.14°, respectively.</p>", "<title>Left–right bending movements at the L5-S1 segment</title>", "<p id=\"Par19\">When there is no load, the displacement on the left side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 2.19 ± 2.28 mm, − 1.07 ± 0.79 mm, and 0.72 ± 0.81 mm, respectively. The displacement on the right side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 2.35 ± 2.37 mm, − 0.86 ± 2.88 mm, and 1.53 ± 0.57 mm, respectively. The rotation degrees along the <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic> axes on both sides are 0.60 ± 2.95°, 1.28 ± 2.07° and 0.03 ± 2.02°, respectively. When there is a load of 10 kg, the displacement on the left side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is − 0.65 ± 0.69 mm, − 2.45 ± 0.48 mm, and − 1.14 ± 1.03 mm, respectively. The displacement on the right side along the coronal axis (<italic>X</italic>-axis), sagittal axis (<italic>Y</italic>-axis), and vertical axis (<italic>Z</italic>-axis) is 0.57 ± 0.85 mm, − 0.17 ± 1.10 mm, and 1.35 ± 0.51 mm, respectively. The rotation degrees along the <italic>α</italic>, <italic>β</italic>, and <italic>γ</italic> axes are − 0.56 ± 2.71°, 3.98 ± 0.37°, and − 1.35 ± 1.62°, respectively. (Table ##TAB##0##1##, Fig. ##FIG##3##4##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par20\">Low back pain is now one of the most common symptoms at work. According to the Bureau of Labor Statistics, musculoskeletal disorders (MSD) accounted for approximately 31% of all work-related injuries in the United States in 2015, with low back-related injuries comprising 40% of all MSDs. Low back pain imposes significant physiological and psychological burdens on patients, as well as substantial social impacts. A research survey conducted in the US revealed that the annual cumulative cost of low back pain exceeds $100 billion, two-thirds of which are indirect costs resulting from wage loss and decreased productivity [##REF##16595438##7##]. The lumbar facet joints are one of the important factors contributing to low back pain [##REF##21266006##8##–##REF##37470372##11##], often referred to as \"facet joint syndrome.\" Studies suggest that approximately 16–40% of chronic low back pain is caused by facet joints [##REF##23147891##12##–##UREF##0##14##]. Research on the movement characteristics of the lumbar facet joints can help us better understand their motion during daily activities, aiding in the analysis of the degenerative causes of facet joints and providing a theoretical basis for the prevention and treatment of facet joint disorders.</p>", "<p id=\"Par21\">Current research often focuses on the non-weight-bearing movement variations of the lumbar facet joints during standing, while there is a lack of relevant studies on the movement patterns of the lumbar facet joints under weight-bearing conditions during sitting. Investigating the movement patterns of the facet joints under weight-bearing conditions during sitting would contribute to a comprehensive understanding of lumbar spine motion and provide better guidance for proper movement patterns and rehabilitation treatments. At present, most studies are limited by conditions, often in two-dimensional plane or in vitro, can not effectively reduce the movement of lumbar joints in vivo, have lower accuracy. Our study utilized the DFIS method to restore the motion changes of the lumbar facet joints in vivo. This method has a high level of accuracy, with reported displacement errors of 0.3 mm and rotational errors of 0.7° [##REF##19301040##6##, ##REF##18469683##15##], enabling a more accurate reflection of the motion changes of the lumbar facet joints in vivo.</p>", "<p id=\"Par22\">Chowdhury et al. observed the changes in the facet joints movements during weight-bearing exercise in 11 healthy subjects [##REF##30074402##16##]. The study found that small joints had significant load effects in lateral bending and superior-inferior translation. After weight-bearing, the L5-S1 joint had greater lateral bending and twisting than the L2-L3, L3-L4, and L4-L5 joints. The authors suggested that the kinematics of lumbar spine small joints were influenced by the magnitude of the load and the direction of adjacent joints. As the orientation of the L5-S1 small joints was more coronal than the L2-L3, L3-L4, and L4-L5 joints, greater lateral bending and twisting were produced. Our study also showed that weight-bearing had a significant effect on facet joint movements, except for the <italic>Y</italic> and <italic>Z</italic> axes in the left L5-S1 segment, where the displacement of small joints was significantly reduced at 10 kg compared to 0 kg. This may be due to the increased pressure on small joints and the decreased gap between the upper and lower facets caused by weight-bearing, resulting in reduced small joint displacement. This effect was more pronounced in the L3-4 and L4-5 segments, which differed from Chowdhury et al.'s finding that weight-bearing had a more significant effect on the L5-S1 segment. We believe that this difference may be due to the lack of fixation of the pelvis and restriction of hip joint movement in Chowdhury et al.'s study, which may have affected the motion of the L5-S1 facet joints; Additionally, the weight used in Chowdhury et al.'s study was different from that in our study, and we speculate that a higher weight may be more likely to induce small joint motion changes. Chowdhury et al.'s study did not measure the rotation angle of small joints, but we found that the rotation angles of small joints in lateral bending were not consistent. In the L3-4 and L4-5 segments, the rotation angle decreased with increasing weight, but in the L5-S1 segment, weight-bearing increased the rotation angle. We believe that this is due to the unique anatomical structure of the L5-S1 joint, which is affected by the sacroiliac joint and changes the motion pattern of the L5-S1 small joints, leading to an increase in rotation angle after weight-bearing.</p>", "<p id=\"Par23\">Song et al. measured the movement of the lumbar facet joints during flexion and extension of the spine in the standing position [##REF##33709625##17##]. After comparing the measurements with 0 kg, 5 kg, and 10 kg loads, the researchers concluded that the load did not increase the range of motion of the lumbar facet joints. This may be due to compensatory effects from muscles and ligaments. Wen et al. studied the effects of loads of 0 kg, 5 kg, and 10 kg on the small joints of the spine during standing posture and concluded that the loads have an impact on the coupled motion of the spine, but the effect on the small joints during spinal lateral bending is not significant [##REF##35189913##18##]. In this study, we believe that the movement of facet joints is influenced by load when sitting. When the load is 10 kg, the displacement of the facet joint was significantly reduced compared to 0 kg. This result is observed in the <italic>X</italic>-axis of the small joints on the left side of the L3/4 segment, the right side of the L3/4 segment, the <italic>Y</italic>-axis of the small joints on both sides of the L3/4 segment, the <italic>Z</italic>-axis of the small joints on both sides of the L3/4 segment, the <italic>X</italic>-axis of the small joints on the left side of the L5/S1 segment, the <italic>Y</italic>-axis of the small joints on both sides of the L5/S1 segment, the <italic>Z</italic>-axis of the small joints on both sides of the L5/S1 segment, and the <italic>X</italic>-axis of the small joints on the right side of the L5/S1 segment. This is different from previous research results. This is different from previous research findings. We believe that the reason for this difference lies in the different postures. When sitting, the pressure on the lumbar spine is greater than when standing, and the range of motion of the lumbar facet joints is relatively larger compared to when standing [##REF##11219760##19##, ##REF##29758964##20##]. Therefore, the effect of load on the lumbar facet joints may be greater during sitting. In addition, the tilt of the pelvis also contributes to the differences in results. When subjects are in a standing position, the pelvis cannot be completely fixed, and spinal lateral bending often accompanies partial pelvic tilt. However, when sitting, the pelvis is fixed in a specific seat and cannot tilt, resulting in less influence on spinal lateral bending. In our study, we found that when a load of 10 kg was applied, the lumbar facet joints exhibited a pattern of lateral translation accompanied by rotation. This lateral bending pattern with translation and rotation in the lumbar facet joints is similar to that observed without load. Among the lumbar facet joints, more parallel displacement occurred at the L3-4 and L4-L5 levels, which may be due to the limited mobility of the L5/S1 facet joints caused by pelvic fixation, resulting in relatively less motion at the L5-S1 level compared to the levels above.</p>", "<p id=\"Par24\">Many studies have found asymmetry in the small joints on the left and right sides [##REF##37661834##21##–##REF##36681952##23##]. Leng et al. suggested that the asymmetry of the lumbar facet joints is correlated with lumbar spondylolisthesis [##REF##36681952##23##]. Wang et al. found a correlation between the asymmetry of the lumbar facet joints and spinal canal stenosis [##REF##36003291##24##]. Kou et al. investigated the asymmetry of lumbar facet joint motion during standing and found that the most pronounced asymmetry occurred in the L3-L4 and L5-S1 facet joints [##REF##35530947##25##]. In our study, we also observed an asymmetrical movement of the lumbar zygapophyseal joints during lateral flexion in the seated position. In the segments of L3-4, L4-5, and L5-S1 without load, both sides of the lumbar zygapophyseal joints exhibited asymmetrical movement patterns. This phenomenon persisted even when a load of 10 kg was added. The load did not affect the asymmetrical movement of the lumbar facet joints. Previous studies have shown that there is anatomical asymmetry in the lumbar zygapophyseal joints [##REF##35930062##26##]. We believe that this anatomical asymmetry in the facet joints causes the asymmetrical movement patterns. This anatomical asymmetry does not change with the presence of a load, and therefore, the load does not affect the asymmetrical movement of the facet joints.</p>", "<p id=\"Par25\">There are several limitations in this study. Firstly, the sample size is small. Due to the complexity of the experiment, the sample size in this study was only 10, which may have led to insignificant results in some cases. Future research can increase the sample size for analysis. Secondly, we only measured the lateral bending motion of the lumbar spine in a seated position. In future studies, we can include rotational and other daily movements for correlation analysis. Lastly, due to the limitations of the projection range, this study only measured the facet joints of the lumbar spine at L3-S1. Future research can measure the facet joints of the upper lumbar spine to better demonstrate the overall motion pattern of the lumbar spine. Despite these limitations, this study, for the first time, investigated the influence of load on lateral bending motion of the lumbar facet joints in a seated position through non-invasive methods. This has important implications for the prevention of lumbar facet degeneration and the treatment of related diseases.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par26\">\n<list list-type=\"order\"><list-item><p id=\"Par27\">When sitting, load-bearing has a certain impact on the displacement of the facet joints during lumbar lateral bending, and this impact occurs simultaneously in translation and rotation.</p></list-item><list-item><p id=\"Par28\">The facet joints on the left and right sides are not symmetrical during lumbar lateral bending.</p></list-item></list>\n</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">To study the effect of weight-bearing on lumbar facet joint during lateral bending in sitting position.</p>", "<title>Methods</title>", "<p id=\"Par2\">Ten normal healthy people (5 males and 5 females) aged 25–39 years (mean 32 ± 4.29 years) were recruited. CT scanning was used to reconstruct the lumbar spine model, and then dual fluoroscopic image system (DFIS) was used to restore the lumbar facet joint movement in sitting position. Finally, the lumbar facet joint translation distance and rotation angle were measured.</p>", "<title>Results</title>", "<p id=\"Par3\">In L3-4 level, the displacement of right facet joint in <italic>Y</italic>-axis was the smallest at 0.05 ± 0.40 mm, the displacement of 0 kg left facet joint in <italic>X</italic>-axis was the largest at 1.68 ± 0.85 mm, and the rotation angle was − 0.57 ± 1.43° to 5.66 ± 2.70° at 10 kg; in L4-5 level, the displacement of right facet joint in <italic>Y</italic>-axis was the smallest at 10 kg, − 0.13 ± 0.91 mm, and the displacement of left facet joint in <italic>Z</italic>-axis was the largest at − 2.11 ± 0.88 mm, and the rotation angle was 0.21 ± 2.14° to 7.89 ± 2.59° at 10 kg; in L5-S1 level, the displacement of right facet joint in <italic>Y</italic>-axis was the smallest at 10 kg, − 0.17 ± 1.10 mm, and the displacement of 0 kg left facet joint in <italic>X</italic>-axis was the largest at 2.19 ± 2.28 mm, and the rotation angle was 0.03 ± 2.02° to 3.98 ± 0.37°.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">In sitting position, weight-bearing has certain influence on the displacement of facet joints during lumbar lateral bending movement, and this influence occurs simultaneously in translation and rotation; the left and right facet joints are not symmetrical during lumbar lateral bending movement.</p>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>YH designed the study and wrote the manuscript. WY and SS participated in the collection of experimental data. ZL Performed data statistics. BR and XZ performed the experiments. JM and XW revised the manuscript.</p>", "<title>Funding</title>", "<p>S&amp;T Program of Hebei (Grant Number:21377762D), the Foundation of Baoding Self-raised Fund Project (Grant Number 2341ZF335).</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par29\">All clinical investigations had been conducted according to the principles expressed in the Declaration of Helsinki. This study was conducted with approval from the Ethics Committee of Affiliated Hospital of Hebei University. Informed consent to participate in the study was obtained from the participant.</p>", "<title>Consent for publication</title>", "<p id=\"Par30\">Written informed consent for publication was obtained from all participants.</p>", "<title>Competing interests</title>", "<p id=\"Par31\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>3D model of the spine established by MIMICS software</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Data collected by subjects in DFIS system consisting of two C-arms</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Schematic diagram of the process of matching the lumbar spine model of 2D-3D through the software. a. import the X-rays acquired by the two C-arms of F1 and F2 into Rhinoceros 5, b. draw the boundary of the lumbar spine in the software, c. import the 3D model reconstructed in Mimics software into Rhinoceros 5, d. adjust the 3D model in the F1 and F2 perspectives until the vertebral body and 3D model in the background overlap. At this point, the movement distance and rotation angle of lumbar facet joints can be measured in the software</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Translation distance and rotation angle of left and right facet joints at different lumbar levels</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Displacement and rotation of left and right facet joints at different lumbar segments</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Segment</th><th align=\"left\">L3-4</th><th align=\"left\"/><th align=\"left\"/><th align=\"left\">L4-5</th><th align=\"left\"/><th align=\"left\"/><th align=\"left\">L5-S1</th><th align=\"left\"/><th align=\"left\"/></tr></thead><tbody><tr><td align=\"left\">Loading</td><td align=\"left\">0 kg</td><td align=\"left\">10 kg</td><td align=\"left\">P</td><td align=\"left\">0 kg</td><td align=\"left\">10 kg</td><td align=\"left\">P</td><td align=\"left\">0 kg</td><td align=\"left\">10 kg</td><td align=\"left\">P</td></tr><tr><td align=\"left\">Translation</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Left (mm)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  X</td><td align=\"left\">1.68 ± 0.86</td><td align=\"left\">0.40 ± 0.74</td><td align=\"left\"> &lt; 0.01</td><td align=\"left\">0.91 ± 1.37</td><td align=\"left\"> − 0.74 ± 1.67</td><td align=\"left\">0.28</td><td align=\"left\">2.19 ± 2.28</td><td align=\"left\"> − 0.65 ± 0.69</td><td align=\"left\"> &lt; 0.01</td></tr><tr><td align=\"left\">  <italic>Y</italic></td><td align=\"left\"> − 0.78 ± 1.10</td><td align=\"left\"> − 0.30 ± 0.65</td><td align=\"left\">0.25</td><td align=\"left\"> − 0.35 ± 1.77</td><td align=\"left\">0.28 ± 0.53</td><td align=\"left\">0.30</td><td align=\"left\"> − 1.07 ± 0.79</td><td align=\"left\"> − 2.45 ± 0.49</td><td align=\"left\"> &lt; 0.01</td></tr><tr><td align=\"left\">  <italic>Z</italic></td><td align=\"left\"> − 1.34 ± 2.84</td><td align=\"left\"> − 0.97 ± 1.02</td><td align=\"left\">0.70</td><td align=\"left\"> − 2.12 ± 0.88</td><td align=\"left\"> − 1.72 ± 2.30</td><td align=\"left\">0.62</td><td align=\"left\">0.72 ± 0.81</td><td align=\"left\"> − 1.14 ± 1.04</td><td align=\"left\"> &lt; 0.01</td></tr><tr><td align=\"left\">Translation</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Right (mm)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  <italic>X</italic></td><td align=\"left\">1.45 ± 0.89</td><td align=\"left\">0.69 ± 0.53</td><td align=\"left\">0.03</td><td align=\"left\">0.62 ± 1.14</td><td align=\"left\"> − 0.36 ± 1.09</td><td align=\"left\">0.06</td><td align=\"left\">2.36 ± 2.37</td><td align=\"left\"> − 0.57 ± 0.85</td><td align=\"left\"> &lt; 0.01</td></tr><tr><td align=\"left\">  <italic>Y</italic></td><td align=\"left\">0.52 ± 0.47</td><td align=\"left\">0.05 ± 0.40</td><td align=\"left\">0.03</td><td align=\"left\">0.53 ± 0.87</td><td align=\"left\"> − 0.13 ± 0.91</td><td align=\"left\">0.11</td><td align=\"left\"> − 0.86 ± 2.88</td><td align=\"left\"> − 0.17 ± 1.10</td><td align=\"left\">0.49</td></tr><tr><td align=\"left\">  <italic>Z</italic></td><td align=\"left\">0.49 ± 2.07</td><td align=\"left\">0.05 ± 1.75</td><td align=\"left\">0.01</td><td align=\"left\">1.61 ± 1.00</td><td align=\"left\">1.17 ± 1.02</td><td align=\"left\">0.35</td><td align=\"left\">1.53 ± 0.57</td><td align=\"left\">1.35 ± 0.51</td><td align=\"left\">0.47</td></tr><tr><td align=\"left\"> Rotation Angle (°)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> <italic>α</italic></td><td align=\"left\"> − 1.41 ± 3.55</td><td align=\"left\"> − 1.01 ± 2.64</td><td align=\"left\">0.78</td><td align=\"left\"> − 0.39 ± 1.52</td><td align=\"left\"> − 1.25 ± 2.59</td><td align=\"left\">0.37</td><td align=\"left\">0.60 ± 2.95</td><td align=\"left\"> − 0.56 ± 2.71</td><td align=\"left\">0.37</td></tr><tr><td align=\"left\"> <italic>β</italic></td><td align=\"left\">5.67 ± 2.70</td><td align=\"left\">2.22 ± 3.70</td><td align=\"left\">0.03</td><td align=\"left\">7.89 ± 2.59</td><td align=\"left\">3.67 ± 5.79</td><td align=\"left\">0.05</td><td align=\"left\">1.28 ± 2.08</td><td align=\"left\">3.98 ± 0.37</td><td align=\"left\"> &lt; 0.01</td></tr><tr><td align=\"left\"> <italic>γ</italic></td><td align=\"left\"> − 2.65 ± 2.05</td><td align=\"left\"> − 0.57 ± 1.43</td><td align=\"left\">0.02</td><td align=\"left\"> − 0.85 ± 3.65</td><td align=\"left\">0.21 ± 2.14</td><td align=\"left\">0.44</td><td align=\"left\">0.03 ± 2.02</td><td align=\"left\"> − 1.35 ± 1.62</td><td align=\"left\">0.11</td></tr></tbody></table></table-wrap>" ]
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[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Ye Han and Wei Yuan are co-first author.</p></fn></fn-group>" ]
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[{"label": ["14."], "surname": ["Manchikanti", "Pampati", "Singh", "Beyer", "Damron", "Fellows"], "given-names": ["L", "V", "V", "C", "K", "B"], "article-title": ["Evaluation of the role of facet joints in persistent low back pain in obesity: a controlled, prospective, comparative evaluation"], "source": ["Pain Phys"], "year": ["2001"], "volume": ["4"], "issue": ["3"], "fpage": ["266"], "lpage": ["272"], "pub-id": ["10.36076/ppj.2001/4/266"]}]
{ "acronym": [], "definition": [] }
26
CC BY
no
2024-01-14 23:43:46
J Orthop Surg Res. 2024 Jan 13; 19:61
oa_package/a6/59/PMC10787429.tar.gz
PMC10787430
38217037
[ "<title>Introduction</title>", "<p id=\"Par2\">Cancer development and progression are intricately associated with the multifaceted tumor microenvironment (TME). This dynamic milieu is shaped by aberrant environmental conditions and complex cellular interactions [##REF##29700396##1##, ##REF##24202395##2##]. In the TME, cancer cells interact with various immune cells such as MDSCs, Tregs, and M2-type TAMs. These immunosuppressive cells collectively hinder the metabolism of T cells required for recruitment, infiltration, proliferation, and activation [##UREF##0##3##–##REF##30057419##5##]. Moreover, The TME is characterized by challenging nutrient deprivation, hypoxia, and acidosis, which significantly influences cellular metabolism. Such conditions compromise the function of anti-tumoral T cells and enhance the resistance to therapeutic interventions [##REF##27396447##6##–##REF##30914826##10##]. It is imperative, therefore, to achieve a deeper understanding of the cellular and environmental interplay in terms of metabolic regulation within the TME. Such knowledge can provide insights into tailoring the properties of the TME for improved cancer therapy outcomes [##UREF##0##3##, ##REF##18836471##11##].</p>", "<p id=\"Par3\">Ferroptosis is a relatively novel form of non-apoptotic regulated cell death characterized by distinct morphological, biochemical, and genetic features [##REF##22632970##12##, ##UREF##1##13##]. Growing evidence implicates ferroptosis in various pathological conditions and diseases, including tumors, cardiomyopathies, ischemia-reperfusion injuries, and neurodegenerative disorders [##REF##33495651##14##–##REF##30737476##17##]. In the field of oncology, ferroptosis has shown potential therapeutic efficacy for a range of cancer types, notably pancreatic ductal adenocarcinoma (PDAC), ovarian cancer, and melanoma [##REF##30692261##15##, ##REF##28462528##18##–##REF##25385600##22##]. The mechanism that influences ferroptosis sensitivity within the TME remains to be fully elucidated. In this review, the focus will be on understanding the differential sensitivities to ferroptosis in the TME, especially as shaped by its environmental and cellular regulation, to establish precise strategies for ferroptosis-based tumor therapy.</p>" ]
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[ "<title>Conclusions and perspectives</title>", "<p id=\"Par57\">The overlap of ferroptosis metabolic pathways within both neoplastic and immune cells presents considerable challenges to the specificity and potency of ferroptosis therapeutics. Worse still, the TME seemingly protects malignant cells against ferroptosis while concurrently predisposing T-cells to ferroptosis. To overcome this, a bifurcated approach is worth considering: systematic characterization of the TME in cellular and environmental variables and immunophenotypes to determine its amenability to ferroptosis; subsequent strategic manipulation of salient environmental attributes, such as hypoxia, acidosis, and nutrient dynamics, to alter cellular metabolism. This metabolic recalibration can engender differential sensitivities to ferroptosis, facilitating targeted ablation of malignant and immunosuppressive cells and rescue of T cells. Ferroptotic cells bolster the immune response by releasing DAMPs, notably ATP and HMGB1. Notably, this therapeutic strategy, underscored by its self-reinforcing mechanisms, holds the potential for synergistic integration with established therapeutic modalities, including immunotherapy, radiotherapy, and chemotherapy.</p>", "<p id=\"Par58\">However, notwithstanding its conceptual appeal, this therapeutic paradigm has inherent challenges. A salient concern is the nebulous understanding of how environmental variables modulate ferroptotic sensitivities across varied cell types. Current research endeavors, while illuminative, are predominantly univariate in design, potentially obfuscating the nuanced interactions in the actual TME. Although TIME has been categorized into ‘hot’, ‘cold’, and ‘altered’ states, a holistic classification predicated on environmental variables related to ferroptosis is conspicuously absent. Consequently, an in-depth exploration of these variables is imperative for accurately gauging metabolic vulnerabilities, thereby facilitating nuanced biomarker and therapeutic target identification. Another formidable challenge lies in the intrinsic heterogeneity and dynamism of TME. This heterogeneity is manifest not just across tumor types, but intriguingly, within individuals and even disparate regions of a singular tumor. The inherent metabolic heterogeneity within tumors, characterized by varied metabolic rates and differential hypoxic regions requires meticulous attention [##REF##18987634##235##]. Hence, the quest for an optimal therapeutic window – wherein neoplastic cells are maximally ferroptosis-sensitive and T cells most ferroptosis-resilient – remains paramount. Thus, the universally applicable biomarkers reliably gauging ferroptosis efficacy across varied TME landscapes is paramount. Moreover, the adaptive metamorphosis of the TME significantly fosters resistance not merely to ferroptosis but also other therapeutics such as radiotherapy, chemotherapy, and immunotherapy [##REF##32106859##76##, ##REF##31101865##236##–##REF##30898264##238##]. This underscores the necessity for both proactive characterization and iterative monitoring of the TME throughout therapeutic interventions. Lastly, no efficient and safe drugs targeting ferroptosis in the clinic. While some agents like Artesunate, Sorafenib, and Cisplatin, have shown promise through their dual functionalities, the transition from bench to bedside remains fraught with challenges [##REF##23505071##239##–##REF##26097885##241##]. Factors such as specificity, sensitivity, the quest for spatial-temporal biomarkers, and the identification of clinically viable drugs emerge as critical, yet unresolved conundrums in the realm of ferroptosis therapy.</p>" ]
[ "<p id=\"Par1\">Ferroptosis, a novel form of cell death triggered by iron-dependent phospholipid peroxidation, presents significant therapeutic potential across diverse cancer types. Central to cellular metabolism, the metabolic pathways associated with ferroptosis are discernible in both cancerous and immune cells. This review begins by delving into the intricate reciprocal regulation of ferroptosis between cancer and immune cells. It subsequently details how factors within the tumor microenvironment (TME) such as nutrient scarcity, hypoxia, and cellular density modulate ferroptosis sensitivity. We conclude by offering a comprehensive examination of distinct immunophenotypes and environmental and metabolic targets geared towards enhancing ferroptosis responsiveness within the TME. In sum, tailoring precise ferroptosis interventions and combination strategies to suit the unique TME of specific cancers may herald improved patient outcomes.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13046-023-02925-5.</p>", "<title>Keywords</title>" ]
[ "<title>Overview of ferroptosis</title>", "<p id=\"Par4\">Ferroptosis, first found in 2012, is characterized by iron-dependent and reactive oxygen species (ROS)-mediated membrane phospholipid containing polyunsaturated fatty acid chains (PUFA-PL) peroxidation, producing excessive PUFA-phospholipid hydroperoxides (PUFA-PLOOH), which leads to membrane rupture and cell death [##REF##22632970##12##, ##REF##28985560##20##]. The synthesis of PUFA-PLOOH relies on two ways, including the enzyme-based mechanism and the non-enzymic mechanism. Massive ROS produced from a non-enzymic Fenton reaction initiated by iron, transported by transferrin receptor. In the presence of iron, PUFA-PLOOH forms alkoxyl phospholipid radical (PLO·), and eventually triggers ferroptosis [##REF##31105042##23##]. ROS plays a vital role in ferroptosis as the promotor of lipid peroxidation. The mitochondria, the major source of ROS, are an influencing factor in ferroptosis sensitivity [##UREF##2##24##]. Acyl-CoA synthetase long-chain family member 4 (ACSL4) and lysophosphatidylcholine acyltransferase 3 (LPCAT3) promote ferroptosis by enriching the polyunsaturated fatty acids (PUFAs) on the cell membrane lipids [##REF##27842070##25##]. System Xc<sup>−</sup>, also known as SLC7A11, on the cell membrane uptakes Cystine (Cys<sub>2</sub>), reduces it to Cysteine (Cys) by thioredoxin reductase (TrxR), and then synthesizes glutathione (GSH) the primary substance neutralizing ROS as well as forming the glutathione peroxidase 4 (GPX4) as the subunit [##REF##33340021##26##]. GPX4 is the main detoxification enzyme that reduces PLOOH to phosphatidyl alcohol PLOH, thereby inhibiting ferroptosis [##REF##24439385##27##]. Recently, research revealed that Cys directly promoted the synthesis of GPX4 by activating mTOR [##REF##33707434##28##]. TRX system, mainly composed of Thioredoxin (Trx) and TrxR, is an alternative antioxidant system related to ferroptosis [##UREF##3##29##, ##REF##28648527##30##]. As a co-factor of GPX4, Trx promotes the expression and function of GPX4 [##UREF##3##29##, ##REF##33634378##31##]. TrxR1 mediates the reduction of Cys<sub>2</sub> transported by system Xc<sup>−</sup> into endogenous Cys synergistically with GPX4 [##REF##20463017##32##]. By alternatively promoting system Xc<sup>−</sup> expression, TrxR1 sustains cell survival after GSH expression is inhibited [##REF##20463017##32##]. A recent study found that the TRX system inhibitors could induce ferroptosis in cancer cells [##REF##31086302##33##]. Coenzymes Q10 (CoQ<sub>10</sub>) is another antioxidant system parallel to GPX4. It is reduced by ferroptosis suppressor protein 1 (FSP1) to a lipophilic radical-trapping antioxidant (RTA) combating ferroptosis [##REF##31634899##34##, ##REF##31634900##35##]. Tetrahydrobiopterin (BH4) biosynthesis essentially and alternatively regulates ferroptosis sensitivity by inhibiting the production of PLOOH after GPX4 inhibition [##REF##32778843##36##]. Dihydroorotate dehydrogenase (DHODH), an enzyme in mitochondria, resists ferroptosis occurring in mitochondria [##REF##33981038##37##]. The systemic molecular mechanisms of ferroptosis have been comprehensively reviewed somewhere else [##REF##33495651##14##, ##REF##28985560##20##, ##REF##33268902##38##]. The schematic diagrams of related regulations are summarized in Fig. ##FIG##0##1##.</p>", "<p id=\"Par5\">\n\n</p>", "<title>Environmental stresses recalibrate metabolism within the TME</title>", "<title>Ferroptosis defense mechanism of T cells</title>", "<p id=\"Par6\">Upon activation, CD4<sup>+</sup> and CD8<sup>+</sup> effector T cells require essential GPX4 to avoid ferroptotic cell death [##REF##24439385##27##, ##REF##25824832##39##, ##REF##1970635##40##]. Interestingly, while system Xc<sup>−</sup> plays a significant role in other cell types, it appears less essential for the proliferation and immunological function of T cells. Indeed, investigations within PDAC models have demonstrated that suppression of system Xc<sup>−</sup> expression notably curtails tumor growth without compromising the systemic anti-tumor immunity mediated by T cells in vivo. This implies the existence of alternative Cys procurement mechanisms within T cells [##REF##31019077##41##]. In the TME, T cells employ alanine-serine-cysteine transporters (ASCT1 and ASCT2) to assimilate both Cys<sub>2</sub> and Cys, predominantly from activated antigen-presenting cells (APCs) such as macrophages and dendritic cells (DCs) [##REF##31019077##41##–##REF##20673163##44##]. These APCs, orchestrate the synthesis of both intracellular and extracellular Trx, which facilitates the breakdown of Cys<sub>2</sub> to Cys for T cell absorption. This process is regulated by the transcription factor, nuclear factor erythroid 2-related factor 2 (NRF2). Notably, the inhibition of NRF2 in T cells is associated with significant downregulation of pivotal molecules including glutamate-cysteine ligase (GCL), system Xc<sup>−</sup>, and GSH synthase [##REF##22355778##42##, ##REF##11792859##45##, ##REF##2364441##46##].</p>", "<p id=\"Par7\">The existence and completeness of a trans-sulfurization pathway in T cells, which would potentially convert methionine to Cys, remains an academic debate. The present study suggests that while such a pathway might be operational, its capacity to satiate the Cys demands of the cell is likely limited [##REF##22355778##42##, ##REF##20673163##44##, ##REF##20028852##47##]. An additional note of interest is the observation that memory T cells exhibit heightened resistance to ferroptosis, a trait possibly attributed to their augmented mitochondrial content, which facilitates enhanced energy production with a concomitant reduction in peroxide generation [##REF##22206904##48##].</p>", "<title>Interplay between ferroptosis and the anti-tumor activity of T cells</title>", "<p id=\"Par8\">Emerging research has elucidated the role of effector T cells in promoting ferroptosis within cancer cells [##REF##12093006##49##–##REF##31043744##51##]. Detailed in vitro and in vivo experiments have revealed a distinct molecular mechanism underpinning this phenomenon: activated CD8<sup>+</sup> T cells secrete IFN-γ which induces ferroptosis in cancer cells. This is achieved through the binding of IFN-γ to IFN-γ receptor I (IFNGR1) on cancer cells, which subsequently activates the JAK/STAT signaling pathway to inhibit the transcriptional activity of downstream system Xc<sup>−</sup> [##REF##31043744##51##, ##REF##34318944##52##]. In tandem, CD4<sup>+</sup> T cells further potentiate the sensitivity of cancer cells to ferroptosis by secreting TNF-α, which binds to TNF-α receptor 1 (TNFR1) on the cancer cells. This interaction results in the inhibition of GSH synthesis and subsequently improves the production of ROS via the activation of nicotinamide adenine dinucleotide phosphate oxidase (NOXs). It is worth noting that the ferroptotic effects induced by this mechanism can be counteracted by the addition of Cys or the use of a TNF-α neutralizing antibody, underscoring the pivotal roles of these molecules in the ferroptotic process [##UREF##4##53##]. Significantly, the anti-tumor efficacy of IFN-γ appears to be a foundational requirement for the subsequent effects of TNF-α. This is potentially attributed to IFN-γ diminishing the reservoir of GSH within the TME, thereby creating a conducive cellular milieu for TNF-α-mediated effects [##REF##27133165##54##].</p>", "<title>Enhanced resistance to ferroptosis in T regulatory cells (Tregs)</title>", "<p id=\"Par9\">Within the intricate milieu of the tumor microenvironment, Tregs play a pivotal role in modulating immune responses, predominantly deriving their energy from fatty acid oxidation [##REF##21317389##55##]. Emerging evidence suggests that Tregs exhibit an augmented resistance to ferroptosis, potentially attributed to their augmented synthesis and secretion of Trx [##REF##25824823##56##–##REF##16557261##60##]. Upon activation, Tregs appear to bolster their anti-ferroptotic defenses by upregulating GPX4. Interestingly, experiments involving GPX4 knock-out in Tregs have demonstrated that co-stimulation of TCR and CD28 leads to an overproduction of superoxide in the mitochondria, thereby precipitating ferroptosis [##REF##32066953##61##]. IL-1β, along with other pro-inflammatory mediators, is released following Treg ferroptosis. This not only triggers T helper 17 (TH17) responses but also augments the activation of DCs and amplifies the anti-tumor efficacy of antigen-specific CD8<sup>+</sup> T cells [##REF##23460726##62##–##REF##33207188##64##]. Paradoxically, oxidative stress-induced apoptosis in Tregs has been observed to release significant amounts of adenosine intriguingly undermining the benefits of immune checkpoint blockade (ICB) [##REF##29083399##65##]. All in all, the nuanced interplay between Treg ferroptosis, cytokine release, and immune modulation offers a promising avenue for therapeutic interventions. The selective secretion of IL-1β by ferroptotic Tregs, in particular, emerges as a potential target in advanced cancer treatments.</p>", "<title>Differential sensitivity to ferroptosis in M2-type versus M1-type TAMs</title>", "<p id=\"Par10\">The TME is enriched with various immune cell populations, among which TAMs play a multifaceted role. Notably, the dichotomy between M1 and M2 types of TAMs offers intriguing insights into their contrasting roles and susceptibilities in oncological contexts. M2-type TAMs, which have been recognized as potent facilitators of tumor progression, intriguingly exhibit an enhanced vulnerability to ferroptosis compared to their M1-type counterparts [##UREF##5##66##]. One of the keystones ensuring the survival of M2-type TAMs in the face of ferroptosis is the pivotal enzyme, GPX4. In stark contrast, M1-type TAMs, encompassing the specialized microglia cells, are equipped with inducible nitric oxide synthase (iNOS). This enzyme is instrumental in producing nitric oxide (NO), a radical molecule endowed with highly reactive chemical properties. As a key modulator of ferroptosis, NO influences the peroxidation of specific lipid moieties, particularly those containing PUFAs such as arachidonic acids (AAs). The ensuing catalytic action, primarily mediated by arachidonic acid lipoxygenase 15 (ALOX-15), fortifies the ferroptosis resistance inherent to M1-type TAMs and microglial cells [##REF##32080625##67##]. The ability of NO to move freely across cellular membranes allows it to protect neighbouring cells from ferroptosis [##REF##32080625##67##, ##UREF##6##68##]. In contrast, the heightened susceptibility of M2-type TAMs to ferroptosis can be attributed to iNOS deficiency. This distinction presents a tantalizing therapeutic opportunity. Harnessing the proclivity of M2-type TAMs towards ferroptosis could offer a dual advantage in cancer therapeutics: not only annihilating malignant cells but also concurrently mitigating the tumor-promoting effects of M2-type TAMs.</p>", "<title>Dynamic cys competition between MDSCs and T cells</title>", "<p id=\"Par11\">In the TME, a nuanced interplay exists between MDSCs and tumor-infiltrating T cells, with Cys acting as a pivotal molecule around which their interactions revolve. MDSCs, by their metabolic and functional dynamics, exhibit a pronounced propensity to engender ferroptosis in tumor-infiltrating T cells. This is achieved primarily through their competitive consumption of both Cys<sub>2</sub> and Cys. Notably, MDSCs actively import Cys<sub>2</sub> through system Xc<sup>−</sup>, subsequently engaging in its conversion to Cys. Although their import rate for Cys<sub>2</sub> mirrors that of T cells, a distinguishing feature of MDSCs is their augmented intracellular storage capability. Their reluctance to export Cys back into the TME, coupled with their active uptake of Cys<sub>2</sub>, results in a significant reduction in the extracellular Cys<sub>2</sub>. As a result, T cells face a diminished availability of Cys [##REF##20028852##47##]. Furthermore, cancer-infiltrating MDSCs uniquely express elevated levels of N-acylsphingosine amidohydrolase (ASAH2). This enzyme plays a decisive role in modulating redox dynamics by destabilizing the p53 protein, thereby curbing ROS production and rendering MDSCs resistant to ferroptosis. Targeting ASAH2, by inhibition, instigates ferroptosis in MDSCs. Such a targeted intervention has demonstrated therapeutic potential, evidenced by the augmented activity of tumor-infiltrating cytotoxic T lymphocytes (CTLs) and subsequent attenuation of tumor progression [##UREF##7##69##].</p>", "<title>Neutrophil ferroptosis and its immunosuppressive effect on anti-tumor immunity</title>", "<p id=\"Par12\">Tumor-associated neutrophils (TANs) within the TME present a dichotomous role, with their function straddling both immune promotion and suppression. Such duality can be attributed to their intrinsic functional plasticity and vast immunological heterogeneity, determinants that collectively shape the clinical trajectory of oncological cases [##REF##31160735##70##]. A subtype, the polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs)—pathologically hyperactive neutrophils—are susceptible to ferroptosis. Intriguingly, while ferroptotic pathways lead to a reduction in PMN-MDSCs, they concurrently intensify their immunosuppressive phenotypes. This is exemplified by the augmented accumulation of AA-PE and subsequent prostaglandin E2 (PGE2) release, impairing T-cell functions and facilitating tumor progression [##REF##36385526##71##]. In the context of glioblastoma (GBM) pathogenesis, the early phase witnesses the upregulation of granulocyte-colony stimulating factor (G-CSF) among other cytokines, resulting from GBM activity, which orchestrates TAN activation. The ensuing high presence of mature TANs propels GBM cell ferroptosis by ferrying myeloperoxidase (MPO) particles, with neutrophilic signatures, into GBM cells. This process, mediated by N-cadherin, can occur through direct interactions or proximal engagements [##REF##25620698##72##]. Following this, necrotized cancer cells liberate an ensemble of damage-associated molecular patterns (DAMPs), IL-8, IL-6, CCL2, and CXCL1, orchestrating microglial recruitment, thereby fostering tumor invasiveness and culminating in a self-reinforcing loop [##UREF##8##73##]. This scenario underscores ferroptosis not merely as a cell death pathway but as a critical determinant modulating tumor growth dynamics and invasiveness [##REF##33110073##74##] (Fig. ##FIG##1##2##). It is imperative, therefore, to discern the specific roles of ferroptosis in shaping the TME, as this offers prospective therapeutic avenues.</p>", "<p id=\"Par13\">\n\n</p>", "<title>Enhancing ferroptosis resistance of cancer-associated fibroblasts (CAFs) in cancer cells</title>", "<p id=\"Par14\">CAFs are not mere bystanders in the TME; they serve as crucial facilitators of tumor progression. Recent studies underscore their critical role in modulating the delicate balance of ferroptosis [##REF##31980749##75##]. One of the salient mechanisms by which CAFs bolster cancer cell resilience against ferroptosis is through the provision of vital antioxidants, specifically GSH and Cys. These molecules have been identified as central mediators in the resistance against both platinum-based therapies and ferroptosis-induced cell death. A recent discovery pinpointed a nuanced strategy wherein CAFs secrete exosome-derived miR-522, which post-transcriptionally inhibits the translation of ALOX15 mRNA in gastric cancer cells. ALOX15 plays an important role in the lipid peroxidation process and the accumulation of ROS, which is a hallmark of ferroptosis. By dampening ALOX15 translation, CAFs indirectly shield gastric cancer cells from ferroptotic death [##REF##32106859##76##]. However, this protective aura crafted by CAFs is not unchallenged. CD8<sup>+</sup> T cells have been observed to counteract the antioxidative strategies of CAFs. They secrete IFN-γ, which, upon binding to its cognate receptor interferon regulatory factor 1 (IRF1) on CAFs, promotes the transcription of gamma-glutamyl transferases (GGT5). GGT5 degrades the extracellular GSH that CAFs might acquire, thereby limiting their antioxidant potential. Further, IFN-γsuppresses system Xc<sup>−</sup> transcription by activating the JAK/STAT pathway in CAFs. Such suppression culminates in reduced intracellular pools of GSH and Cys, rendering the neighboring cancer cells susceptible to ferroptosis once more [##REF##27133165##54##].</p>", "<title>The role of lipid peroxidation in influencing DCs antigen presentation</title>", "<p id=\"Par15\">DCs serve as the linchpins of immune initiation, especially within the tumor milieu, where Tumor-associated DCs (TADCs) play a quintessential role in igniting and sustaining T-cell-mediated anti-tumor responses. However, the integrity of their function is not unchallenged in the TME. Recent investigations have pointed to a paradoxical relationship between lipid peroxidation, a pivotal component of ferroptosis, and the antigen presentation abilities of TADCs. Excessive inflammation, especially induced by lipopolysaccharide (LPS), has been found to precipitate ferroptotic events in DCs. Moreover, a seminal study delineated that a surge in LPS levels led not just to ferroptosis but concomitantly instigated immune dysregulation in DCs. Delving deeper into the molecular intricacies revealed Sesn2, traditionally known for its role in apoptosis regulation, as a protective entity safeguarding DCs against ferroptosis, potentially orchestrated via the ATF4-CHOP-CHAC1 signaling cascade [##REF##34482365##77##]. However, another layer of complexity is added by 4-hydroxynonenal (4-HNE), a by-product of lipid peroxidation prevalent in the TME. This molecule was discerned to impair TADCs’ antigen presentation capabilities. Mechanistic insights divulged that 4-HNE exerts its effects primarily by perpetuating the activation of the X-box binding protein (XBP1) gene, subsequently triggering a cascade of endoplasmic reticulum (ER) stress events. This stress, in turn, culminates in an accumulation of oxidized lipids and a surfeit of ROS, collectively compromising the antigen-presenting capacity of TADCs [##REF##20622859##78##, ##REF##26073941##79##].</p>", "<p id=\"Par16\">Interestingly, the activation dynamics of TADCs also unravel a distinct molecular interplay involving ALOX12 and ALOX15 enzymes. These enzymes are found to actively peroxidize both exogenous sources like low-density lipoproteins (LDL) and endogenous membrane lipids, transmuting them into oxidized phosphatidylcholine (Ox-PC). Notably, this transformation, especially in an ischemia-reperfusion injury model, induces ferroptosis and concomitantly stimulates the antioxidant guardian NRF2, which in synergy with 4-HNE, impedes DC maturation. Moreover, the lipid peroxidation machinery, notably NOX2 located in the endosomal membrane of DCs, facilitates the ingress of tumor-associated antigens into the cytoplasm, a crucial step for efficient cross-presentation to CD8 + T cells [##REF##26907999##80##]. It’s imperative to note that M2-TAMs, known for their pro-tumorigenic attributes, also express ALOX12 and ALOX15, raising pertinent questions regarding their potential roles in TAM maturation and polarization dynamics [##REF##25844901##81##–##REF##33513080##84##]. Accordingly, it provides a profound insight into the potential immunosuppressive attributes of TADCs, underscoring the need for targeted therapeutic interventions.”</p>", "<title>Natural kill (NK) cell function regulated by ferroptosis</title>", "<p id=\"Par17\">NK cells have always been recognized for their adeptness in eliminating malignant cells that deftly evade CD8 + T cell surveillance [##REF##31907401##85##]. Within the tumor microenvironment, a specialized subset, Tumor-associated NK (TANK) cells, emerge as pivotal sentinels. Intriguingly, the TME, a hotspot of lipid peroxidation stress, casts a profound influence on these TANK cells. This stress manifests not just as a biochemical change but translates to discernible alterations in the NK cells, most notably, ferroptosis-like cellular morphology and the induction of proteins traditionally associated with ferroptosis. The implications of this lipid peroxidation stress are multifold. A consequential reduction in glycolysis, a crucial metabolic pathway for TANK cell effector functions, dampens their anti-tumor ardor. Yet, nature’s intrinsic checks and balances emerge in the form of NRF2, a linchpin in ferroptosis regulation. NRF2 orchestrates a metabolic recalibration in TANK cells, reviving both glucose metabolism and oxidative phosphorylation (OXPHOS), with a pivotal assist from glutamine supplementation [##UREF##10##86##]. Further delineating the NK cell-ferroptosis nexus, novel therapeutic modalities like CAR-NK cells have entered the limelight. Their ability to induce cancer cell ferroptosis, primarily through the release of IFN-γ which downregulates the SLC3A and SLC7A11 expression, is noteworthy [##REF##35706368##87##]. However, this intricate relationship warrants deeper exploration, as it promises potential breakthroughs in therapeutic applications. Understanding this dynamic could be pivotal in reshaping cancer therapeutics, as schematically presented in Fig. ##FIG##2##3##.</p>", "<p id=\"Par18\">\n\n</p>", "<title>Dynamic modulation of immune response by ferroptotic cancer cells through DAMPs</title>", "<p id=\"Par19\">The intersection of ferroptosis and its potential to induce immunogenic cell death (ICD) remains a contentious issue in current cancer biology research. Although some studies underscore ferroptosis exhibiting hallmark attributes of ICD, the relationship appears to be nuanced and temporally regulated [##UREF##11##88##]. In the initial stages of ferroptosis, there is a prominent release of DAMPs intrinsically related to ICD. Concomitant with this is an elevated ROS production and endoplasmic reticulum (ER) stress, which further magnify DAMP surface exposure. This amplified DAMP exposure is posited to enhance the CTLs-mediated anti-tumor response, providing a potential avenue for leveraging immune responses in cancer treatment [##UREF##11##88##–##REF##23157435##91##]. Endometrial carcinoma (EC), especially in its early and low-grade manifestations, offers compelling insights into this dynamic. Here, initial ferroptotic cell phases have been associated with the secretion of ATP and HMGB1, quintessential DAMPs. These molecules are subsequently identified by TAMs and DCs, resulting in their maturation and activation. Once activated, APCs intensify the inflammatory milieu by secreting cytokines like IL-6, potentially enhancing T-cell infiltration into the tumor and thus bolstering the adaptive immune response [##UREF##13##92##]. However, a pivotal consideration is the dynamic nature of DAMP release. As ferroptosis progresses, the consistent depletion of DAMPs, notably ATP and HMGB1, results in the gradual abrogation of cancer cell immunogenicity. A case in point is calreticulin (CRT), a canonical DAMP. CRT, upon release from apoptotic cells, transforms Ecto-CRT, playing a key role in modulating APC behavior [##UREF##11##88##, ##REF##17657249##93##]. However, Peter et al. recently found that ferroptosis is not a kind of ICD regardless of ferroptosis stages although typical anti-tumor DAMPs are indeed released in this process. Ferroptosis cancer cells reduce DC maturation and cross-presentation of soluble antigens and consequently inhibit immune response.</p>", "<p id=\"Par20\">Some DAMPs released by ferroptotic cancer cells fuel cancer progression [##UREF##12##89##–##REF##23157435##91##]. These DAMPs are usually produced in the process of ferroptosis and derived from peroxidative byproducts in cancer cells. 1-steaoryl-2-15-HpETE-sn-glycero-3-phosphatidylethanolamine (SAPE-OOH) accumulates on the ferroptotic cancer cell membrane and emits an “eat me” signal upon ferroptosis occurs. Recognized by a kind of pattern recognition receptor (PRR), the toll-like receptor (TLR) 2 of TAMs, SAPE-OOH directly guides them to phagocytize ferroptotic cells [##REF##33432112##94##]. Another recent study revealed that peroxide stress triggers autophagy-dependent ferroptosis of PDAC cells and these cells produce DAMP-like 4-HNE and 8-hydroxy-2′-deoxyguanosine (8-OHG) to accelerate the migration and infiltration of TAMs [##UREF##14##95##, ##REF##33311482##96##]. TAMs take up exosomes containing KRASG12D protein, a kind of DAMPs released by ferroptotic PDAC cells, through advanced glycosylation end product-specific receptor (AGER) and polarize into the immunosuppressive type by promoting STAT3-dependent fatty acid oxidation [##REF##25341034##97##–##REF##33522932##99##]. 8-OHG and GMP-AMP synthase (cGAS), two by-products of DNA peroxidation damage in cancer cells attract and activate M2-TAMs by mediating stimulator of interferon genes (STING) pathway activation in the stroma. These TAMs pathologically release various cytokines like IL-6 and NOS2 and ultimately promote the occurrence and development of PDAC [##REF##33311482##96##]. Whether these tumor-promoting effects are time-dependent remains unknown.</p>", "<title>Metabolism reprogramming and ferroptosis vulnerability by environment stresses in TME</title>", "<p id=\"Par21\">Ferroptosis is closely associated with cellular redox metabolism and environmental condition. In the TME, cells adjust metabolic pattern and intensity in response to environmental stresses and reprogrammed metabolism is the hallmark of cancers. The competition for nutrients and extreme environmental conditions like acidosis and hypoxia in TME ultimately regulate ferroptosis and accelerate cancer development (Fig. ##FIG##3##4##) [##REF##26321679##100##–##REF##29386217##102##].</p>", "<p id=\"Par22\">\n\n</p>", "<title>Enhancing ferroptosis resistance of cancer by glucose Starvation in TME</title>", "<p id=\"Par23\">Within the TME, rapidly proliferating cells, such as malignant cells and activated T cells, predominantly rely on glucose as their primary energy source through heightened aerobic glycolysis [##UREF##15##103##]. Recent findings have illustrated that cancer cells, in conjunction with myeloid cells, consume the majority of the available glucose in the TME [##REF##33828302##104##]. Notably, the depletion of glucose appears to confer protection against ferroptosis for both cancer cells and immunosuppressive cells, while concurrently attenuating the anti-tumor functionalities of activated T cells within the TME [##UREF##10##86##, ##REF##26321679##100##]. Intriguingly, a study postulated that under conditions of glucose scarcity, cancer cells adapt by depleting their ATP reserves, allowing them to evade ferroptosis. This energy crisis catalyzes the activation of the AMP-activated protein kinase (AMPK) pathway, which in turn suppresses the synthesis of PUFAs, consequently imparting resistance to ferroptosis [##REF##32029897##105##]. In another pivotal study, it was demonstrated that the uptake of glucose via glucose transporter 1 (GLUT1) potentiates cystine-dependent ferroptosis in PDAC cells. Mechanistically, glucose facilitates glycolysis to promote pyruvate oxidation, TCA cycle and fatty acid synthesis. Glucose deprivation-induced overexpression of pyruvate dehydrogenase kinase 4 (PDK4) subsequently inhibits the tricarboxylic acid (TCA) cycle and lipid peroxidation processes, facilitated by ALOX5 [##REF##33626342##106##]. Of clinical relevance, the efficacy of CD8<sup>+</sup> T cells against tumors diminishes in a glucose-deprived environment [##REF##18792400##107##]. Conversely, active regulatory T cells (Tregs) appear to flourish under such glucose constraints, preferentially metabolizing lactic acid to fuel processes such as the TCA cycle and gluconeogenesis, thereby sustaining their suppressive activities [##REF##33589820##108##]. Despite the pro-tumor advantages conferred by glucose deprivation, one must not overlook the metabolic vulnerabilities it exposes. Recent insights have elucidated that cancer cells with elevated expression of system Xc<sup>−</sup> become susceptible under glucose-restricted conditions in the TME. Pertinently, the targeted inhibition of system Xc<sup>−</sup> can incite ferroptosis in these cancer cells [##UREF##16##109##].</p>", "<title>Amino acid competition for ferroptosis resistance in the TME</title>", "<p id=\"Par24\">The aggressive proliferation of cancer cells, combined with the aberrant tumor vasculature, leads to a scarcity of Cys<sub>2</sub>, Cys, and Glutamine (Gln) in the TME [##REF##25644265##110##, ##REF##27617932##111##]. This sets off intensified oxidative stress, pushing cells within the TME to intensify their reliance on the GSH-based antioxidant system [##REF##21376230##112##, ##REF##19194462##113##]. Notably, anti-tumor immune cells compete with cancer cells and immunosuppressive cells, for Cys and Cys<sub>2</sub> [##REF##27869804##114##].</p>", "<p id=\"Par25\">Emerging evidence from PDAC and chronic B lymphocytic leukemia (CLL) investigations suggests that cancer cells employ alternate strategies to circumvent ferroptosis in the TME. Fascinatingly, in vivo tests show that system Xc<sup>−</sup>-KO PDAC cells can still foster tumors in athymic mice [##REF##27869804##114##–##UREF##17##116##]. A cyclical exchange emerges involving Cys and Cys<sub>2</sub> between system Xc<sup>−</sup>-KO cancer cells, CAFs, and unaltered cancer cells in the TME. Specifically, CAFs and the native cancer cells internalize Cys<sub>2</sub>, metabolizing it to Cys, which is then recycled back into the TME. Here, system Xc<sup>−</sup>-KO PDAC cells absorb it via alternative transporters like ASCT1, ASCT2, LAT1, and SNATs [##UREF##17##116##]. Additionally, bone marrow stromal cells (BMSCs), marked by elevated system Xc<sup>−</sup> expression, have been observed to exude Cys for neighboring CLL cells with heightened demand for GSH and diminished system Xc<sup>−</sup> expression [##REF##22344033##117##, ##REF##30202049##118##]. To form a comprehensive understanding, it is imperative to consider the presence and distribution of APCs, MDSCs, and CAFs, as they likely influence the Cys supply dynamics between T cells and cancer cells.</p>", "<p id=\"Par26\">Gln, much like glucose, is also a critical energy substrate for immune and cancer cells. Contemporary in vivo studies have accentuated that diverse tumors prioritize exogenous Gln, underlining its irreplaceable metabolic function [##REF##33828302##104##]. Gln serves as a complementary source for the TCA cycle. Transported chiefly via SNAT1 and ASCT2, Gln is processed into Glu by glutaminase (GLS). This Glu then morphs into α-ketoglutarate (α-KG), central to the TCA cycle and fatty acid biosynthesis, in a process known as glutaminolysis [##REF##26166707##119##–##UREF##18##121##]. Gao et al. illustrates the essential role of glutaminolysis in promoting CDI ferroptosis. Specifically, part of Glu, synthesized via glutaminolysis, is swapped for Cys through system Xc-, amplifying CDI ferroptosis [##REF##26166707##119##, ##REF##22228304##122##, ##REF##27034505##123##]. Subsequent studies reveal that a significant chunk of exogenous Gln, about a third to half, is essential for the Cys exchange via system Xc<sup>−</sup> [##REF##2903864##124##].</p>", "<title>Reprogrammed lipids metabolism inhibiting anti-tumor immune</title>", "<p id=\"Par27\">Activated and resting T cells both incorporate external lipids essential for their metabolism [##REF##23298210##125##]. Lipid metabolism acts as a regulator for ferroptosis sensitivity and CD36 play a key role in it. Within the TME, the lipid metabolism of CD8<sup>+</sup> T cells undergoes a transformation, characterized by elevated expression of CD36 and a noticeable shift towards reliance on PUFAs. Both cholesterol and fatty acids amplify the expression of the fatty acid translocase CD36 in tumor-infiltrating CD8<sup>+</sup> T cells. This, in turn, boosts the uptake and breakdown of PUFAs and compounds rich in PUFAs, such as oxidized low-density lipoproteins (Ox-LDLs) and oxidized phospholipids (Ox-PLs). The outcome of this shift is twofold: the induction of T-cell ferroptosis and a resultant dysfunction [##REF##27842070##25##, ##UREF##19##126##–##REF##27506793##132##]. In tandem, lipid peroxidation activates P38 kinase, further suppressing T cell function. However, overexpression of GPX4 has shown promise in rescuing these T cells in vivo [##REF##27506793##132##–##UREF##24##134##]. Strategically targeting CD36 amplifies the infiltration capacity and anti-tumor response of CD8<sup>+</sup> T cells [##REF##32066953##61##].</p>", "<p id=\"Par28\">Furthermore, immunosuppressive Tregs exhibit metabolic adaptability in the TME through heightened CD36 expression. Tregs with elevated CD36 expression can preserve their mitochondrial health under high oxidative stress. This is achieved via the peroxisome proliferator-activated receptor-β (PPAR-β), which raises levels of nicotinamide adenine dinucleotide (NAD) and the NAD/NADH ratio [##REF##32066953##61##]. Interestingly, CD36 sees substantial expression in HCC cells, which heightens aerobic glycolysis via the PI3K/AKT/mTOR pathway. This results in an increased lactic acid output, further driving cancer progression [##REF##33771982##135##]. Consequently, the presence of lipids and the acidotic nature of the TME foster ferroptosis in effector T cells but shield Tregs from ferroptosis due to heightened CD36 expression. Extended exposure to cholesterol augments intracellular lipid intake and buildup. This process escalates the expression and activity of GPX4, making cancer cells more resilient against ferroptosis and thus fostering cancer cell metastasis [##REF##34429409##136##].</p>", "<title>Acidification stress enabling cancer cells to evade ferroptosis</title>", "<p id=\"Par29\">Cancer cells intensively utilize anaerobic glycolysis, leading to the production and release of substantial amounts of lactic acid, resulting in extracellular acidification [##REF##31171526##127##, ##REF##34656878##137##]. Hepatocellular carcinoma cells (HCCs) efficiently uptake lactic acid through transporters like hydroxycarboxylic acid receptor 1 (HCAR1) and monocarboxylate transporter 1 (MCT1). Elevated lactic acid levels stimulate the AMPK pathway, leading to an increase in monounsaturated fatty acids (MUFAs) in cell membranes and a decline in ACSL4 expression, helping cells resist ferroptosis [##REF##33296645##138##].</p>", "<p id=\"Par30\">This acidic environment bolsters tumor metastasis by sidestepping ferroptosis. In numerous cancers, lymphatic metastasis tends to precede blood metastasis [##UREF##25##139##, ##UREF##26##140##]. Cancer cells within lymphatic fluid exhibit greater resilience against ferroptosis than those in the bloodstream [##REF##30008815##141##, ##REF##32814895##142##]. One proposed mechanism is that the high oxidative stress in the blood promotes ferroptosis in cancer cells, while those in lymphatic fluid remain unscathed [##REF##26466563##143##, ##REF##26446958##144##]. Notably, lymphatic fluid has an abundance of oleic acid, a type of MUFA. Cancer cells harness this, adjusting their lipid profile to decrease the proportion of PUFAs, facilitated by fatty acid transport proteins (FATP). This uptake of oleic acid plays a unique role, shielding cancer cells from ferroptosis in an ACSL3-dependent manner. Further, the GSH/GSSG ratio is markedly elevated in lymphatic fluid, thereby reducing oxidative stress experienced by the cancer cells.</p>", "<title>Modulation of ferroptosis resistance in cancer cells and TAMs mediated by hypoxia</title>", "<p id=\"Par31\">Hypoxic environments have been recognized to play crucial roles in modulating ferroptosis resistance in both immune and cancer cells. In malignant mesothelioma (MM) cells, the overexpression of carbonic anhydrase 9 (CA-9) orchestrates iron metabolism, granting these cells a marked resistance to ferroptosis during hypoxic conditions [##REF##31442913##145##]. Such resistance in the context of hypoxia has also been documented in hepatocellular carcinoma (HCC), cervical cancer, and MM [##REF##34609072##146##, ##UREF##27##147##]. Similarly, peritoneal metastases of gastric cancer (GC), which are inherently characterized by hypoxia, leverage the HIF-1α pathway to counteract ferroptosis. Specifically, HIF-1α upregulates the transcription of the peritoneal metastasis-associated long non-coding RNA (PMAN). This, in turn, bolsters the production of the ELAV Like RNA Binding Protein 1 (ELAVL1), which stabilizes the translation of SLC7A11 mRNA to defend ferroptosis [##REF##35447413##148##]. However, an anomalous observation in renal clear-cell carcinoma (CCC) reveals that hypoxia, counterintuitively, accentuates the susceptibility of these cancer cells to ferroptosis. Here, HIF-2α selectively augments the cancer cell membrane’s lipid composition with PUFAs by inducing the hypoxia-inducible lipid droplet-associated protein (HILPDA) gene. This modulation renders the cancer cells more prone to ferroptosis in a GPX4-dependent manner [##REF##30962421##149##]. Furthermore, hypoxic environments are implicated in the anomalous formation of neovasculature and the accumulation of acid. This cumulatively ushers in nutrient scarcity and an acidic milieu, instigating a metabolic shift in lipid and glucose pathways, which indirectly sways the ferroptosis sensitivity of cells [##REF##11902584##150##, ##REF##31711497##151##].</p>", "<p id=\"Par32\">In tumors with relatively higher oxygen concentrations, exemplified by early-stage lung cancer and lung metastases, cancer cells mitigate their ferroptosis susceptibility. A notable mechanism involves the selective overexpression of the N-ethyl-maleimide sensitive fusion protein (NSF1), a synthetase modulating iron homeostasis, and the assimilation of sulfur in Cys for synthesizing iron-sulfur clusters (ISCs), which curtails the cellular iron burden. By suppressing NFS1 expression, a surge in iron starvation response is observed, thereby synergistically amplifying ferroptosis induced by agents like erastin or through Cys deprivation [##REF##29168506##152##].</p>", "<p id=\"Par33\">On the immune front, hypoxia is observed to skew TAMs towards the M2 phenotype, thereby favoring ferroptosis resistance through iron metabolic pathways [##REF##27482883##153##, ##REF##26982356##154##]. Investigations on osteoclasts reveal that under normoxic conditions, bone marrow-derived macrophages (BMDMs) propel ferroptosis through ferritinophagy and an iron-starvation response, the latter of which is potentiated by the receptor activator of NF-κB ligand (RANKL), leading to iron overload. In contrast, hypoxic conditions induce human primary macrophages to elevate ferritin expression patterns (e.g., mitochondrial FTMT and FTH), diminishing free intracellular iron and shielding them from ferroptosis. At the molecular level, HIFs directly stifle NCOA4 transcription while simultaneously amplifying the JNK pathway, leading to the production of miR-6862-5p which inhibits NCOA4 translation. This intricately modulated pathway culminates in NCOA4 binding to FTMT, inhibiting ferritinophagy, a specialized autophagic process that triggers ferroptosis by the degradation of ferritin [##REF##32810738##155##–##REF##34006412##157##]. Additionally, hypoxic environments bolster HIF-1α expression in macrophages, thereby inhibiting iron-starvation response, which ultimately attenuates their ferroptosis sensitivity [##REF##33895289##158##]. HIF-2α has been also discerned to elevate the expression of ferroportin (FPN), which depletes intracellular iron content, effectively stymieing ferroptosis [##REF##21419768##159##]. Conclusively, the polarization of TAMs into the M2 phenotype and their evasion from ferroptosis is intricately mediated by hypoxia.</p>", "<title>Cellular interaction and density as a modulator of ferroptosis resistance in Neoplasm</title>", "<p id=\"Par34\">In the intricate milieu of solid tumors, intercellular adhesion, facilitated through E-cadherin, emerges as a central mediator that orchestrates resistance to ferroptosis. This is achieved predominantly via the modulation of the Hippo signaling cascade [##REF##31341276##160##]. Subsequently, this pathway exerts an inhibitory influence on its downstream effector, Yes-associated protein 1 (YAP). The resultant suppression curtails the expression of pivotal proteins such as transferrin receptor 1 (TFRC) and ACSL4, both paramount in determining cellular susceptibility to ferroptosis across in vivo and in vitro paradigms [##REF##31341276##160##]. As another key effector of Hippo pathway, the activity and expression of the PDZ-binding motif (TAZ) is also repressed by escalated cellular density in renal cell carcinoma (RCC) and ovarian cancer (OVCA). TAZ repression has been implicated in reduction of ferroptosis sensitivity, achieved via the inhibition of EMP1-NADPH Oxidase 4 (NOX4) nexus [##REF##33110073##74##, ##REF##31341276##160##–##UREF##29##162##]. Such repression also precipitates a decline in the production of angiopoietin receptor 4 (ANGPTL4), culminating in attenuated activity of NADPH oxidase 2 (NOX2) and concomitantly ferroptotic susceptibility [##REF##31641008##163##]. Taken together, these underscore the pivotal role of cellular interaction and density in amplifying the resistance to ferroptosis in cancer cells.</p>", "<title>Targeting immunophenotype and environment stress to sensitize ferroptosis</title>", "<p id=\"Par35\">The inherent heterogeneity of the TME and the concomitant overlap in metabolic processes governing ferroptosis among immune and neoplastic cells present formidable challenges in optimizing ferroptosis-centric therapeutic modalities [##REF##26248267##164##, ##REF##28187284##165##]. Notably, the manifestation of ferroptosis resistance not only undermines the direct efficacy of ferroptosis inducers but also limits the potential of combinatorial therapeutic strategies. Thus, a ferroptosis combined strategic approach, rooted in the specific environmental, metabolic, and immune characteristics, may offer a tailored mechanism to enhance ferroptotic susceptibility exclusively in cancer cells.</p>", "<title>Immunophenotypic stratification for ferroptosis therapeutics in TME</title>", "<p id=\"Par36\">The intricate heterogeneity of the TME, along with the shared metabolic dependencies of immune cells and cancer cells on ferroptosis pathways, underscores the complexities of ferroptosis therapy [##REF##26248267##164##, ##REF##28187284##165##]. Integrative approaches, particularly combining immune checkpoint blockade (ICB) with ferroptosis-augmenting agents such as system Xc<sup>−</sup> inhibitors, Cys modulators, and GPX4 blockers, have showcased promising anti-tumor potential [##UREF##11##88##, ##UREF##12##89##, ##REF##23157435##91##, ##REF##16778987##166##]. Yet, the therapeutic suitability hinges crucially on specific immunophenotypes of TME, delineated by precise evaluation criteria. It is imperative to understand that immunophenotyping assesses the spatial distribution, diversity, and density of immune cells within TME landscapes. Based on the dual parameters of tumor immunogenicity and immune cell infiltration, we can broadly classify immunophenotypes into three archetypes: cold, hot, and altered tumors [##UREF##30##167##]. (Refer to Table ##TAB##0##1## for comprehensive details).</p>", "<p id=\"Par37\">\n\n</p>", "<title>Hot tumors</title>", "<p id=\"Par38\">Typically marked by high microsatellite instability (MSI-H), these tumors inherently promote robust infiltration of T-cells within the TME core [##REF##30610226##168##]. Considering the heightened susceptibility of activated T cells to ferroptosis, hot tumors may not be prime candidates for initial ferroptosis induction [##REF##25824832##39##]. A deeper dive into the metabolic milieu reveals nuanced interplay, especially around Cys dynamics between cancer cells and T cells, compounded by subsequent competitive interactions with MDSCs. As such, a meticulous evaluation of the spatial distribution and metabolic activity of APCs and MDSCs in juxtaposition to T cells could provide vital predictive insights for ferroptosis therapeutic trajectories [##REF##31019077##41##, ##REF##22355778##42##, ##REF##25824823##56##]. Notably, while hot tumors exhibit a generally favorable response trajectory to immunotherapy, the emergence of therapeutic resistance remains unresolved [##REF##28187290##169##]. This resistance is engendered by a myriad of intrinsic and adaptive immunosuppressive shifts that evolve with dynamic TME alterations, such as PD-L1 overexpression, selective recruitment of immunosuppressive cell phenotypes, and the eventual T cell functional exhaustion [##REF##27828943##170##, ##REF##32000802##171##]. Given this backdrop, the adjunctive use of ferroptosis inducers might offer a therapeutic advantage, particularly as dedifferentiated cancer cell phenotypes, with their accentuated ferroptotic sensitivity, come into focus, where GPX4 emerges as a pivotal mediator [##REF##33110073##74##, ##REF##31175120##115##, ##UREF##31##172##, ##REF##32896720##173##]. Researchers recently in melanoma model found that ferroptosis is positively associated with immunotherapy and cancer with high ferroptosis activity tends to have a hot TME [##REF##35945204##174##]. Researchers recently also found that ferrptosis-related genes (FRG)-based high-risk score is positively correlated with enrichment of ICB-related positive signatures in the GBM, which possibly predicts ferroptosis treatment combined with immunotherapy [##REF##33969928##175##].</p>", "<title>Cold tumors</title>", "<p id=\"Par39\">Distinctly characterized by a relative lack of central inflammation, these tumors pose a clinical conundrum to elevate CTL infiltration, thereby amplifying the immune response [##REF##30610226##168##, ##REF##32610070##176##]. In this scenario, ferroptosis not only offers therapeutic potential but also serves as an immunological catalyst. Specifically, DAMPs exuded from ferroptotic cancer cells can elicit pronounced immunogenicity, in turn driving the recruitment of APCs and T cells to invoke a tailored adaptive immune response [##UREF##11##88##, ##UREF##13##92##, ##REF##33432112##94##, ##REF##25019241##177##]. However, it’s crucial to elucidate the temporal kinetics of DAMP release, aiming to determine the optimal therapeutic temporal window.</p>", "<title>Altered tumors</title>", "<p id=\"Par40\">This category encompasses both immune-exclusive and immune-suppressed phenotypes. The former manifests barriers hindering immune cell infiltration, whereas the latter presents a TME saturated with immunosuppressive entities — notably Tregs, MDSCs, and M2-type TAMs — that impair the intrinsic anti-tumor efficacy of immune cells [##REF##30610226##168##, ##REF##19258510##178##, ##REF##24648340##179##]. These immunosupressive cells sensitive to ferroptosis. ICB combined with ferroptosis therapy may have the most clinical benefit for the immunosuppressive type and reshape the immunotype more senstive to immunotherapy. In immune-exclusive phenotypic landscapes, a salient feature is the peripheral T cell localization, barred from accessing the tumor core. This restrictive pattern begs further scrutiny, especially within the framework of ferroptosis and the potential modulatory influence of DAMPs on immune infiltration dynamics. Reasons for the infiltrative barrier of T cells include the lack of chemokines like C-X-C motif ligands (CXCLs) and C-C motif ligands (CCLs), deregulation of extracellular matrix proteins, abnormal vasculature, and hypoxia [##UREF##32##180##–##REF##29120755##182##]. It appears that this type of TME rarely benefits from ferroptosis-based treatment. Whether some DAMPs released by ferroptosis cancer cells play an alternative role in inducing immune cell infiltration remains obscure. Ferroptosis and its ability to reshape the physical barrier need to be further investigated in the future.</p>", "<title>Leveraging specific metabolic phenotypes of cancer with environmental stressors for ferroptosis sensitization</title>", "<p id=\"Par41\">Tumor-infiltrating cancer cells often manifest distinct metabolic phenotypes that render them more susceptible to ferroptosis. For instance, clear cell renal cell carcinoma (ccRCC) is distinguished by its high lipid and glycogen content, which provides a unique therapeutic vulnerability [##REF##32814895##142##]. A seminal study has elucidated that Von Hippel-Lindau (VHL)-deficient ccRCC, which features characteristic lipid and glycogen-laden cytoplasmic deposits, circumvents ferroptosis via the upregulation of the adipokine chemerin. This upregulation serves a dual role, aiding both autocrine and paracrine signaling of hypoxia-inducible factor (HIF)-2α and krueppel-like factor 6 (KLF6). On a molecular level, chemerin serves to stabilize lipid oxidation and fatty acid oxidation (FAO) equilibrium within the cancer cells. Additionally, it amplifies the expression of HIF-1α and HIF-2α in an autocrine manner, underscoring its multifaceted role in modulating the metabolic landscape of tumors [##REF##33757970##183##]. Furthermore, basal-like breast cancers (BLBC), exhibit specific metabolic shifts favoring transsulfuration. When the TME is starved of Cys<sub>2</sub> and Cys, cancer cells activate the GCN2-ATF4 axis, bolstering the expression of CTH and CBS, two enzymes vital for the transsulfuration pathway to produce Cys. This metabolic phenotype is highly sensitive to Cys levels [##UREF##33##184##, ##UREF##34##185##]. The luminal androgen receptor (LAR) subtype of TNBC, a specific metabolic subtype characterized by the increasing expression of oxidized phosphatidylethanolamines and glutathione metabolism, especially GPX4, is hypersensitive to ferroptosis induced by GPX4 inhibitors [##REF##36257316##186##]. Recent findings have illuminated a particular subtype of small cell lung cancer (SCLC) that, while resistant to ferroptosis, displays an addiction to the TRX system. Remarkably, inhibitory interventions targeting TRX render this subtype conspicuously susceptible to ferroptosis [##UREF##35##187##]. In a similar vein, melanomas that undergo epithelial-to-mesenchymal transition (EMT) exhibit an increased sensitivity to ferroptosis. However, this characteristic is juxtaposed against their inherent resistance to immunotherapies, highlighting the intricate interplay of metabolic and immune landscapes within tumor microenvironments [##REF##32814895##142##].</p>", "<title>Integrative therapeutic strategies by navigating the environmental complexities of the TME</title>", "<p id=\"Par42\">Environmental intricacies within the TME, including hypoxic conditions, nutrient scarcity, and lactic acid accrual, not only bolster neoplastic resistance to ferroptosis but concomitantly exacerbate T cell vulnerability thereto [##UREF##20##129##, ##UREF##21##130##, ##REF##31442913##145##, ##REF##34609072##146##]. Consequently, strategies aimed at reconfiguring these TME constraints present intriguing therapeutic avenues, as outlined in Table ##TAB##1##2##.</p>", "<p id=\"Par43\">\n\n</p>", "<p id=\"Par44\">Due to the glucose starvation, cancer cells exhibit a nuanced metabolic interdependence on both Gln and Cys, situating the system Xc<sup>−</sup> at a pivotal juncture between nutrient reliance and ferroptosis defense.</p>", "<p id=\"Par45\">A research by Goji et al. highlights that, under glucose-starved conditions in vitro, the additional Cys<sub>2</sub> uptake via system Xc<sup>−</sup> swiftly triggers NADPH exhaustion, ROS generation, and ensuing cell death in glioblastoma cells [##REF##29038291##188##]. These revelations spotlight a potential therapeutic avenue: destabilizing the balance between Gln and Cys could potentially thwart cancer cell growth [##UREF##16##109##]. Some investigations in vivo have demonstrated that solitary Gln blockade not only orchestrates neoplastic cell demise but also markedly augments T cell anti-tumoral activity and ameliorates conditions of hypoxia, acidosis, and nutrient paucity [##REF##33828302##104##, ##REF##28429737##189##, ##UREF##36##190##]. Conjoint therapeutic regimens encompassing Gln and system Xc<sup>−</sup> blockades emerge as prospective interventions. Study indicates that cancer cells with an upregulated system Xc- display an increased Gln dependence, though glucose can somewhat alleviate this dependency [##REF##28429737##189##]. This suggests that anti-tumor effects mediated by Gln blockade may amplify on tumor cells with high system Xc expression. Intriguingly, tumors harboring KRAS mutations, exemplified by pancreatic neoplasms, resort to micropinocytosis for extracellular protein uptake, subsequently catabolizing these into Gln [##UREF##37##191##, ##REF##23665962##192##]. Tumors with MYC oncogenic aberrations exhibit a pronounced Gln metabolic proclivity, postulating its potential utility as a therapeutic biomarker [##REF##28429737##189##, ##REF##19033189##193##].</p>", "<p id=\"Par46\">Acidosis in TME instigates a metabolic paradigm shift, predominantly steered by HIF-1α, transitioning from aerobic glycolysis towards glutamine and lipid metabolism for both energy production and intermediate biosynthesis. Such acidic vicinities, concomitant with hypoxia and metabolite build-up like lactic acid, necessitate therapeutic consideration [##REF##28912578##194##]. Both HIFs and CD36 emerge as pivotal therapeutic fulcrums. Cumulative data in vivo and in vitro authenticate the roles of both HIF-2α and HIF-1α in potentiating CD36 expression, consequently amplifying fatty acid assimilation in hypoxic cells [##REF##32432822##195##, ##REF##19640849##196##]. CD36 inhibition not only disrupts Tregs mitochondrial functionality but also augments ferroptotic sensitization in neoplasms through lactic acid attenuation, while HIFs inhibition prevents the pro-tumor polarization of TAMs, simultaneously reducing neoplastic ferroptotic resistance. Conjoint targeting of CD36 and HIFs offers therapeutic promise.</p>", "<p id=\"Par47\">Moreover, the positive correlation between neoplastic cell interaction and density and ferroptosis resistance suggests that the TME’s cellular composition could serve as an indicative parameter for gauging ferroptosis resilience and the clinical efficacy of ferroptosis-centric therapeutics. In this context, the potential exploitation of blockers, such as E-cadherin and the Hippo signaling cascade, remains an area of academic and therapeutic interest.</p>", "<title>Cellular regulation of ferroptosis defensive mechanism in the TME</title>", "<p id=\"Par48\">In cancers predicated on GPX4 dependency, Cys availability emerges as a pivotal determinant of neoplastic resistance to ferroptosis. Within the TME, rigorous competition ensues between cancer cells and T cells for Cys acquisition [##REF##31019077##41##, ##REF##11792859##45##]. The complex cellular conditions within the TME wields a substantial influence on the sensitivity to ferroptosis. Considering the overarching influence of MDSCs, CAFs and M2-TAMs in protecting cancer cells but sensitizing T cells to ferroptosis, particularly in malignancies such as PDAC that are replete with these cellular subsets, integrative strategies that concurrently target these cellular entities and induce cancer cell ferroptosis appear cogent. Additionally, M2-TAMs fortify HIFs expression, which fosters T-cell susceptibility to ferroptosis while concurrently imparting ferroptotic resilience of neoplastic cells. It is noteworthy that DAMPs, when liberated by ferroptotic M2-TAMs, potentiate the immune response of T cells, [##REF##35706368##87##, ##REF##23385730##197##]. An area that warrants deeper academic exploration pertains to the TRX antioxidant system. Historically, its significance might have been somewhat overshadowed. Such insights, while nascent, underscore the profound therapeutic potential inherent in unraveling the complexities of cellular interactions and dependencies within the TME.</p>", "<title>Comprehensive immunotherapy, chemotherapy and radiotherapy treatments with ferroptosis</title>", "<title>Immunotherapy treatment with ferroptosis in clinical</title>", "<p id=\"Par49\">Researchers have made plenty of beneficial explorations in the combination of immunotherapy and ferroptosis treatment. In the LAR subtype of TNBC, GPX4 inhibitors enhance the anti-tumor immunity. The combination of GPX4 inhibitor and PD-1 blockade is more efficient than monotherapy in vivo [##REF##36257316##186##]. In glioma, where ferroptosis is the main programmed cell death (PCD), ferroptosis contributed to immunosuppressive TME mediated by TAMs, which leads to malignant progression and poor prognosis. Blocking ferroptosis is thought to be an efficient method to improve the efficacy of ICB [##REF##35148413##198##]. Researchers in melanoma developed a ferroptosis score (FPS) model based on 32 ferroptosis-related genes to predict the outcome of cancer. Then, they found that high-FPS may predict more active tumor immune microenvironment and better efficacy of ICB such as PD-1 blockade [##REF##35945204##174##]. Fan et al. found that BEBT-908, an inhibitor targeting PI3K and HDAC, induced immunogenic ferroptotic cell death of cancer cells and enhanced ICB therapy by upregulating MHC class I and activating IFN-γ signal [##REF##34711611##199##]. Statin promotes immunotherapy by promoting ferroptosis of NSCLC cancer cells and inhibiting PD-L1 expression [##UREF##38##200##]. FSP1 inhibition greatly promoted ferroptosis of cancer cells and infiltration of immune cells like DCs, macrophages, and T cells. iFSP1 synergistic with immunotherapy significantly reduced the burden of HCC in vivo [##REF##36893885##201##]. Researchers found inflammation-associated ferroptosis (IAF) biomarkers positively predicts the PD-L1 expression, MSI, TMB and ICB response rate [##REF##37248957##202##]. Short-time starvation of methionine promotes ferroptosis by stimulation of CHAC1 transcription synergistically with CD8 + T cells and enhances ICB therapy. Exogenous Methionine intermittent starvation, system xc- and PD-1 blockade combination treatment have a profound anti-tumor efficacy [##REF##37553341##203##]. Ferritin light chain (FTL) facilitates cancer cell ferroptosis in GBM to polarize TAMs into the M2-type contributing to pro-tumor TME. Inhibition of FTL is a promising strategy to sensitize GBM to PD-1 blockade [##REF##37441589##204##].</p>", "<title>Integrating ferroptosis with chemotherapeutic strategies</title>", "<p id=\"Par50\">Chemotherapy remains a pivotal therapeutic modality for a plethora of solid malignancies, yet the specter of chemoresistance invariably poses a significant impediment [##UREF##39##205##]. Intriguingly, a discernible nexus has been identified between cisplatin resistance and ferroptosis resistance within the tumor milieu. Malignant cells that manifest cisplatin resistance concomitantly exhibit upregulation of genes affiliated with ferroptosis resistance [##UREF##40##206##–##REF##27354763##208##]. In this context, cisplatin-resistant neoplastic cells overexpress the Wnt pathway membrane receptor, frizzled homolog 7 (FZD7), which subsequently activates TP63, culminating in augmented GPX4 expression [##REF##29212036##209##, ##REF##33172933##210##]. A myriad of cancer phenotypes evolves cisplatin resistance by elevating the expression of system Xc<sup>−</sup> and preserving elevated GSH concentrations [##REF##12644836##211##–##UREF##41##213##]. Recent investigations underscore that cisplatin can indeed incite ferroptosis in cancer cells, highlighting the potential role of chemotherapy as a pivotal trigger for ferroptosis [##REF##28494534##214##, ##REF##33781830##215##]. Drug-resistant malignant cells, in tandem with adjacent stromal constituents, might engender a protective cocoon, enabling vulnerable cancerous cells to elude both ferroptosis and chemotherapy. Notably, CAFs have been implicated in curtailing cisplatin accumulation, thereby promoting resistance to both chemotherapy and ferroptosis by proffering GSH and cysteine to ovarian cancer (OVCA) cells [##REF##27133165##54##]. Further, the miR-4443, found to be amplified in cisplatin-resistant non-small cell lung cancer (NSCLC) cells, is conveyed to sensitive cells via exosomes, thereby amplifying FSP1 expression, pivotal for averting ferroptosis. In contrast, IFN-γ, secreted by CD8<sup>+</sup> T cells, diminishes system Xc<sup>−</sup> in malignant cells, thereby mitigating cisplatin resistance through the JAK/STAT signaling cascade [##REF##27133165##54##]. The intricate orchestration between cisplatin resistance mechanisms and the ferroptosis pathway cannot be overstated [##REF##33781830##215##]. Poignantly, co-administration of GPX4 and system Xc<sup>−</sup> inhibitors alongside cisplatin has surmounted chemotherapy resistance, thereby magnifying the anti-neoplastic response in diverse tumors [##REF##28494534##214##, ##REF##29343855##216##, ##UREF##42##217##].</p>", "<p id=\"Par51\">The resistance to the chemotherapeutic agent Temozolomide (TMZ), primarily deployed for gliomas, is also intricately tethered to ferroptosis resistance, engendered by elevated system Xc<sup>−</sup> and GSH expression, which concurrently magnify TMZ sensitivity [##REF##32656078##218##, ##REF##25585997##219##]. Furthermore, malignant cells modulate intracellular iron homeostasis via lipocalin-2, thereby obviating ferroptosis and instigating resistance to 5-fluorouracil [##REF##34146401##220##]. Such chemoresistant phenotypes strikingly mirror ferroptosis resistance patterns, especially concerning canonical targets like GPX4, system Xc<sup>−</sup>, FSP1, and NRF2. Consequently, profiling these ferroptosis targets in chemoresistant neoplasms emerges as an imperious necessity. However, the adaptive response to chemotherapy encompasses the induction of the MTDH gene, which amplifies the mesenchymal phenotype of neoplasms, bolstering drug resistance. Nevertheless, diminishing GPX4 and system Xc<sup>−</sup> expression can augment susceptibility to ferroptosis [##REF##31527591##221##]. Ferroptosis resistance surfaces as a novel rationale underpinning post-chemotherapy tumor resurgence.</p>", "<p id=\"Par52\">For PDAC patients, surgical intervention coupled with adjuvant multi-drug chemotherapy remains the bulwark for enhancing survival. Gemcitabine resistance, inherent in PDAC, continues to perplex clinicians [##REF##30341417##222##]. Recent elucidations intimate that ferroptosis resistance, spearheaded by system Xc<sup>−</sup>hyperexpression, is conjoined with gemcitabine resistance [##REF##33313092##223##, ##REF##18648370##224##]. Intriguingly, system Xc<sup>−</sup> inhibition in PDAC cells engenders GSH depletion in vitro, precipitating ferroptosis and resuscitating sensitivity to both gemcitabine and cisplatin [##REF##31175120##115##].</p>", "<p id=\"Par53\">The profound interplay between chemoresistance and ferroptosis resistance in neoplasms necessitates re-envisioning therapeutic paradigms. The resurgence of tumors post-chemotherapy can be attributed, at least partially, to ferroptosis resistance. This accentuates the theoretical viability of amalgamated treatment regimens. In this milieu, modulating the TME and metabolic targets to exclusively amplify the ferroptosis sensitivity in malignant cells might emerge as the lynchpin in transcending the barriers of chemoresistance.</p>", "<title>Ferroptosis synergy in radiotherapeutic strategies</title>", "<p id=\"Par54\">Radiotherapy (RT) operates by leveraging ionizing radiation (IR) to catalyze the generation of ROS and free radicals, thereby inflicting damage upon DNA and cellular membranes [##REF##33537080##225##]. Recent revelations suggest that ferroptosis plays a pivotal role as a novel mechanism underlying RT-induced oncogenic cell death [##REF##31949285##226##, ##REF##31899616##227##]. A notable phenotype is that cancer cells demonstrating radioresistance also manifest a concomitant resistance to ferroptosis [##REF##31899616##227##, ##UREF##43##228##]. Specifically, lung cancers with kelch-like ECH-associated protein 1 (KEAP1) mutations exhibit resistance to ferroptosis and radiotherapy. This is mediated via the augmented transcription of CoQ/FSP1 under the auspices of NRF2. Critically, targeting the CoQ/FSP1 axis can precipitate ferroptosis in KEAP1-deficient lung cancers, thus bolstering their radiosensitivity [##REF##35459868##229##]. This process appears to be intertwined with the surge in ROS and ACSL4 production. However, tumors harboring P53 mutations provide an intriguing counter-narrative. Within this milieu, RT augments the expression of the P53 gene, countering the ferroptosis resistance elicited by system Xc<sup>−</sup> upregulation and GSH synthesis, leading to enhanced radiosensitivity [##REF##33927351##230##].</p>", "<p id=\"Par55\">The amplification of RT-induced ferroptosis can synergistically potentiate the immune response. From a mechanistic vantage, the radiation-induced bystander effect (RIBE) manifests in RT-afflicted cells through the liberation of radiation-tinged microparticles (RT-MPs). This instigates ICD within proximal cancer cells, predominantly via ferroptosis. Such ferroptotic cells lure an enhanced infiltration of TAMs. These TAMs undergo a transformative polarization towards an anti-tumoral phenotype, guided by the activation of the JAK/STAT and MAPK pathways. Importantly, these TAMs augment the expression of PD-L1 in neoplastic cells through the endocytic uptake of RT-MPs, which markedly enhances immunotherapeutic outcomes [##REF##32232155##231##]. Additionally, activated CD8 + T cells bolster the radiotherapeutic effect via ferroptosis. The tandem actions of IFN-γ derived from CD8 + T cells and the activation of the ataxia-telangiectasia mutated (ATM) gene by radiotherapy synergistically inhibit SCL7A11 expression, optimizing therapeutic outcomes [##REF##31554642##232##, ##REF##31320750##233##].</p>", "<p id=\"Par56\">Yet, hypoxia in the TME can induce hypoxia-inducible factors (HIFs), creating barriers to both radiotherapy and ferroptosis [##REF##31711497##151##]. Consequently, system Xc<sup>−</sup> and GPX4 witness an adaptive overexpression within cancer cells, offering a sanctuary against radiotherapy. Therefore, ferroptosis inducers can provide a synergistic boon to radiotherapeutic endeavors [##REF##31949285##226##, ##REF##31800616##234##]. Given the profound mechanistic interlinkages between ferroptosis and radiation therapy, factors catalyzing ferroptosis resistance emerge as critical players in shaping radiotherapeutic outcomes. The efficacy of radiotherapy can be substantially amplified by judiciously coupling it with agents that sensitize malignant cells to ferroptosis.</p>", "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contribution</title>", "<p>YZH, YLZ, and SY draft the manuscript. JYL, MYW, and PY provided advice on the draft. QFL (Qiaofei Liu) and QL (Quan Liao) revised the manuscript. All authors reviewed and approved the final version.</p>", "<title>Funding</title>", "<p>This work was supported by the National Natural Science Foundation of China (82373230,82373289,82172765), National High-Level Hospital Clinical Research Funding (2022-PUMCH-D-001), CAMS Innovation Fund for Medical Sciences (CIFMS, 2021-I2M-1-002).</p>", "<title>Data Availability</title>", "<p>Not applicable.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par59\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par60\">All authors agreed the publication.</p>", "<title>Competing interests</title>", "<p id=\"Par61\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Regulation of ferroptosis [##REF##34312075##242##]: cells require PUFAs for maintaining energy metabolism, with tremendous ROS production to oxidize PUFAs, especially AAs into PLOOH, which leads to cell membrane rupture and cell death. Iron catalyzes this process. System Xc<sup>−</sup> transports Cys<sub>2</sub> for the synthesis of GSH. GPX4 reduces the PLOOH into PLOH by GSH to resist ferroptosis. TXN pathway plays as an alternative way when GPX4 is inhibited. BH4 and CoQ also act as anti-ferroptosis way due to the function of eliminating ROS. In mitochondria, where ROS proliferates, DHODH inhibits mitochondrial ferroptosis cooperating with mitochondria GPX4</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>TANs are attracted by necrosis cancer tissue releasing HMGB1 and move to TME, where they are polarized and activated as N2-type TANs by TGF-β and G-CSF secreted from cancer cells. These TANs promote the ferroptosis of cancer cells by MPO, which fuels tumor progression. Ferroptotic cancer cells attract TAMs by other DAMPs, including 4-HNE, 8-OHG, and SAPE-OOH, and these TAMs are polarized into pro-tumor M2-type TAMs. Ferroptotic cancer cells amplify immune response by inducing ICD to mature and activate APCs</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>The complex interaction of cells in the TME: CD8<sup>+</sup> T cells kill cancer cells by promoting ferroptosis. Ferroptotic cancer cells release damage-associated molecular patterns (DAMPs), inducing the maturation of DCs and enhancing immune response. Activated APCs like DCs and macrophages reduce Cys<sub>2</sub> into Cys to supply CD8<sup>+</sup> T cells for GSH synthesis. MDSCs with a powerful intracellular storage capacity of Cys<sub>2</sub> compete with APCs for Cys<sub>2</sub>, promoting T cell ferroptosis. CAFs are principal donor cells of GSH for cancer cells to help cancer cells fight ferroptosis and resist chemotherapy drugs like Pt. CAFs also secrete exosome-miR-522 to inhibit ALOX15 translation in cancer cells. CD8<sup>+</sup> T cells promote GGT5 and interfere with system Xc<sup>−</sup> expression reducing GSH supplements for cancer cells</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Various metabolism process exists in TME, including lipid, amino acid, and glucose metabolism. Cholesterol in TME induces CD36 overexpression in T cells to promote the absorption of PUFAs, Ox-LDL, and Ox-PL in cells, fueling the ferroptosis of Tregs and CD8<sup>+</sup> T cells. However, CD36 expression on Tregs maintains mitochondrial fitness to protect them from ferroptosis. Intensive glycolysis of cancer cells in TME leads to glucose starvation. It dictates ferroptosis resistance by activating the AMPK pathway to improve the MUFAs proportion of cell membrane and inducing over-expression of PDK4 to repress the TCA cycle and activity of ALOX. Lactic acid is taken in cancer cells and activates the AMPK pathway and ACSL4 to inhibit ferroptosis. Gln has recently been thought of as the leading energy metabolism resource participating in TCA and FA synthesis by glutaminolysis. Gln metabolism antagonizes with system Xc<sup>−</sup> antioxidation function</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Possible combination therapy for these immunophenotypes of TME with different immune feature</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Immune phenotype</th><th align=\"left\">Features</th><th align=\"left\">Treatment strategy</th></tr></thead><tbody><tr><td align=\"left\">Cold tumor</td><td align=\"left\">T cell deficiency, low tumor mutational burden, and poor antigen presentation [##REF##30610226##168##]</td><td align=\"left\">Promote cancer ferroptosis to heat cancer and combine with immunotherapy like ICB.</td></tr><tr><td align=\"left\">Immune-suppressive tumor</td><td align=\"left\">Full of immunosuppressive cells like MDSCs, Tregs, and M2-type TAMs with local adaptive immunosuppression [##REF##27084738##243##]</td><td align=\"left\">Combine immunotherapy with ferroptosis therapy targeting immunosuppressive cells, especially MDSCs, and M2-TAMs.</td></tr><tr><td align=\"left\">Immune-excluded tumor</td><td align=\"left\">ECM, hypoxia, and deficient chemokines inhibiting the recruitment of T cells and establishing immunosuppression [##REF##30610226##168##]</td><td align=\"left\">Need more investigation. HIFs inhibitors combined with ferroptosis therapy and chemokines may be an optional method.</td></tr><tr><td align=\"left\">Hot tumor</td><td align=\"left\">Adequate infiltration of anti-cancer T cells in the center of TME [##REF##32161398##244##]</td><td align=\"left\">Combine with ferroptosis therapy when drug resistance to immunotherapy occurs, especially for cancer cells with dedifferentiated phenotypes.</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>The possible microenvironmental sensitization biomarkers and targets synergistic with ferroptosis inducers and sensitizing mechanisms</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Synergistic sensitization targets</th><th align=\"left\">Microenvironmental factors</th><th align=\"left\">Mechanisms</th></tr></thead><tbody><tr><td align=\"left\">CD36 and HIFs</td><td align=\"left\"><p>Lipids, PUFAs, and</p><p>hypoxia</p></td><td align=\"left\">Suppression of CD36 expression decreases ferroptosis sensitivity of anti-tumor T cells and destroys mitochondria fitness of Treg. HIFs antibody prevents pro-tumor polarization of TAMs and facilitates M2-type TAMs ferroptosis by affecting iron metabolism [##REF##27482883##153##, ##REF##26982356##154##]. CD36 and HIFs have a synergistic effect [##REF##32432822##195##, ##REF##19640849##196##].</td></tr><tr><td align=\"left\">HCAR1and MCT1</td><td align=\"left\">Lactic acid</td><td align=\"left\">The abundant lactic acid in the TME is taken in cancer cells by transporters HCAR1 and MCT1. It activates the AMPK pathway to produce more anti-ferroptosis MUFAs, and a high level of lactic acid also inhibits the expression of ACSL4 [##REF##33296645##138##, ##REF##28416194##245##].</td></tr><tr><td align=\"left\">Gln/system Xc<sup>−</sup></td><td align=\"left\">Glucose, Gln and Cys</td><td align=\"left\">Gln metabolism antagonizes the antioxidation function of system Xc<sup>−</sup>. Cys-deprivation triggers the death of cancer cells with extensive expression of system Xc<sup>−</sup>. Conversely, CDI ferroptosis occurs in cancer cells with low expression of system Xc<sup>−</sup> [##UREF##16##109##].</td></tr><tr><td align=\"left\">E-cadherin</td><td align=\"left\">Cancer cell interaction</td><td align=\"left\">Interaction of cancer cells promotes the expression of E-cadherin to activate the Hippo pathway, inhibiting the expression of ANGPTL4, TFRC, and ACSL4 and the production of ROS to maintain resistance to ferroptosis [##REF##31341276##160##, ##UREF##29##162##].</td></tr></tbody></table></table-wrap>" ]
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[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Yuze Hua, Sen Yang, Yalu Zhang contributed equally to this work.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"13046_2023_2925_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>", "<media xlink:href=\"13046_2023_2925_MOESM2_ESM.docx\"><caption><p>Supplementary Material 2</p></caption></media>" ]
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{ "acronym": [ "4-HNE", "8-OHG", "α-KG", "AA", "ACSL4", "AGER", "ALOX-15", "AMPK", "ANGPTL4", "APCs", "ASAH2", "ASCT", "ATM", "BH4", "CAFs", "CBS", "CCC", "ccRCC", "CDI", "cGAS", "CLL", "CoQ10", "CRT", "CTH", "CTX", "Cys", "Cys2", "DAMPs", "DCs", "DHODH", "EC", "ECM", "ELAVL1", "EMP1-NOX4", "ER", "FPN", "FSP1", "FTH", "FTMT", "GBM", "GC", "GCL", "G-CSF", "GGT5", "Gln", "GLS", "GPX4", "GSH", "HCAR1", "HCC", "HIFs", "HILPDA", "HO-1", "ICB", "ICD", "IG", "IL-4il", "ILCs", "iNOS", "LDL", "L-Glu", "MCT1", "MDSCs", "MMP", "MPO", "mROS", "MSI-H", "NAD+/ Coenzyme I", "NCOA4", "NK cells", "NOXs", "ox-PC", "Ox-PE", "PDAC", "PDK4", "PLOOH", "PPAR-β", "PRRs", "PUFA", "PUFA-PL", "PUFAs", "RANKL", "RIBE", "ROS", "RT", "RTA", "RT-MPs", "SAPE-OOH", "SCD1", "SNAT1", "STING", "TAA", "TADCs", "TAMs", "ta-NKs", "TANs", "TAZ", "TCA", "TFRC", "TLRs", "TME", "TMZ", "TNFR1", "Trf1", "TrxR", "TXN or TRX", "TXNRD1", "XBP1", "BMSCs" ], "definition": [ "4-hydroxynonenal", "8-hydroxy-2′-deoxyguanosine", "α-ketoglutarate", "Arachidonic acid", "Acyl-CoA synthetase long-chain family member 4", "Advanced glycosylation end product-specific receptor", "Arachidonic acid lipoxygenase 15", "AMP-activated protein kinase", "Angiopoietin receptor 4", "Antigen presentation cells", "N-acylsphingosine amidohydrolase", "Alanine-serine-cysteine transporter", "Ataxia-Telangiectasia Mutated", "Tetrahvdrobiopterin", "Cancer-associated fibroblasts", "Cystathionine β-synthase", "Clear-cell carcinoma", "Clear cell renal cell carcinoma", "Cysteine-deprivation-induced", "GMP-AMP synthase", "Chronic B lymphocytic leukemia", "Coenzymes Q10", "Calreticulin", "Cystathionine γ-lyase", "Cyclophosphamide", "Cysteine", "Cystine", "Damage-associated molecular patterns", "Dendritic cells", "Dihydroorotate dehydrogenase", "Endometrial cancer", "Extracellular matrix", "Peritoneal metastasis associated long noncoding RNA (PMAN) to improve ELAV Like RNA Binding Protein 1", "Epithelial membrane protein 1-NADPH oxidase 4", "Endoplasmic reticulum", "Ferroportin", "Ferroptosis suppressor protein 1", "Ferritin heavy (chain)", "Mitochondrial ferritin", "Glioblastoma", "Gastric cancer", "Glutamate-cysteine ligase", "Granulocyte-colony stimulating factor", "Gamma-glutamyl transferases", "Glutamine", "Glutaminase", "Glutathione peroxidase 4", "Glutathione", "Hydroxycarboxylic acid receptor 1", "Hepatocellular carcinoma", "Hypoxia-inducible factors", "Hypoxia-inducible lipid droplet-associated protein", "Heme oxygenase-1", "Immune checkpoint blockade", "Immunogenic cell death", "Immunogenicity", "Interleukin-4-induced1", "Innate lymphoid cells", "Inducible nitric oxide synthase", "Low-density lipoproteins", "L-glutamic acid", "Monocarboxylate transporter 1", "Myeloid-derived suppressor cells", "Mitochondrial membrane potential", "Myeloperoxidase", "Mitochondrial ROS", "High microsatellite instability", "Nicotinamide adenine dinucleotide", "Nuclear receptor coactivator 4", "Natural killer cells", "Nicotinamide adenine dinucleotide phosphate oxidase", "Oxidize phosphatidylcholine", "Oxidized phosphatidylethanolamine", "Pancreatic ductal adenocarcinoma", "Pyruvate dehydrogenase kinase 4", "Phospholipid hydroperoxides", "Peroxisome proliferator-activated receptor-β", "Pattern recognition receptors", "Polyunsaturated fatty acids", "Polyunsaturated fatty acids-phospholipid", "Polyunsaturated fatty acids", "Receptor activator of nuclear factor kappa-B ligand", "Radiation-induced bystander effect", "Reactive oxygen species", "Radiation therapy", "Radical-trapping antioxidant", "Radiation therapy-microparticles", "1-steaoryl-2-15-HpETE-sn-glycero-3-phosphatidylethanolamine", "Stearoyl-CoA desaturase-1", "Sodium-coupled neutral amino acid transporter 1", "Stimulator of interferon genes", "Tumor-associated antigens", "Tumor-associated dendritic cells", "Tumor-associated macrophages", "Tumor-associated NK cells", "Tumor-associated neutrophils", "PDZ-binding motif", "Tricarboxylic acid cycle", "Transferrin receptor 1", "Toll-like receptors", "Tumor microenvironment", "Temozolomide", "TNF-α receptor 1", "Transferrin receptor 1", "Thioredoxin reductase", "Thioredoxin", "Thioredoxin reductase1", "X-box binding protein", "Bone marrow stromal cells" ] }
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2024-01-14 23:43:46
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oa_package/44/b3/PMC10787430.tar.gz
PMC10787431
38216969
[ "<title>Introduction</title>", "<p id=\"Par7\">In recent decades, Africa has witnessed a surge in the frequency and duration of heat waves associated with climate change [##REF##32620857##1##]. In Kenya, this increase is notable in dry and arid areas of the East Coast and Eastern parts of Turkana, Garissa, Isiolo, Mandera and Marsabit counties [##UREF##0##2##]. Kenya has also been experiencing significant drought events, exacerbating food and water security challenges across numerous communities and precipitating severe hardships. This is particularly pronounced among vulnerable groups, such as pregnant women, children and newborns, rendering the intersection of environment, climate and health a critical focal point for research [##REF##33148618##3##, ##UREF##1##4##].</p>", "<p id=\"Par8\">Epidemiological and physiological studies have shown that neonates (babies under 28 days) are very susceptible to extreme temperatures. Their limited ability to thermoregulate and dependence on caregivers underscores their vulnerability [##REF##35850106##5##–##REF##21968768##7##]. High ambient temperatures may affect neonatal health through four interconnected pathways: infectious diseases, nutrition and hydration, ability to care for the newborn and related health systems [##REF##31266553##8##–##REF##33278369##11##]. In particular, high temperatures may increase the risk of morbidity and mortality associated with infectious diseases, such as diarrheal diseases and malaria, among infants in low income settings. In addition, under high temperatures and challenging environmental and farming conditions, maintaining optimal breastfeeding practices may become a challenge as mothers require enough nutritious food and fluids to help in breastmilk production [##UREF##4##12##]. A systematic review by Edney et al. found that breastfeeding is sufficient for infants’ hydration needs even in hot weather [##REF##36147803##13##]. Moreover, breastfeeding practices vary seasonally and may be influenced by factors such as agricultural activities. In Ethiopia, a study examining the time women spend planting and harvesting versus time spend engaging in exclusive breastfeeding found that women were unlikely to breastfeed when rainfall was higher (25 cm of average monthly rain versus 5 cm). This is because they spend most of their time farming, were unlikely to attend antenatal clinics, and are less likely to receive information on optimal breastfeeding behaviors [##REF##34149138##14##]. In a study of infant feeding practices in Burkina Faso, we found an effect of high temperature after adjusting for the effects of the season (a 23-minute reduction in daily breastfeeding duration per 10 °C increase in temperature) [##REF##36198451##15##].</p>", "<p id=\"Par9\">Finally, high temperatures are associated with adverse effects on maternal mental health and wellbeing. High temperatures are associated with increased anxiety [##REF##33799230##16##], lack of sleep [##UREF##5##17##, ##REF##22738673##18##] and irritability [##REF##24366537##19##], which might have a repercussion on mothers and how they take care of their Infants. Recognizing the interconnectedness of maternal and neonatal welfare is imperative, especially in regions with limited research on the effects of high temperatures on mothers and their neonates.</p>", "<p id=\"Par10\">In sub-Saharan Africa, there is limited research on the effects of high ambient temperatures on mothers and their neonates. In addressing the research gap, our study in Kilifi County, Kenya, explores the community’s observations of the effects of high ambient temperatures on women during pregnancy, postpartum, and their neonates. As part of the CHAMNHA [Climate, Heat Maternal and Neonatal Health Africa] transdisciplinary research project, our findings contribute valuable insights into understanding the complex interplay between climate, heat, maternal health, and neonatal outcomes in the region, offering critical information for policy and intervention strategies. Previously, we have found that pregnant women are negatively affected by heat, and it interferes with their daily activities [##REF##37725839##20##]. This paper focuses on the observed effect of high ambient temperatures on postpartum.</p>" ]
[ "<title>Methods</title>", "<title>Research design</title>", "<p id=\"Par11\">A qualitative descriptive study involving focus group discussions (FGDs), in-depth interviews (IDIs) complemented by key informant interviews (KIIs). The research was conducted between January 2021 to April 2022, the hottest months in Kilifi [##UREF##6##21##] (temperatures are described in Table ##SUPPL##0##1##). We used the Consolidated Criteria for Reporting Qualitative Research (COREQ): a 32-item checklist for interviews and focus groups (appendix ##SUPPL##1##2##) [##REF##17872937##22##].</p>", "<title>Research context</title>", "<p id=\"Par12\">This study was conducted in Kilifi County in Kenya’s Coast Province, in the sub-counties of Kaloleni and Rabai, which have a total population of 304,778. Kilifi County has an annual crude birth rate of 26 per 1,000 population [##UREF##7##23##, ##UREF##8##24##]. According to the Kilifi 2022 factsheet, literacy levels in the region are relatively low, with only 51% of males and 49% of females having successfully completed primary education. The predominant economic activity in the region is tourism. From a socio-economic standpoint, the sub-counties rank among the most impoverished constituencies along the coastal region, with 70% of the population residing below the poverty line, in contrast to the national rate of 47% [##UREF##9##25##]. Maternal, neonatal, and child health indicators in the county fall below the national average [##UREF##9##25##, ##UREF##10##26##]. Kilifi County exhibits one of the highest under-5 mortality rates in Kenya, with 87 deaths per 1,000 live births, despite the government’s initiative to offer cost-free facility-based antenatal, delivery, and postpartum services to all women [##UREF##11##27##]. Given its rural nature, communities are widely dispersed geographically, and health facilities are often situated at a considerable distance from these communities [##REF##31910210##28##, ##REF##34217281##29##]. Homesteads are large, comprising grandchildren, co-wives, parents-in-law, and other older relatives. During the late stages of pregnancy and childbirth, some women receive support from their mothers-in-law, who assist with daily living activities.</p>", "<title>Study population and sampling</title>", "<p id=\"Par13\">We conducted interviews with 99 participants across Kaloleni and Rabai sub-counties, Kilifi, involving 10 in-depth interviews with pregnant women and 12 with postpartum mothers. Additionally, nine focus group discussions (FGDs) were organized, with three each for mothers-in-law, male spouses, and Community Health Volunteers (CHV). Sixteen key informant interviews were conducted, representing diverse sectors such as health, water, agriculture, meteorology, local administration, public health, religious institutions, environmental advocacy, and traditional birth attendants (TBAs). This comprehensive sampling strategy helped elicit a heterogeneity of perspectives, supporting robust triangulation of participant narratives. For instance, engagement with pregnant and breastfeeding women, their close family members, and CHVs guiding them through the delivery process provided firsthand insights into their lived experiences.</p>", "<title>Recruitment and inclusion and exclusion criteria</title>", "<p id=\"Par14\">Aga Khan University has worked in Kilifi for the past six years and has built successful social networks with CHVs and facility health workers. We used these networks to recruit study participants in rural areas of Kilifi.</p>", "<p id=\"Par15\">Participants were eligible for the IDIs if they were willing and able to provide informed consent and audio recorded during the interview. Pregnant women were eligible for recruitment if their pregnancy were at least 28-week gestational age as confirmed by a healthcare worker. Both primi- or multi-gravidae were eligible to participate in the study. Postpartum women were eligible at 4 to 8 weeks after childbirth. We considered the ethical implications of the additional physical and mental burden of interviewing new mothers immediately after birth in the heat. We wanted mothers to be comfortable enough to narrate their experiences. Although we intended to interview mothers up to 8 weeks, all the mothers we interviewed had babies between 4 and 5 weeks. Key informants were recruited if they held a key leadership role in the community or in relevant county ministries such as Health, Water, Agriculture, and Meteorology in the past two years.</p>", "<p id=\"Par16\">Based on the inclusion criteria, facility health workers and CHVs identified potential interviewees through the health facilities and in the communities. To reduce bias, all identified interviewees were further screened by the research team to ensure that they made the criteria, were willing to consent and participate in the study, and their male spouses/partners had been informed. Following recruitment, interviews were scheduled at an appropriate time and date. Participants were screened by the field researchers prior to interviews to ensure that they met all the inclusion criteria. This was the first study on climate change heat exposure’s impact on maternal health, and the women we interviewed had not been interrogated on this topic.</p>", "<title>Data collection</title>", "<p id=\"Par17\">The research was designed by medical anthropologists (AL and FS) and reviewed by CHAMNHA team members with extensive research design experience. AL, a Kenyan social scientist, supervised field data implementation. Field researchers had extensive experience conducting public health and community research in Kilifi and received hands-on training that included role-playing using the study guide and feedback sessions.</p>", "<p id=\"Par18\">The data collection tools were piloted in one FGD with CHVs, a pregnant woman, and a postpartum woman. This revealed that some terms used in the interview guides were likely to be misunderstood. For instance, the term ‘high ambient temperatures’ was sometimes confused with ‘fire’ or ‘drought’, and the word ‘facilities’ was assumed to mean ‘accommodation’. The field team discussed appropriate terminology to reduce confusion (for example, adding the word ‘health’ before facilities and using the local terms <italic>“Joto”</italic> or <italic>“Jua kali”</italic> (translated as “when it is extremely hot”).</p>", "<title>Interviewing</title>", "<p id=\"Par19\">Individual In-Depth Interviews (IDIs) and FGDs were conducted by researchers AL, PK, and SC at the nearest health facilities to participants’ homes, either within a designated room or outdoors beneath a tree. Each FGD comprised six to nine participants. Informed consent procedures were initiated at the commencement of the FGD, during which the researchers delivered comprehensive information in Kiswahili about the study at the group level. Subsequently, consent for participation and permission to individually audio record were obtained from each participant. Those unable to provide a written signature were assisted to consent using a thumbprint.</p>", "<p id=\"Par20\">Interviews for key informants were conducted in their offices, which they considered most convenient. These interviews were conducted in both English and Kiswahili, as most of the participants in this group could read and write in English. An open-ended, flexible topic guide (appendix ##SUPPL##2##3##) was used to structure the discussions to encourage free-flowing dialogue. The IDIs and KIIs took at most one hour, while FGDs took one to two and a half hours. The study guide had broad introductory questions and explored themes on both the direct and indirect effects of high temperatures on pregnant and post-partum women. Themes explored include indigenous knowledge and beliefs about how high ambient temperatures affect pregnant and postpartum women, the developing foetus and the neonate; local norms around strategies and practices to manage high ambient temperatures during pregnancy and in the postpartum period; the role of men and other family members supporting pregnant and postpartum women and their neonates; existing interventions and actions in the community to help vulnerable populations when it is very hot, and the usefulness of daily or seasonal climate forecasts. Snacks and drinks were provided at the venue for all the participants, and transport costs for travelling to the venue were reimbursed. All participants were informed of COVID-19 preventive measures and the field team provided hand sanitizer and face masks.</p>", "<title>Data saturation</title>", "<p id=\"Par21\">Guest et al. [##UREF##12##30##] note that in qualitative research, data saturation occurs within the first twelve interviews. In this study, we considered sample sizes for IDIs, FGDs and KIIs adequate for answering study questions and as reflecting the point at which data saturation was reached. We started with in-depth interviews, which were accompanied by detailed field notes. These field notes from IDIs were shared and deliberated upon daily among all researchers throughout the data collection process. Key themes, such as the indirect and direct effects of heat on both the mother and the baby, were identified and further explored in subsequent FGDs and KIIs until saturation was attained.</p>", "<title>Data management and analysis</title>", "<p id=\"Par22\">Data transcription was done verbatim by a professional transcriber, assisted by study researchers. All field audio recordings, transcribed data and field notes were saved on the Aga Khan University’s data-protected password computer. For transcription accuracy, two researchers (PK and AL) checked the transcripts against the audio recordings. We followed Braun and Clarke’s (2006) thematic analysis framework to guide the analysis [##UREF##13##31##]. Data were analysed using NVIVO 12 software.</p>", "<title>Data familiarization</title>", "<p id=\"Par23\">During data collection, study researchers (AL, PK and FS) read all the field notes and discussed the key issues as they emerged in the data collection process.</p>", "<title>Generating initial codes</title>", "<p id=\"Par24\">A codebook was developed following open coding of a small sample of transcripts, using both deductive (topics that were derived from the interview guides) and inductive (findings emerging from interviewees’ narratives) analysis. Using both deductive and inductive approaches allowed us to have a more nuanced understanding of participants’ experiences of caring for neonates in extreme heat situations.</p>", "<title>Searching for themes (categories)</title>", "<p id=\"Par25\">AL examined data on the impact of high temperatures on postpartum women and their neonates by extracting and applying segments of the texts across the IDIs, FGDs and KIIs. This process entailed reviewing coding outputs and comparing them to identify salient patterns and themes for data interpretation. Categories were then charted manually in a matrix to help visualize possible relationships between themes, as illustrated in Fig. ##SUPPL##3##1##.</p>", "<title>Reviewing themes</title>", "<p id=\"Par26\">The data were checked and discussed with members of the larger team, to ensure saturation had been reached on the themes as presented below.</p>" ]
[ "<title>Results</title>", "<title>Participants’ socio-demographic characteristics</title>", "<p id=\"Par27\">We interviewed 12 postpartum mothers, 10 pregnant women, 19 mothers-in-law, 20 male spouses, 22 CHVs and 16 key informants including medical officers, public health promotion officers, traditional birth attendants, reproductive health officers, a nutritionist, local chiefs and religious leaders. Data from one pregnant woman is not available for this study due to poor audio recordings.</p>", "<p id=\"Par28\">The pregnant and postpartum women we interviewed were aged 17 to 39, had primary school education and the majority of them (over 60%) were unemployed, while a few participated in casual and informal work. Women under 18 years were considered emancipated minors if married. The mothers-in-law were aged between 35 and 63 years, the majority had no formal education, practised farming for economic activities and had relatively large families. The male spouses interviewed were aged between 24 and 63 years, were self-employed and had completed at least high school. Most CHVs had their own small businesses, worked between 10 and 30 h per week and had been in the role for more than two years. The Key informants had worked at least for two years in their respective ministries in a senior role. Tables 2, 3 and 4 (appendix ##SUPPL##0##1##) summarise our participants socio-demographics.</p>", "<title>Key findings: perceived effects of high temperatures on postpartum women and their neonates</title>", "<p id=\"Par29\">Our findings from community members interviewed for this study suggest that high temperatures affect mothers and their neonates in multiple ways. Several health conditions in neonates were perceived to be a direct effect of the heat, including injuries on the skin and mouth, as well as impact on the wellbeing and behavior of the neonate (distress, crying). Heat impacts made it difficult to feed, interact and bath the neonate. In addition, the heat had significant effects on the postpartum women, including exhaustion, discomfort, and the inability for mothers to take care of themselves. These heat effects on the mother also have implications for infant care and wellbeing.</p>", "<p id=\"Par30\">Heat impacts were exacerbated by the drought. The post-partum women reported increased workload because water sources were farther away, and negative impacts on agriculture and loss of shading around the home. This increased the women’s exhaustion in the heat. Community members noted that some postpartum women re-commenced household duties such as fetching water and firewood and farming immediately after birth. Our participants linked these chores with longer periods of postpartum bleeding. In addition, heat and insufficient water led to reduced personal hygiene. Houses are often poorly ventilated and participants reported that the indoor heat made it difficult to use mosquito nets, which would protect mother and baby from malaria. Many factors contributed to a reduced quality of care for the neonate, and these are explored in more detail below.</p>", "<p id=\"Par31\">Low agricultural yields were associated with food scarcity and perceived to lead to low breast milk production, making it difficult for the mother to breastfeed exclusively. Additionally, mothers characterized both indoor and outdoor environments as inhospitable during periods of intense heat, reaching the point where they felt they had “nowhere to escape. We present a conceptual framework (described in supplementary Fig. ##SUPPL##3##1##) that summarizes the direct and indirect pathways of high temperatures on postpartum women and their newborns.</p>", "<title>Heat-related skin problems in neonates</title>", "<p id=\"Par33\">Participants described how they are beginning to see more neonates with damaged skin and attributed this to high temperatures becoming more common. Common descriptions of these injuries included “blisters’, “skin peeling off”, “heat rash”, and “skin patches”. Blisters were reported to develop immediately after birth, if not at birth, making it difficult to care for neonates.</p>", "<p id=\"Par36\">Male spouses shared similar sentiments about blisters developing into wounds on the babies’ skin.</p>", "<p id=\"Par39\">CHVs reported seeing babies developing blisters all over their bodies including the head.</p>", "<p id=\"Par42\">Key informants and male spouses shared similar observations but described it as “heat rash”, “skin patches”, and “skin peeling off” rather than as “blisters”.</p>", "<p id=\"Par49\">A community chief who was a key informant for the study shared the same views and noted that local behavioral practices such as covering small babies with multiple layers of clothes may amplify the heat burden on the neonate’s already compromised skin.</p>", "<p id=\"Par52\">The chiefs’ reports aligned with field researchers’ observations that neonates were typically covered in many layers of clothes and/or blankets during the interviews.</p>", "<title>Difficulties in caring for the neonate in the heat</title>", "<p id=\"Par53\">The direct effect of heat makes babies uncomfortable, making it difficult for mothers to take care of them. Some male spouses described neonates as “having no peace”, “uncomfortable”, “crying all the time”, “cannot sleep”, or “can’t concentrate on breastfeeding”.</p>", "<p id=\"Par55\">Across our participants, there was a consensus on the difficulties postpartum women experienced taking care of their babies.</p>", "<p id=\"Par58\">Male spouses interviewed in this study also alluded to mothers’ difficulties breastfeeding their babies due to the discomfort caused by the heat.</p>", "<p id=\"Par61\">Reports from community health volunteers and key informants from the ministry of health suggest that Kangaroo Mother Care (KMC), a method recommended to improve the wellbeing and development of low birthweight babies by maximising skin-to-skin contact, is challenging to perform in the condition of extreme heat. KMC was reported to increase perspiration in both mothers and babies, resulting in intense discomfort for both.</p>", "<p id=\"Par64\">Views from some stakeholders align with observations made by CHVs -however, for some key informants like the community health officers, hot temperatures’ effect on water supply implies that mothers may not bathe daily, affecting their bodily hygiene. Thus, they did not view KMC as beneficial due to the lack of hygiene in many mothers.</p>", "<p id=\"Par67\">\n<list list-type=\"bullet\"><list-item><p id=\"Par68\">\n<bold><italic>Contextual factors that increase heat exposures and affect the care of the neonate.</italic></bold>\n</p></list-item></list>\n</p>", "<p id=\"Par69\">Indoor heat in the poorly ventilated homes increased discomfort among the mother and the neonate making it cumbersome for the mother to breastfeed. Some participants said that the heat does not subside at night, which may harm both the mother and child.</p>", "<p id=\"Par72\">Male spouses described how cooking with solid fuel in these homes intersects with high temperatures, and with there being not enough space to escape, causing sweating.</p>", "<p id=\"Par75\">These conditions inside homes were said to make it difficult to use mosquito nets. It was reported that mothers refused to use mosquito nets because they heightened the severity of the heat.</p>", "<p id=\"Par78\">Further, our data suggests that mothers’ participation in household duties such as fetching water takes them away from their neonates for many hours. Participants had observed mothers getting stressed performing these chores and viewed this as hurting milk production.</p>", "<p id=\"Par81\">Spending many hours performing activities of daily living (ADL) outside the home was also linked to mothers decision to introduce solid food to their babies prematurely, i.e. earlier than 6 months as reported by a key informant from the ministry of health.</p>", "<p id=\"Par83\">Participants described how some villages have not harvested for three years, while in other areas, participants report low yields and animal deaths owing to water scarcity. Moreover, the interplay between high ambient temperatures, drought and food insecurity was potentially linked to low breast milk production, which in turn was seen as influencing mother’s ability to perform exclusive breastfeeding.</p>", "<title>Exhaustion and delayed postnatal care</title>", "<p id=\"Par86\">When asked how high temperatures affect postpartum women, community members reported that consequences for women included exhaustion and delayed postnatal care. Key informants for this study reported that the delay in post-natal attendance arises from the communal notion of the baby’s skin being delicate and not wanting to endanger the baby in the scorching sunshine.</p>", "<p id=\"Par91\">Although distance to the health facility was described as one of the causes of a delay in or even reduced uptake of postnatal care, however, CHVs and community chiefs suggested that the fear of walking in the heat intersects with women’s exhaustion from other activities of daily living such as fetching water early in the morning.</p>", "<p id=\"Par96\">In periods of high temperatures, postpartum women may prioritize fetching water as opposed to attending postnatal clinics. The views of community health volunteers below align with the chiefs and other community members’ observations.</p>", "<title>Longer healing period for mothers</title>", "<p id=\"Par99\">Male spouses and CHVs linked high ambient temperatures to prolonged postnatal bleeding and longer periods of healing in the postpartum</p>", "<p id=\"Par104\">Similar sentiments were shared by the key informants who also associated extreme heat with slow healing in postpartum.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par107\">Diverse participants in this study described poor health outcomes in neonates in Kilifi and attributed skin problems, discomfort and restlessness, and a reduced nutritional intake during high ambient temperatures in the County. The discomfort was exacerbated by intolerable indoor home environments, making it challenging for mothers to provide care and for infants to breastfeed and sleep. Participants in the study believed that the insufficient breast milk production and the early introduction of alternative foods to infants before six months of age were attributed to the impact of high temperatures on food production. Additionally, they pointed out that the extended hours mothers spent performing outdoor chores away from home also contributed to these feeding practices. It remains uncertain whether all the health issues mentioned by participants can be definitively linked to the prevailing heat, however.</p>", "<title>Breastfeeding</title>", "<p id=\"Par108\">A World Health Organization (WHO) and a United Nations Children and Environment Fund (UNICEF) Global Breastfeeding Scorecard Report shows that worldwide, 41% of children under the age of six months were exclusively breastfed in 2019 [##UREF##14##32##]. In Africa, more than 95% of infants aged 6 months are breastfed, but the rate of exclusive breastfeeding (EBF) is reported to be low, with exceptions in Rwanda and Burundi where EBF is reported to be &gt; 80% up to age 6 months [##UREF##15##33##]. Under six months, the rate of EBF in Kenya has been estimated to be 61% [##UREF##16##34##]. Pre-lacteal feeding includes water and other liquids and is caused by factors such as maternal education, C-section, the sex of the child and home delivery [##REF##23924230##35##, ##REF##26858835##36##].</p>", "<p>Community members in Kilifi identified low rates of EBF through three main mechanisms: (1) direct high ambient temperatures may cause blisters on the baby’s skin and in the mouth, which are uncomfortable for the baby; (2) low breast milk production linked to scarcity of food, and (3) raised temperatures in poorly ventilated houses exacerbating discomfort for both mothers and babies. These observed linkages require further scientific investigation.</p>", "<p>Barriers to breastfeeding – including those related to heat – are interlinked, and interventions must address them from a systems perspective. Firstly, there is a need to provide cool comfortable spaces where women can nurse when it is hot, both in the communities and in health facilities, by equipping them with electricity for fans and cooling. Secondly, there is a need for programs and policies in settings such as Kilifi to provide the essentials, including supplies of clean water and nutritious foods for pregnant and nursing women, to overcome the problem of food and water insecurity for this vulnerable group. Thirdly, CHVs should be strategically utilized as conduits for disseminating education on the significance of breastfeeding during hot weather and the imperative of maintaining proper hydration. Furthermore, enhanced guidance from healthcare providers is key, as they play a critical role in informing and advising pregnant and postpartum women and their families on EBF, while also incorporating the active involvement of partners and fathers [##UREF##17##37##, ##REF##26183031##38##]. Finally, substantial investments to ameliorate the built environment are requisite, necessitating multi-sectoral coordination and innovative methodologies to cool indoor living spaces, particularly in resource-constrained settings. Initiatives such as reducing indoor pollution through the provision of eco-friendly cooking stoves with lower emissions, heightened fuel efficiency, and improved air quality to mothers in these locales may further contribute to mitigating the perceived temperature in homes.</p>", "<title>Direct effect on the skin</title>", "<p id=\"Par111\">Although skin diseases are common in children in Africa [##REF##11167692##39##, ##REF##26359248##40##], published research in this area is scant, particularly skin diseases in neonates. In our study, the impacts of heat were perceived to cause a range of skin conditions in infants. Although clinically, there are skin conditions caused by heat (e.g. prickly heat), it is difficult to interpret which skin conditions were more prevalent and the role of heat or sunlight. Researchers in this study observed the common practice of heavily layering neonates, attributed to cultural beliefs aimed at protecting them from the ‘evil eye.’ These practices potentially exacerbate the heat burden on neonatal skin. Addressing these customs requires an awareness-raising and behavior change intervention, leveraging key influencers such as chiefs, Community Health Volunteers (CHVs), community elders, and public health officers. Furthermore, to provide appropriate care for infant skin, there is a need for clinical research focusing on skin diseases in newborns in the region. Such research could elucidate the correlation between high ambient temperatures and skin diseases in neonates.</p>", "<title>Kangaroo Mother Care</title>", "<p id=\"Par112\">Skin-to-skin care is protective against a wide variety of adverse neonatal outcomes, especially in those born too soon, and facilitates close observation of the baby. KMC has the potential to prevent many neonatal complications and even improves exclusive breastfeeding. However, swaddling neonates when it is hot can be harmful because of the baby’s poor thermoregulatory capacity as they cannot dispose of the excess heat [##UREF##18##41##, ##UREF##19##42##]. Sharing a bed with a newborn during periods of extreme high temperature is not recommended as it may result in child death [##REF##26515228##43##]. Findings from this study suggest that mothers may be reluctant to practice KMC in the heat, owing to the discomfort involved. The need to improve community health facilities for KMC is key, considering that many Kilifian mothers give birth to underweight babies [##REF##37076795##44##, ##UREF##20##45##]. Interventions such as solar-powered electricity to cool buildings and health facilities are warranted.</p>", "<title>Delayed postnatal care and slower healing processes</title>", "<p id=\"Par113\">Engaging in household and outdoor chores under elevated temperatures was reported to precipitate exhaustion among mothers. It is imperative to initiate community-wide educational campaigns elucidating the perils associated with climate change and the impact of heightened temperatures on postpartum women and neonates. Such awareness initiatives are pivotal in fostering community support mechanisms, particularly in alleviating the burden of daily chores on women in these communities. Furthermore, strategic investments are warranted in establishing healthcare facilities proximate to residences, ensuring enhanced accessibility for women seeking postnatal care (PNC) during hot weather conditions. Simultaneously, considerations for bolstering transportation infrastructure to existing facilities within Kilifi County are crucial components of a comprehensive approach to maternal and neonatal well-being.</p>", "<title>Priority interventions</title>", "<p id=\"Par114\">Delivery of heat-health early warning weather information to inform mothers to take protective measures when it is hot is urgently needed. CHVs who work closely with women in the communities could be trained to deliver these messages. Community education on extreme heat impacts on mothers and their newborns health and wellbeing is urgently required. Importantly, greening the homes and health facilities and ensuring that women have accessible clean water in their homes and health facilities is an essential first step towards alleviating the effects of heat exposure.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par115\">Being the first study of its kind in East Africa, particularly in a region that experiences high temperatures and drought throughout the year, these findings contribute to a much-neglected area. Our study participants were carefully selected to include community members who could speak directly about their observed experiences of the effects of high temperatures on women and their neonates. The study’s qualitative and anthropological approach to data collection enabled us to build a nuanced understanding of how extreme heat impacts neonatal health. The intersection between drought and food insecurity was a significant and dominating concern. Drought clearly exacerbates the heat risks, thus highlighting the importance of also looking at women’s experiences in non-drought situations. Dermatology was an unexpected finding for researchers, and therefore we have limited data to understand what exactly the described skin diseases are. There were also missed opportunities in the interviewing where themes such as dehydration and interactions between mother and baby and the help infants received while mothers were away were not adequately followed up and explored. Nonetheless, interviewing a wide range of community members who support women as they welcome their neonates into the world provided deep insights into their experience. Lastly, it is important to highlight that our qualitative data is based on community members views, and epidemiological evidence would help to establish an association between neonatal outcomes and high temperatures. Data from the Kilifi Health Demographic Surveillance System (KHDSS) for Young Infants (YI), described as children below 60 days, indicate high mortality rates due several factors, including low birth weight, sepsis, birth asphyxia and preterm complications [##UREF##20##45##].</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par116\">High ambient temperatures impact directly on neonatal health, bringing discomfort and skin problems while reducing women’s ability to exclusively breastfeed and undertake other aspects of infant care. Heat exposures are exacerbated by poor housing, in which indoor temperatures are raised by indoor fires and inadequately ventilated homes. High temperatures and drought increase the physical burden upon women by increasing the distances that need to be covered in the heat, and the drought has increased malnutrition in mothers and babies. These findings point to the need to initiate and implement multi-sectoral policies and programs to mitigate the negative impacts of extreme heat on maternal and neonatal health in rural Kilifi and similar settings. As the earth continues to warm over the coming decades, such interventions will become essential. Our finding shows the emerging gaps that need to be addressed to maintain the progress that has been made in the last decade in reducing the maternal and neonatal mortalities. Climate change is a threat to neonatal health and there is an urgent need to put strategies and interventions in place to support neonatal care in low-and-middle-income countries.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">To understand community perspectives on the effects of high ambient temperature on the health and wellbeing of neonates, and impacts on post-partum women and infant care in Kilifi.</p>", "<title>Design</title>", "<p id=\"Par2\">Qualitative study using key informant interviews, in-depth interviews and focus group discussions with pregnant and postpartum women (<italic>n</italic> = 22), mothers-in-law (<italic>n</italic> = 19), male spouses (<italic>n</italic> = 20), community health volunteers (CHVs) (<italic>n</italic> = 22) and stakeholders from health and government ministries (<italic>n</italic> = 16).</p>", "<title>Settings</title>", "<p id=\"Par3\">We conducted our research in Kilifi County in Kenya’s Coast Province. The area is largely rural and during summer, air temperatures can reach 37˚C and rarely go below 23˚C.</p>", "<title>Data analysis</title>", "<p id=\"Par4\">Data were analyzed in NVivo 12, using both inductive and deductive approaches.</p>", "<title>Results</title>", "<p id=\"Par5\">High ambient temperature is perceived by community members to have direct and indirect health pathways in pregnancy and postpartum periods, including on the neonates. The direct impacts include injuries on the neonate’s skin and in the mouth, leading to discomfort and affecting breastfeeding and sleeping. Participants described babies as “having no peace”. Heat effects were perceived to be amplified by indoor air pollution and heat from indoor cooking fires. Community members believed that exclusive breastfeeding was not practical in conditions of extreme heat because it lowered breast milk production, which was, in turn, linked to a low scarcity of food and time spend by mothers away from their neonates performing household chores. Kangaroo Mother Care (KMC) was also negatively affected. Participants reported that postpartum women took longer to heal in the heat, were exhausted most of the time and tended not to attend postnatal care.</p>", "<title>Conclusions</title>", "<p id=\"Par6\">High ambient temperatures affect postpartum women and their neonates through direct and indirect pathways. Discomfort makes it difficult for the mother to care for the baby. Multi-sectoral policies and programs are required to mitigate the negative impacts of high ambient temperatures on maternal and neonatal health in rural Kilifi and similar settings.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12887-023-04517-w.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We are grateful to all our participants in Kaloleni and Rabai sub-counties in Kilifi Kenya. We are grateful to Sophie Chabeda for assisting to collect some of the qualitative data.</p>", "<title>Author contributions</title>", "<p>AL: Development of first draft, conceptualization, data collection, analysis and interpretationFS: Conceptualisation, analysis, interpretation and revision of the original manuscriptPK: Data collection, analysis and interpretationBN, SK, VF, NR, SL, MC, CP, KK and JH: Conceptualisation, data interpretation and revision of the original manuscript.MC,SL,SK and BN: Funding aquisition.</p>", "<title>Funding</title>", "<p>This work was supported by the Natural Environment Research Council (NERC) [grant numbers NE/T013613/1, NE/T01363X/1]; Research Council of Norway (RCN) [grant number 312601]; The Swedish Research Council for Health, Working Life and Welfare in collaboration with the Swedish Research Council (Forte) [grant number 2019 − 01570]; and the National Science Foundation (NSF) [grant number ICER-2028598]; coordinated through a Belmont Forum partnership.</p>", "<title>Data availability</title>", "<p>The datasets generated and/or analyzed during the current study are not publicly available because it is possible for someone from the study sites to deduce participants if they get access to the full transcript but are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to participate</title>", "<p id=\"Par118\">This study observed the Principles of the Declaration of Helsinki. Ethical approval was received from the Aga Khan University Ethics Committee ref 2020/IERC-94 (v2); National Commission for Science and Technology &amp; Innovation Ref BAHAMAS ABS/P/20/7568; and London School of Hygiene and Tropical Medicine Ref: 22685. Administrative clearance was obtained from the Kilifi County Office ref DOM/KLF/RESCH/vol.1/66. Informed consent was obtained from all subjects and their legal guardian (s). All information collected was kept confidential, and no names or other identifying information was disclosed during data collection and reporting.</p>", "<title>Consent for publication</title>", "<p id=\"Par119\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par1323\">The authors declare no competing interests.</p>" ]
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[ "<disp-quote><p id=\"Par34\">The temperature was higher than usual [and] one week after delivering the baby had blisters … You couldn’t be able to undress the baby because those blisters were producing water, and in cases [where] they burst, they formed a wound because of the warm temperature.</p><p id=\"Par35\">IDI - Postpartum woman, Chalani.</p></disp-quote>", "<disp-quote><p id=\"Par37\">The baby is normally affected because of hot temperatures. The baby gets blister like wounds …because of hot temperatures. And in most cases, the baby cries very often because of the heat.</p><p id=\"Par38\">FGD- Male CHVs, Kasemene,</p></disp-quote>", "<disp-quote><p id=\"Par40\">Also, these babies who are born normally develop ‘<italic>malenge lenge</italic>’ (blisters; Kiswahili). You can get a baby who has developed those <italic>malenge lenge</italic> all over the body. Even up to the head. That is due to the heat. Even if it is born at full term, some of them are normally born when they have already developed those <italic>malenge lenge</italic>.</p><p id=\"Par41\">FGD - Female CHVs, Ribe.</p></disp-quote>", "<disp-quote><p id=\"Par43\">You will get people telling you that the baby has a fever, even if they [the babies] have a heat rash. What is worse is [that] they [babies] will be crying and scratching themselves, instead of breastfeeding.</p><p id=\"Par44\">KII - Ministry of Health Official, Kilifi.</p><p id=\"Par45\">… I even have experienced one of my children suffer[ing] skin rashes and something like the skin has some patches and when I consulted a clinician, definitely the answer was that this is heat rash, which is so extreme that even the child cannot sleep during the night, the child was crying and, in most cases, it is not treatable.</p><p id=\"Par46\">KII, Public Health Official- Kilifi.</p><p id=\"Par47\">The heat situation affects the baby’s skin. … You may find the baby has rashes, then the peeling off (skin) and crying a lot.</p><p id=\"Par48\">FGD, male spouses, Gotani.</p></disp-quote>", "<disp-quote><p id=\"Par50\">It [heat] really affects [the baby] and you would find that the skin of the young baby [is] peeling off, the first skin peeling off because of the heat. And as [in] my community [they] say that the baby must be totally covered, … so it has to be totally covered and so we totally cover the baby, and it is very hot, then the skin peels off.</p><p id=\"Par51\">KII, Chief, Kilifi.</p></disp-quote>", "<disp-quote><p id=\"Par54\">…the baby has no peace in the night, hot temperatures make the baby to cry, the baby is never comfortable at all.</p></disp-quote>", "<disp-quote><p id=\"Par56\">I would undress myself and the same to the baby; if the baby has blisters, you can’t even breastfeed him, instead, [baby] keeps on crying.</p><p id=\"Par57\">IDI, postpartum woman, Chalani.</p></disp-quote>", "<disp-quote><p id=\"Par59\">The extreme heat affects the baby during breastfeeding, it affects the baby because she can’t concentrate on breastfeeding… even breastfeeding she can’t do it well. … the baby should be breastfed throughout, but when there is more heat, the baby is uncomfortable to breastfeed as he cries due to hot temperatures. It is really a problem.</p><p id=\"Par60\">FGD, Male Spouses, Viragoni.</p></disp-quote>", "<disp-quote><p id=\"Par62\">It will be a problem for the baby to be put in Kangaroo style. For you yourself [post-partum mother], you are already sweating all the time. So how will you put that baby into the Kangaroo style? Will you not be endangering the baby more? It will be trouble on top of trouble.</p><p id=\"Par63\">FGD, Female Community Health Volunteers, Rabai.</p></disp-quote>", "<disp-quote><p id=\"Par65\">…, it is a good idea [KMC] but with aspects of hygiene, something needs to be checked and adhered to. Because we could be advocating for Kangaroo for the mother but looking at the hygiene status, the probability of having water – like how many times does that mother take bath? It is also an issue that needs to be considered, so it all goes around the hygiene and the whole benefit of Kangaroo.</p><p id=\"Par66\">KII, Community health officer, Rabai.</p></disp-quote>", "<disp-quote><p id=\"Par70\">When she [mother] is in that house, cooking is in there, everything in there, with a newborn baby, it is a must that it will affect the baby because of the smoke, dust, and hotness. Sometimes [baby] will be crying at night, and you wonder what the matter is, yet it is the house’s condition as it is because it lacks windows, nothing, no coldness, it’s hot. It disturbs the child….</p><p id=\"Par71\">FGD, Mothers-in-law, Buni.</p></disp-quote>", "<disp-quote><p id=\"Par73\">According to our living standards, you will find that as common citizens, we prepare food in a small house using firewood. The heat becomes too much inside the small houses [and] they start sweating. They wish to strip naked but cannot.</p><p id=\"Par74\">FGD, Male Spouses, Kamkomani.</p></disp-quote>", "<disp-quote><p id=\"Par76\">During hot periods, they fold up their mosquito nets and put them on the hung line because they say sleeping under them increases the already high heat. So, sleeping is like that [sleeping without mosquitoe net]. So, it affects women and even newborns. Therefore, it now affects almost everyone.</p><p id=\"Par77\">FGD - Male CHV-Kasemeni.</p></disp-quote>", "<disp-quote><p id=\"Par79\">…a postnatal woman has to walk about two kilometers searching for water. And maybe she must go with about two or three other people and if she has to make three or four trips, she gets very tired. And if she gets very tired, a neonatal baby won’t get enough breast milk because the mother is stressed up because of thinking about where and how to get water and other household essentials. And when they are stressed, breast milk production is not there.</p><p id=\"Par80\">FGD, Male Community Health Volunteers, Kilifi.</p></disp-quote>", "<disp-quote><p id=\"Par82\">It affects the mother because—due to the tasks that she performs in the sun—she will not produce enough milk to breastfeed the child. Therefore, the child is introduced to weaning before six months elapse. They (nursing mothers) have no (option) otherwise, and they have to ensure the child is full by the time they go to the farm or walk long distances to collect water. The child is forced early to eat things it should not, due to circumstance, and this is a risk to it and the mother. I think people [in Kilifi] do not understand [the dangers]. They think that [introducing solid food early] is the best.</p></disp-quote>", "<disp-quote><p id=\"Par84\">The support is needed because this woman who has no food and she is exclusively breastfeeding—you will find they [the babies] don’t reach the [age of] 6 months. That is the truth! You will find a woman has started feeding the baby on food, aaaha! You will ask her why she is feeding this baby, and he hasn’t attained that level [of development]? She will answer you that ‘There is nothing here [no milk in the breast]. Nothing is coming out [milk is not coming out of the breast], and the baby is crying.’ Another woman will say it: ‘[My baby] keeps breastfeeding. … I have to look for porridge, and that porridge— remember—it will be without sugar. There is a challenge [here], there is a challenge with [lack of] food. That is the truth! If we want people to be supported, there is a problem with food. There are people who are suffering….</p><p id=\"Par85\">FGD, Female Community Health Volunteers, Ribe.</p></disp-quote>", "<disp-quote><p id=\"Par87\">There is a notion that is around, which is not a notion as such but a belief that the infant’s skin is a bit delicate and sensitive… so, if one thinks that ‘I have a few kilometers to get to the hospital for the post-natal clinic, then along the way I will be exposing my kid to the dust, direct heat and sun’ – which they feel is not good.</p><p id=\"Par88\">KII, Public Health Officer, Rabai.</p><p id=\"Par89\">It [high temperatures] reduces [post-natal attendance] because you can’t walk too far, most of our facilities are too far from the villages, so you can’t walk to the facility, so most of them [postpartum women] will not attend the clinics.</p><p id=\"Par90\">KII, Community Health Officer, Kaloleni.</p></disp-quote>", "<disp-quote><p id=\"Par92\">They will prefer not to go to the hospital after walking all that distance for water. Therefore, they will not be able to follow up on their progress with the clinics.</p><p id=\"Par93\">KII, Chief, Kaloleni.</p><p id=\"Par94\">Sometime as hot as it is and if one is very far from the dispensary or the health facility and she is supposed to go, before visiting the facility she has to make sure there is availability of water inside the house…. So, she may delay and decide not to go after fetching the water, being very tired and it is a distance to the health facility, she may decide either to attend late or not to attend</p><p id=\"Par95\">KII, Chief, Rabai.</p></disp-quote>", "<disp-quote><p id=\"Par97\">Women in our place, they really fear these hot temperatures…maybe someone woke up in the morning to go look for water. Because the most important item in the house is water. She has taken two hours to fetch water. When she comes back, the temperature is already gone up. It is really “burning” very much. Do you think she can carry the baby? And maybe she doesn’t have even an umbrella. She will say, she will go tomorrow, and tomorrow and like that, like that because water problem is a daily routine. And when she comes, the temperatures are already gone up. She postpones again.</p><p id=\"Par98\">FGD, Community Health Volunteer, Ribe.</p></disp-quote>", "<disp-quote><p id=\"Par100\">As for the mother, after delivery, she experiences unusual things, such as bleeding, she never gets dry fast.</p><p id=\"Par101\">FGD, male spouses, Kamokamani,</p><p id=\"Par102\">…The state of ability to heal will be there but it is slow. It won’t be that one which happens fast enough. It is because during hot temperature, the wound is normally watery, and this makes it not to heal fast.</p><p id=\"Par103\">FGD, Community Health Volunteers, Ribe.</p></disp-quote>", "<disp-quote><p id=\"Par105\">It (high temperatures) can affect the healing for those who have C section … I think it can just affect the healing of the mother. Because of the wound, when you have a wound and when it is too hot, it doesn’t heal that fast.</p><p id=\"Par106\">KII, Community Health Officer, Kaloleni.</p></disp-quote>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12887_2023_4517_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>", "<media xlink:href=\"12887_2023_4517_MOESM2_ESM.docx\"><caption><p>Supplementary Material 2</p></caption></media>", "<media xlink:href=\"12887_2023_4517_MOESM3_ESM.docx\"><caption><p>Supplementary Material 3</p></caption></media>", "<media xlink:href=\"12887_2023_4517_MOESM4_ESM.docx\"><caption><p>Supplementary Material 4</p></caption></media>" ]
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"], "ext-link": ["https://cgspace.cgiar.org/bitstream/handle/10568/80453/Kilifi_Climate%20Risk%20Profile.pdf"]}, {"label": ["24."], "mixed-citation": ["Kilifi county. County Government of Kilifi: Kilifi County Department of Health [cited 2019 25 Nov]. Available from: "], "ext-link": ["http://webz-kenya.com/khco/background/"]}, {"label": ["25."], "mixed-citation": ["Government of Kenya (GOK). Kenya Population and Housing Census (KPHC)., Kenya National Bureau of Statistics, Nairobi, Kenya 2009. "], "ext-link": ["https://s3-eu-west-1.amazonaws.com/s3.sourceafrica.net/documents/21195/Census-2009.pd"]}, {"label": ["26."], "mixed-citation": ["County Government of Kilifi. Kilifi County Department of Health [Internet]. 2019. Available from: "], "ext-link": ["http://webz-kenya.com/khco/background/"]}, {"label": ["27."], "mixed-citation": ["Kilifi County., editor Kaloleni/Rabai Sub-counties/Kilifi County, Annual Workplan https://"], "ext-link": ["kilifi.go.ke/wp-content/uploads/2021/11/ANNUAL-DEVELOPMENT-PLAN-2018_2019-FINANCIAL-YEAR.pdf"]}, {"label": ["30."], "surname": ["Guest", "Bunce", "Johnson"], "given-names": ["G", "A", "L"], "article-title": ["How many interviews are Enough? An experiment with data saturation and variability"], "source": ["Field Methods"], "year": ["2006"], "volume": ["18"], "issue": ["1"], "fpage": ["59"], "lpage": ["82"], "pub-id": ["10.1177/1525822X05279903"]}, {"label": ["31."], "mixed-citation": ["Braun V, Clarke V. Using thematic analysis in psychology. 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{ "acronym": [], "definition": [] }
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CC BY
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2024-01-14 23:43:46
BMC Pediatr. 2024 Jan 13; 24:36
oa_package/d5/2b/PMC10787431.tar.gz
PMC10787432
38217052
[ "<title>Background</title>", "<p id=\"Par11\">Offering the best possible care, improving the lives of the community, and contributing to the broader scientific knowledge are some of the key motivators for conducting health-related research [##REF##35186876##1##, ##REF##32586311##2##]. Ensuring knowledge gained from research is appropriately disseminated and/or translated is vital to achieving this goal. This process is often labelled as knowledge translation (KT) and is defined as “the dynamic and iterative process that includes the synthesis, dissemination, exchange, and ethically sound application of knowledge to improve health, provide more effective health services and products, and strengthen the healthcare system” (p.4) [##UREF##0##3##]. Knowledge producers, such as researchers, play a central role in this process. They can influence the dissemination of knowledge through how the findings are presented and communicated and through the selection of target audiences [##REF##31900230##4##, ##UREF##1##5##]. Researchers can apply passive and untargeted strategies, such as publishing in peer-reviewed journals, mass mailings, or conference presentations. They can also apply more active and tailored strategies, such as plain language summaries, patient decision support aids, and interactive small group meetings with end-users [##REF##8192299##6##–##REF##30984733##8##].</p>", "<p id=\"Par12\">Whilst these dissemination strategies are necessary to spread information, they are not sufficient to ensure actual use of knowledge [##UREF##1##5##, ##UREF##3##9##]. Therefore, in addition to disseminating research findings, researchers are encouraged to involve research end-users, such as policymakers and practitioners, throughout the entire research process. The goal of end-user engagement is to increase the relevance of the research as well as to improve the accessibility, appropriateness, and understandability of the research evidence [##UREF##1##5##, ##REF##35985787##10##]. In order to achieve these goals, it is important to establish meaningful and active collaborations between researchers and end-users in determining research priorities, conducting the research, interpreting outcomes, and translating findings into policy and practice [##REF##35985787##10##, ##REF##30788147##11##]. An essential step in minimising the knowledge-to-practice gap is gaining an understanding of how researchers disseminate and engage end-users in their research.</p>", "<p id=\"Par13\">A number of studies have investigated how researchers facilitate the KT process through dissemination and end-user engagement. A survey [##REF##17204143##12##] conducted in 2001 among health researchers in Alberta, Canada, tried to provide objective measures of passive strategies—by summing the number of publications in the last five years—and active strategies—by summing the number of plain language reports and the number of times they involved end-users in their research. The authors found that researchers reported more passive than active dissemination of their research, with this particularly evident among basic science researchers. Similar findings have emerged in other surveys of researchers working in health-related fields, with more reporting using mostly passive diffusion strategies, including academic journals (88–99%) and academic conferences (90–93%) than active tailored approaches, such as plain language summaries (33–64%) and face-to-face meetings (48–68%) [##REF##25491890##13##–##REF##19698186##16##]. A 2012 survey study found that only one-third of US-based health researchers involved end-users in their research [##UREF##4##17##]. Consistent with this, a more recent international survey found that involving end-users was the least employed KT strategy of authors of public health trial publications [##REF##35101044##15##]. A more in-depth exploration [##REF##30788147##11##] showed that health researchers in Canada mostly engaged end-users in their research by informing them about their findings or by getting their feedback on certain aspects of the research. Only a few actively collaborated with end-users throughout the research process. The authors also reported that researchers believed that some basic and biomedical research areas were not appropriate for engagement throughout the research process with end-users such as patients and the public.</p>", "<p id=\"Par14\">These results highlight the knowledge-to-practice gap that the field of KT faces. Studies have shown that the effective use of KT activities is associated with a greater impact of the research on public health policy and practice [##REF##35101044##15##, ##REF##26198428##18##]. In particular, disseminating study findings and providing training to end-users on how to use the intervention have been identified as the most effective KT strategies in ensuring the translation of trial findings [##REF##35101044##15##]. Despite the importance of dissemination and end-user engagement activities, there is a lack of understanding of whether these activities are influenced by certain characteristics of the knowledge being produced and the person conducting the research, such as the career stage of the researcher, the setting in which the researcher is based, the type of research conducted, and whether the researcher has been trained on KT. Whilst it has been suggested that these characteristics can influence KT activities [##REF##18182604##19##, ##UREF##5##20##], this has not been thoroughly investigated to our knowledge. This is an important knowledge gap as understanding these factors can help future efforts to improve KT.</p>", "<p id=\"Par15\">The aim of this international survey study is to examine researchers’ views on and practices of two aspects of KT (dissemination and exchange) in the field of transfusion medicine. This is a multidisciplinary field focusing on the collection, storage, and use of blood and blood-related products [##REF##11176862##21##, ##REF##20726958##22##]. Transfusion medicine includes basic science research, such as investigations into reducing viral transmission of blood products, treatment methods using blood-related products, and optimal storage solutions of blood and blood components. It also includes applied science research, which focuses on blood donor management such as increasing blood donor recruitment and retention and reducing adverse events in relation to the collection of blood [##REF##20726958##22##, ##REF##17845263##23##]. Research conducted in this area is driven by gaps in knowledge and operational needs. Researchers can be based in an applied setting, such as a blood collection agency or a hospital, and/or an academic setting, such as a university or research institute [##REF##20726958##22##]. A recent review of the published literature showed that, whilst there is some evidence of KT practices in transfusion medicine, it is in the early stages [##REF##33797069##24##]. Further, researchers in this field are faced with similar KT barriers as others, such as lack of time, funding, and/or resources. They also perceive maintaining good relationships with end-users as critical to the KT process [##REF##37357984##25##]. We extend these findings by examining researchers’ KT activities in the area of transfusion medicine. Specifically, our study objectives were to examine (1) transfusion medicine researchers’ views of and attitudes towards KT, (2) their knowledge dissemination activities, and (3) their end-user engagement activities. We examined the differences by career stage, work setting, research type, and KT training. Documenting these views and activities by researchers is important to gain an understanding of how to minimise the knowledge-to-practice gap in transfusion medicine.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par16\">This paper presents a component of a larger cross-sectional survey study on KT in transfusion medicine that was conducted with an international cohort of researchers. Data were collected and managed using REDCap electronic data capture tools hosted at the University of Sydney. Participants were recruited through five main strategies using a combination of direct emails to corresponding authors of published articles in well-known transfusion medicine journals and grant recipients of research relating to transfusion medicine (<italic>n</italic> = 1645), distribution via an international blood operator network, and public social media posts in May 2022, with details published elsewhere [##REF##37357984##25##]. Participants were excluded from participating in the study if they indicated in the screening question that they did not spend any of their working time on research activities. Ethical approval to conduct the study was obtained from the University of Sydney (#2021/854). The STROBE Checklist [##REF##17947786##26##] was used to guide our reporting (see Additional file ##SUPPL##0##1##).</p>", "<title>Survey instrument</title>", "<p id=\"Par17\">The questionnaire was developed using existing literature on KT activities and end-user research engagement [##REF##8192299##6##, ##REF##30788147##11##, ##UREF##6##27##, ##REF##30206084##28##]. Feedback was sought on the wording of the questions and survey flow from three individuals working in transfusion medicine as a researcher or medical officer.</p>", "<p id=\"Par18\">The questionnaire consisted of several sections. First, participants were asked a range of demographic and work-related questions including gender, country currently based, primary and secondary work setting, current type of research methodology being used, years active in transfusion medicine, and whether they have ever received training on KT. The second part focused on dissemination activities whereby participants were asked “To what extent do you do the following activities to disseminate your research findings?”, rating 11 activities on a 5-point Likert scale (1 = never, 5 = always). The list of dissemination activities was informed by Lomas’ taxonomy [##REF##8192299##6##] and the Guide to Knowledge Translation Planning at CIHR [##UREF##6##27##]. The third part of the questionnaire focused on end-user engagement activities informed by Crockett et al. [##REF##30788147##11##] and included multiple-choice questions on the level of end-user engagement in general (“At what level have you engaged end-users in your research?”), identifying which end-user groups they have ever involved in their research (“Who have you engaged in the research process?”), and at what research stage (“Please indicate those research phases where you have experience engaging with end-users.”). The final part of the survey elicited participants’ views about who should be responsible for and the importance of KT using 12 statements informed by Lynch et al. [##REF##30206084##28##] that participants responded to on 5-point Likert scales (1 = strongly disagree, 5 = strongly agree). Survey questions are available in Additional file ##SUPPL##1##2##.</p>", "<title>Statistical analysis</title>", "<p id=\"Par19\">For descriptive analyses, adopting the approach taken by Lynch et al. [##REF##30206084##28##], responses to the statements on the importance of KT on 5-point Likert scales were collapsed into three categories as affirmative (strongly agree, agree), neutral (neutral), and not affirmative (disagree, strongly disagree). Similarly, responses to diffusion and dissemination activities given on 5-point Likert scales were categorised as never, rarely/occasionally, and frequently/always for ease of interpretation. In addition, end-user groups were combined as blood donors/recipients (blood donors, blood recipients), front-line staff (blood collection staff, blood processing staff, hospital staff), senior management/policymakers, general public, and others.</p>", "<p id=\"Par20\">For comparative analyses, responses to primary and secondary work settings were collapsed to create a new variable “work setting”, with the categories “academic” (university and/or research institute), “applied” (government department/agency, blood collection agency, hospital setting, and/or other healthcare service), and “joint” (university/research institute and government department/blood collection agency/hospital setting/other healthcare service). Further, participants’ “research type” was derived from data on research methods with the categories “basic science” (animal studies and/or biospecimen analysis research) and “applied science” (all remaining categories). The career stage was derived from years active in transfusion medicine, with the categories “early/mid-career” (1–15 years) and “established career” (16 years and over). Finally, “KT training” was dichotomised as yes or no, with no comprising responses of “no” and “don’t know/unsure”.</p>", "<p id=\"Par21\">Sample characteristics and responses to survey items are described using medians (interquartile range) and means (standard deviation) for continuous variables and by frequencies (percentages) for categorical variables. Differences between career stage, work setting, research type, and KT training were investigated using independent <italic>t</italic>-tests, chi-squared tests, and one-way analysis of variance, with significant effects further investigated using Tukey’s HSD tests. All analyses were performed using statistical software (IBM SPSS Statistics 28.0; IBM Corporation) with statistical significance defined as <italic>p</italic> &lt; 0.05.</p>" ]
[ "<title>Results</title>", "<p id=\"Par22\">A total of 131 people responded to the survey. However, 10% (<italic>n</italic> = 13) did not complete the relevant survey sections, and one participant indicated not conducting research, leaving 117 eligible responses available for analysis. Table ##TAB##0##1## shows the characteristics of the final sample. Participants were diverse in gender, with approximately equal numbers of men and women, and diverse in their work setting, with 41% indicating working in two different settings. When combining the two types of work settings, 23% worked solely in an academic setting, 48% worked solely in an applied setting, and 28% worked in a joint setting. Participants also used a wide variety of research methods, with 33% using at least one basic science method. Further, participants were quite experienced, with 43% having worked in the area of transfusion medicine for more than 15 years (range 1–50 years). The sample included participants from 33 countries, including Australia, the USA, the Netherlands, Canada, the UK, Cameroon, Argentina, Saudi Arabia, and South Korea.\n</p>", "<title>Importance, ability, and responsibility for knowledge translation</title>", "<p id=\"Par23\">Researchers’ views on the importance of and responsibility for KT are presented in Table ##TAB##1##2##. Most participants felt that translating their research is important, and only a few reported that their research is not the sort that can be translated. KT was seen by most participants as the responsibility of clinicians (70%), with fewer attributing KT’s responsibility to researchers (58%). When cross-tabulating these two items, half of the sample (51%) indicated that both clinicians and researchers are responsible for KT, with one quarter reporting it was the responsibility of clinicians only (23%), and smaller numbers indicating KT is the responsibility of researchers only (10%), or neither agreeing nor disagreeing with both statements (16%). However, when asked about their own role, two-thirds of participants felt it was their responsibility to translate their research, with only a few transferring this responsibility to someone else in their team. Despite this sense of responsibility, a third of the participants felt that spending time on KT would take them away from their research. Less than half of the sample reported knowing which strategies to use or felt that they had the skills to translate their research. When looking at KT supports, only a small proportion of the sample reported that adequate funding was available to support KT. Further, most participants agreed that specialised implementation researchers should translate their research and that every research team should include such a researcher.\n</p>", "<p id=\"Par24\">Significant differences were found in perceived importance, ability, and responsibility for KT by career stage, research type, work setting, and KT training. Participants differed in their perceived ability to engage in KT, with more experienced researchers reporting knowing which strategies to use (3.58 ± 0.77 vs. 3.03 ± 1.03, <italic>t</italic>(104) = − 3.07, <italic>p</italic> = 0.003) and having the skills to ensure research is translated (3.47 ± 0.75 vs. 3.07 ± 1.09, <italic>t</italic>(100.44) = − 2.22, <italic>p</italic> = 0.029), to a greater extent than less experienced researchers. In addition, researchers with KT training reported significantly greater scores on knowledge of KT strategies (3.72 ± 0.70 vs. 3.05 ± 0.98, <italic>t</italic>(92.72) = 4.10, <italic>p</italic> &lt; 0.001), and perceived KT skills (3.58 ± 0.73 vs. 3.05 ± 1.01, <italic>t</italic>(107) = 2.79, <italic>p</italic> = 0.006), than researchers not reporting any KT training. Further, basic science researchers reported greater KT skills than applied science researchers (3.51 ± 0.80 vs. 3.12 ± 1.02, <italic>t</italic>(103) = 2.05, <italic>p</italic> = 0.043). A significant difference was found in clinician responsibility of KT by work setting, <italic>F</italic>(2,106) = 3.10, <italic>p</italic> = 0.049, with researchers working in a joint work setting more likely to report KT as the responsibility of clinicians than researchers in an academic work setting (4.06 ± 0.72 vs. 3.56 ± 0.65, <italic>p</italic> = 0.039) and researchers working an applied setting not being significantly different from other groups (3.88 ± 0.83, both <italic>p</italic>’s &gt; 0.05). Finally, more experienced researchers reported greater funding to support KT than less experienced researchers (2.60 ± 0.96 vs. 2.09 ± 0.81, <italic>t</italic>(92.15) = − 2.95, <italic>p</italic> = 0.004).</p>", "<title>Dissemination activities</title>", "<p id=\"Par25\">Examining how research findings are shared (see Table ##TAB##2##3##), most researchers used diffusion activities “frequently” or “always” (86%), with most publishing in peer-reviewed journals and presenting at academic conferences. Researchers reported using more active dissemination activities to a slightly lesser extent (60%), with the most frequently used methods being plain language summaries, new educational materials, or interactive small group meetings/workshops.\n</p>", "<p id=\"Par26\">Comparative analysis showed significant differences in dissemination activities by experience, work setting, and KT training, but not research type. More experienced researchers reported using detailed reports (3.46 ± 0.99 vs. 3.02 ± 1.27, <italic>t</italic>(109) = − 2.01, <italic>p</italic> = 0.047) and developing new education materials (3.20 ± 0.86 vs. 2.76 ± 1.07, <italic>t</italic>(110) = − 2.38, <italic>p</italic> = 0.019), to a greater extent than less experienced researchers. A significant difference was found in publishing in peer-reviewed journals by work setting, <italic>F</italic>(2,71.55) = 27.13, <italic>p</italic> &lt; 0.001, with researchers working in an academic setting (4.78 ± 0.42) reporting using this more frequently than those working in a joint work setting (4.27 ± 0.76) or an applied work setting (3.54 ± 1.13), all <italic>p</italic>’s &lt; 0.05. Further, a significant difference was found in academic conference presentations by work setting, <italic>F</italic>(2,70.28) = 7.80, <italic>p</italic> &lt; 0.001, with researchers working in applied work settings (3.57 ± 1.01) reporting using this method of dissemination less frequently than those working in an academic setting (4.26 ± 0.59, <italic>p</italic> &lt; 0.001) or a joint work setting (4.09 ± 0.77, <italic>p</italic> = 0.020). However, no significant difference in dissemination through presentation at academic conferences was observed between researchers working in academic and joint settings (<italic>p</italic> = 0.606).</p>", "<p id=\"Par27\">Several significant differences were observed in the use of dissemination activities between those who received KT training and those who did not. In particular, researchers reporting KT training more frequently developed new educational materials/sessions (3.31 ± 0.79 vs. 2.76 ± 1.05, <italic>t</italic>(114) = 2.78, <italic>p</italic> = 0.006), prepared a policy or evidence brief (3.03 ± 0.73 vs. 2.62 ± 0.96, <italic>t</italic>(91.35) = 2.52, <italic>p</italic> = 0.013), organised an interactive small group meeting/workshop (3.14 ± 0.76 vs. 2.76 ± 1.02, <italic>t</italic>(88.83) = 2.20, <italic>p</italic> = 0.030), organised a media campaign (2.36 ± 0.87 vs. 1.70 ± 0.92, <italic>t</italic>(111) = 3.62, <italic>p</italic> &lt; 0.001), networked with end-users (2.86 ± 0.92 vs. 2.38 ± 1.06, <italic>t</italic>(115) = 2.42, <italic>p</italic> = 0.017), and engaged champions to share research findings (2.97 ± 0.87 vs. 2.31 ± 0.99, <italic>t</italic>(115) = 3.49, <italic>p</italic> &lt; 0.001).</p>", "<title>Level of end-user engagement</title>", "<p id=\"Par28\">Table ##TAB##3##4## shows the self-reported level of end-user engagement. Most participants had engaged end-users in their research (87%). Participants reported that their engagement with end-users was mainly centred around informing them about findings through presentations, meetings, plain language summaries, or research papers, although 72% reported engaging end-users in their research beyond these activities. Almost half of the participants had consulted end-users about a research component or involved them directly throughout the research process. A quarter of participants reported having partnered with end-users in each aspect of the research. A small proportion of participants reported conducting end-user-initiated research.\n</p>", "<p id=\"Par29\">Significant differences were found in end-user engagement by career stage, work setting, and KT training. In particular, a greater proportion of established career researchers engaged end-users in their research beyond dissemination compared to early/mid-career researchers (82% vs. 65%, <italic>χ</italic><sup>2</sup>(1) = 4.01, <italic>p</italic> = 0.045), with significant differences also found between researchers in a joint work setting (88%) compared to an applied work setting (71%) or an academic work setting (52%, <italic>χ</italic><sup>2</sup>(2) = 12.33, <italic>p</italic> = 0.002), and between researchers with KT training (86%) compared to those without (65%, <italic>χ</italic><sup>2</sup>(1) = 5.77, <italic>p</italic> = 0.016). Further, a greater proportion of researchers working in a joint work setting (55%) reported partnering with end-users compared to an academic work setting (30%) or an applied work setting (8.9%, <italic>χ</italic><sup>2</sup>(2) = 22.22, <italic>p</italic> &lt; 0.001). In addition, a significant difference in partnering with end users was also found in researchers with KT training (41%) compared to those without (21%, <italic>χ</italic><sup>2</sup>(1) = 4.74, <italic>p</italic> = 0.030). Finally, a greater proportion of researchers in an academic work setting (33%) reported not engaging end-users in their research compared to researchers in applied work settings (11%) or joint work settings (3.0%, <italic>χ</italic><sup>2</sup>(2) = 12.33, <italic>p</italic> = 0.002). No significant differences in end-user engagement were found by research type.</p>", "<title>Specific end-user groups and research stages</title>", "<p id=\"Par30\">Follow-up questions were asked of those who reported engaging end-users in their research (<italic>n</italic> = 84) to determine which end-user groups they engaged and at what stage in the research process (see Table ##TAB##4##5##). The most common groups involved in research were frontline staff (80%) and senior management/policy-makers (79%), followed by blood donors/recipients (58%) and the general public (23%). Participants reported having experience engaging end-users throughout all of the research phases, with the most frequently reported phase being data collection (68%), followed by input into the study design and determining future research priorities stemming from results (both 56%). The least reported phases were data analysis (27%) and evaluation of research processes (23%).\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par31\">Translating research is seen as important by transfusion medicine researchers, with most considering it their responsibility to ensure that their research is translated. However, many researchers feel they do not have skills or knowledge of strategies to translate the knowledge gained from their research. Researchers typically focus on sharing their knowledge through traditional diffusion strategies, with more tailored dissemination approaches used to a lesser extent. Further, whilst most participants had informed end-users of their research findings, only half of the sample also had experience with consulting end-users about a research component or involving them throughout the research process. Only slightly more than 1 in 4 researchers in this study reported an experience working in genuine partnership with end-users and only 1 in 6 had conducted end-user-initiated research. These findings are aligned with other studies [##REF##17204143##12##–##REF##19698186##16##] conducted in other health-related areas where traditional diffusion strategies were more frequently used than tailored approaches.</p>", "<p id=\"Par32\">However, our study did find differences in the use of dissemination strategies. Training in KT was found to be associated with greater perceived KT skills and knowledge of KT strategies. It was also associated with greater use of tailored dissemination strategies, such as developing new educational materials/sessions and small group meetings or workshops, and end-user engagement activities, such as partnering with end-users, compared to those without. The benefits of KT training were also documented in a recent study where trainees had greater knowledge of KT, perceived skills to practice KT, and greater perceived ability to engage with end-users after receiving KT training [##REF##37488655##29##]. This suggests that providing KT training to transfusion medicine researchers may be an effective strategy to increase KT in this area. Whilst this difference may be attributed to researchers with an interest in KT undergoing training, many of our surveyed sample identified that they would like to have access to KT education and training [##REF##37357984##25##]. Further research is needed to develop and evaluate a KT training programme for transfusion medicine researchers as a way to increase their knowledge, confidence, and use of KT activities.</p>", "<p id=\"Par33\">Our research also identified a difference in KT views and activities by career stage. Established researchers reported greater knowledge of KT strategies, skills to facilitate KT, and available funding for KT than less experienced researchers. This discrepancy in abilities and resources may have affected KT practices, with established researchers having written detailed reports, developed new education materials, and engaged end-users in their research to a greater extent than early/mid-career researchers. A potential explanation for this finding may be that researchers working in transfusion medicine for a longer period of time have had the opportunity to conduct more research and therefore have had a greater need for knowledge to be translated compared to researchers relatively new to the area. Further, they may have had more time to form connections with end-users and gain experiential knowledge on effective KT strategies as no significant differences were found between the two groups in self-reported KT training. It is important that this knowledge is shared with early and mid-career researchers to support their KT efforts through for example mentoring or collaboration through facilitated networks [##REF##27737693##30##–##REF##34778809##32##]. It is recommended that these knowledge sharing strategies are further investigated.</p>", "<p id=\"Par34\">Another factor that appears to affect KT practice is the setting in which the researcher is located. We found that researchers working solely in an academic setting reported more traditional diffusion strategies and less end-user engagement activities than researchers working (to some extent) in an applied setting. There are several possible explanations for this finding. Some academic institutions may place a greater emphasis on traditional diffusion methods, such as peer-reviewed publications, as performance indicators and considerations for promotion. In contrast, health services may place a greater value on research that leads to improved outcomes for their patients, blood donors, staff, or the health service itself [##UREF##7##33##]. Further, funding may affect the type and topic of the research conducted; researchers working in applied settings are often funded directly by the blood collection agency or health service who desire practical solutions to their issues [##REF##20726958##22##]. In contrast to health services, external funding bodies may place more emphasis on traditional diffusion strategies [##REF##26183210##34##, ##REF##22531033##35##]. Finally, researchers working in an applied or joint position within a blood collection agency or other health service may have had more opportunities to create end-user networks and find it easier to engage with these networks throughout the research process. As a result, the knowledge generated through the research may be more directly relevant to issues faced by the blood collection agency or health service and more easily translatable to policy and/or practice [##UREF##1##5##, ##REF##35985787##10##, ##REF##30788147##11##, ##REF##32106847##36##].</p>", "<p id=\"Par35\">Of equal interest is the limited differences observed between basic and applied science researchers. In our study, with the exception of basic science researchers reporting greater KT skills, no differences were found between basic science researchers and applied science researchers in their views of KT, how they share their knowledge, and the extent they engage end-users in their research. This is somewhat surprising as the literature has suggested that the purpose of KT differs between the two groups. Basic science researchers are assumed to focus on translation to clinical science and knowledge, with outcomes such as clinical use or commercialisation of new treatments. On the other hand, applied sciences are assumed to focus on translation to healthcare and services, with outcomes such as treatments are being used appropriately [##REF##18182604##19##, ##UREF##5##20##]. However, our findings align with the experiences of stroke rehabilitation researchers, in which pre-clinical and clinical researchers reported similar research translation views and practices [##REF##30206084##28##]. This suggests that, whilst their KT purpose may differ, basic and applied science researchers apply similar KT dissemination and end-user engagement activities.</p>", "<title>Limitations</title>", "<p id=\"Par36\">There were several limitations to the study. First, researchers with no interest in KT may have opted out of participating affecting the generalisability of the results. Second, the sample size was relatively small in comparison with the number of survey invitations sent directly to corresponding authors and grant recipients as well as likely views of the social media posts. However, our sample was diverse in the type of research, work setting, location, career stage, and self-reported KT training suggesting our insights reflect the broader transfusion medicine research community. Third, our sample may include research trainees as we did not screen for this in our survey. Whilst this may have influenced some of our findings regarding less experienced researchers, our recommendation for the need to better support less experienced researchers through sharing knowledge of established researchers remains. Fourth, the study materials, including the questionnaire, were only presented in English, which may have limited our sample to researchers fluent in English. Nevertheless, our sample does include participants from a wide range of countries. Fifth, we only focused on two aspects of KT, and further research is needed to examine researchers’ practices relating to the synthesis and application of knowledge. Finally, KT activities were self-reported and assessed over their career in general as a transfusion medicine researcher, which may have led to some recall bias. In addition, it may have also led to social desirability bias causing overreporting of KT activities. Future research could look to measuring KT activities more objectively.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par37\">This study showed that transfusion medicine researchers consider KT as being important and feel it is part of their responsibility. However, there appear to be gaps in their knowledge and limited support to conduct KT. Our work highlights that KT knowledge needs to be shared across all health-related areas, including transfusion medicine, to ensure knowledge producers, such as researchers, can benefit from advancements made in the field of KT and implementation science.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Health research is often driven by the desire to improve the care and health of the community; however, the translation of research evidence into policy and practice is not guaranteed. Knowledge translation (KT) activities, such as dissemination and end-user engagement by researchers, are important to achieving this goal. This study examined researchers’ views on and practices of KT in the field of transfusion medicine.</p>", "<title>Methods</title>", "<p id=\"Par2\">An anonymous, cross-sectional survey was distributed to transfusion medicine researchers in May 2022 by emailing corresponding authors of papers in four major blood journals, emailing grant recipients, posting on social media, and through international blood operator networks. Comparative analyses were conducted for career stage, work setting, research type, and KT training.</p>", "<title>Results</title>", "<p id=\"Par3\">The final sample included 117 researchers from 33 countries. Most participants reported that research translation was important (86%) and felt it was their responsibility (69%). Fewer than half felt they had the skills to translate their research (45%) or knew which strategies to employ (45%). When examining how research findings are shared, most reported using diffusion activities (86%), including publishing in peer-reviewed journals (74%), or presenting at academic conferences (72%). Fewer used dissemination methods (60%), such as developing educational materials (29%) or writing plain language summaries (30%). Greater use of tailored dissemination strategies was seen among researchers with KT training, whilst traditional diffusion strategies were used more by those working in an academic setting. Most participants had engaged end-users in their research (72%), primarily to consult on a research component (47%) or to involve them in the research process (45%). End-user engagement was greater among researchers with established careers, working in both academic and applied settings, and with KT training.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Whilst participating researchers acknowledged the importance of KT, they typically focused on traditional diffusion strategies. This is despite well-established knowledge of the limited impact of these strategies in achieving KT. Those with KT training were more likely to use tailored dissemination strategies and engage end-users in their research. This demonstrates the value of sharing knowledge from the KT field with health researchers to facilitate KT.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s43058-024-00546-3.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Authors’ contributions</title>", "<p>AT, BM, TD, and AW designed and planned the study. AT was responsible for the study conduct. BM and TD assisted with the data collection. AT wrote the first draft of the manuscript. All authors have been involved in drafting the manuscript and approved the final manuscript.</p>", "<title>Funding</title>", "<p>Australian governments fund Australian Red Cross Lifeblood for the provision of blood, blood products, and services to the Australian community.</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated and/or analysed during the current study are not publicly available due to privacy restrictions but may be available from the corresponding author upon reasonable request, subject to ethics and institutional approval.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par38\">This project has been approved by the University of Sydney Human Research Committee (2021/854).</p>", "<title>Consent for publication</title>", "<p id=\"Par39\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par40\">The authors declare that they have no competing interests.</p>" ]
[]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Participant characteristics (<italic>n</italic> = 117)<sup>a</sup></p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\"><italic>n</italic> (%)</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\"><italic>Gender</italic></td></tr><tr><td align=\"left\"> Man/male</td><td align=\"left\">58 (49.6)</td></tr><tr><td align=\"left\"> Woman/female</td><td align=\"left\">57 (48.7)</td></tr><tr><td align=\"left\"> Non-binary</td><td align=\"left\">1 (0.9)</td></tr><tr><td align=\"left\"> Prefer not to say</td><td align=\"left\">1 (0.9)</td></tr><tr><td align=\"left\" colspan=\"2\"><italic>Main work setting</italic></td></tr><tr><td align=\"left\"> University</td><td align=\"left\">28 (23.9)</td></tr><tr><td align=\"left\"> Research institute</td><td align=\"left\">11 (9.4)</td></tr><tr><td align=\"left\"> Government department or agency</td><td align=\"left\">2 (1.7)</td></tr><tr><td align=\"left\"> Blood collection agency</td><td align=\"left\">36 (30.8)</td></tr><tr><td align=\"left\"> Hospital setting</td><td align=\"left\">32 (27.4)</td></tr><tr><td align=\"left\"> Healthcare service (other)</td><td align=\"left\">1 (0.9)</td></tr><tr><td align=\"left\"> Other</td><td align=\"left\">6 (5.1)</td></tr><tr><td align=\"left\"> Missing</td><td align=\"left\">1 (0.9)</td></tr><tr><td align=\"left\" colspan=\"2\"><italic>Secondary work setting</italic></td></tr><tr><td align=\"left\"> University</td><td align=\"left\">24 (20.5)</td></tr><tr><td align=\"left\"> Research institute</td><td align=\"left\">2 (1.7)</td></tr><tr><td align=\"left\"> Government department or agency</td><td align=\"left\">7 (6.0)</td></tr><tr><td align=\"left\"> Blood collection agency</td><td align=\"left\">7 (6.0)</td></tr><tr><td align=\"left\"> Hospital setting</td><td align=\"left\">8 (6.8)</td></tr><tr><td align=\"left\"> None</td><td align=\"left\">65 (55.6)</td></tr><tr><td align=\"left\"> Missing</td><td align=\"left\">4 (3.4)</td></tr><tr><td align=\"left\" colspan=\"2\"><italic>Type of methods (MC)</italic></td></tr><tr><td align=\"left\"> Animal studies</td><td align=\"left\">11 (9.4)</td></tr><tr><td align=\"left\"> Biospecimen analysis research</td><td align=\"left\">39 (33.3)</td></tr><tr><td align=\"left\"> Data linkage research</td><td align=\"left\">33 (28.2)</td></tr><tr><td align=\"left\"> Epidemiological research</td><td align=\"left\">48 (41.0)</td></tr><tr><td align=\"left\"> Interventional/clinical trials research</td><td align=\"left\">39 (33.3)</td></tr><tr><td align=\"left\"> Qualitative research</td><td align=\"left\">46 (39.3)</td></tr><tr><td align=\"left\"> Quantitative research</td><td align=\"left\">53 (45.3)</td></tr><tr><td align=\"left\"> Other</td><td align=\"left\">17 (14.5)</td></tr><tr><td align=\"left\" colspan=\"2\"><italic>Career stage</italic></td></tr><tr><td align=\"left\"> Years active in transfusion medicine</td><td align=\"left\">16.6 (± 10.5)</td></tr><tr><td align=\"left\"> Early to mid-career (1–15 years)</td><td align=\"left\">63 (53.8)</td></tr><tr><td align=\"left\"> Established (16–50 years)</td><td align=\"left\">50 (42.7)</td></tr><tr><td align=\"left\"> Not specified</td><td align=\"left\">4 (3.4)</td></tr><tr><td align=\"left\" colspan=\"2\"><italic>Knowledge translation training</italic></td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">37 (31.6)</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">69 (59.0)</td></tr><tr><td align=\"left\"> Unsure/do not know</td><td align=\"left\">11 (9.4)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Researchers’ views on the importance and responsibility of knowledge translation (<italic>n</italic> = 117)<sup>a</sup></p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Statement</th><th align=\"left\" rowspan=\"2\">Median (IQR)</th><th align=\"left\" colspan=\"4\">Level of agreement, <italic>n</italic> (%)</th></tr><tr><th align=\"left\"><bold>Disagree</bold></th><th align=\"left\"><bold>Neutral</bold></th><th align=\"left\"><bold>Agree</bold></th><th align=\"left\"><bold><italic>Missing</italic></bold></th></tr></thead><tbody><tr><td align=\"left\">1. It is important to me that my research is translated</td><td align=\"left\">5 (4–5)</td><td align=\"left\">0</td><td align=\"left\">11 (9.4)</td><td align=\"left\">100 (85.5)</td><td align=\"left\">6 <italic>(5.1)</italic></td></tr><tr><td align=\"left\">2. My research is not the sort of research that can be translated</td><td align=\"left\">2 (1–2)</td><td align=\"left\">97 (82.9)</td><td align=\"left\">10 (8.5)</td><td align=\"left\">4 (3.4)</td><td align=\"left\"><italic>6 (5.1)</italic></td></tr><tr><td align=\"left\">3. It is my responsibility to ensure that my research is translated</td><td align=\"left\">4 (3–4)</td><td align=\"left\">10 (8.5)</td><td align=\"left\">19 (16.2)</td><td align=\"left\">81 (69.2)</td><td align=\"left\"><italic>7 (6.0)</italic></td></tr><tr><td align=\"left\">4. Research translation is the responsibility of someone else in my team</td><td align=\"left\">3 (2–3)</td><td align=\"left\">53 (45.3)</td><td align=\"left\">43 (36.8)</td><td align=\"left\">13 (11.1)</td><td align=\"left\"><italic>8 (6.8)</italic></td></tr><tr><td align=\"left\">5. Researchers should be responsible for translating research findings into practice</td><td align=\"left\">4 (3–4)</td><td align=\"left\">10 (8.5)</td><td align=\"left\">33 (28.2)</td><td align=\"left\">68 (58.1)</td><td align=\"left\"><italic>6 (5.1)</italic></td></tr><tr><td align=\"left\">6. Clinicians should be responsible for translating findings into clinical practice</td><td align=\"left\">4 (3–4)</td><td align=\"left\">5 (4.3)</td><td align=\"left\">23 (19.7)</td><td align=\"left\">82 (70.1)</td><td align=\"left\"><italic>7 (6.0)</italic></td></tr><tr><td align=\"left\">7. I know which strategies should be used (by myself/others) to translate my research</td><td align=\"left\">3 (3–4)</td><td align=\"left\">26 (22.2)</td><td align=\"left\">31 (26.5)</td><td align=\"left\">53 (45.3)</td><td align=\"left\">7 <italic>(6.8)</italic></td></tr><tr><td align=\"left\">8. I have the skills to ensure my research is translated</td><td align=\"left\">3 (3–4)</td><td align=\"left\">25 (21.4)</td><td align=\"left\">31 (26.5)</td><td align=\"left\">53 (45.3)</td><td align=\"left\"><italic>8 (6.8)</italic></td></tr><tr><td align=\"left\">9. There is adequate funding to support translation of research</td><td align=\"left\">2 (2–3)</td><td align=\"left\">71 (60.7)</td><td align=\"left\">26 (22.2)</td><td align=\"left\">12 (10.3)</td><td align=\"left\"><italic>8 (6.8)</italic></td></tr><tr><td align=\"left\">10. Spending time on translating my research would take me away from research (or other work-related activities) I enjoy</td><td align=\"left\">3 (2–4)</td><td align=\"left\">44 (37.6)</td><td align=\"left\">27 (23.1)</td><td align=\"left\">37 (31.6)</td><td align=\"left\"><italic>9 (7.7)</italic></td></tr><tr><td align=\"left\">11. Researchers with experience/interest in implementation should translate my research</td><td align=\"left\">4 (3–4)</td><td align=\"left\">6 (5.1)</td><td align=\"left\">29 (24.8)</td><td align=\"left\">75 (64.1)</td><td align=\"left\"><italic>7 (6.0)</italic></td></tr><tr><td align=\"left\">12. Every research team should include a researcher with expertise in implementation</td><td align=\"left\">4 (3–4)</td><td align=\"left\">11 (9.4)</td><td align=\"left\">25 (21.4)</td><td align=\"left\">75 (64.1)</td><td align=\"left\"><italic>6 (5.1)</italic></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Diffusion and dissemination activities (<italic>n</italic> = 117)<sup>a</sup></p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Activities to disseminate research findings</th><th align=\"left\" rowspan=\"2\">Median (IQR)</th><th align=\"left\" colspan=\"4\">Level of engagement, <italic>n</italic> (%)</th></tr><tr><th align=\"left\"><bold>Never</bold></th><th align=\"left\"><bold>Rarely/occasionally</bold></th><th align=\"left\"><bold>Frequently/always</bold></th><th align=\"left\"><bold><italic>Missing</italic></bold></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"6\"><italic>Diffusion activities</italic></td></tr><tr><td align=\"left\"> Publishing in peer-reviewed journals</td><td align=\"left\">4 (3–5)</td><td align=\"left\">3 (2.6)</td><td align=\"left\">28 (23.9)</td><td align=\"left\">86 (73.5)</td><td align=\"left\"><italic>–</italic></td></tr><tr><td align=\"left\"> Presenting at an academic conference</td><td align=\"left\">4 (3–5)</td><td align=\"left\">2 (1.7)</td><td align=\"left\">31 (26.5)</td><td align=\"left\">84 (71.8)</td><td align=\"left\"><italic>–</italic></td></tr><tr><td align=\"left\"> Detailed research reports</td><td align=\"left\">3 (2–4)</td><td align=\"left\">12 (10.3)</td><td align=\"left\">53 (45.3)</td><td align=\"left\">50 (42.7)</td><td align=\"left\"><italic>2 (1.7)</italic></td></tr><tr><td align=\"left\" colspan=\"6\"><italic>Dissemination activities</italic></td></tr><tr><td align=\"left\"> Developing new educational materials</td><td align=\"left\">3 (2–4)</td><td align=\"left\">12 (10.3)</td><td align=\"left\">70 (59.8)</td><td align=\"left\">34 (29.1)</td><td align=\"left\"><italic>1 (0.9)</italic></td></tr><tr><td align=\"left\"> Writing plain language summaries</td><td align=\"left\">3 (2–4)</td><td align=\"left\">10 (8.5)</td><td align=\"left\">71 (60.7)</td><td align=\"left\">35 (29.9)</td><td align=\"left\"><italic>1 (0.9)</italic></td></tr><tr><td align=\"left\"> Organising an interactive small group meeting/workshop</td><td align=\"left\">3 (2–4)</td><td align=\"left\">13 (11.1)</td><td align=\"left\">71 (60.7)</td><td align=\"left\">32 (27.4)</td><td align=\"left\"><italic>1 (0.9)</italic></td></tr><tr><td align=\"left\"> Preparing a policy or an evidence brief and disseminating it to relevant audiences (e.g. policymakers, health service providers, or administrators)</td><td align=\"left\">3 (2–3)</td><td align=\"left\">12 (10.3)</td><td align=\"left\">83 (70.9)</td><td align=\"left\">21 (17.9)</td><td align=\"left\"><italic>1 (0.9)</italic></td></tr><tr><td align=\"left\"> Creating networks or networking with end-users such as policymakers and practitioners (e.g. give presentations to relevant networks)</td><td align=\"left\">3 (2–3)</td><td align=\"left\">24 (20.5)</td><td align=\"left\">75 (64.1)</td><td align=\"left\">18 (15.4)</td><td align=\"left\"><italic>–</italic></td></tr><tr><td align=\"left\"> Engage champions or opinion leaders (e.g. directors, managers) to assist with sharing of research findings</td><td align=\"left\">2 (2–3)</td><td align=\"left\">19 (16.2)</td><td align=\"left\">78 (66.7)</td><td align=\"left\">20 (17.1)</td><td align=\"left\"><italic>–</italic></td></tr><tr><td align=\"left\"> Engaging with social media (e.g. Facebook, Twitter)</td><td align=\"left\">2 (1–3)</td><td align=\"left\">35 (29.9)</td><td align=\"left\">61 (52.1)</td><td align=\"left\">20 (17.1)</td><td align=\"left\"><italic>1 (0.9)</italic></td></tr><tr><td align=\"left\"> Organising a media release/outreach campaign</td><td align=\"left\">2 (1–3)</td><td align=\"left\">48 (41.0)</td><td align=\"left\">57 (48.7)</td><td align=\"left\">8 (6.8)</td><td align=\"left\"><italic>4 (3.4)</italic></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Level of end-user engagement (<italic>n</italic> = 117)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Level of engagement</th><th align=\"left\"><italic>n</italic> (%)</th></tr></thead><tbody><tr><td align=\"left\">Letting them know about your research findings</td><td align=\"left\">70 (62.5)</td></tr><tr><td align=\"left\"> Sent them my research papers</td><td align=\"left\">34 (30.4)</td></tr><tr><td align=\"left\"> Sent them evidence briefs or plain language summaries</td><td align=\"left\">38 (33.9)</td></tr><tr><td align=\"left\"> Presented my research to them</td><td align=\"left\">49 (43.8)</td></tr><tr><td align=\"left\"> Held meetings, roundtables, or forums to discuss my research</td><td align=\"left\">41 (36.6)</td></tr><tr><td align=\"left\">Obtaining their feedback or input in any component of research</td><td align=\"left\">53 (47.3)</td></tr><tr><td align=\"left\">Working directly with end-users throughout the research process to ensure that concerns and aspirations are consistently understood and considered to the maximum extent possible</td><td align=\"left\">50 (44.6)</td></tr><tr><td align=\"left\">Partnering with end-users (i.e. shared decision-making) in each aspect of the research process</td><td align=\"left\">31 (27.7)</td></tr><tr><td align=\"left\">End-user-initiated research</td><td align=\"left\">19 (17.0)</td></tr><tr><td align=\"left\">I have not engaged end-users in my research</td><td align=\"left\">15 (13.4)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Engagement phase (<italic>n</italic> = 84)<sup>a</sup></p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Research phase</th><th align=\"left\"><italic>n</italic> (%)</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\"><bold>End-user groups</bold></td></tr><tr><td align=\"left\">Blood donors/recipients</td><td align=\"left\">49 (58.3)</td></tr><tr><td align=\"left\">Front-line staff</td><td align=\"left\">67 (79.8)</td></tr><tr><td align=\"left\">Senior management/policymakers</td><td align=\"left\">66 (78.6)</td></tr><tr><td align=\"left\">General public</td><td align=\"left\">19 (22.6)</td></tr><tr><td align=\"left\">Other</td><td align=\"left\">9 (10.7)</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Research phase</bold></td></tr><tr><td align=\"left\">Research priority-setting</td><td align=\"left\">40 (47.6)</td></tr><tr><td align=\"left\">Grant proposal/protocol writing</td><td align=\"left\">42 (50.0)</td></tr><tr><td align=\"left\">Input into methodology/study design</td><td align=\"left\">47 (56.0)</td></tr><tr><td align=\"left\">Development of research questions</td><td align=\"left\">45 (53.6)</td></tr><tr><td align=\"left\">Data collection</td><td align=\"left\">57 (67.9)</td></tr><tr><td align=\"left\">Data analysis</td><td align=\"left\">23 (27.4)</td></tr><tr><td align=\"left\">Interpretation of results</td><td align=\"left\">37 (44.0)</td></tr><tr><td align=\"left\">Input into the selection of research translation products</td><td align=\"left\">27 (32.1)</td></tr><tr><td align=\"left\">Evaluation of research processes</td><td align=\"left\">19 (22.6)</td></tr><tr><td align=\"left\">Determining future research priorities stemming from results</td><td align=\"left\">47 (56.0)</td></tr></tbody></table></table-wrap>" ]
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[ "<boxed-text><label>Contributions to the literature</label><p id=\"Par6\">\n<list list-type=\"bullet\"><list-item><p id=\"Par7\">This study showed that whilst researchers feel responsible for knowledge translation (KT), many do not feel they have the skills or knowledge to effectively translate their research.</p></list-item><list-item><p id=\"Par8\">Traditional diffusion strategies remain the most common ways to share research knowledge in transfusion medicine.</p></list-item><list-item><p id=\"Par9\">The findings of this paper showed differences in KT practices by career stage, work setting, and self-reported KT training</p></list-item><list-item><p id=\"Par10\">This indicates the potential for KT training to increase the use of tailored dissemination strategies and end-user engagement among researchers.</p></list-item></list></p></boxed-text>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup>Years active in transfusion medicine presented as mean (standard deviation)</p><p><italic>MC</italic> multiple choice</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>Rated as strongly disagree (1) to strongly agree (5). For frequencies, “agree”, “strongly agree”, “disagree”, and “strongly disagree” pooled together</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>Rated as never (1) to always (5). For frequencies, “frequently” and “always”, and “rarely” and “occasionally” were pooled together</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>Asked only to those who indicated engaging end-users in their research. Multiple choice</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"43058_2024_546_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1.</bold> STROBE Statement—checklist of items that should be included in reports of observational studies.</p></caption></media>", "<media xlink:href=\"43058_2024_546_MOESM2_ESM.docx\"><caption><p><bold>Additional file 2.</bold> Questionnaire Knowledge Translation in Transfusion Medicine.</p></caption></media>" ]
[{"label": ["3."], "surname": ["Straus", "Tetroe", "Graham", "Straus", "Tetroe", "Graham"], "given-names": ["SE", "J", "ID", "SE", "J", "ID"], "article-title": ["Knowledge translation: What it is and what is isn\u2019t"], "source": ["Knowledge translation in health care: moving from evidence to practice"], "year": ["2013"], "publisher-loc": ["Chichester"], "publisher-name": ["John Wiley & Sons"], "fpage": ["3"], "lpage": ["13"]}, {"label": ["5."], "surname": ["Brownson", "Eyler", "Harris", "Moore", "Tabak"], "given-names": ["RC", "AA", "JK", "JB", "RG"], "article-title": ["Getting the word out: new approaches for disseminating public health science"], "source": ["Public Health Manag Pract"], "year": ["2018"], "volume": ["24"], "issue": ["2"], "fpage": ["102"], "lpage": ["111"], "pub-id": ["10.1097/PHH.0000000000000673"]}, {"label": ["7."], "mixed-citation": ["Graham ID, Tetroe J, Gagnon M. Knowledge dissemination: end of grant knowledge translation. In: Straus SE, Tetroe J, Graham ID, editors. Knowledge translation in health care: moving from evidence to practice. Chichester: Wiley; 2013. p. 75\u201392."]}, {"label": ["9."], "mixed-citation": ["Rabin BA, Brownson RC. Terminology for dissemination and implementation research. In: Brownson RC, Colditz GA, Proctor EK, editors. Dissemination and implementation research in health: translating science to practice. 2 ed. New York: Oxford University Press; 2018. p. 19\u201346."]}, {"label": ["17"], "surname": ["Brownson", "Jacobs", "Tabak", "Hoehner", "Stamatakis"], "given-names": ["RC", "JA", "RG", "CM", "KA"], "article-title": ["Designing for dissemination among public health researchers: findings from a national survey in the United States"], "source": ["Am J Public Health (1971)"], "year": ["2013"], "volume": ["103"], "issue": ["9"], "fpage": ["1693"], "lpage": ["9"], "pub-id": ["10.2105/AJPH.2012.301165"]}, {"label": ["20."], "surname": ["Grimshaw", "Eccles", "Lavis", "Hill", "Squires"], "given-names": ["JM", "MP", "JN", "SJ", "JE"], "article-title": ["Knowledge translation of research findings"], "source": ["Implement Sci"], "year": ["2012"], "volume": ["7"], "issue": ["1"], "fpage": ["1"], "lpage": ["17"], "pub-id": ["10.1186/1748-5908-7-50"]}, {"label": ["27."], "collab": ["Canadian Institutes of Health Research"], "source": ["Guide to knowledge translation planning at CIHR: integrated and end-of-grant approaches"], "year": ["2012"], "publisher-loc": ["Ottawa"], "publisher-name": ["Canadian Institutes of Health Research"]}, {"label": ["33."], "surname": ["McNeal", "Glasgow", "Brownson", "Matlock", "Peterson", "Daugherty"], "given-names": ["DM", "RE", "RC", "DD", "PN", "SL"], "article-title": ["Perspectives of scientists on disseminating research findings to non-research audiences"], "source": ["J Clin Transl Sci"], "year": ["2021"], "volume": ["5"], "issue": ["1"], "fpage": ["e61"], "pub-id": ["10.1017/cts.2020.563"]}]
{ "acronym": [ "KT" ], "definition": [ "Knowledge translation" ] }
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2024-01-14 23:43:46
Implement Sci Commun. 2024 Jan 12; 5:9
oa_package/73/7f/PMC10787432.tar.gz
PMC10787433
38217063
[ "<title>Background</title>", "<p id=\"Par4\">Melatonin is a pineal hormone known for its role in the regulation of circadian [##REF##1394610##1##] and seasonal rhythms [##REF##8120796##2##], in addition to glucose and lipid metabolism [##REF##33080320##3##, ##REF##31901302##4##] with a role in obesity [##UREF##0##5##], anti-inflammation and antioxidation [##REF##18571301##6##–##UREF##2##8##].</p>", "<p id=\"Par5\">Melatonin exerts its roles through two melatonin G protein-coupled receptors: melatonin receptor 1 A (encoded by <italic>MTNR1A</italic> gene) and melatonin receptor 1B (encoded by <italic>MTNR1B</italic> gene) [##REF##23712359##9##, ##REF##27551178##10##]. The two receptors are expressed on the nervous system, pancreas, liver, skeletal muscle, adipose tissue, and ovaries [##REF##18571301##6##, ##REF##22245784##11##]. The two melatonin receptors have been implicated in the risk of mental and metabolic disorders such as type 2 diabetes (T2D) [##REF##30531911##12##–##UREF##4##14##] and depression (MDD) [##UREF##4##14##, ##REF##21353709##15##].</p>", "<p id=\"Par6\">Of interest, polycystic ovarian syndrome (PCOS), a complex and common hormonal disorder affecting women of reproductive age and characterized by anovulation, hyperandrogenism, and polycystic ovaries, is commonly associated with type 2 diabetes (T2D) [##REF##23065822##16##] and mental traits, including anxiety [##REF##20117778##17##, ##REF##34165386##18##] and depression [##REF##34642910##19##, ##REF##36117653##20##]. PCOS, which affects approximately 6-18% of women worldwide [##REF##35934017##21##] and can lead to long-term health consequences, including infertility, metabolic syndrome, cardiovascular disease, is a genetically complex disorder that involves the interplay of multiple genes and environmental factors [##UREF##5##22##]. PCOS is linked to a variety of possible pathogenetic impairments, distinct or overlapping, including the neuroendocrine pathways, and ovarian and adrenal hormonal secretions [##REF##27459230##23##]. The circadian rhythm and melatonin system have been implicated in PCOS [##REF##33358334##24##]. Candidate gene studies have associated PCOS with several genes, including the insulin receptor gene (<italic>INSR</italic>) [##REF##33969141##25##], insulin-like growth factor (IGF) system genes, luteinizing hormone (LH) /chorionic gonadotropin receptor gene (<italic>LHCGR</italic>) [##REF##36585675##26##], genes involved in androgen biosynthesis and steroid hormone metabolism (<italic>CYP11</italic>) [##REF##33969141##25##], and the melatonin receptor genes (<italic>MTNR1A</italic> and <italic>MTNR1B</italic>) [##UREF##6##27##]. Melatonin receptors are expressed on the surface of ovarian granulosa cells [##REF##11600542##28##] and variations in the melatonin receptor genes have been associated with increased risk of PCOS in both familial and sporadic cases [##UREF##6##27##]. We have recently reported the linkage and linkage plus association of variants in <italic>MTNR1A</italic> with familial type 2 diabetes [##UREF##3##13##] and in <italic>MTNR1B</italic> [##UREF##4##14##] with familial type 2 diabetes and type 2 diabetes-depression comorbidity. In this study, we aimed to investigate whether the <italic>MTNR1A</italic> and <italic>MTNR1B</italic> genes are in linkage to and/or linkage disequilibrium (LD, i.e., association joint to linkage) with PCOS in Italian families.</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par7\">We originally recruited for a type 2 diabetes (T2D) study 212 Italian families, which were later phenotyped for PCOS according to the phenotypes for PCOS necessary to meet the Rotterdam diagnostic criteria (presence of at least two of these three characteristics: chronic anovulation or oligomenorrhea, clinical or biochemical hyperandrogenism, and/or polycystic ovaries) [##REF##14688154##29##]. We amplified by microarray 14 variants in the <italic>MTNR1A</italic> gene and 6 variants in the <italic>MTNR1B</italic> gene and tested them for linkage and LD with PCOS, using Pseudomarker [##REF##21811076##30##] with dominant and recessive models with complete or incomplete penetrance, after excluding genotyping and Mendelian errors via PLINK [##REF##17701901##31##]. The first tool (Pseudomarker) offers a robust method to simultaneously examine linkage and LD in a combination of family and singleton samples, utilizing the true pedigree relationships without relying on artificial assumptions to rectify linkage effects in statistics [##REF##21811076##30##]. The second tool (PLINK) is a well-known toolset for whole genome association analysis that is both free and open-source, engineered to efficiently conduct various fundamental, large-scale analyses. We used the correlation coefficient of variants with data from the 1000 Genomes Project (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.internationalgenome.org/data-portal/population/TSI\">https://www.internationalgenome.org/data-portal/population/TSI</ext-link>) to estimate the presence of LD blocks.</p>", "<p id=\"Par8\"><italic>In-Silico</italic> Analysis. We used different bioinformatics tools to predict the risk variants’ roles in transcription factor (TF) binding (SNP Function Prediction) [##UREF##7##32##], miRNA binding (mirSNP) [##UREF##8##33##], splicing (SpliceAI) [##REF##30661751##34##], and regulatory potential (RegulomeDB) [##REF##22955989##35##].</p>" ]
[ "<title>Results and discussion</title>", "<p id=\"Par9\">We detected 4 variants in the <italic>MTNR1A</italic> gene and 2 variants in the <italic>MTNR1B</italic> gene significantly linked and/or associated (LD) with the risk of PCOS (<italic>P</italic> &lt; 0.05) (Table ##TAB##0##1##). The variants were significant across different inheritance models (Fig. ##FIG##0##1##). Two variants (rs2119883 and rs13147179) were within an LD block (Set01). All variants are novel and have not been reported before with PCOS or any of its related phenotypes (i.e., T2D, obesity, insulin resistance, metabolic syndrome, hyperglycemia, oligomenorrhea, anovulation, irregular menses, hyperandrogenism, MDD, male-pattern baldness, acne, hirsutism, infertility), excluding T2D for 3 risk variants and T2D-MDD for 1 risk variant. Within peninsular families, the same risk alleles of the two variants (<italic>MTNR1B</italic>-rs61747139 and <italic>MTNR1A</italic>-rs2119883) were previously linked to and associated with the risk of T2D [##UREF##3##13##, ##UREF##4##14##], confirming the interrelatedness of these complex phenotypes. On the other hand, the non-risk alleles of the two variants (<italic>MTNR1A</italic>-rs13147179 and <italic>MTNR1B</italic>-rs4601728) were linked and associated with T2D and T2D-MDD comorbidity respectively [##UREF##3##13##, ##UREF##4##14##], indicating multiple association at the allelic level and possibly the presence of LD with other contributing yet undetected variants. Via our bioinformatic analyses, we found that the risk allele (A) of the variant <italic>MTNR1A</italic>-rs13147179 disrupts the binding of Kruppel-like factor 5 (KLF5) which is hypomethylated in the ovarian tissue in PCOS [##REF##34113617##36##], potentially extending the role of this variant to epigenetic mechanisms. We also found that the risk allele (G) of the variant <italic>MTNR1B</italic>-rs61747139 affects the binding of transcription factor AP2A (TFAP2A) which is expressed in the brain, liver, pancreas, and ovaries [##UREF##9##37##] and forms a part of the signaling network of PCOS at least in vitro [##REF##31146003##38##]. PCOS patients in our study could therefore be at higher risk due to altered expression of genes in PCOS pathways. Our study therefore implicates novel melatonin receptor genes’ variants in the risk of PCOS with potential functional roles. It also offers the possibility of inhibitors of melatonin metabolism (e.g., coumarins [##REF##27588415##39##]) as novel therapeutic modalities in the treatment of PCOS. However, more studies are needed to validate these results.</p>", "<p id=\"Par12\">\n\n</p>", "<p id=\"Par11\">\n\n</p>" ]
[ "<title>Results and discussion</title>", "<p id=\"Par9\">We detected 4 variants in the <italic>MTNR1A</italic> gene and 2 variants in the <italic>MTNR1B</italic> gene significantly linked and/or associated (LD) with the risk of PCOS (<italic>P</italic> &lt; 0.05) (Table ##TAB##0##1##). The variants were significant across different inheritance models (Fig. ##FIG##0##1##). Two variants (rs2119883 and rs13147179) were within an LD block (Set01). All variants are novel and have not been reported before with PCOS or any of its related phenotypes (i.e., T2D, obesity, insulin resistance, metabolic syndrome, hyperglycemia, oligomenorrhea, anovulation, irregular menses, hyperandrogenism, MDD, male-pattern baldness, acne, hirsutism, infertility), excluding T2D for 3 risk variants and T2D-MDD for 1 risk variant. Within peninsular families, the same risk alleles of the two variants (<italic>MTNR1B</italic>-rs61747139 and <italic>MTNR1A</italic>-rs2119883) were previously linked to and associated with the risk of T2D [##UREF##3##13##, ##UREF##4##14##], confirming the interrelatedness of these complex phenotypes. On the other hand, the non-risk alleles of the two variants (<italic>MTNR1A</italic>-rs13147179 and <italic>MTNR1B</italic>-rs4601728) were linked and associated with T2D and T2D-MDD comorbidity respectively [##UREF##3##13##, ##UREF##4##14##], indicating multiple association at the allelic level and possibly the presence of LD with other contributing yet undetected variants. Via our bioinformatic analyses, we found that the risk allele (A) of the variant <italic>MTNR1A</italic>-rs13147179 disrupts the binding of Kruppel-like factor 5 (KLF5) which is hypomethylated in the ovarian tissue in PCOS [##REF##34113617##36##], potentially extending the role of this variant to epigenetic mechanisms. We also found that the risk allele (G) of the variant <italic>MTNR1B</italic>-rs61747139 affects the binding of transcription factor AP2A (TFAP2A) which is expressed in the brain, liver, pancreas, and ovaries [##UREF##9##37##] and forms a part of the signaling network of PCOS at least in vitro [##REF##31146003##38##]. PCOS patients in our study could therefore be at higher risk due to altered expression of genes in PCOS pathways. Our study therefore implicates novel melatonin receptor genes’ variants in the risk of PCOS with potential functional roles. It also offers the possibility of inhibitors of melatonin metabolism (e.g., coumarins [##REF##27588415##39##]) as novel therapeutic modalities in the treatment of PCOS. However, more studies are needed to validate these results.</p>", "<p id=\"Par12\">\n\n</p>", "<p id=\"Par11\">\n\n</p>" ]
[]
[ "<p id=\"Par1\">Polycystic ovarian syndrome (PCOS) is a genetically complex disorder that involves the interplay of multiple genes and environmental factors. It is characterized by anovulation and irregular menses and is associated with type 2 diabetes. Neuroendocrine pathways and ovarian and adrenal dysfunctions are possibly implicated in the disorder pathogenesis. The melatonin system plays a role in PCOS. Melatonin receptors are expressed on the surface of ovarian granulosa cells, and variations in the melatonin receptor genes have been associated with increased risk of PCOS in both familial and sporadic cases. We have recently reported the association of variants in <italic>MTNR1A</italic> and <italic>MTNR1B</italic> genes with familial type 2 diabetes. In this study, we aimed to investigate whether <italic>MTNR1A</italic> and <italic>MTNR1B</italic> contribute to PCOS risk in peninsular families. In 212 Italian families phenotyped for PCOS, we amplified by microarray 14 variants in the <italic>MTNR1A</italic> gene and 6 variants in the <italic>MTNR1B</italic> gene and tested them for linkage and linkage disequilibrium with PCOS. We detected 4 variants in the <italic>MTNR1A</italic> gene and 2 variants in the <italic>MTNR1B</italic> gene significantly linked and/or in linkage disequilibrium with the risk of PCOS (<italic>P</italic> &lt; 0.05). All variants are novel and have not been reported before with PCOS or any of its related phenotypes, except for 3 variants previously reported by us to confer risk for type 2 diabetes and 1 variant for type 2 diabetes-depression comorbidity. These findings implicate novel melatonin receptor genes’ variants in the risk of PCOS with potential functional roles.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We thank the families who participated in the study, and we thank Bios Biotech Multi-Diagnostic Health Center, Rome, Italy, for data access and for financial, medical, and laboratory staff support. This publication was supported in part with the funds received under Nebraska Laws 2021, LB 380, Sect. 109 awarded to C.G. (PI), Creighton University School of Medicine, through the Nebraska Department of Health &amp; Human Services (DHHS). Its contents represent the views of the authors and do not necessarily represent the official views of the State of Nebraska or DHHS.</p>", "<title>Author contributions</title>", "<p>C.G. (https://orcid.org/0000-0002-3873-6617) conceived and performed the study and critically revised the manuscript. T.T.P. (https://orcid.org/0000-0001-6056-4244) helped with the data interpretation and manuscript critical revision. Q.M.A.T drafted the manuscript and helped with literature search.</p>", "<title>Data availability</title>", "<p>The study data are available on reasonable request, and due to lacking specific patients’ consent and privacy restrictions, they are not publicly available.</p>", "<title>Declarations</title>", "<title>Ethics approval</title>", "<p id=\"Par14\">Families were recruited following the Helsinki declaration guidelines, and individuals provided written informed consent prior to participation. The Bios Ethical Committee approved this study (Prot.PR/Mg/Cg/311,708).</p>", "<title>Competing interests</title>", "<p id=\"Par20\">The authors declare no competing interests.</p>", "<title>Authors’ information</title>", "<p id=\"Par21\">C.G. is Professor of Medicine and Chief of Endocrinology and Endowed Puller Chair at Creighton University School of Medicine, Omaha, NE, and Adjunct Professor of Public Health Sciences, Penn State University College of Medicine, Hershey, PA; Q.M.A.T. is an internal medicine resident at Creighton University School of Medicine, Omaha, NE. T.T.P. is a Professor of Psychiatry at the University of Maryland School of Medicine, Baltimore, MD, and a research investigator with the Rocky Mountain MIRECC, Aurora, CO, and the VISN 5 MIRECC, Baltimore, MD.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Parametric Analysis Results of Polycystic Ovarian Syndrome (PCOS) <italic>MTNR1A</italic>- and <italic>MTNR1B</italic>-Risk Single Nucleotide Polymorphisms (SNPs)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Polycystic Ovarian Syndrome (PCOS) <italic>MTNR1A</italic>- and <italic>MTNR1B</italic>-Risk Single Nucleotide Polymorphisms (SNPs)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Gene</th><th align=\"left\">Model<sup>1</sup></th><th align=\"left\">SNP</th><th align=\"left\">Position</th><th align=\"left\">Ref</th><th align=\"left\">Alt</th><th align=\"left\">Risk Allele</th><th align=\"left\">Consequence</th><th align=\"left\">LD block</th><th align=\"left\">Reported in PCOS or related phenotype?<sup>2</sup></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"4\">\n<italic>MTNR1A</italic>\n</td><td align=\"left\">D1, D2, R1, R2</td><td align=\"left\">rs6820205</td><td char=\".\" align=\"char\">186,543,713</td><td align=\"left\">T</td><td align=\"left\">C</td><td align=\"left\">C</td><td align=\"left\">Intronic</td><td align=\"left\">Independent</td><td align=\"left\">Novel</td></tr><tr><td align=\"left\">D1, D2, R1, R2</td><td align=\"left\">rs2119883</td><td char=\".\" align=\"char\">186,547,921</td><td align=\"left\">C</td><td align=\"left\">T</td><td align=\"left\">T</td><td align=\"left\">Intronic</td><td align=\"left\">Set01</td><td align=\"left\">T2D<sup>3</sup> [##UREF##3##13##]</td></tr><tr><td align=\"left\">D1</td><td align=\"left\">rs4862706</td><td char=\".\" align=\"char\">186,552,540</td><td align=\"left\">G</td><td align=\"left\">A</td><td align=\"left\">A</td><td align=\"left\">Intronic</td><td align=\"left\">Independent</td><td align=\"left\">Novel</td></tr><tr><td align=\"left\">D1, D2</td><td align=\"left\">rs13147179</td><td char=\".\" align=\"char\">186,554,365</td><td align=\"left\">G</td><td align=\"left\">A</td><td align=\"left\">A</td><td align=\"left\">Intronic</td><td align=\"left\">Set01</td><td align=\"left\">T2D<sup>3</sup> [##UREF##3##13##]</td></tr><tr><td align=\"left\" rowspan=\"2\">\n<italic>MTNR1B</italic>\n</td><td align=\"left\">D1, R1</td><td align=\"left\">rs4601728</td><td char=\".\" align=\"char\">92,971,992</td><td align=\"left\">A</td><td align=\"left\">G</td><td align=\"left\">G</td><td align=\"left\">Intronic</td><td align=\"left\">Independent</td><td align=\"left\">T2D-MDD<sup>4</sup> [##UREF##4##14##]</td></tr><tr><td align=\"left\">D1, D2, R1</td><td align=\"left\">rs61747139</td><td char=\".\" align=\"char\">92,981,951</td><td align=\"left\">A</td><td align=\"left\">G</td><td align=\"left\">G</td><td align=\"left\">Missense</td><td align=\"left\">Independent</td><td align=\"left\">T2D<sup>3</sup> [##UREF##4##14##]</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
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[ "<table-wrap-foot><p><sup>1</sup>Models: D1: dominant, complete penetrance, D2: dominant, incomplete penetrance, R1: recessive, complete penetrance, R2: recessive, incomplete penetrance. <sup>2</sup>(i.e., type 2 diabetes, obesity, insulin resistance, metabolic syndrome, hyperglycemia, oligoamenorrhea, anovulation, irregular menses, hyperandrogenism, male-pattern baldness, acne, hirsutism, infertility). <sup>3</sup>T2D=type 2 diabetes, <sup>4</sup>MDD=major depressive disorder)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13048_2024_1343_Figa_HTML\" id=\"d32e551\"/>" ]
[]
[{"label": ["5."], "mixed-citation": ["Guan Q et al. "], "italic": ["Mechanisms of melatonin in obesity: a review"]}, {"label": ["7."], "mixed-citation": ["Ferlazzo N et al. "], "italic": ["Is melatonin the cornucopia of the 21st Century?"]}, {"label": ["8."], "mixed-citation": ["Chitimus DM et al. "], "italic": ["Melatonin\u2019s Impact on Antioxidative and Anti-Inflammatory Reprogramming in Homeostasis and Disease"]}, {"label": ["13."], "mixed-citation": ["Amin M, Gragnoli C. Melatonin receptor 1A gene (MTNR1A) linkage and association to type 2 diabetes in Italian families. Eur Rev Med Pharm Sci (In Press; 2023."]}, {"label": ["14."], "mixed-citation": ["Amin M et al. "], "italic": ["The role of melatonin receptor 1B gene (MTNR1B) in the susceptibility to depression and type 2 diabetes comorbidity"]}, {"label": ["22."], "surname": ["Unluturk"], "given-names": ["U"], "article-title": ["The genetic basis of the polycystic ovary syndrome: a Literature Review including discussion of PPAR-gamma"], "source": ["PPAR Res"], "year": ["2007"], "volume": ["2007"], "fpage": ["p49109"], "pub-id": ["10.1155/2007/49109"]}, {"label": ["27."], "mixed-citation": ["Yi S et al. "], "italic": ["Association between melatonin receptor gene polymorphisms and polycystic ovarian syndrome: a systematic review and meta-analysis"]}, {"label": ["32."], "mixed-citation": ["Xu Z, Taylor JA. "], "italic": ["SNPinfo: Integrating GWAS and candidate gene information into functional SNP selection for genetic association studies"]}, {"label": ["33."], "surname": ["Liu"], "given-names": ["C"], "article-title": ["MirSNP, a database of polymorphisms altering miRNA target sites, identifies miRNA-related SNPs in GWAS SNPs and eQTLs"], "source": ["BMC Genomics"], "year": ["2012"], "volume": ["2012 13"], "issue": ["1"], "fpage": ["1"], "lpage": ["10"]}, {"label": ["37."], "surname": ["Stelzer"], "given-names": ["G"], "article-title": ["The GeneCards suite: from Gene Data Mining to Disease Genome sequence analyses"], "source": ["Curr Protoc Bioinformatics"], "year": ["2016"], "volume": ["54"], "fpage": ["p1301"], "lpage": ["13033"], "pub-id": ["10.1002/cpbi.5"]}]
{ "acronym": [], "definition": [] }
39
CC BY
no
2024-01-14 23:43:46
J Ovarian Res. 2024 Jan 13; 17:17
oa_package/45/07/PMC10787433.tar.gz
PMC10787434
38216868
[ "<title>Introduction</title>", "<p id=\"Par6\">Colorectal cancer, which includes rectal cancer, is the third most commonly diagnosed cancer globally [##REF##22943008##1##]. Rectal cancer alone accounts for more than one-third of all cases. In 2020, the estimated number of rectal cancer cases in the USA was 43,340, representing 3.2% of all cancer-related deaths [##REF##32133645##2##]. Furthermore, the prevalence of rectal cancer is on the rise, particularly in Western countries [##REF##31616522##3##]. With advances in both surgical and adjuvant therapies for rectal cancer, there has been a decrease in the need for abdominoperineal resection with end colostomy. Instead, a preferred procedure, especially for mid and low rectal cancers, involves chemoradiation therapy followed by low anterior resection, often accompanied by a temporary protective ileostomy [##REF##23575392##4##].</p>", "<p id=\"Par7\">Nonetheless, one potential outcome of this surgical procedure is the development of a condition called low anterior resection syndrome (LARS). Individuals who experience LARS face a range of symptoms that arise after stoma reversal, including increased bowel movements, urgency, difficulty controlling bowel movements, and a sensation of incomplete evacuation. These symptoms can significantly affect patients’ quality of life [##REF##32749603##5##, ##UREF##0##6##] . The prevalence of LARS is considerable, with approximately 80–90% of patients who undergo sphincter-preserving surgery experiencing different levels of symptom severity in the short term [##REF##26651116##7##]. Risk factors for LARS development include a low anastomosis, temporary diverting stoma, obstructive presenting symptoms, and anastomotic complications [##REF##26340884##8##]. Chemoradiotherapy, especially neoadjuvant or adjuvant radiotherapy, although decreasing the risk for cancer recurrence, causes additional damage to the motor-sensory system and has been consistently associated with a higher risk for LARS [##REF##17294197##9##].</p>", "<p id=\"Par8\">Some bowel adaptation is thought to occur by about 12 months post operatively [##REF##26651116##7##]. Limited data exists on the long-term persistence of LARS symptoms in cancer survivors, or on the risk factors for these. The aims of current study, therefore, were to describe the long-term symptom outcomes of low anterior resection, to identify modifiable risk factors for the persistence of these symptoms, and specifically to evaluate the utility of perioperative anorectal physiological testing and anorectal physiotherapy treatment in these patients.</p>" ]
[ "<title>Methods and materials</title>", "<title>Study population</title>", "<p id=\"Par9\">A retrospective cohort study was performed. All consecutive patients undergoing low anterior resection surgery between 2010 and 2018 at the Rambam Health Care Campus were screened for eligibility. Exclusion criteria included active stoma at the time of follow up, active local oncologic disease or distant metastasis following surgery, or need for extended or recurrent colonic surgery. During 2019–2020, patients who met the criteria were contacted and given the opportunity to participate by responding to comprehensive questionnaires including LARS, Fecal Incontinence Severity Index (FISI), 36-Item Short Form and the Fecal Incontinence Quality of Life (FI-QOL).</p>", "<p id=\"Par10\">Study parts (Fig. ##FIG##0##1##):<list list-type=\"order\"><list-item><p id=\"Par11\">At the retrospective part data was collected including clinical characteristics, details of primary treatment (i.e. type of surgery, chemoradiation therapy, post-surgery complications), results of perioperative anorectal physiological assessment (anorectal manometry and balloon expulsion testing) and treatment (anorectal physiotherapy with biofeedback). Coloanal anastomosis and colorectal anastomosis were defined as below and above 4 cm from the anal verge, respectively, although exact anastomotic height was not reported.</p></list-item><list-item><p id=\"Par12\">In the prospective phase of the study, all patients who had undergone surgery at least 1 year prior were approached and given the opportunity to participate in a long-term follow-up study. These patients were assessed using questionnaires to evaluate the severity of their symptoms and their quality of life. The severity indexes and quality of life measures obtained during the long-term follow-up were then analyzed to determine any correlations with baseline clinical characteristics, perioperative anorectal physiological testing, and anorectal physiotherapy with biofeedback treatment.</p></list-item></list></p>", "<title>Ethics</title>", "<p id=\"Par13\">This study was conducted under the guidelines and approval of the Local Helsinki Committee (Approval number: 0572–17-RMB).</p>", "<title>Anorectal physiological testing</title>", "<p id=\"Par14\">Patients were referred before or after stoma closure for anorectal physiological testing, including anorectal manometry (ARM) and balloon expulsion test (BET), by surgeons. For ARM, a solid-state catheter comprised of 12 circumferential sensors and a compliant balloon attached to the end was used (Medtronic, Minneapolis, USA). The catheter was connected to calibrated pressure transducers and data were displayed in digital form on a computer using ManoScan acquisition software, version 3.0 (Medtronic, Minneapolis, USA). Maximal anal sphincter resting pressure (MRP) and maximal voluntary absolute and incremental contraction squeeze pressures (MSP) were recorded. The defecation maneuver was assessed by asking the patient to ‘push down’ as if defecating, and rectal and anal pressures were recorded during the maneuver. Next, a non-latex balloon positioned in the rectal vault was inflated up to 50 ml to elicit the recto-anal sphincteric inhibitory reflex (RAIR). Gradual inflation of the same balloon by 10 ml increments up to a maximal volume of 300 ml was performed, and the intra-rectal volume required to produce an initial sensation, the first urge to evacuate and the maximum tolerated volume (MTV) were recorded. Lastly, two additional variables were documented: rectal pressure on RAIR (50 ml of air in rectal balloon) and the presence of anal slow waves (defined as cyclic and spontaneous pressure auscultations in the resting state).</p>", "<p id=\"Par15\">Rectal BET was performed using a standard single use anorectal balloon expulsion catheter (Mississauga, ON, Canada). The procedure involved inflating the rectal balloon with 50 mL of warm water, after which the patient, seated on a private toilet, was timed to determine how long it took to expel the balloon. A balloon expulsion time exceeding 60 seconds was regarded as abnormal. This test was performed to assess the ability of the patient’s rectal muscles to expel the balloon effectively.</p>", "<p id=\"Par16\">In cases where high pressures or very early pain (&lt; 50 ml) were recorded in the post-surgical neo-rectum during balloon inflation, RAIR, sensory testing and balloon expulsion test were not performed in order to minimize the risk of procedure related complications such as perforation or bleeding.</p>", "<title>Anorectal physiotherapy treatment</title>", "<p id=\"Par17\">For the subgroup of patients performing perioperative ARM, all were also offered pelvic floor physiotherapy and biofeedback. The physiotherapy training consisted of 30- to 60-minute once weekly sessions under the care of a single pelvic floor physiotherapist. The protocol included education regarding the anatomy of normal defecation, advice on correct toilet positioning, diaphragmatic breathing, and use of a foot stool. Instrumental biofeedback (BF) was also performed using an electromyographic (EMG) anal probe (Myomed 632x, Enraf-Nonius, Rotterdam, Netherlands) for anal muscle strengthening and endurance training. Computer assisted visual BF and verbal feedback from the therapist were used to instruct patients and improve their motor control in contraction and relaxation. In cases of weakened muscle contraction, electric stimulation was performed using the same EMG anal probe. During training of active contraction, electric stimulation to the anal sphincter was given to increase muscle strength and endurance. Patients were instructed to continue practicing at home with anal sphincter and pelvic floor exercises for relaxation, muscle squeezes and the evacuation techniques learned during the treatment sessions.</p>", "<title>Questionnaires at long term follow up</title>", "<p id=\"Par18\">Questionnaires included: LARS score, Fecal Incontinence Severity Index, 36-Item Short Form and the Fecal Incontinence Quality of Life (FI-QOL). The LARS score is a validated questionnaire in multiple languages, although without specific validation for Hebrew translation. It consists of five items that are specifically designed to assess bowel function following sphincter-preserving surgery for rectal cancer [##REF##22504191##10##]. The questionnaire evaluates the presence and severity of various symptoms, including flatus incontinence, liquid stool incontinence, frequency of bowel movements, clustering of stools, and urgency. The total score ranges from 0 to 42, with scores between 0 and 20 indicating no LARS, scores between 21 and 29 indicating minor LARS, and scores between 30 and 42 indicating major LARS [##REF##22504191##10##, ##REF##23598379##11##]. Fecal incontinence severity index (FISI) was used as a more specific measure of incontinence severity [##REF##10613469##12##]. Patients were also requested to report the number of bowel movements per day and to describe their stool consistency according to the Bristol Stool Form Scale. Quality of life was assessed by two questionnaires. The Medical Outcome Study (MOS) 36-Item Short Form Health Survey (SF-36) was used as a nonspecific general health evaluation of quality of life [##REF##1593914##13##]. The Fecal Incontinence Quality of Life (FI-QOL) questionnaire was used as a more specific symptom-related quality of life questionnaire [##REF##10813117##14##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par19\">Statistical analysis was performed Using R 4.0.5 (R foundation for statistical computing). Medians and interquartile ranges, and absolute numbers and percentages were used to describe continuous and categorical variables respectively. Chi-square test was performed to compare categorical variables and Mann-Whitney U test was performed to compare continuous variables. The strength of the relationship between two quantitative measures was estimated by calculating Pearson’s r correlation coefficient. Correlation strength was evaluated as moderate at an r value between + 0.5 to + 0.7 or between − 0.7 to − 0.5 and strong at a value greater than + 0.7 or smaller than − 0.7. Multivariable logistic regression was used to assess the adjusted association between several factors both clinically important and that significantly differed on univariate analysis, and major LARS. All statistical tests were two-tailed and a <italic>p</italic> value less than 0.05 was considered statistically significant.</p>" ]
[ "<title>Results</title>", "<title>Baseline characteristics</title>", "<p id=\"Par20\">Among 184 patients undergoing sphincter preserving surgery for rectal cancer from 2010 to 2018, 115 patients were included in the study. Reasons for exclusion are described in Fig. ##FIG##0##1##. Baseline characteristics of patients included are described in Table ##TAB##0##1##. Tumor location was in the lower rectum (&lt; 8 cm from the anal verge) in 68 (59%) of cases, with an average distance of 6.9 ± 3.1 cm from the anal verge. 109 (92%) patients received neoadjuvant chemoradiation before surgery and a single patient underwent only chemotherapy. All patients underwent a low anterior resection with total meso-rectal excision (TME), with coloanal anastomosis performed in 38 (33%) of patients. A temporary protective ileostomy was performed in 110 (96%) patients. Surgical staging included 40 cases at stage 0/I, 38 cases at stage II, 36 cases at stage III and one case at stage IV. 23 (20%) patients had postoperative complications, most commonly anorectal strictures (14 patients). Other complications included small bowel obstruction (7 patients), pelvic abscess or anorectal fistula (2 patients) and impotence (2 patients). Thirty three (30%) patients received post-surgical adjuvant chemotherapy. Stoma reversal was performed following a normal rectal examination, rectoscopy and gastrografin enema, an average of 6 ± 4 months from initial surgery.\n</p>", "<title>Perioperative anorectal physiological testing and physiotherapy</title>", "<p id=\"Par21\">Sixty-five (57%) patients underwent anorectal manometry (ARM) following surgery, 45% of them before stoma closure. Median time between surgery to ARM was 10 months (range 2–82). Anal resting pressure was low (&lt; 68 mmHg) in 63% of patients and anal absolute squeeze pressure was low (&lt; 100 mmHg) in 23% of patients. In 47% of patients a paradoxical contraction or absent anal relaxation were recorded on push maneuver. In 41 (63%) patients rectal sensation and/or BET were not fully performed due to high pressures in the neo-rectum or early pain. Among 24 patients who performed BET, evacuation time was abnormal (&gt; 60 seconds) in 13 (54%) of them. No complications were noted.</p>", "<p id=\"Par22\">Compared to colorectal anastomosis, patients who underwent coloanal anastomosis were more likely to display a low resting pressure (77% vs. 52%, <italic>p</italic> = 0.04) and absence of RAIR (72% vs. 25%, <italic>p</italic> &lt; 0.01). Compared to patients with no post-surgery complications, patients who suffered from post-surgery complications were more likely to display a low anal squeeze pressure (33% vs. 74%, respectively, <italic>p</italic> = 0.05) and absence of RAIR (14% vs. 40%, respectively, <italic>p</italic> &lt; 0.01). Time between surgery to stoma closure or time between surgery to ARM showed no effect on ARM results. Physiology results before or after stoma closure showed no significant difference in resting or squeeze pressures. Similarly, push maneuver dynamics did not differ before compared to after stoma closure.</p>", "<p id=\"Par23\">24 (37%) patients underwent perioperative anorectal physiotherapy (median 4 sessions, range 1–12), 32% of them before stoma closure. Anal electric stimulation (ES) was performed in 23 (92%) of these patients. Patients with lower anal squeeze pressure, lower first sensation and lower MTV where more likely to be referred for treatment (Supplementary Table ##SUPPL##0##1##).</p>", "<title>Long term follow up</title>", "<p id=\"Par24\">Eighty (70%) patients completed the long term follow-up questionnaires. The median time of follow-up was 4 years from stoma reversal (IQR 2–5 years). Mean time from surgery to stoma closure for these patients was 6 ± 4 months. There were no differences in baseline parameters between these patients and patients not included in the follow-up analysis (<italic>N</italic> = 35) (Supplementary Table ##SUPPL##0##2##). At long term follow up, median LARS score was 36 (IQR 26–39), with 55 (69%) patients classified as major LARS (score &gt; 30). Other long term outcomes are summarized in Table ##TAB##1##2##.\n</p>", "<title>Predictors of long term LARS outcomes</title>", "<title>Clinical and surgical predictors of long term outcomes</title>", "<p id=\"Par25\">Patients with major LARS at long term were compared with patients with non-major LARS (Table ##TAB##2##3##). Presence of major LARS was associated with a longer time delay from primary surgery to stoma reversal (6.8 vs. 4.8 months, <italic>p</italic> = 0.03) and with undergoing adjuvant chemotherapy (38% vs. 8%; <italic>p</italic> = 0.01). There was a borderline significant association between adjuvant chemotherapy and delay in stoma closure (median 4 vs. 6 months; <italic>p</italic> = 0.05), although a multi-variate analysis incorporating these two predictors did not reveal either as independent risk factors. Patients referred for perioperative physiological testing by the surgical team were more likely to still suffer from major LARS at long term follow up (64% vs. 16%, <italic>p</italic> &lt; 0.001). Timing of ARM before or after stoma closure or time following surgery was not associated with outcome measures (median 11 months [IQR: 6–23] in major LARS vs. 10 months [IQR: 5–18] in the non-major LARS group). No significant differences in outcomes was observed regarding gender, neoadjuvant radiotherapy or perioperative complications (Table ##TAB##2##3##). On multivariable analysis, incorporating coloanal anastomosis and protective ileostomy as independent variables, colorectal anastomosis was associated with a reduced risk of major LARS at follow up (OR 0.22; 95% CI 0.03, 0.88; <italic>p</italic> = 0.03). Additionally, for each additional month of delay in closing the temporary stoma, there was a trend for increased risk for long term LARS, although not reaching statistical significance (OR 1.10; 95% CI 0.93, 1.38; <italic>p</italic> = 0.07).\n</p>", "<title>Perioperative anorectal physiological testing results as predictors of long term outcomes</title>", "<p id=\"Par26\">Thirty nine patients in the long term follow up cohort had been referred for perioperative physiology testing. Two of these patients failed to perform ARM and one patient performed ARM only after 80 months, and these 3 patients were excluded. In the remaining patients who underwent testing and were available for long term follow up (<italic>n</italic> = 36; 45%), higher squeeze (absolute or incremental) anal pressures and higher rectal pressures on push were all associated with better quality of life as measured by FIQOL questionnaire (<italic>p</italic> &lt; 0.05 for all, Table ##TAB##3##4##).\n</p>", "<p id=\"Par27\">Following referral for testing, 19 (53%) of these 39 patients were treated with anorectal physiotherapy (median 4 sessions, range 1–12), 32% of them before stoma closure. Long term outcomes for these patients were poor, similar to patients referred to ARM but who did not perform BF (major LARS in 94% vs 95%, respectively; p = NS; Table ##TAB##4##5##).\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par28\">Our study aimed to investigate long term anorectal symptoms and their impact on quality of life in rectal cancer survivors following low anterior resection, and correlation of these symptoms to baseline anorectal manometry (ARM) parameters and physiotherapy with anorectal biofeedback (BF). The main finding of the study is the long term persistence of severe symptoms and impairment in quality of life. Severity score results at a median of 4 years follow up showed 69% of patients still reporting symptoms of major LARS, and 84% of patients reporting some degree of fecal incontinence. The prevalence of LARS in the literature is wide, reporting a range of 25 to 80% of post-surgical patients [##REF##26340884##8##, ##REF##23076289##15##–##UREF##3##18##]. This difference might be explained by the different prevalence of suspected risk factors for LARS between the studies. For example, in the study of Sturiale et al. [##UREF##2##17##], only 20% of patients reported symptoms of major LARS following low anterior resection. In this study, 42% of patients did not have a temporary stoma constructed, and only 44% of patients received neoadjuvant therapy. Similarly, none of the patients in the study by Ekkart et al. [##REF##26340884##8##] received neoadjuvant therapy and only 41% had a temporary stoma, resulting in only 18% prevalence of major LARS. This is contrast to our cohort, where almost all patients received neoadjuvant chemoradiation therapy and had a temporary protective stoma, probably resulting in a higher risk for developing LARS.</p>", "<p id=\"Par29\">When symptoms of LARS do appear, they are unfortunately often long lasting. In a large retrospective study conducted on patients who underwent curative resection for rectal cancer in Denmark between 2001 and 2007, 41% of patients still experienced symptoms of major LARS at a mean follow-up of 54 months, while no association was found between major LARS and the time since surgery [##UREF##1##16##]. Our results show even worse long term outcomes, possibly again relating to our higher prevalence of baseline risk factors.</p>", "<p id=\"Par30\">In patients with a temporary stoma, we show that a delay in reversal surgery was associated with worse quality of life at long term follow up. This effect of prolonged intervals between surgery to stoma closure shown in our study is consistent with the results of a recent meta-analysis [##REF##33792822##19##]. While the construction of a temporary stoma is recommended in most guidelines as it reduces the rate of anastomotic leakage and reoperations, the optimal timing of stoma closure ranges widely and is not yet clearly defined [##REF##17667498##20##, ##REF##28399874##21##]. Some studies recommend early closure of the stoma to reduce morbidity, even as early as 2 weeks following initial surgery, while others have shown that stoma closure earlier than 3 months after initial surgery was associated with increased morbidity [##REF##28399874##21##]. Our results provide another incentive for early rather than later closure of the stoma. Multiple factors may explain delay in stoma closure, including patient-, surgical- and oncological-related factors. Due to our study design we could not assess for all factors, but we do show that adjuvant chemotherapy by itself was also associated with long term major LARS. This finding goes in line with recent meta-analysis by Ye and colleagues [##REF##34362620##22##]. Whether postponing stoma reversal until chemotherapy completion or chemotherapy itself are the major risk factors remains unanswered.</p>", "<p id=\"Par31\">As expected, our study findings confirmed the significance of anastomosis height in relation to postoperative outcomes. Another recent meta-analysis revealed that a lower tumor height, resulting in a lower anastomotic height, was linked to a higher likelihood of developing LARS after surgery; specifically, individuals with less than 4 cm of remnant rectum had a 46% risk of experiencing major LARS, whereas those with 4 cm or more of remnant rectum had a lower risk of 10% for major LARS [##UREF##4##23##]. Our study revealed even more unfavorable outcomes in the long term for this patient group. Other patient characteristics (age, gender, tumor stage, surgery complications etc.) were not associated with long term symptom severity. Our observation regarding similar results achieved between the genders are in line again with Ye et al. recent meta-analysis [##REF##34362620##22##]. We do note though that these finding in our cohort might be explained by the high overall rates of patients suffering from severe symptoms of LARS, making it difficult to perform an accurate analysis of other factors affecting these symptoms.</p>", "<p id=\"Par32\">In our study referral for per-operative physiological testing by itself was associated with worse long term results, probably reflecting a referral bias. The ability of anorectal physiological testing results to predict long term outcomes of patients is debated [##UREF##5##24##–##UREF##6##28##]. A subset of our patients performed perioperative ARM and BET, and some parameters were shown to predict long term impact of bowel dysfunction on quality of life: higher absolute and increment squeeze pressures were found to correlate with less severe quality of life measures on follow up. Nevertheless, the clinical implications of these findings might be limited, as definition of normal and abnormal values is problematic, and categorizing patients as “poor sphincter function” might be difficult [##UREF##5##24##]. About 40% of patients in our cohort suffered from major LARS despite having normal anal sphincter function on anorectal manometry. While some previous studies have shown the benefits of ARM in evaluating fecal incontinence and/or constipation due to non-surgical etiologies [##REF##31407463##25##], studies evaluating the correlation between ARM and symptoms of bowel dysfunction in surgical patients vary in their results. Dulskas et al. [##REF##27437391##26##] showed no correlation between severity of incontinence and results of anorectal manometry following surgert. On the other hand, Inhát et al. [##REF##29094352##27##] showed that patients with major LARS displayed significantly lower resting pressures and sensation thresholds, compared to patients with no LARS or minor LARS. Similarly, Matzel et al. [ ##UREF##6##28##] showed maximal tolerable volume and neorectal compliance were significantly correlated to incontinence severity following LAR. Thus, it seems that although ARM might have some role in predicting quality of life or symptom severity following stoma reversal, the clinical use of this data might be problematic.</p>", "<p id=\"Par33\">Anorectal physiotherapy treatment had no effect on long term outcomes in our study. This contrasts with previous studies [##REF##21755415##29##–##REF##18452041##32##]. For example, Bartlett et al. [##REF##21755415##29##] showed an improvement in continence and symptom related quality of life in post-surgical patients undergoing BF treatment. Reduction in scores of severity indexes was demonstrated following treatment in the studies by Kim et al. [##REF##21825890##30##] and Liang et al. [##UREF##7##31##], as well as improvement of anorectal physiological function on anorectal manometry. Similar effect of BF on symptoms was shown by Pucciani et al. [##REF##18452041##32##], yet no change in physiology testing results was seen in this study. Several reasons might explain the minimal effect of physiotherapy seen in our study. First, as no baseline measurements were made in our study prior to treatment, a before-after analysis of symptoms improvement could not be made. Second, measurements of outcomes in the aforementioned studies, as well as in other studies evaluating BF treatment, were made shortly after the final treatment session. As shown by Mazor et al. [##UREF##8##33##], benefits of BF in patients with fecal incontinence due to non-surgical etiology waned in about a third of the patients at a median of 7 year long-term follow-up. Moreover, at long-term follow-up, improvements in patients’ quality of life measures following BF were no longer evident. This declining trend might explain the minimal effect of BF on long term outcomes seen in our study. Lastly, in our study, baseline anorectal physiological testing results in patients who performed physiotherapy were worse than in patients that were not treated. As ARM was performed before physiotherapy, this suggests that patients who presented with a more impaired anorectal function were more likely to be referred for additional therapy such as physiotherapy, reflecting a selection bias.</p>", "<p id=\"Par34\">Due to the retrospective design of our study, it is challenging to establish definitive diagnostic and therapeutic conclusions. Still, an important finding of the current study is the inconsistencies in diagnosis and treatment of patients following low anterior resection, as evident by the time differences in stoma closure and referral to physiotherapy, performance of anorectal physiological testing either before or after stoma closure, and the variable number of physiotherapy sessions. Current treatment options for LARS are symptom based, using existing options for non-surgical patients with fecal incontinence, fecal urgency, and rectal evacuatory disorders. Moreover, sacral neuromodulation, a relatively recent treatment option for patients with LARS, was not available to our patients during the study time-frame. Our results emphasize the strong need for prospective studies examining a well-established protocol and evaluating patients’ symptoms, quality of life and anorectal physiology results before and after treatment, including a long term follow up arm.</p>", "<p id=\"Par35\">In summary, our study provides evidence for the long-term persistence of major LARS symptoms and a decline in quality of life among the majority of patients who underwent low anterior resection surgery. Longer intervals between surgery and stoma closure and adjuvant chemotherapy and were found to be associated with an increased risk of LARS severity, emphasizing the importance of carefully considering the timing of stoma reversal surgery. Additionally, poor anal sphincter function, as determined by anorectal manometry, either before or after stoma closure, was predictive of a lower quality of life. Our findings suggest that the studied physiotherapy treatment protocol offers minimal long-term benefit, at least for the more severely affected patients. There is a critical need for improvement in current treatment options, including the use of a more comprehensive anorectal bowel function protocol and/or sacral neuromodulation, to better address suffering in this patient population.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Rectal cancer is commonly treated by chemoradiation therapy, followed by the low anterior resection anal sphincter-preserving surgery, with a temporary protecting ileostomy. After reversal of the stoma a condition known as low anterior resection syndrome (LARS) can occur characterized by a combination of symptoms such as urgent bowel movements, lack of control over bowel movements, and difficulty fully emptying the bowels. These symptoms have a significant negative impact on the quality of life for individuals who have survived the cancer. Currently, there is limited available data regarding the presence, risk factors, and effects of treatment for these symptoms during long-term follow-up.</p>", "<title>Aims</title>", "<p id=\"Par2\">To evaluate long term outcomes of low anterior resection surgery and its correlation to baseline anorectal manometry (ARM) parameters and physiotherapy with anorectal biofeedback (BF) treatment.</p>", "<title>Methods</title>", "<p id=\"Par3\">One hundred fifteen patients (74 males, age 63 ± 11) who underwent low anterior resection surgery for rectal cancer were included in the study. Following surgery, patients were managed by surgical and oncologic team, with more symptomatic LARS patients referred for further evaluation and treatment by gastroenterologists. At follow up, patients were contacted and offered participation in a long term follow up by answering symptom severity and quality of life (QOL) questionnaires.</p>", "<title>Results</title>", "<p id=\"Par4\">80 (70%) patients agreed to participate in the long term follow up study (median 4 years from stoma reversal, range 1–8). Mean time from surgery to stoma closure was 6 ± 4 months. At long term follow up, mean LARS score was 30 (SD 11), with 55 (69%) patients classified as major LARS (score &gt; 30). Presence of major LARS was associated with longer time from surgery to stoma reversal (6.8 vs. 4.8 months; <italic>p</italic> = 0.03) and with adjuvant chemotherapy (38% vs. 8%; <italic>p</italic> = 0.01). Patients initially referred for ARM and BF were more likely to suffer from major LARS at long term follow up (64% vs. 16%, <italic>p</italic> &lt; 0.001). In the subgroup of patients who underwent perioperative ARM (<italic>n</italic> = 36), higher maximal squeeze pressure, higher maximal incremental squeeze pressure and higher rectal pressure on push were all associated with better long-term outcomes of QOL parameters (<italic>p</italic> &lt; 0.05 for all). 21(54%) of patients referred to ARM were treated with BF, but long term outcomes for these patients were not different from those who did not perform BF.</p>", "<title>Conclusions</title>", "<p id=\"Par5\">A significant number of patients continue to experience severe symptoms and a decline in their quality of life even 4 years after undergoing low anterior resection surgery. Prolonged time until stoma reversal and adjuvant chemotherapy emerged as the primary risk factors for a negative prognosis. It is important to note that referring patients for anorectal physiology testing alone tended to predict poorer long-term outcomes, indicating the presence of selection bias. However, certain measurable manometric parameters could potentially aid in identifying patients who are at a higher risk of experiencing unfavorable functional outcomes. There is a critical need to enhance current treatment options for this patient group.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12876-023-03112-8.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We wish to acknowledge physiotherapist Helaine Lotan for her clinical work and dedication in anorectal physiotherapy and biofeedback treatment for all patients included in the study.</p>", "<title>Authors’ contributions</title>", "<p>Eduard Koifman – planned the study, collected data, interpreted the data and jointly drafted the manuscript, reviewed and approved the final manuscript. Mor Armoni - planned the study, collected data, interpreted the data and jointly drafted the manuscript, reviewed and approved the final manuscript. Yuri Gorelik - conducted statistical analysis, reviewed and approved the final manuscript. Assaf Harbi - performed surgeries and patient follow-ups, reviewed and approved the final manuscript. Yulia Streltsin - performed physiological studies, reviewed and approved the final manuscript. Daniel Duek - performed surgeries and patient follow-ups, reviewed and approved the final manuscript. Rita Brun - planned the study, interpreted the data and jointly drafted the manuscript, reviewed and approved the final manuscript. Yoav Mazor - planned the study, conducted statistical analysis, interpreted the data and jointly drafted the manuscript, reviewed and approved the final manuscript.</p>", "<title>Funding</title>", "<p>No funding was obtained for this study.</p>", "<title>Availability of data and materials</title>", "<p>We attach the our raw data to the manuscript.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par36\">All methods were carried out in accordance with Israeli Medical Association guidelines and Israeli regulation. Study protocol was approved by RAMBAM Health Care Center Helsinki Committee. Informed consent was obtained from all subjects before their inclusion in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par37\">All authors gave their consent for publication.</p>", "<title>Competing interests</title>", "<p id=\"Par38\">The authors declare no competing interests</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Study population patients flowchart. Abbreviation: ARM- Anorectal manometry</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics of patients undergoing low anterior resection (<italic>n</italic> = 115)</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">Age- mean, years (SD)</td><td align=\"left\">63 (11)</td></tr><tr><td align=\"left\">Gender (M: F)</td><td align=\"left\">73:42</td></tr><tr><td align=\"left\">Tumor distance from anal verge - mean, cm (SD)</td><td align=\"left\">6.9 (3.1)</td></tr><tr><td align=\"left\">Neoadjuvant chemoradiotherapy -n (%)</td><td align=\"left\">109<sup>a</sup> (92%)</td></tr><tr><td align=\"left\">Adjuvant chemotherapy – n (%)</td><td align=\"left\">33 (29%)</td></tr><tr><td align=\"left\">Type of anastomosis</td><td align=\"left\"/></tr><tr><td align=\"left\"> Colorectal anastomosis– n (%)</td><td align=\"left\">77 (67%)</td></tr><tr><td align=\"left\"> Coloanal anastomosis– n (%)</td><td align=\"left\">38 (33%)</td></tr><tr><td align=\"left\">Temporary protective ileostomy– n (%)</td><td align=\"left\">110 (96%)</td></tr><tr><td align=\"left\">Post-surgery complication (including pelvic abscess, anorectal fistula, and strictures) - n (%)</td><td align=\"left\">23 (20%)</td></tr><tr><td align=\"left\">Tumor Stage (TNM) at surgery</td><td align=\"left\"/></tr><tr><td align=\"left\"> 0 or 1 n (%)</td><td align=\"left\">40 (35%)</td></tr><tr><td align=\"left\"> 2– n (%)</td><td align=\"left\">38 (33%)</td></tr><tr><td align=\"left\"> 3– n (%)</td><td align=\"left\">36 (31%)</td></tr><tr><td align=\"left\"> 4– n (%)</td><td align=\"left\">1 (1%)</td></tr><tr><td align=\"left\">Time to stoma closure- mean, months (SD)</td><td align=\"left\">6 (4)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Long term outcomes (<italic>n</italic> = 80)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>Median [IQR]</th><th>N (%)</th></tr></thead><tbody><tr><td>Time to follow up – years</td><td>4.0 [2.0, 5.0]</td><td/></tr><tr><td>LARS score (range 0–42)</td><td>36.5 [26.2,39,5]</td><td/></tr><tr><td>LARS – categorized</td><td/><td/></tr><tr><td> Mild</td><td/><td>16 (20%)</td></tr><tr><td> Moderate</td><td/><td>9 (11%)</td></tr><tr><td> Major</td><td/><td>55 (69%)</td></tr><tr><td>FISI (range 0–61)</td><td>23.0 [11.0, 42,2]</td><td/></tr><tr><td>SF36 (range 0–100)</td><td/><td/></tr><tr><td> Overall average</td><td>58.3 [36.0, 81.2]</td><td/></tr><tr><td> Physical function</td><td>65.0 [30.0, 90.0]</td><td/></tr><tr><td> Social function</td><td>62.5 [25.0, 100.0]</td><td/></tr><tr><td> Role limitation – physical</td><td>25.0 [0.0, 100.0]</td><td/></tr><tr><td> Role limitation – emotional</td><td>66.7 [0.0, 100.0]</td><td/></tr><tr><td> Energy/fatigue</td><td>45.0 [35.0, 60.0]</td><td/></tr><tr><td> Emotional well being</td><td>64.0 [48.0, 76.0]</td><td/></tr><tr><td> Pain</td><td>67.5 [33.8,90.0]</td><td/></tr><tr><td> General health</td><td>55.0 [40.0, 75.0]</td><td/></tr><tr><td>FIQOL (range 0–5)</td><td/><td/></tr><tr><td> Lifestyle</td><td>2.6 [1.6, 3.8]</td><td/></tr><tr><td> Coping/behaviour</td><td>1.8 [1.3, 3.1]</td><td/></tr><tr><td> Depression/self-perception</td><td>3.0 [1.9, 3.9]</td><td/></tr><tr><td> Embarrassment</td><td>2.3 [1.3, 3.3]</td><td/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Comparison of long-term outcomes following low anterior resection: patients with major (scores ≥30) low anterior resection syndrome (LARS) vs non-major (scores &lt; 30) LARS</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>Major LARS<break/><italic>N</italic> = 55</th><th>Non-major LARS<break/><italic>N</italic> = 25</th><th><italic>P</italic> value for difference</th></tr></thead><tbody><tr><td>Age- years; mean (SD)</td><td>61.4 (12.3)</td><td>65.3 (9.9)</td><td>NS</td></tr><tr><td>Distance of tumor from anal verge-cm; mean(SD)</td><td>6.5 (3.3)</td><td>6.9 (3.5)</td><td>NS</td></tr><tr><td>Time to stoma closure –months; mean(SD)</td><td>6.8 (4.6)</td><td>4.8 (2.8)</td><td>0.03</td></tr><tr><td>Average time of follow-up- years; mean(SD)</td><td>3.7 (1.8)</td><td>4.4 (1.5)</td><td>NS</td></tr><tr><td>Gender – male; n (%)</td><td>37 (67%)</td><td>17 (68%)</td><td>NS</td></tr><tr><td>Pathological staging at surgery; n(%)</td><td colspan=\"3\"/></tr><tr><td> Stage 0</td><td>10 (18%)</td><td>9 (36%)</td><td rowspan=\"5\">NS</td></tr><tr><td> Stage 1</td><td>7 (12.7%)</td><td>4 (16%)</td></tr><tr><td> Stage 2</td><td>18 (33%)</td><td>4 (16%)</td></tr><tr><td> Stage 3</td><td>19 (35%)</td><td>8 (32%)</td></tr><tr><td> Stage 4</td><td>1 (2%)</td><td>0 (0%)</td></tr><tr><td>Neo-adjuvant chemoradiation therapy; n (%)</td><td>52 (94.5)<sup>a</sup></td><td>21 (84)</td><td>NS</td></tr><tr><td>Patients with colo-anal anastomosis; n (%)</td><td>23 (42)</td><td>6 (24)</td><td>0.09</td></tr><tr><td>Protective ileostomy; n (%)</td><td>53 (96.4)</td><td>23 (92)</td><td>NS</td></tr><tr><td>Perioperative anastomotic dehiscence/pelvic abscess; n(%)</td><td>2 (3.6)</td><td>0 (0)</td><td>NS</td></tr><tr><td>Adjuvant chemotherapy; n (%)</td><td>21 (38)</td><td>2 (8)</td><td>0.01</td></tr><tr><td>Anal/rectal stricture following surgery; n (%)</td><td>6 (10.9)</td><td>2 (8)</td><td>NS</td></tr><tr><td>Referred for anorectal manometry; n (%)</td><td>35 (64)</td><td>4 (16)</td><td>&lt; 0.001</td></tr><tr><td>Referred for anorectal biofeedback; n (%)</td><td>22 (40)</td><td>2 (8)</td><td>0.003</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Correlation between perioperative anorectal manometry results and long term follow up questionnaire scores (<italic>n</italic>=36)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th rowspan=\"2\"/><th colspan=\"2\">LARS score</th><th colspan=\"2\">FISI score</th><th colspan=\"2\">SF36 Overall Average</th><th colspan=\"2\">FIQOL Lifestyle</th></tr><tr><th>correlation</th><th><italic>P</italic> value</th><th>correlation</th><th><italic>P</italic> value</th><th>correlation</th><th><italic>P</italic> value</th><th>correlation</th><th><italic>P</italic> value</th></tr></thead><tbody><tr><td>MRP</td><td>-0.088</td><td>0.61</td><td>+0.179</td><td>0.3</td><td>+0.24</td><td>0.16</td><td>+0.036</td><td>0.84</td></tr><tr><td>MSP</td><td>-0.254</td><td>0.13</td><td>+0.013</td><td>0.94</td><td>+0.09</td><td>0.61</td><td>+0.457</td><td><bold>0.01</bold></td></tr><tr><td>MISP</td><td>-0.198</td><td>0.25</td><td>-0.01</td><td>0.96</td><td>-0.011</td><td>0.95</td><td>+0.469</td><td><bold>0.01</bold></td></tr><tr><td>Rectal Pressure on Push</td><td>-0.275</td><td>0.11</td><td>-0.269</td><td>0.12</td><td>+0.4</td><td>0.02</td><td>+0.488</td><td><bold>0.01</bold></td></tr><tr><td>Rectal Pressure on RAIR 50 ml</td><td>+0.074</td><td>0.71</td><td>+0.079</td><td>0.7</td><td>-0.064</td><td>0.76</td><td>-0.154</td><td>0.452</td></tr><tr><td>First Sensation<sup>a</sup></td><td>-0.026</td><td>0.92</td><td>-0.144</td><td>0.56</td><td>+0.199</td><td>0.43</td><td>+0.009</td><td>0.97</td></tr><tr><td>Urge<sup>a</sup></td><td>+0.001</td><td>0.99</td><td>-0.188</td><td>0.5</td><td>+0.254</td><td>0.38</td><td>-0.032</td><td>0.14</td></tr><tr><td>MTV<sup>a</sup></td><td>-0.333</td><td>0.27</td><td>-0.283</td><td>0.35</td><td>-0.06</td><td>0.85</td><td>-0.138</td><td>0.67</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Association between biofeedback treatment and long term functional outcomes and quality of life in patients referred for perioperative anorectal biofeedback (<italic>n</italic> = 39)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th>Anorectal biofeedback<break/><italic>N</italic> = 21</th><th>No anorectal biofeedback<break/><italic>N</italic> = 18</th><th><italic>P</italic> value</th></tr></thead><tbody><tr><td>Major LARS – n (%)</td><td>20/21 (95%)</td><td>17/18 (94%)</td><td>NS</td></tr><tr><td>LARS score – mean (SD)</td><td>38.5 (3.4)</td><td>35.9 (6.6)</td><td>NS</td></tr><tr><td>FISI score – mean (SD)</td><td>37.2 (15.7)</td><td>35.1 (15.6)</td><td>NS</td></tr><tr><td>SF-36 score – mean (SD)</td><td>52.9 (15.8)</td><td>52.9 (23.6)</td><td>NS</td></tr><tr><td>FI QOL Lifestyle – mean (SD)</td><td>1.9 (0.9)</td><td>1.9 (0.9)</td><td>NS</td></tr><tr><td>FI QOL Coping – mean (SD)</td><td>1.7 (0.8)</td><td>1.7 (0.8)</td><td>NS</td></tr><tr><td>FI QOL Self – mean (SD)</td><td>2.3 (0.8)</td><td>2.4 (0.9)</td><td>NS</td></tr><tr><td>FI QOL Embarrassment – mean (SD)</td><td>1.8 (0.9)</td><td>1.9 (0.9)</td><td>NS</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup>1 patient received chemotherapy alone</p></table-wrap-foot>", "<table-wrap-foot><p><italic>LARS</italic> Lower Anterior Resection Syndrome, <italic>FISI</italic> Fecal Incontinence Severity Index, <italic>SF36</italic> 36-Item Short Form Health Survey, <italic>FIQOL</italic> Fecal Incontinence Quality of Life</p></table-wrap-foot>", "<table-wrap-foot><p><italic>SD</italic> Standard deviation, <italic>NS</italic> non significant</p><p><sup>a</sup>1 patient received chemotherapy alone</p></table-wrap-foot>", "<table-wrap-foot><p><italic>MRP</italic> maximal resting pressure, <italic>MSP</italic> maximal squeeze pressure, <italic>RAIR</italic> Rectoanal inhibitory reflex, <italic>MISP</italic> Maximal Incremental Squeeze Pressure, <italic>First sensation</italic> First rectal sensation threshold, <italic>Urge</italic> Defecation urge sensation threshold, <italic>MTV</italic> Maximal tolerated volume</p><p><sup>a</sup>Procedures performed in 42% of patients</p></table-wrap-foot>", "<table-wrap-foot><p><italic>SF-36</italic> Short form health state questionnaire, <italic>FI-QOL</italic> fecal incontinence quality of life, <italic>LARS</italic> Low anterior resection ssyndrome score, <italic>FISI</italic> Fecal incontinence severity index</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12876_2023_3112_Fig1_HTML\" id=\"MO1\"/>" ]
[ "<media xlink:href=\"12876_2023_3112_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1.</bold>\n</p></caption></media>" ]
[{"label": ["6."], "surname": ["Kupsch", "Jackisch", "Matzel", "Zimmer", "Schreiber", "Sims", "Witzigmann", "Stelzner"], "given-names": ["J", "T", "KE", "J", "A", "A", "H", "S"], "article-title": ["Outcome of bowel function following anterior resection for rectal cancer \u2013 an analysis using the low anterior resection syndrome (LARS) score"], "source": ["Int J Color Dis."], "year": ["2018"], "volume": ["33"], "fpage": ["787"], "lpage": ["798"], "pub-id": ["10.1007/s00384-018-3006-x"]}, {"label": ["16."], "surname": ["Bregendahl", "Emmertsen", "Lous", "Laurberg"], "given-names": ["S", "KJ", "J", "S"], "article-title": ["Bowel dysfunction after low anterior resection with and without neoadjuvant therapy for rectal cancer: a population-based cross-sectional study"], "source": ["Color Dis."], "year": ["2013"], "volume": ["15"], "issue": ["9"], "fpage": ["1130"], "lpage": ["1139"], "pub-id": ["10.1111/codi.12244"]}, {"label": ["17."], "surname": ["Sturiale", "Martellucci", "Zurli", "Vaccaro", "Brusciano", "Limongelli", "Docimo", "Valeri"], "given-names": ["A", "J", "L", "C", "L", "P", "L", "A"], "article-title": ["Long-term functional follow-up after anterior rectal resection for cancer"], "source": ["Int J Color Dis."], "year": ["2017"], "volume": ["32"], "fpage": ["83"], "lpage": ["88"], "pub-id": ["10.1007/s00384-016-2659-6"]}, {"label": ["18."], "surname": ["Rasmussen", "Petersen", "Christiansen"], "given-names": ["OO", "IK", "J"], "article-title": ["Anorectal function following low anterior resection"], "source": ["Color Dis."], "year": ["2003"], "volume": ["5"], "issue": ["3"], "fpage": ["258"], "lpage": ["261"], "pub-id": ["10.1046/j.1463-1318.2003.00439.x"]}, {"label": ["23."], "surname": ["Croese", "Lonie", "Trollope", "Vangaveti", "Ho"], "given-names": ["A", "J", "A", "VN", "YH"], "article-title": ["A meta-analysis of the prevalence of low anterior resection syndrome and systematic review of risk factors"], "source": ["Int J Surg."], "year": ["2018"], "volume": ["2018"], "fpage": ["234"], "lpage": ["241"], "pub-id": ["10.1016/j.ijsu.2018.06.031"]}, {"label": ["24."], "surname": ["Felt-Bersma", "Meuwissen"], "given-names": ["RJF", "SG"], "article-title": ["Anal manometry"], "source": ["Int J Color Dis."], "year": ["1990"], "volume": ["5"], "fpage": ["170"], "lpage": ["173"], "pub-id": ["10.1007/BF00300413"]}, {"label": ["28."], "surname": ["Matzel", "Bittorf", "G\u00fcnther", "Stadelmaier", "Hohenberger"], "given-names": ["KE", "B", "K", "U", "W"], "article-title": ["Rectal resection with low anastomosis: functional outcome"], "source": ["Color Dis."], "year": ["2003"], "volume": ["5"], "fpage": ["458"], "lpage": ["464"], "pub-id": ["10.1046/j.1463-1318.2003.t01-1-00503.x"]}, {"label": ["31."], "surname": ["Liang", "Ding", "Chen", "Wang", "Du", "Cui"], "given-names": ["Z", "W", "W", "Z", "P", "L"], "article-title": ["Therapeutic evaluation of biofeedback therapy in the treatment of anterior resection syndrome after sphincter-saving surgery for rectal Cancer"], "source": ["Clin Colorectal Cancer."], "year": ["2016"], "volume": ["15"], "fpage": ["101"], "lpage": ["107"], "pub-id": ["10.1016/j.clcc.2015.11.002"]}, {"label": ["33."], "surname": ["Mazor", "Ejova", "Andrews", "Jones", "Kellow", "Malcolm"], "given-names": ["Y", "A", "A", "M", "J", "A"], "article-title": ["Long-term outcome of anorectal biofeedback for treatment of fecal incontinence"], "source": ["Neurogastroenterol Motil."], "year": ["2018"], "volume": ["30"], "fpage": ["e13389"], "pub-id": ["10.1111/nmo.13389"]}]
{ "acronym": [], "definition": [] }
33
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2024-01-14 23:43:46
BMC Gastroenterol. 2024 Jan 12; 24:31
oa_package/5a/0b/PMC10787434.tar.gz
PMC10787435
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Femoral neck fractures are a serious public health concern, especially in older adults, due to their association with increased rates of morbidity and mortality. These fractures are also associated with reduced mobility, diminished quality of life, and increased risk of complications [##REF##16809710##1##, ##REF##16299013##2##]. Various surgical techniques have been developed and refined to optimize clinical outcomes in the treatment of femoral neck fractures. Two commonly used techniques are the use of the femoral neck system (FNS) and the use of cannulated compression screws (CCSs). CCSs are widely employed due to their technical simplicity, minimal invasiveness, and cost-effectiveness [##REF##35832467##3##]. However, studies have indicated potential limitations of CCSs, such as suboptimal biomechanical stability resulting in nonunion and avascular necrosis of the femoral head [##REF##15589931##4##, ##REF##29885670##5##]. The FNS is a more modern technology than is the CCS; the FNS has superior biomechanical properties that increase the likelihood of fracture union and reduce the likelihood of complications [##REF##25480307##6##, ##REF##34348753##7##]. Advancements have continued in orthopedic techniques and technologies; however, a comprehensive and analytical comparison of the FNS with CCSs, particularly a comparison that focuses on clinical outcomes in older adult patients, has not yet been conducted. Older adult patients present a unique set of challenges, given their increased likelihood of osteoporosis and other illnesses and their relatively low physiological reserves; the choice of fixation method is thus critical in these patients [##REF##12049882##8##, ##REF##8717549##9##].</p>", "<p id=\"Par6\">This study compared the efficacy of the FNS and CCSs for the treatment of femoral neck fractures in older adults. The findings of this study contribute to our understanding of the optimal treatment protocol for femoral neck fractures and can ultimately reduce the morbidity and mortality associated with femoral neck fractures in this vulnerable demographic. Through an evidence-based approach, this study highlighted the advantages and limitations of both fixation methods, providing guidance to clinicians when making decisions related to the management of femoral neck fractures in older adult patients.</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par7\">This was a retrospective cohort study. Data were extracted from multiple health-care databases. The clinical outcomes achieved using the FNS versus CCSs for the fixation of femoral neck fractures in patients aged 60 years or older were compared. Ethical approval was obtained from the Ethics Committee of the Institutional Review Board of Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation. Patient consent was waived due to the retrospective nature of the study. All data were anonymized to maintain confidentiality.</p>", "<p id=\"Par8\">The study population comprised patients aged 60 years or older with a diagnosis of femoral neck fracture of Pauwels classification type II who received surgical fixation using the FNS or CCSs in a single eastern Taiwan medical center between January 2020 and June 2022. Patients were excluded if they had (1) a history of polytrauma or additional fractures affecting the outcomes, (2) pathological fractures, or (3) incomplete medical records. Patients were assigned to the FNS group if they underwent femoral neck fracture fixation using the FNS (DePuy-Synthes, Zuchwil, Switzerland), or to the CCS group if their fixation using the 3 or 4 cannulated compression screws (Fig. ##FIG##0##1##).</p>", "<p id=\"Par9\">\n\n</p>", "<p id=\"Par10\">Patients received treatment within 24 h of receiving a diagnosis of fracture. Surgeries were performed by 5 orthopedic surgeons who each had at least 5 years of experience in trauma surgery. All patients underwent the same rehabilitation program, which consisted of the following: (1) mobilization in bed in postoperative day 1; (2) quadriceps femoris exercises and both passive and active hip, knee, and ankle exercises, which were initiated on postoperative days 1–3; (3) partial weight-bearing exercises with walker frame assistance, which were initiated on postoperative days 3–7 on the basis of the patient’s recovery status; (4) near full weight-bearing exercises with walking stick assistance, which were undertaken independently by the patients in accordance with their recovery status 3–6 months after surgery. on the basis of the patient’s recovery status and bone healing progress; and (5) full weight-bearing exercises, which were initiated in postoperative months 3–6 on the basis of the patient’s recovery status and bone healing progress.</p>", "<p id=\"Par11\">Data on demographic characteristics, preoperative health status (evaluated using the Charlson comorbidity index), perioperative parameters, and postoperative adverse events were retrospectively collected from electronic medical records. The primary outcome was the rate of postoperative complications, which were nonunion or malunion, hardware failure, femoral head osteonecrosis, and surgical site infection. This outcome is presented as the number of adverse events per patient.</p>", "<title>Statistical analysis</title>", "<p id=\"Par12\">Descriptive statistics were used to analyze the data. Categorical variables were compared using chi-square tests, and continuous variables were compared using independent t tests. A stepwise multivariate linear regression analysis was performed to estimate associations between the incidence of revision surgery and various demographic and clinical parameters. <italic>P</italic> values of &lt; 0.05 indicated statistical significance.</p>" ]
[ "<title>Results</title>", "<title>Demographic characteristics</title>", "<p id=\"Par13\">In total, 40 women were enrolled and categorized into the FNS group (<italic>n</italic> = 12) or CCS group (<italic>n</italic> = 28). The average age of the patients was 73.50 years (standard deviation: 11.55 years). Their average T-score for bone mineral density was − 2.90 (standard deviation: 0.60), and their mean body mass index was 22.90 kg/m<sup>2</sup> (standard deviation: 5.01 kg/m<sup>2</sup>; Table ##TAB##0##1##). The mean Charlson comorbidity index score for the entire cohort was 3.55 (standard deviation: 1.87). No significant differences in any of the demographic characteristics were discovered between the FNS and CCS groups (Table ##TAB##0##1##).</p>", "<p id=\"Par14\">\n\n</p>", "<title>Surgical metrics and intraoperative variables</title>", "<p id=\"Par15\">The average surgical duration for the entire cohort was 52.88 min (standard deviation: 22.19 min). The surgical duration was slightly longer in the FNS group (58.25 ± 13.83 min) than in the CCS group (50.57 ± 24.80 min); however, this difference was not significant. The mean intraoperative blood loss was greater in the FNS group (166.67 ± 80.75 cc) than in the CCS group (84.29 ± 47.05 cc; <italic>P</italic> = 0.002), and the mean hospital stay was longer in the FNS group (7.25 ± 3.57 days) than in the CCS group (5.00 ± 2.33 days; <italic>P</italic> = 0.023; Table ##TAB##0##1##).</p>", "<title>Postoperative complications and adverse events</title>", "<p id=\"Par16\">The mean duration until the first adverse event was 1.57 ± 2.76 months, and the average number of adverse events per patient was 0.58 ± 1.03 (Table ##TAB##0##1##). The FNS group had 3 cases of nonunion or malunion, 2 cases of hardware failure, and 1 case of osteonecrosis, whereas the CCS group had 1 case of nonunion or malunion, 1 case of hardware failure and 6 cases of osteonecrosis. Infection did not occur in either group (Table ##TAB##0##1##). This study investigated the risk factors associated with the incidence of revision surgery. The only significant risk factor for revision surgery was longer duration between surgical fixation and the first adverse event (OR = 5.51, 95% confidence interval = 1.38–21.93; <italic>P</italic> = 0.015; Table ##TAB##1##2##).</p>", "<p id=\"Par17\">\n\n</p>", "<title>Case presentation</title>", "<title>Case 1 (FNS group)</title>", "<p id=\"Par18\">A woman aged 71 years with hyperthyroidism s/p total thyroidectomy was experiencing right hip pain after a fall. The woman was diagnosed with right transcervical femoral neck fracture (Pauwels Type II). Injury films are shown in Fig. ##FIG##1##2##A, B. Immediate postoperative radiographs indicated anatomic fracture reduction and fixation with the FNS (Fig. ##FIG##1##2##C, D). By the 6-month follow-up, the patient’s fracture had healed, and anatomic alignment had been maintained (Fig. ##FIG##1##2##E, F). The patient was able to walk without assistance at 8 months after her operation.</p>", "<p id=\"Par19\">\n\n</p>", "<title>Case 2 (FNS group)</title>", "<p id=\"Par20\">A woman aged 74 years with a history of hypertension, type II diabetes mellitus, and osteoporosis was given a diagnosis of left subcapital femoral neck fracture (Pauwels Type II) after a road traffic accident (Fig. ##FIG##2##3##A, B). Immediate postoperative radiographs indicated anatomic fracture reduction and fixation with the FNS (Fig. ##FIG##2##3##C, D). However, implant cutout was required 8 months later (Fig. ##FIG##2##3##E, F). Subsequently, the implant was removed, and bipolar hemiarthroplasty was performed (Fig. ##FIG##2##3##G, H). Malunion and shortening of the femoral neck were noted during the operation. The patient was able to walk without assistance at 6 weeks after the bipolar hemiarthroplasty.</p>", "<p id=\"Par21\">\n\n</p>", "<title>Case 3 (CCS group)</title>", "<p id=\"Par22\">A woman aged 80 years with a history of hypertension and osteoporosis was given a diagnosis of right subcapital femoral neck fracture (Pauwels Type II) after a fall (Fig. ##FIG##3##4##A). Immediate postoperative radiographs indicated anatomic fracture reduction and fixation with 3 CCSs (Fig. ##FIG##3##4##B, C). By the 12-month follow-up, the fracture had healed, and anatomic alignment had been maintained (Fig. ##FIG##3##4##D, E). The implant was removed in postoperative month 15 (Fig. ##FIG##3##4##F).</p>", "<p id=\"Par23\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par24\">Fixation with the FNS did not appear to be superior to fixation with CCSs in our cohort of older adult women (mean age 73.50 ± 11.55 years) with Pauwels classification type II femoral neck fractures. No significant differences in demographic characteristics were found between the groups in our study. This study contributes to the limited body of English-language literature comparing the FNS with CCSs for the treatment of femoral neck fractures in older adults, acknowledging the possibility of relevant research in non-English publications. Stoffel et al. reported that the FNS is a valid alternative treatment technique for unstable femoral neck fractures and that, from the biomechanical perspective, it has comparable stability to the Dynamic Hip Screw systems and is superior to the use of CCSs [##REF##27755333##10##]. Huang et al. claimed that for treating vertical femoral neck fractures, the FNS may be superior to traditional CCSs in terms of their biomechanical and clinical aspects [##REF##36859241##11##]. For nongeriatric patients with femoral neck fracture (stable or unstable), the FNS was effective in improving hip function and reducing the femoral neck shortening rate and fluoroscopy exposure. The FNS was also associated with a lower incidence of complications compared with CCSs [##REF##36703126##12##, ##REF##34399801##13##]. However, according to a systemic review and meta-analysis conducted by Rajnish et al. the rates of various complications—such as implant failure, nonunion, and avascular necrosis—are similar between the FNS and CCSs, and neither technique is superior in terms of improvement in final functional status or pain relief [##REF##35601207##14##]. Our results are consistent with the findings of that meta-analysis. In our study, greater mean intraoperative blood loss and longer hospital stays were discovered in the FNS group than in the CCS group; these factors may explain the nonsuperiority of the FNS method. Older adults are likely to have comorbidities that affect surgical outcomes, and the relative simplicity and shorter operative time associated with CCSs might make CCSs a more appropriate technique for older adults when considering the overall risk posed by a surgery [##REF##27580947##15##]. In addition, in older adult women, low bone quality may undermine the mechanical advantages offered by more advanced systems such as the FNS. By contrast, CCSs, being less reliant on bone quality for stability, may perform comparably in such patients [##REF##25582596##16##]. Although the FNS was designed to provide angular stability, its efficacy is partly dependent on the bone’s ability to support the implant, and this support is compromised in osteoporotic bone. Essentially, the FNS provides enhanced stability but requires sufficient bone integrity for optimal function [##REF##36703126##12##]. By contrast, CCSs are less dependent on bone quality, and although they provide less stability than does the FNS, CSSs provide multidirectional fixation and remain effective even in osteoporotic bone [##REF##37536196##17##]. The overall outcome in femoral neck fracture repair depends on not only mechanical stability but also the biological environment, which may be less favorable in older adults [##UREF##0##18##]. Another consideration that is often overlooked but increasingly relevant in health-care decision-making is cost-effectiveness. Due to its complex design, the FNS is more expensive than are traditional, simpler systems. Patients receiving treatment with the FNS may have smaller resources to allocate to postoperative supportive care, which appeared in one study to be as important as the surgical method in the treatment of femoral neck fractures [##REF##29385235##19##].</p>", "<p id=\"Par25\">The most notable differences in the observed outcomes between the groups in our study were the higher incidence of osteonecrosis in the CCS group and the higher incidence of nonunion or malunion in the FNS group. CCSs, although beneficial in compressing fractures, may interfere with residual blood flow to the femoral head, potentially contributing to the development of osteonecrosis [##REF##25480307##6##, ##REF##31822345##20##]. This risk is likely influenced by the number and arrangement of screws [##REF##16140828##21##]. The FNS may mitigate the risk of vascular insult because it is a less invasive and more biomechanically stable construct [##REF##20194320##22##]. The risk of nonunion or malunion, which are significant postoperative setbacks, is influenced by multiple factors, such as surgical technique, bone integrity, and implant attributes [##REF##27919767##23##]. Although the FNS provides superior mechanical stability, it may paradoxically inhibit the bone-healing process by inadvertently suppressing callus formation [##UREF##1##24##, ##REF##15773648##25##]. These complications are likely more prominent in older adult patients than in younger patients.</p>", "<p id=\"Par26\">A significant risk factor for revision surgery was found to be longer duration between surgical fixation and the first adverse event. Early complications are often linked to surgical factors, whereas late complications tend to be associated with patient factors, such as underlying health conditions or rehabilitation challenges [##REF##37120515##26##]. A delayed onset of the first adverse event may indicate a period of subclinical vulnerability, where unapparent issues accumulate, leading to a cascade of complications later on. This explanation is supported by research indicating that initial postoperative stability does not always preclude late complications [##REF##25480307##6##]. Older adult patients, particularly those with comorbidities or poor nutritional status, may exhibit a delayed response to the initial surgical trauma, culminating in late-onset complications [##REF##30217470##27##]. Additionally, extended periods without complications may encourage less stringent postoperative monitoring or adherence to rehabilitation protocols. Consistent rehabilitation and follow-up are crucial to the early detection and management of complications [##REF##16140828##21##]. For older adult patients with femoral neck fracture who have undergone surgery, regular and intensive follow-up and outpatient visits may be necessary until the fracture has healed and complications at the fracture site have been ruled out.</p>", "<p id=\"Par27\">On the basis of our findings and review of the literature, possible indications for the FNS include the following: (1) unstable or comminuted femoral neck fracture [##REF##36859241##11##], (2) a history of nonunion with CCSs [##REF##34399801##13##], and (3) younger patients [##REF##34351048##28##]. Contraindications for the FNS include the following: (1) cost considerations [##REF##29385235##19##], (2) less experienced surgeons for whom the technical complexity of the FNS may be excessive [##UREF##2##29##], and (3) older adult patients who lack the resources to obtain supportive care during their recovery [##REF##34399801##13##]. The choice between the FNS or CCSs should be tailored to the individual patient’s needs, the characteristics of their fracture, and the clinical setting. Although the FNS shows promise for complex fracture patterns and demanding functional scenarios, its higher cost and technical complexity makes it less universally applicable than CCSs for older adult patients.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par29\">Our study provides essential insights into the relative efficacy of the FNS versus CCSs in the surgical management of Pauwels classification type II femoral neck fractures in an older adult female population with low bone mass. The FNS was not found to be superior to CCSs for fixation of femoral neck fractures in this specific cohort. The FNS may be associated with greater intraoperative blood loss and a longer hospital stay than are CCSs. The surgical method did not appear to be a significant risk factor for revision surgery; however, longer duration between surgery and the first adverse event was a risk factor for revision surgery. Regular follow-up is necessary. The present findings may serve as a reference for orthopedic surgeons making decisions on the best surgical method for treating older adult patients, especially when cost considerations are important. The findings may be limited by the study’s small sample size. Future research with larger and more diverse populations, longer follow-ups, and functional outcome collection is essential to validate and expand upon the findings, ultimately guiding clinical decision-making regarding hip fracture surgery.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Femoral neck fractures in older adult patients are a major concern and often necessitate surgical intervention. This study compared the clinical outcomes of 2 surgical techniques: the femoral neck system (FNS) and cannulated compression screws (CCSs).</p>", "<title>Methods</title>", "<p id=\"Par2\">A total of 40 female patients (mean age 73.50 ± 11.55 years) with femoral neck fractures of Pauwels classification type II and receiving surgical fixation between 2020 and 2022 were enrolled. The patients were categorized into an FNS group (<italic>n =</italic> 12) or a CCS group (<italic>n</italic> = 28), and surgical duration, intraoperative blood loss, length of hospital stay, and incidence of postoperative adverse events were analyzed.</p>", "<title>Results</title>", "<p id=\"Par3\">No significant intergroup differences in demographic characteristics were discovered. The mean surgical duration for all patients was 52.88 ± 22.19 min, with no significant difference between the groups. However, the FNS group experienced significantly higher intraoperative blood loss (<italic>P</italic> = 0.002) and longer hospital stay (<italic>P</italic> = 0.023) than did the CCS group. The incidence of osteonecrosis was higher in the CCS group, whereas the incidence of nonunion or malunion was higher in the FNS group. The surgical method did not appear to be a significant risk factor. The main risk factor for revision surgery was longer duration until the first adverse event (<italic>P</italic> = 0.015).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The FNS does not appear to provide superior surgical outcomes compared with CCSs in older adult women with Pauwels classification type II femoral neck fractures. A longer duration between surgical fixation and the first adverse event before stabilization of the fracture site may be a risk factor for revision surgery.</p>", "<title>Keywords</title>" ]
[ "<title>Implications and limitations</title>", "<p id=\"Par28\">This study was limited by its small and women-only sample, which may have affected the statistical power, effect size, and generalizability of the findings. Nevertheless, our findings have several clinical implications. For instance, the lack of significant differences in surgical duration between the FNS and CCS groups implies that either method can be implemented without notable alterations to a surgical workflow. However, the greater blood loss and longer hospital stay associated with the FNS may necessitate more comprehensive preoperative planning and postoperative care. To build upon the findings of this study and enhance understanding of the clinical efficacy of the FNS versus CCSs, future studies should involve larger sample sizes, more diverse populations of patients from multiple institutions, long-term follow-ups, subgroup analyses, and propensity score matching. Patient-reported outcomes and functional score data could also be analyzed.</p>" ]
[ "<title>Acknowledgements</title>", "<p>This manuscript was edited by Wallace Academic Editing.</p>", "<title>Author contributions</title>", "<p>SCY interpretation of data, WTW contributed to the conception, CHP contributed to design of the work, TKY contributed to design of the work, CMC contributed to the acquisition, KLL contributed to the acquisition, TCY interpretation of data, IHC substantively revised the article, JHW performed analysis, KTY drafted the article. All the authors equally contributed to generate the ideas behind this contribution. They jointly wrote and revised the various versions of the manuscript. The authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study received no funding.</p>", "<title>Data availability</title>", "<p>All data generated or analyzed during this study are included in this published article.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par33\">The studies involving human participants were reviewed and approved by the Research Ethics Committee of Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation (No. IRB111-016-B). The patients have provided their written informed consent to participate in this study.</p>", "<title>Consent for publication</title>", "<p id=\"Par34\">Written informed consent for publication was obtained from all patients included in this study.</p>", "<title>Competing interests</title>", "<p id=\"Par30\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The flowchart of this study</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>A 71 y/o woman with right transcervical femoral neck fracture (Pauwel Type II): <bold>A</bold> Preoperative AP view; <bold>B</bold> Preoperative lateral view; <bold>C</bold> Immediate postoperative AP view; <bold>D</bold> Immediate postoperative lateral view; <bold>E</bold> Postoperative AP view at 6 months; <bold>F</bold> Postoperative lateral view at 6 months</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>A 74 y/o woman with subcapital femoral neck fracture (Pauwel Type II): <bold>A</bold> Preoperative AP view; <bold>B</bold> Preoperative 3D reconstruction CT scan; <bold>C</bold> Immediate postoperative AP view; <bold>D</bold> Immediate postoperative lateral view; <bold>E</bold> Postoperative AP view at 8 months; <bold>F</bold> Postoperative lateral view at 8 months; <bold>G</bold> Post-hemiarthroplasty AP view; <bold>H</bold> Post-hemiarthroplasty Lateral view</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>A 80 y/o woman with right transcervical femoral neck fracture (Pauwel Type II): <bold>A</bold> Preoperative AP view; <bold>B</bold> Immediate postoperative AP view; <bold>C</bold> Immediate postoperative lateral view; <bold>D</bold> Postoperative AP view at 12 months; <bold>E</bold> Postoperative lateral view at 12 months; <bold>F</bold> Postoperative AP view after removal of implants</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Demographics (<italic>n</italic> = 40)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Item</th><th align=\"left\">FNS</th><th align=\"left\">CCS</th><th align=\"left\">Total</th><th align=\"left\"><bold><italic>P</italic></bold>-value</th></tr></thead><tbody><tr><td align=\"left\">N</td><td align=\"left\">12</td><td align=\"left\">28</td><td align=\"left\">40</td><td align=\"left\"/></tr><tr><td align=\"left\">Age</td><td align=\"left\">68.08 ± 7.94</td><td align=\"left\">75.82 ± 12.18</td><td align=\"left\">73.50 ± 11.55</td><td align=\"left\">0.051</td></tr><tr><td align=\"left\">BMD T score</td><td align=\"left\">-2.83 ± 0.41</td><td align=\"left\">-2.93 ± 0.66</td><td align=\"left\">-2.90 ± 0.60</td><td align=\"left\">0.649</td></tr><tr><td align=\"left\">BMI (kgw/m2)</td><td align=\"left\">22.96 ± 4.07</td><td align=\"left\">22.88 ± 5.43</td><td align=\"left\">22.90 ± 5.01</td><td align=\"left\">0.962</td></tr><tr><td align=\"left\">CCI</td><td align=\"left\">3.58 ± 1.93</td><td align=\"left\">3.54 ± 1.86</td><td align=\"left\">3.55 ± 1.87</td><td align=\"left\">0.853</td></tr><tr><td align=\"left\">Surgical time (mins)</td><td align=\"left\">58.25 ± 13.83</td><td align=\"left\">50.57 ± 24.80</td><td align=\"left\">52.88 ± 22.19</td><td align=\"left\">0.322</td></tr><tr><td align=\"left\">Blood loss (cc)</td><td align=\"left\">166.67 ± 80.75</td><td align=\"left\">84.29 ± 47.05</td><td align=\"left\">109 ± 51.11</td><td align=\"left\">0.002*</td></tr><tr><td align=\"left\">LOS (days)</td><td align=\"left\">7.25 ± 3.57</td><td align=\"left\">5.00 ± 2.33</td><td align=\"left\">5.68 ± 2.90</td><td align=\"left\">0.023*</td></tr><tr><td align=\"left\">Duration to first adverse event (months)</td><td align=\"left\">1.56 ± 1.70</td><td align=\"left\">1.57 ± 3.14</td><td align=\"left\">1.57 ± 2.76</td><td align=\"left\">0.989</td></tr><tr><td align=\"left\">Adverse event number</td><td align=\"left\">0.83 ± 1.27</td><td align=\"left\">0.46 ± 0.92</td><td align=\"left\">0.58 ± 1.03</td><td align=\"left\">0.307</td></tr><tr><td align=\"left\">Nonunion / Malunion</td><td align=\"left\">3 (25%)</td><td align=\"left\">1 (3.6%)</td><td align=\"left\">4 (10%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Hardware failure</td><td align=\"left\">2 (16.7%)</td><td align=\"left\">1 (3.6%)</td><td align=\"left\">3 (7.5%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Osteonecrosis</td><td align=\"left\">1 (8.3%)</td><td align=\"left\">6 (21.4%)</td><td align=\"left\">7 (17.5%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Surgical site infection</td><td align=\"left\">0 (0%)</td><td align=\"left\">0 (0%)</td><td align=\"left\">0 (0%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Revision (%)</td><td align=\"left\">2(16.7%)</td><td align=\"left\">6(21.4%)</td><td align=\"left\">8(20.0%)</td><td align=\"left\">1.000</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Risk factors associated with revision surgery (<italic>n</italic> = 40)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"2\">Crude</th><th align=\"left\" colspan=\"2\">Adjusted</th></tr><tr><th align=\"left\">OR (95% CI)</th><th align=\"left\"><bold><italic>P</italic></bold>-value</th><th align=\"left\">OR (95% CI)</th><th align=\"left\"><bold><italic>P</italic></bold>-value</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\">1.03 (0.96, 1.11)</td><td align=\"left\">0.355</td><td align=\"left\">1.25 (0.85, 1.82)</td><td align=\"left\">0.254</td></tr><tr><td align=\"left\">Method (FNS vs. CCS)</td><td align=\"left\">0.73 (0.13, 4.29)</td><td align=\"left\">0.731</td><td align=\"left\">0.42 (-0.32, 1.22)</td><td align=\"left\">0.272</td></tr><tr><td align=\"left\">BMD T score</td><td align=\"left\">0.32 (0.07, 1.44)</td><td align=\"left\">0.136</td><td align=\"left\">1.23 (0.02, 64.87)</td><td align=\"left\">0.919</td></tr><tr><td align=\"left\">BMI (kgw/m<sup>2</sup>)</td><td align=\"left\">0.88 (0.73, 1.08)</td><td align=\"left\">0.216</td><td align=\"left\">0.98 (0.68, 1.42)</td><td align=\"left\">0.922</td></tr><tr><td align=\"left\">CCI</td><td align=\"left\">1.23 (0.83, 1.81)</td><td align=\"left\">0.302</td><td align=\"left\">0.36 (0.06, 2.12)</td><td align=\"left\">0.261</td></tr><tr><td align=\"left\">Surgical time (mins)</td><td align=\"left\">0.98 (0.95, 1.03)</td><td align=\"left\">0.444</td><td align=\"left\">-0.03 (-0.06, 0.01)</td><td align=\"left\">0.082</td></tr><tr><td align=\"left\">Blood loss (cc)</td><td align=\"left\">1.00 (1.00, 1.01)</td><td align=\"left\">0.723</td><td align=\"left\">0.02 (-0.01, 0.04)</td><td align=\"left\">0.312</td></tr><tr><td align=\"left\">LOS (days)</td><td align=\"left\">1.07 (0.83, 1.38)</td><td align=\"left\">0.621</td><td align=\"left\">-0.03 (-0.11, 0.05)</td><td align=\"left\">0.411</td></tr><tr><td align=\"left\">Duration to first adverse event (months)</td><td align=\"left\">3.66 (1.57, 8.54)</td><td align=\"left\">0.003*</td><td align=\"left\">5.51 (1.38, 21.93)</td><td align=\"left\">0.015*</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>BMD</italic> bone mineral density, <italic>BMI</italic> body mass index, <italic>LOS</italic> length of stay, <italic>FNS</italic> femoral neck system, <italic>CCS</italic> conventional compression screws, <italic>CCI</italic> charlson comorbidity index</p><p>Data are presented as <italic>n</italic> or mean ± standard deviation. *<italic>P</italic>-value &lt; 0.05 was considered statistically significant after test</p></table-wrap-foot>", "<table-wrap-foot><p><italic>BMD</italic> bone mineral density, <italic>BMI</italic> body mass index, <italic>LOS</italic> length of stay, <italic>FNS</italic> femoral neck system, <italic>CCS</italic> conventional compression screws</p><p>Data are presented as odds ratio (95% CI). *<italic>P</italic>-value &lt; 0.05 was considered statistically significant after test.</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[]
[{"label": ["18."], "surname": ["Meinberg", "Clark", "Miclau", "Marcucio", "Miclau"], "given-names": ["EG", "D", "KR", "R", "T"], "article-title": ["Fracture repair in the elderly: clinical and experimental considerations"], "source": ["Injury"], "year": ["2019"], "volume": ["50"], "issue": ["Suppl 1Suppl 1"], "fpage": ["62"], "lpage": ["S65"], "pub-id": ["10.1016/j.injury.2019.05.005"]}, {"label": ["24."], "mixed-citation": ["Garg B, Marimuthu K, Kumar V, Malhotra R, Kotwal PP. Outcome of short proximal femoral nail antirotation and dynamic hip screw for fixation of unstable trochanteric fractures. A randomised prospective comparative trial. Hip Int. 2011;21(5):531-6. Retraction in: Spencer RF. Hip Int. 2012;22(4):487."]}, {"label": ["29."], "surname": ["Maffulli", "Aicale"], "given-names": ["N", "R"], "article-title": ["Proximal femoral fractures in the Elderly: a few things to know, and some to forget"], "source": ["Med (Kaunas)"], "year": ["2022"], "volume": ["58"], "issue": ["10"], "fpage": ["1314"]}]
{ "acronym": [ "FNS", "CCS" ], "definition": [ "femoral neck system", "cannulated compression screws" ] }
29
CC BY
no
2024-01-14 23:43:46
BMC Musculoskelet Disord. 2024 Jan 13; 25:62
oa_package/ed/82/PMC10787435.tar.gz
PMC10787436
38216937
[ "<title>Background</title>", "<p id=\"Par4\">Osteosarcoma, also known as osteogenic sarcoma, is the most prevalent malignant tumor of bone. Derived from the mesenchymal cells, osteosarcoma is one of the most lethal and malignant tumors in children and adolescents [##REF##27956436##1##–##REF##10526292##3##]. Currently, the main clinical treatment for osteosarcoma is neoadjuvant chemotherapy (high-dose methotrexate, doxorubicin, and cisplatin) combined with local surgical resection [##REF##36481668##4##]. However, due to the high incidence of drug resistance and distant metastasis, the survival period of patients remains short [##REF##31928458##5##]. Additionally, because osteosarcoma has widespread genomic alterations, it is difficult to identify specific molecular targets for effective precise therapy, which often leads to adverse effects during chemotherapy [##REF##28338660##6##]. Therefore, new treatment methods are urgently needed to address drug targeting, drug resistance, and distant metastasis in osteosarcoma to improve patient prognoses.</p>", "<p id=\"Par5\">Intracellular ion stability is crucial for maintaining cell osmotic pressure and proper physiological functions, whereas imbalances in intracellular ion homeostasis will lead to cell death. Studies have shown that drastic changes in intracellular ion concentrations, such as Cl<sup>−</sup>, Ca<sup>2+</sup>, and K<sup>+</sup>, can lead to cell death through apoptosis, autophagy, necroptosis, ferroptosis, oxidative stress, and endoplasmic reticulum (ER) stress [##REF##25264571##7##–##REF##27890727##11##]. In this context, various synthetic structures have been proposed to mimic the physiological transport function in living systems [##UREF##0##12##–##REF##31844288##20##]. In particular, drug-like small-molecule ion transporters [##UREF##3##21##–##REF##22713747##26##] have been proposed as a promising cancer therapy by facilitating anion transport into cells, which could induce apoptosis through caspase-dependent pathways [##REF##25242483##27##–##REF##28644464##29##]. In cells, anion transporters have been shown to facilitate Cl<sup>−</sup> and Na<sup>+</sup> influx into cytosols, which will lead to reactive oxygen species (ROS) increase, release of cytochrome c from mitochondria, and finally apoptosis through caspase-dependent pathways [##REF##25242483##27##]. Squaramide-based ion transporter has also been shown to disrupt autophagy [##REF##28644464##29##], which renders it a promising candidate as cancer therapy. However, small-molecule based anion transporters lack targeting abilities, which limits their curing effect in vivo. Previous studies have thus been limited to in vitro experiments. The in vivo therapeutic effect of anion transporters for cancers thus needs further investigation.</p>", "<p id=\"Par6\">Furthermore, because osteosarcoma lacks specific surface markers, the development of targeting peptides for osteosarcoma has become a new research hotspot. For instance, Liu et al. developed intranuclear nanoribbons formed upon dephosphorylation of leucine-rich L- or D-phosphopeptide catalyzed by alkaline phosphatase (ALP) to selectively kill osteosarcoma cells. The peptide can directly kill osteosarcoma cells and minimize the drug resistance caused by repeated treatment [##REF##36102872##30##]. Additionally, Lin et al. screened peptides that can target osteosarcoma cells through phage display techniques. The peptide only has the ability to recognize osteosarcoma cells but can’t kill osteosarcoma cells by itself. By self-assembling with nanodrugs, it can selectively kill osteosarcoma cells in vivo [##REF##35396783##31##]. Furthermore, reprogramming tumor-associated macrophages (TAMs) from the M2 phenotype that inhibits tumor immunity to the M1 phenotype that promotes tumor immunity is another important target for tumor treatment and many drugs are designed to regulate the tumor immune microenvironment as a means of treating tumors [##REF##35974096##32##, ##REF##33619259##33##].</p>", "<p id=\"Par7\">In this study, we selected ion transporter PTU, TFPTU, and BTFPTU that can self-integrate into cell membranes as candidate compounds. Through in vitro experiments, we identified BTFPTU as having the best tumor killing effect. Osteosarcoma-targeting peptides (OTP) and BTFPTU were loaded into liposomes through self-assembly process for osteosarcoma treatment. Through in vitro and in vivo experiments, we found that the assembled supramolecular drug (OTP-BP-L) had good targeting and killing effects on osteosarcoma cells, as well as anti-drug resistance and the ability to regulate the tumor immune microenvironment. These results demonstrate that OTP-BTFPTU can be used as a new strategy for osteosarcoma treatment.</p>" ]
[ "<title>Methods</title>", "<title>Dynamic light scattering</title>", "<p id=\"Par36\">The size of the LUVs was characterized by dynamic light scattering (DLS) using a NanoBrook Omni (Brookhaven Instruments Corporation). A laser wavelength of 659 nm and a scattering angle of 90° were used.</p>", "<title>Cationic selectivity</title>", "<p id=\"Par37\">Egg yolk phosphatidylcholine was dissolved in CH<sub>3</sub>Cl, (10 mg/mL, Shanghai Macklin Biochemical, China). The lipid solution was evaporated to form a thin film by purging N<sub>2</sub> slowly. After drying the resulting film under high vacuum overnight at room temperature, the film was hydrated with 4-(2- hydroxyethyl)-1-piperazine-ethane sulfonic acid (HEPES) buffer solution (1 mL, 25 mM HEPES, 100 mM MCl, M = Li<sup>+</sup>, Na<sup>+</sup>, K<sup>+</sup>, Cs<sup>+</sup>, pH = 7.0) containing a pH sensitive dye 8-hydrox-ypyrene-1,3,6-trisulfonic acid (HPTS, 0.2 mM) at 40℃ for 2 h to give a milky suspension. The mixture was then subjected to 10 freeze-thaw cycles (freezing in liquid N<sub>2</sub> for 1 min and thawing at water bath for 2 min). The vesicle suspension was extruded through polycarbonate membrane (0.2 μm) to produce a homogeneous suspension of LUVs of about 200 nm in diameter with HPTS encapsulated inside. The extravesicular HPTS dye was removed by using size exclusion chromatography (stationary phase: Sephadex G-50, Shanghai Macklin Biochemical, China, mobile phase: HEPES buffer with 100 mM NaCl) and diluted with the mobile phase to yield 3 mL lipid stock solution.</p>", "<p id=\"Par38\">100 µL of HPTS-containing LUVs and 10 µL PTU/TFPTU/BTFPTU in a certain concentration were added to 900 µL of HEPES buffer (25 mM HEPES, 100 mM MCl, M = Li<sup>+</sup>, Na<sup>+</sup>, K<sup>+</sup>, Cs<sup>+</sup>, pH = 7.0) in a clean fluorescence cuvette. Then mix the above solution evenly. This cuvette was placed on the fluorescence instrument (at t = 0 s). Fluorescence emission intensity of HPTS was monitored. 10 µL of 5 M MOH (M = Li<sup>+</sup>, Na<sup>+</sup>, K<sup>+</sup>, Cs<sup>+</sup>) was added at t = 20 s to generate pH gradient across lipid bilayer and recorded simultaneously for 300 s using fluorescence spectrophotometer (Hitachi, F-4700, Japan). Finally at t = 320 s, 10µL of 10% Triton X-100 was added to destroy all vesicles which resulted in destruction of pH gradient to achieve the maximum change in fluorescence emission intensity of HPTS dye.</p>", "<title>Anionic selectivity</title>", "<p id=\"Par39\">Egg yolk phosphatidylcholine was added in CH<sub>3</sub>Cl. (10 mg/mL, Shanghai Macklin Biochemical, China). The lipid was evaporated by purging N<sub>2</sub> slowly. After drying the resulting film under high vacuum overnight at room temperature, the film was hydrated with HEPES buffer solution (1 mL, 25 mM HEPES, 50 mM Na<sub>2</sub>SO<sub>4</sub>/100 mM NaX, X = HCO<sub>3</sub><sup>−</sup>, NO<sub>3</sub><sup>−</sup>, Cl<sup>−</sup>, Br<sup>−</sup>, pH = 7.0, except NaHCO<sub>3</sub> buffer pH = 7.3) containing 0.2 mM HPTS at 40℃ for 2 h to give a milky suspension. The mixture was then subjected to 10 freeze-thaw cycles (freezing in liquid N<sub>2</sub> for 1 min and thawing at water bath for 2 min). The vesicle suspension was extruded through polycarbonate membrane (0.2 μm) to produce a homogeneous suspension of large unilamellar vesicles (LUVs) of about 200 nm in diameter with HPTS encapsulated inside. The extravesicular HPTS dye was removed by using size exclusion chromatography (stationary phase: Sephadex G-50, Shanghai Macklin Biochemical, China, mobile phase: HEPES buffer with 100 mM NaCl) and diluted with the mobile phase to yield 3 mL lipid stock solution.</p>", "<p id=\"Par40\">100 µL of HPTS-containing LUVs and 10 µL PTU/TFPTU/BTFPTU in a certain concentration were added to 900 µL of HEPES buffer (25 mM HEPES, 50 mM Na<sub>2</sub>SO<sub>4</sub>/100 mM NaX, X = HCO<sub>3</sub><sup>−</sup>, NO<sub>3</sub><sup>−</sup>, Cl<sup>−</sup>, Br<sup>−</sup>, pH = 7.0, except NaHCO<sub>3</sub> buffer pH = 7.3) in a clean fluorescence cuvette. Then mix the above solution evenly. This cuvette was placed on the fluorescence instrument (at t = 0s). Fluorescence emission intensity of HPTS was monitored over time. 10 µL of 5 M NaOH was added at t = 20 s to generate pH gradient across lipid bilayer and recorded simultaneously for 300 s using fluorescence spectrophotometer (Hitachi, F-4700, Japan). Finally at t = 320 s, 10 µL of 10% Triton X-100 was added to destroy all vesicles which resulted in destruction of pH gradient to achieve the maximum change in fluorescence emission intensity of HPTS dye.</p>", "<title>Sample pretreatment for TEM</title>", "<p id=\"Par41\">The thin pure carbon film coated grids (400 mesh, Zhongjingkeyi Technology Co., Ltd) were firstly hydrophilic treated applying sample. Grids were first placed on a clean slide (carbon-coated side is facing up), then moved into ion sputter instrument and discharge treated under vacuum condition for 8 s (~ 5 Pa, 10 ~ 15 mA).</p>", "<p id=\"Par42\">Three drops of UranyLess EM stain (Haide Chuangye (Beijing) Biotechnology Co., Ltd.) were applied on the surface of parafilm in advance. The processed grid was clamped with self-locking tweezer (carbon-coated side is facing up) and 3 µL sample solution was placed on it, adsorbed for 30 s, then liquid was blotted up with filter paper and the grid was immediately inserted into a drop of uranyless EM stain (carbon-coated side is facing down) and gently shaken for 10 s, blotted up with filter paper and inserted into the second drop of uranyless EM stain, stained for 10 s, blotted up with filter paper. Finally the grid was inserted into the third drop of uranyless EM for 1 min prior to blotting up with filter paper and further dried in dryer. The stained sample was characterized with JEM 1400 Plus (JEOL) with an acceleration voltage of 120 kv.</p>", "<title>Cell culture</title>", "<p id=\"Par43\">Two human OS cell lines, including HOS (ATCC: CRL-1543) and 143B (ATCC: CRL-8303) were purchased from the (ATCC, Manassas, VA, USA). Triple negative breast cancer cell lines (BT549 and MDA-MB-231) were provided by Prof. Jun Zhang (Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang, China) and Sorafenib-resistant hepatoma cell line (MHCC-97 H-SR) was provided by Prof. Xian Wang (Department of oncology, Sir Run Run Shaw Hospital, Zhejiang, China). HOS, 143B, MDA-MB-231 and MHCC-97 H were cultured in Dulbecco’s modified Eagle’s medium (DMEM) and BT549 was cultured in 1640 medium containing 10% fetal bovine serum (FBS, Gibco, Gaithersburg, MD, USA) with 5% CO<sub>2</sub> at 37℃.</p>", "<title>Colony-formation assay</title>", "<p id=\"Par44\">HOS and 143B cells were trypsinized and seeded at a density of 3 × 10<sup>3</sup> cells/well into a 12-well plate. After 5 days of culture with treatment, the cells were washed with phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde for 30 min. The fixed colonies were stained with 1% crystal violet solution for 10 min at room temperature. The colonies were imaged and counted under a microscope after washed by PBS.</p>", "<title>Wound-healing assay</title>", "<p id=\"Par45\">We prepared the Culture-insert (80,209, ibidi, Germany) and seeded HOS or 143B cells in 24-well plates. Culture-insert was removed after 24 h cell culture. Subsequently, HOS or 143B cells were cultured with treatment for 24 h and the cells were washed twice with PBS. The images of cell-free gap from the same position were captured by microscopy at 0 and 24 h. The ratio of the area of wound-healing was quantified by Image J software (NIH, Bethesda, MD, USA).</p>", "<title>Transwell migration assay</title>", "<p id=\"Par46\">We used 24-well transwell chambers (140,644, Thermo Scientific, USA) to evaluate migration capability of HOS and 143B cells. Cells were resuspended with FBS-free DMEM and seeded into upper chambers (5 × 10<sup>4</sup> cells/well). 500 µL DMEM containing 20% FBS was added to the lower chambers. Following 24 h of culture with different treatment, cells in the upper chamber were removed and the lower side of the chamber was gently washed twice with PBS and fixed with 4% paraformaldehyde for 30 min at room temperature. Cells were stained with 1% crystal violet solution for 10 min and washed by PBS for five times. Cells which detained in the upper side were wiped off and images were captured by microscopy.</p>", "<title>EdU assay</title>", "<p id=\"Par47\">HOS or 143B cells were seeded in 24-well plates (5 × 10<sup>4</sup> cells/well) and cultured with different treatment. After 24 h, cells were staining with EdU and Hoechst dye according to the instructions (C10310-1, Cell-Light EdU Apollo567 In Vitro Kit, RIBOBIO, China).</p>", "<title>Apoptosis and cell cycle analysis</title>", "<p id=\"Par48\">HOS or 143B cells were seeded into 12-well plates (2 × 10<sup>5</sup> cells/well) and cultured with different treatment for 24 h after they were adherent. For cell apoptosis assay or cell cycle analysis, cells were trypsinized, centrifuged, washed with ice-cold PBS and stained with Annexin V-FITC/PI (40,302, YEASEN, China) or PI (40,301, YEASEN, China) for 15–30 min according to the instructions. Finally, the different apoptosis period and cell cycle of cells were analyzed by a flow cytometer (BD FACSCANTO II, BD Biosciences, USA).</p>", "<title>Subcutaneous xenograft tumor and lung metastasis models</title>", "<p id=\"Par49\">Nude mice (male, 4-week-old) was provided by the Animal Center of the Sir Run Run Shaw Hospital (Zhejiang, China). Subcutaneous xenograft tumor or lung metastasis model was established with a total of 1 × 10<sup>7</sup> HOS cells, which stably transfected with luciferase reporter gene, in 0.1 mL of PBS injected into the right flank of the mice or tail vein. After 2 weeks, the tumor-bearing mice of subcutaneous xenograft tumor or lung metastasis model were divided into two groups randomly, which were injected with 0.1 mL of saline or OTP-BTFPTU liposomes (1 × 10<sup>− 5</sup> M) twice a week via tail vein. After 2 weeks treatment, the tumor-bearing mice were performed with live imaging and sacrificed to obtain the tumor. Tumor volume was calculated by the equation v = ab<sup>2</sup>/2.</p>", "<title>In vivo fluorescence imaging of OTP-BTFPTU liposomes</title>", "<p id=\"Par50\">After 2 weeks of tumor formation, 0.1 mL of saline or OTP-BTFPTU liposomes (1 × 10<sup>− 5</sup> M) was injected to tumor-bearing mouse through tail vein. All mice were anesthetized with a 5% isoflurane/oxygen mixture and scanned under in vivo Imaging System (Ex/Em:493/517 nm) (IVIS Lumina LT, PerkinElmer, USA) 24 h after intravenous injection.</p>", "<title>Histology assay</title>", "<p id=\"Par51\">The osteosarcoma, lung, heart, kidney, liver, spleen samples were fixed in 4% paraformaldehyde at room temperature for 2 days. The slices of about 4 μm were used for H&amp;E (hematoxylin and eosin) staining and immunohistochemical staining. We performed immunohistochemical staining for c-Myc (sc-40, Santa Cruz, 1:100), E-Cadherin (EM0502, HUABIO, 1:100) and N-Cadherin (ET1607-37, HUABIO, 1:100) according to the formerly protocol [##REF##35060345##50##]. As for immunofluorescence staining, the primary antibody of F4/80 (sc-377,009, Santa Cruz, 1:100), CD86 (ET1606-50, HUABIO, 1:100) and CD206 (ab64694, Abcam, 1:100) were applied at 4 °C overnight. The secondary antibody of Goat anti-Rabbit IgG (H + L) Secondary Antibody (Alexa Fluor 555) (A31572, Invitrogen, 1:400) and Goat anti-Mouse IgG (H + L) Secondary Antibody (Alexa Fluor 488) (A11001, Invitrogen, 1:400) were applied at room temperature for 2 h.</p>", "<title>Western blot analysis</title>", "<p id=\"Par52\">HOS and 143B cells were plated (5 × 10<sup>5</sup> cells/well) in 6-well plates. Cells were cultured with different treatment for indicated time. RIPA (Solarbio, Beijing, China) mixed with 100mM phenylmethanesulfonyl fluoride (Beyotime, Zhengzhou, China), Protease Inhibitor Cocktail (Millipore, USA) and Phosphatase Inhibitor Cocktail (CWBIO, China) were used to extract the proteins. The extract was centrifuged for 10 min at 12,000 rpm under 4℃ and the obtained supernatants were heated for 10 min at 100℃. For Western blotting, we performed SDS–PAGE (10%) according to the previously described protocol [##REF##33469231##51##]. The protein bands were visualized by Amersham Imager 600 (GE, USA). Image J was employed to analyze the images. Following antibodies were used for Western blotting: Apoptosis Antibody Sampler Kit (9915, Cell Signaling Technology, 1:1000), LC3 Rabbit Antibody (2775, Cell Signaling Technology, 1:1000), SQSTM1 Rabbit Antibody (39,749, Cell Signaling Technology, 1:1000), ATF4 Rabbit Antibody (ET1612-37, HUABIO, 1:1000), ATF6 Mouse Antibody (sc-166,659, Santa Cruz, 1:1000), PERK Rabbit Antibody (ab229912, Abcam, 1:1000), BiP Rabbit Antibody (3177, Cell Signaling Technology, 1:1000), CHOP Rabbit Antibody (ET1703-05, HUABIO, 1:1000), GAPDH Mouse Antibody (AC002, ABclonal, 1:1000).</p>", "<title>Cellular immunofluorescent staining</title>", "<p id=\"Par53\">DiD Perchlorate (D8700, Solarbio, China) was used for cell membrane staining according to the instructions. In brief, cells were incubated with 5 µM dye solution at 37℃ for 20 min and washed with DMEM for 3 times. The images were taken by confocal microscopy (Olympus Corporation, Japan) (Ex/Em:644/663nm).</p>", "<title>Statistical analysis</title>", "<p id=\"Par54\">All data were represented as mean ± S.D. SPSS 19.0 (SPSS, Chicago) served for statistical analyses. Statistical differences were analyzed by two-tailed Student’s t-test or one-way ANOVA followed by Tukey’s post hoc analyses where appropriate. P-value ≤ 0.05 was considered statistically significant as indicated in the figure legend.</p>" ]
[ "<title>Result</title>", "<title>Synthetic procedures and characterization data of PTU, TFPTU and BTFPTU</title>", "<p id=\"Par8\">Bimodal ion transporters used in this study were based on thiourea groups, and were synthesized by reacting bis(2-aminoethyl) ether with corresponding isothiocyanates (Fig. ##FIG##0##1##A). Detailed synthetic processes have been reported somewhere else [##UREF##7##34##] and the <sup>1</sup>H NMR spectrum of PTU, TFPTU and BTFPTU in DMSO-<italic>d</italic>6 were shown in the Fig. ##SUPPL##0##S1##A-C.</p>", "<p id=\"Par9\">\n\n</p>", "<p id=\"Par10\">We tested the cationic and anionic selectivity of PTU, TFPTU and BTFPTU by using 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS) assay. The results showed that the ion transporters exhibited distinct ion selectivity towards, and similar transporting activities for cations (Fig. ##FIG##0##1##B-D). The diameters of LUVs of egg yolk phosphatidylcholine (EYPC) and EYPC with PTU were similar, indicating that insertion of ion transporters has minimum effect on lipid membranes (Fig. ##FIG##0##1##E).</p>", "<title>BTFPTU inhibits the proliferation and migration of osteosarcoma cells in vitro</title>", "<p id=\"Par11\">Studies have shown that disruption of intracellular ion concentration homeostasis can activate multiple pathways such as apoptosis, autophagy, pyroptosis, ferroptosis, oxidative stress, and ER stress, ultimately leading to cell death [##REF##25264571##7##–##REF##27890727##11##]. Based on the above theory, we investigated whether PTU, TFPTU, and BTFPTU could disrupt the ion homeostasis of osteosarcoma cells and kill them. Firstly, osteosarcoma cell lines (HOS and 143B cells) were treated with increased concentrations of PTU, TFPTU, and BTFPTU. CCK-8 assay showed that PTU had minimum effect on cell viability, while TFPTU and BTFPTU exhibited concentration-dependent cytotoxicity against osteosarcoma cells and BTFPTU had stronger cell toxicity than TFPTU (Fig. ##FIG##1##2##A and Fig. ##SUPPL##0##S2##A). Similarly, clone formation assay showed that TFPTU and BTFPTU concentration-dependently impaired colony-forming ability of osteosarcoma cells (Fig. ##FIG##1##2##B, C and Fig. ##SUPPL##0##S2##B, C). Based on the results of CCK-8 and clone formation assays, we selected BTFPTU, which exhibited the strongest cytotoxicity against osteosarcoma cells, for following experiments.</p>", "<p id=\"Par12\">\n\n</p>", "<p id=\"Par13\">EdU assay further confirmed that BTFPTU reduced cell viability (Fig. ##FIG##1##2##D and Fig. ##SUPPL##0##S2##D), and flow cytometry showed that BTFPTU significantly increased the apoptosis of osteosarcoma cells (Fig. ##FIG##1##2##E, F). After confirming that BTFPTU could significantly inhibit the proliferation and promote apoptosis of osteosarcoma cells, we further explored whether it will affect the migration ability of osteosarcoma cells. As revealed by Transwell and wound healing assays (Fig. ##FIG##1##2##G-J and Fig. ##SUPPL##0##S2##E, F), the migration ability of osteosarcoma cells was impeded after treatment with BTFPTU. The epithelial-mesenchymal transition (EMT) process and unlimited proliferation ability are important prerequisites for the migration and distant metastasis of osteosarcoma cells [##REF##25965573##35##]. The EMT markers N-cadherin, vimentin and proto-oncogene c-Myc in osteosarcoma cells were significantly downregulated with BTFPTU treatment (Fig. ##FIG##1##2##K and Fig. ##SUPPL##0##S2##G, H). In summary, BTFPTU can significantly inhibit the proliferation and migration ability of osteosarcoma cells in vitro.</p>", "<title>BTFPTU triggers transcriptional reprogramming of HOS cells</title>", "<p id=\"Par14\">In order to further investigate the mechanism of osteosarcoma cell death induced by BTFPTU, we performed RNA sequencing (RNA-seq) analysis on HOS cells treated with either PBS or BTFPTU for 24 h (Fig. ##FIG##2##3##). The volcano plot showed that, compared with the control group, there were 2218 upregulated genes and 994 downregulated genes with statistically significant differences in expression level in the BTFPTU treatment group (Fig. ##FIG##2##3##A). The results of the differential gene clustering heatmap showed that control and BTFPTU treatment group could be well clustered, indicating that the gene expression characteristics in each group were similar (Fig. ##FIG##2##3##B). Furthermore, the network of enriched terms showed that the BTFPTU treatment caused prominent changes in the expression of genes related to cell proliferation and death, such as unfolded protein response (UPR), response to ER stress, G1 to S cell cycle control, PI3K-Akt pathway, and cell population proliferation (Fig. ##FIG##2##3##C). In KEGG (Kyoto encyclopedia of genes and genomes) enrichment analysis, PI3K-Akt, P53, TGF-β, MAPK pathway, cell cycle, DNA replication and apoptosis pathway all entered the top 40 (Fig. ##FIG##2##3##D). GO (Gene Ontology) enrichment analysis showed that BTFPTU altered pathways of biological regulation, protein binding, and cell membrane component, which we were particularly interested in (Fig. ##FIG##2##3##E). BTFPTU enhanced UPR and impaired cell cycle, especially G1 to S phase in GSEA analysis (Fig. ##SUPPL##0##S3##A-F). The RNA-seq data fully demonstrated that BTFPTU induced transcriptional reprogramming in HOS cells, which may lead to cell death through multiple pathways, providing new directions for subsequent experiments.</p>", "<p id=\"Par15\">\n\n</p>", "<title>BTFPTU causes osteosarcoma cell death through multiple pathways in vitro</title>", "<p id=\"Par16\">Studies have shown that disruption of ion homeostasis affects diverse cellular functions, such as gene and protein expression and activities, post-translational modifications of proteins, cellular volume, cell cycle, cell proliferation and differentiation, membrane potential, reactive oxygen species levels, and intracellular/extracellular pH, leading to cell death [##REF##31231963##36##, ##REF##27222916##37##]. To investigate the mechanism by which BTFPTU induces cell death, we first examined whether it altered the ion homeostasis of osteosarcoma cells. Previous studies have shown that small-molecule ion transporters can transport ions driven by concentration gradients [##REF##27356157##38##, ##REF##28634604##39##], and Fig. ##FIG##0##1##F showed that BTFPTU had high transporting efficiency for chloride ions. Therefore, we used MQAE fluorescence staining to detect the intracellular chloride ion concentration. After 3 h of BTFPTU treatment, the influx of chloride ions caused a significant increase in the intracellular chloride ion concentration (MQAE fluorescence intensity is inversely proportional to the intracellular chloride ion concentration) (Fig. ##FIG##3##4##A). This suggested that BTFPTU could cause cell death by altering the ion homeostasis of cells.</p>", "<p id=\"Par17\">\n\n</p>", "<p id=\"Par18\">By analyzing the RNA-seq data, we found that BTFPTU treatment activated multiple pathways leading to cell growth arrest or death in osteosarcoma cells. The relevant pathways involved in the RNA-seq data were further validated. Firstly, we verified the ER stress and autophagy pathways. The expression of ER stress marker proteins such as m-ATF6, ATF4, PERK, BIP, and CHOP were significantly upregulated, while the expression of autophagy-related protein SQSTM1 was downregulated and LC3B was upregulated (Fig. ##FIG##3##4##B, C and Fig. ##SUPPL##0##S4##A, B). Similarly, after BTFPTU treatment, the expression levels of active forms of apoptotic proteins such as C-Caspase3, C-Caspase7, C-Caspase9, and C-PARP increased gradually with increasing BTFPTU concentration, while the expression levels of Caspase3, Caspase7, Caspase9, and PARP remained unchanged (Fig. ##FIG##3##4##D and Fig. ##SUPPL##0##S4##C). Flow cytometry analysis of cell cycle proved that BTFPTU arrested osteosarcoma cells in the G1 phase and prevented them from entering the S phase (Fig. ##FIG##3##4##E, F). All of the above results are consistent with the RNA-seq data, indicating that BTFPTU inhibits cell proliferation or induces cell death by activating ER stress and autophagy pathways, disrupting the normal cell cycle, and increasing the expression of active forms of apoptotic proteins. Subsequently, the inhibitors of apoptosis (Z-VAD-FMK, BI-6C9), pyroptosis (Ac-YVAD-cmk, MCC950), ferroptosis (Ferrostatin-1, Liproxstatin-1), autophagy (Chloroquine, 3-Methyladenine), and necroptosis (Necrostatin-1) were applied to investigate which form of cell death inhibition can rescue osteosarcoma cells treated with BTFPTU. The CCK-8 results showed that only the pan caspase inhibitor, Z-VAD-FMK, had a partial rescue effect on cell viability (Fig. ##FIG##3##4##G). These results indicated that BTFPTU induced multiple modes of cell death in osteosarcoma cells by disrupting the ion homeostasis of cells, especially the chloride ion homeostasis.</p>", "<title>The self-assembled OTP-BTFPTU supramolecular liposomes inhibits the proliferation and migration of HOS cells in vitro</title>", "<p id=\"Par19\">As BTFPTU is an ion transporter that can insert into the cell membranes and disrupt ion homeostasis, we designed a self-assembling complex to achieve targeted treatment of osteosarcoma lesions, which can reduce toxicity to other organs. The osteosarcoma targeting peptide (OTP, with the sequence of TPPRVPLLTFGS) was identified by phage display techniques, which can recognize and target osteosarcoma [##REF##35396783##31##].We further modified the peptide by adding FITC and EDA-Tetradecanoic acid which allowed for better binding of the peptide to the lipid membrane. Then we mixed the modified OTP, BTFPTU, and liposomes (assembly scheme: 2 mg peptide + 646 µg BTFPTU + 10 mg liposomes per ml of solution) for self-assembly, as shown in Fig. ##FIG##4##5##A.</p>", "<p id=\"Par20\">\n\n</p>", "<p id=\"Par21\">Transmission electron microscopy (TEM) revealed that the self-assembled osteosarcoma targeting peptide-BTFPTU supramolecular liposomes (OTP-BP-L) possessed a well-defined vesicular structure (Fig. ##FIG##4##5##B). Immunofluorescence results showed that OTP-BP-L had co-localization with cell membrane, indicating that OTP-BP-L can insert into the cell membrane and function as ion transporters (Fig. ##FIG##4##5##C). CCK-8 and EdU assays (Fig. ##FIG##4##5##D, E) shown that OTP-BP-L inhibited the proliferation of HOS cells, and flow cytometry proved that OTP-BP-L increased apoptosis in HOS cells (Fig. ##FIG##4##5##F, G). Similarly, after treatment with OTP-BP-L, the migration ability and expression levels of EMT marker proteins in HOS cells were significantly inhibited (Fig. ##FIG##4##5##H-M). To further confirm the toxic effects of OTP-BP-L on osteosarcoma cells, we measured the expression levels of apoptosis, ER stress, and autophagy-related proteins. Western blotting demonstrated that OTP-BP-L also could activate apoptosis, ER stress, and autophagy-related pathways, leading to cell death (Fig. ##SUPPL##0##S5##A-F). These data confirmed that OTP-BTFPTU supramolecular liposomes inhibited the proliferation and migration of HOS cells in vitro.</p>", "<title>OTP-BTFPTU liposomes suppresses osteosarcoma tumorigenesis and metastasis in vivo</title>", "<p id=\"Par22\">We have confirmed that the self-assembled OTP-BP-L can kill HOS cells in vitro. To further investigate its therapeutic effect on osteosarcoma in vivo, we established subcutaneous xenograft tumor and lung metastasis models with HOS cells stably transfected with luciferase reporter gene. To verify the tumor-homing ability of OTP-BP-L, we used in vivo fluorescence imaging to locate OTP-BP-L one day after intravenous injection. Strong fluorescence signals were detected in the subcutaneous tumor area, indicating that OTP-BP-L had good tumor-targeting ability and accumulated in tumor tissue (Fig. ##FIG##5##6##A, B). After 2 weeks of treatment with normal saline or OTP-BP-L, the luminescence signals in the subcutaneous tumor area of the OTP-BP-L treatment group were barely detectable, indicating that OTP-BP-L significantly inhibited subcutaneous tumor growth (Fig. ##FIG##5##6##C, D). Furthermore, OTP-BP-L treatment obviously decreased the tumor volume and weight compared to those in the control group (Fig. ##FIG##5##6##E-G). The expression of c-Myc and N-cadherin was reduced while the expression of E-cadherin was increased in tumor tissue by OTP-BP-L treatment (Fig. ##FIG##5##6##H). To evaluate the toxicity of OTP-BP-L to other organs, we isolated important organs such as the heart, kidney, liver, lung, and spleen, and performed HE staining. The results showed that OTP-BP-L treatment did not cause significant damage to these organs (Fig. ##FIG##5##6##I).</p>", "<p id=\"Par23\">\n\n</p>", "<p id=\"Par24\">In the lung metastasis model, OTP-BP-L also reduced the luminescence signals and the size of lung metastatic foci (Fig. ##SUPPL##0##S6##A-C). OTP-BP-L inhibited distant metastasis of osteosarcoma and reduced the expression of c-Myc and N-cadherin while increasing the expression of E-cadherin (Fig. ##SUPPL##0##S6##D, E). These results indicated that OTP-BP-L had good targeting ability and therapeutic effect on osteosarcoma in situ lesions, and significantly inhibited distant metastasis of osteosarcoma in vivo.</p>", "<title>OTP-BTFPTU liposomes exhibit anti-drug resistance and can regulate the tumor immune microenvironment</title>", "<p id=\"Par25\">OTP-BP-L demonstrated good therapeutic effects on both in situ tumors and distant metastasis of osteosarcoma in vivo, so we wondered if OTP-BP-L was treating osteosarcoma only through its direct toxicity to osteosarcoma cells. Since osteosarcoma is prone to developing resistance to many drugs, which limits their therapeutic efficacy [##REF##14679136##40##, ##REF##18385200##41##], we investigated the anti-drug resistance of OTP-BP-L. Firstly, we treated strong drug resistance cell lines, such as cisplatin-resistant osteosarcoma cell line (HOS-DDPR), triple negative breast cancer cell lines (BT549 and MDA-MB-231) and sorafenib-resistant hepatoma cell line (MHCC-97 H-SR), with OTP-BP-L. The result showed that OTP-BP-L was still effective in killing drug resistance cell lines of osteosarcoma and other tumors (Fig. ##FIG##6##7##A).</p>", "<p id=\"Par26\">\n\n</p>", "<p id=\"Par27\">In addition to the direct toxicity to tumor cells, the therapeutic effect of a drug on tumors in vivo also depends on its regulation of the tumor immune microenvironment. Tumor-associated macrophages (TAMs) are crucial for the development and progression of tumors, and it is generally believed that reprogramming of TAMs towards M1 phenotype can inhibit tumor growth [##REF##35974096##32##, ##REF##33619259##33##]. Based on this theory, we investigated the effect of OTP-BP-L-treated CM on the polarization of bone marrow-derived macrophages (BMMs) in vitro. HOS cells were treated with 0.5 µM OTP-BP-L for 24 h and the supernatant was collected after removing large cell fragments through centrifugation (Fig. ##FIG##6##7##B). The collected supernatant was then used as conditioned medium (CM) for BMMs culture. The qPCR results showed that OTP-BP-L-treated CM could increase the expression of CD86, iNOS, IL-1β, and IL-6, while inhibiting the expression of IL-10, ARG1, TGF-β, and CD206. These results indicated that the cell lysate products from OTP-BP-L treatment group promoted M1 polarization of macrophages and inhibited M2 polarization (Fig. ##FIG##6##7##C and Fig. ##SUPPL##0##S7##A). To further validate the regulation of TAMs polarization by OTP-BP-L in vivo, we defined CD86<sup>+</sup>/F4/80<sup>+</sup> cells as M1 macrophages and CD206<sup>+</sup>/F4/80<sup>+</sup> cells as M2 macrophages according to Michael Klichinsky et al. [##REF##32361713##42##], and performed immunofluorescence staining on tumor tissue sections. OTP-BP-L treatment significantly promoted M1 polarization and inhibited M2 polarization of TAMs (Fig. ##FIG##6##7##D-G). The results proved that OTP-BP-L could achieve its therapeutic effect by regulating the tumor immune microenvironment.</p>", "<p id=\"Par28\">In summary, OTP-BP-L exhibited anti-drug resistance and ability to regulate the tumor immune microenvironment in vivo, which provided a new approach for the treatment of osteosarcoma.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par29\">Osteosarcoma is a highly malignant tumor that commonly occurs in children and adolescents, and is characterized by a high propensity for distant metastasis, drug resistance and high heterogeneity, with a lack of targeted treatment strategies. As a result, the treatment of osteosarcoma has been a major challenge in clinical treatment [##REF##31928458##5##, ##REF##30009886##43##]. In this study, we addressed several major issues in osteosarcoma treatment by using a synthetic transmembrane ion transporter (BTFPTU). By loading ion transporters and osteosarcoma-targeting peptides (OTP) into liposomes, the self-assembled supramolecular drug can target and eliminate osteosarcoma lesions, resist drug resistance, and regulate the immune microenvironment in vivo.</p>", "<p id=\"Par30\">We have synthesized three ion transporters based on O-bridged scaffold with different functional groups. As shown in our previous study, the ion transport activity increases when adding electron-withdrawing groups such as -CF<sub>3</sub> to the transporters [##UREF##7##34##]. For example, when modified with two -CF<sub>3</sub> groups instead of one, the EC50 value (effective concentration needed to achieve half of the chloride influx after addition of transporter) increased from 0.041 mol% for TFPTU to 0.0045 mol% for BTFPTU. We screened three types of ion transporters, PTU, TFPTU, and BTFPTU, and found that BTFPTU had the best therapeutic efficacy against osteosarcoma in vitro.</p>", "<p id=\"Par31\">Over the past 40 years, researchers have been exploring the mechanisms of chemoresistance in osteosarcoma, including drug inactivation, changes in drug targets, drug efflux, epigenetic changes, EMT, and inhibition of cell death. Although understanding of chemoresistance in osteosarcoma has deepened, effective methods to address this issue are still lacking. The current consensus is that tumor cells are more likely to develop resistance to the drug which causes a single mode of cell death [##REF##12142169##44##–##REF##12204532##46##]. BTFPTU is a transmembrane ion transporter that can insert into the cell membrane without the need for recognition sites or intracellular metabolic processes, and disrupt intracellular ion homeostasis, especially chloride ion homeostasis. Imbalance of intracellular chloride ion homeostasis affects diverse cellular functions and ultimately leads to cell death [##REF##31231963##36##, ##REF##27222916##37##]. Due to its direct binding to the cell membrane, BTFPTU is difficult to be expelled from cells unless the cells die. These characteristics determine that osteosarcoma cells are unlikely to develop resistance to this type of ion transporters through drug inactivation, changes in drug targets, or drug efflux. Although previous studies have also investigated the effects of ion transporters on cells in vitro, these studies have only explored the induction of cell death through apoptosis. Our research has, for the first time, revealed that this class of ion transporters can induce cell death through various mechanisms, including activation of ER stress, autophagy, and cell cycle arrest. Furthermore, BTFPTU-induced multi-mode cell death was less likely to induce drug resistance in osteosarcoma cells compared to single- mode cell death.</p>", "<p id=\"Par32\">The high heterogeneity of osteosarcoma has led to the lack of targeted drugs for clinical treatment. Despite the heterogeneity of tissues or organs, phage display techniques can still identify tissue or organ specific binding peptides [##REF##8598934##47##]. Furthermore, compared to targeted drugs such as antibodies, targeted peptides selected by phage display have more precise binding sites [##REF##22725698##48##]. Lin et al. used phage display techniques to screen for a peptide, which only had recognition function for osteosarcoma and didn’t have killing effect on tumor cells [##REF##35396783##31##]. Since the identification of this peptide was based on HOS cells, we used HOS cells for subsequent studies as well. We utilized this OTP and modified it with FITC and EDA-Tetradecanoic acid to improve its binding to the lipid membrane. BTFPTU, OTP and liposomes self-assembled into a supramolecular drug (OTP-BP-L) which used for the treatment of osteosarcoma. OTP-BP-L had good targeting ability and therapeutic efficacy against osteosarcoma in situ lesions in vivo, and could significantly inhibit distant metastasis of osteosarcoma. The toxicity to other organs under systemic application of OTP-BP-L was also considered, and experiments showed that OTP-BP-L didn’t cause significant damage to important organs during treatment. To further apply OTP-BP-L in vivo, the retention time in tumor tissue and metabolic processes of OTP-BP-L will be the focus of our future research.</p>", "<p id=\"Par33\">Further studies on OTP-BP-L showed that it had good killing effects on drug resistant tumor cell lines, indicating that OTP-BP-L also has good anti-resistance properties. In vivo application is different from cell culture in vitro because the lysate products after cell death have a crucial impact on the tumor tissue and its microenvironment. Unlike tumor cells, stromal cell types within the tumor microenvironment (TME) are genetically stable and thus represent an attractive therapeutic target with reduced risk of resistance and tumor recurrence [##REF##24202395##49##]. Tumor-associated macrophages (TAMs) are an essential component of the tumor microenvironment and have a role in the orchestration of various processes, including resistance to chemotherapeutic agents and checkpoint blockade immunotherapy [##REF##35974096##32##]. The in vitro and in vivo experiments indicated that OTP-BP-L treatment remodeled the tumor immune microenvironment, promoting the polarization of TAMs towards the M1 phenotype that inhibited tumor growth.</p>", "<p id=\"Par34\">In summary, the self-assembly osteosarcoma targeting peptide-BTFPTU supramolecular liposomes had good tumor targeting capability, exhibited anti-drug resistance and regulated the tumor immune microenvironment. This work not only demonstrated the biomedical value of small-molecule anion transporters in vivo, but also provided an innovative approach for the treatment of osteosarcoma.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par35\">In summary, we have demonstrated for the first time that small-molecule anion transporters are capable of killing osteosarcoma cells through multiple pathways, rather than solely relying on the previously reported caspase-dependent apoptotic pathway. Through a co-assembly process, we have successfully prepared supramolecular drugs by loading anion transporters into osteosarcoma targeting peptide functionalized liposomes. The assemblies, OTP-BP-L, show excellent targeting and therapeutic effect towards osteosarcoma tumors. Furthermore, the supramolecular drug shows a strong ability to regulate the tumor immune microenvironment in subcutaneous xenograft tumor and lung metastasis models. This work not only demonstrated the biomedical value of small-molecule anion transporters in vivo, but also provided an innovative approach for the treatment of osteosarcoma.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Osteosarcoma represents a serious clinical challenge due to its widespread genomic alterations, tendency for drug resistance and distant metastasis. New treatment methods are urgently needed to address those treatment difficulties in osteosarcoma to improve patient prognoses. In recent years, small-molecule based anion transporter have emerged as innovative and promising therapeutic compound with various biomedical applications. However, due to a lack of efficient delivery methods, using ion transporters as therapeutic drugs in vivo remains a major challenge.</p>", "<title>Result</title>", "<p id=\"Par2\">Herein, we developed self-assembled supramolecular drugs based on small-molecule anion transporters, which exhibited potent therapeutic effect towards osteosarcoma both in vitro and in vivo. The anion transporters can disrupt intracellular ion homeostasis, inhibit proliferation, migration, epithelial-mesenchymal transition process, and lead to osteosarcoma cell death. RNA sequencing, western blot and flow cytometry indicated reprogramming of HOS cells and induced cell death through multiple pathways. These pathways included activation of endoplasmic reticulum stress, autophagy, apoptosis and cell cycle arrest, which avoided the development of drug resistance in osteosarcoma cells. Functionalized with osteosarcoma targeting peptide, the assembled supramolecular drug showed excellent targeted anticancer therapy against subcutaneous xenograft tumor and lung metastasis models. Besides good tumor targeting capability and anti-drug resistance, the efficacy of the assembly was also attributed to its ability to regulate the tumor immune microenvironment in vivo.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">In summary, we have demonstrated for the first time that small-molecule anion transporters are capable of killing osteosarcoma cells through multiple pathways. The assemblies, OTP-BP-L, show excellent targeting and therapeutic effect towards osteosarcoma tumors. Furthermore, the supramolecular drug shows a strong ability to regulate the tumor immune microenvironment in vivo. This work not only demonstrated the biomedical value of small-molecule anion transporters in vivo, but also provided an innovative approach for the treatment of osteosarcoma.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12951-023-02270-x.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank Prof. Jun Zhang for providing triple negative breast cancer cell lines (BT549 and MDA-MB-231) and Prof. Xian Wang for providing Sorafenib-resistant hepatoma cell line (MHCC-97 H-SR).</p>", "<title>Author contributions</title>", "<p>ZYZ, XAW and YYL performed the experiments, analyzed the data and edited the manuscript. SYT, HL and ZYJ performed mice experiments. HXW and JYJ performed TEM experiments. FDZ conceived the project and revised the manuscript. CL, JHL and JC conceived the project, designed the experiments and edited the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by the National Nature Science Foundation of China (No. 82272520, 82272521, 22271102), Natural Science Foundation of Guangdong Province (No. 2023A1515011279).</p>", "<title>Data availability</title>", "<p>All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper are available from the authors upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethical approval</title>", "<p id=\"Par56\">All animal experiments were approved by the ethics committee of Zhejiang University (ZJU20210091), which followed the Guidelines for Care and Use of Laboratory Animals from National Institutes of Health. The study didn’t involve human participants, human data or human tissue.</p>", "<title>Consent for publication</title>", "<p id=\"Par57\">Not applicable.</p>", "<title><bold>Competing interests</bold></title>", "<p id=\"Par58\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Synthetic procedures and transmembrane ion transport properties of PTU, TFPTU and BTFPTU. (<bold>A</bold>) Synthetic routes of PTU, TFPTU and BTFPTU. (<bold>B–D</bold>) Anionic and cationic selectivity of PTU, TFPTU and BTFPTU determined using the HPTS assays. (<bold>E</bold>) Dynamic light scattering (DLS) measurements of large unilamellar vesicles (LUVs) made from blank EYPC and EYPC with anion transporter PTU</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>BTFPTU inhibits the proliferation and migration of osteosarcoma cells in vitro. (<bold>A</bold>) Viability of HOS cells with PTU, TFPTU or BTFPTU treatment for 24 h using Cell Counting Kit-8 assay. (<bold>B</bold>) Effect of PTU, TFPTU or BTFPTU treatment for 48 h on the colony-forming ability of HOS cells based on colony formation assays. Scale bar, 200 μm. (<bold>C</bold>) Quantification of the colony number. (<bold>D</bold>) HOS cells were treated with different concentrations of BTFPTU for 24 h, and the cell proliferation was characterized by the EdU assay. Scale bar, 200 μm. (<bold>E</bold>) Flow cytometry to determine apoptosis of HOS and 143B cells with or without BTFPTU (2 µM) treatment for 12 h by Annexin V-FITC/PI apoptosis detection. (<bold>F</bold>) Quantification of apoptosis rate of HOS and 143B cells. (<bold>G</bold>) Cell migration abilities of HOS and 143B cells treated with different concentrations of BTFPTU for 24 h were measured by Transwell migration assays. Scale bar, 200 μm. (<bold>H</bold>) Quantification of the migration abilities of HOS and 143B cells. (<bold>I</bold>) The wound healing assay was used to evaluate the migration abilities of HOS cells treated with different concentrations of BTFPTU for 24 h. Scale bar, 50 μm. (<bold>J</bold>) Quantification of the wound closure rate. (<bold>K</bold>) The protein expression of N-Cadherin, Vimentin and c-Myc were measured by Western blot analysis in HOS cells treated with varying concentrations of BTFPTU for 24 h. The data represent the mean ± SD of three independent experiments. *p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001 for a comparison with the control group or as indicated</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>BTFPTU triggers transcriptional reprogramming of HOS cells. (<bold>A</bold>) Volcano plot of RNA sequencing (RNA-seq) analysis on HOS cells treated with either PBS or BTFPTU for 24 h. (<bold>B</bold>) The differential gene clustering heatmap of RNA-seq analysis. (<bold>C</bold>) The network of enriched terms of RNA-seq analysis. The left figure was colored by P-value and terms containing more genes tended to have a more significant P-value. The right figure was colored by cluster ID and nodes share the same cluster were typically close to each other. (<bold>D</bold>) KEGG enrichment of RNA-seq analysis. (<bold>E</bold>) GO enrichment of RNA-seq analysis. p &lt; 0.05 is defined as having a significant difference for comparison with the control group</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>BTFPTU causes osteosarcoma cells death through multiple pathways in vitro. (<bold>A</bold>) Immunofluorescence of intracellular chloride ions in HOS cells treated with or without BTFPTU (2 µM) treatment for 6 h using MQAE staining. Scale bar, 200 μm. (<bold>B</bold>) The expression of ER stress proteins was measured by Western blot analysis in HOS and 143B cells treated with varying concentrations of BTFPTU for 24 h. (<bold>C</bold>) The expression of autophagy-related proteins was measured by Western blot analysis in HOS and 143B cells treated with varying concentrations of BTFPTU for 24 h. (<bold>D</bold>) The expression of apoptosis proteins was measured by Western blot analysis in HOS and 143B cells treated with varying concentrations of BTFPTU for 24 h. (<bold>E</bold>) Flow cytometry to detect cell cycle of HOS and 143B cells with or without BTFPTU (2 µM) treatment for 12 h by PI staining. (<bold>F</bold>) Quantification of different cell cycle phases of HOS and 143B cells. (<bold>G</bold>) Cell viability of HOS and 143B cells with Z-VAD (10 µM), BI-6 C (5 µM), AC (5 µM), MCC (10 µM), Fer-1 (5 µM), Lip-1 (2.5 µM), CQ (2.5 µM), 3-MA (2.5 mM) or nec-1 (5 µM) treatment under PTU, TFPTU or BTFPTU treatment for 24 h using Cell Counting Kit-8 assay. The data represent the mean ± SD of three independent experiments. *p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001 for a comparison with the control group or as indicated</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>The self-assembled OTP-BTFPTU supramolecular liposomes inhibits the proliferation and migration of HOS cells in vitro. (<bold>A</bold>) Schematic illustration of osteosarcoma targeting peptide (OTP)-BTFPTU supramolecular liposomes prepared through self-assembly. (<bold>B</bold>) The TEM images of OTP-BTFPTU liposomes. Scale bar, 100 nm. (<bold>C</bold>) FITC (green), DID (red) and DAPI (blue) immunofluorescence of HOS cells with or without OTP-BTFPTU (2 µM) liposomes treatment for 3 h. Scale bar, 20 μm. (<bold>D</bold>) Cell viability of HOS cells with OTP-PTU, OTP-TFPTU or OTP-BTFPTU liposomes treatment for 24 h using Cell Counting Kit-8 assay. (<bold>E</bold>) HOS cells were treated with different concentrations of OTP-BTFPTU liposomes for 24 h and the cell proliferation was characterized by EdU assay. Scale bar, 200 μm. (<bold>F</bold>) Flow cytometry to evaluate apoptosis of HOS cells with or without OTP-BTFPTU liposomes (2 µM) treatment for 12 h by Annexin V-FITC/PI apoptosis detection. (<bold>G</bold>) Quantification of apoptosis rate of HOS cells. (<bold>H</bold>) Cell migration abilities of HOS cells treated with different concentrations of OTP-BTFPTU liposomes for 24 h were measured by Transwell migration assays. Scale bar, 200 μm. (<bold>I</bold>) Quantification of the migration abilities of HOS cells. (<bold>J</bold>) The wound healing assay was used to evaluate the migration abilities of HOS cells treated with different concentrations of OTP-BTFPTU liposomes for 24 h. Scale bar, 50 μm. (<bold>K</bold>) Quantification of the wound closure rate. (<bold>L</bold>) The protein expression of N-Cadherin, Vimentin and c-Myc was measured by Western blot analysis in HOS cells treated with varying concentrations of OTP-BTFPTU liposomes for 24 h. (<bold>M</bold>) Quantification and normalization of the gray levels of N-Cadherin, Vimentin and c-Myc proteins to that of GAPDH in HOS cells using Image J. The data represent the mean ± SD of three independent experiments. *p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001 for a comparison with the control group or as indicated</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>OTP-BTFPTU liposomes suppresses osteosarcoma tumorigenesis and metastasis in vivo. (<bold>A</bold>) Living fluorescence imaging of subcutaneous xenograft tumor model mice, which were injected with 0.1 mL of saline or OTP-BTFPTU liposomes (5 × 10 − 5 M) through tail vein. The imaging was performed 24 h after injection (n = 4). (<bold>B</bold>) Quantification of the relative fluorescence of the nude mice which were injected with saline or OTP-BTFPTU liposomes. (<bold>C</bold>) Living luminescence imaging of subcutaneous xenograft tumor model mice with saline or OTP-BTFPTU liposomes treatment (n = 4). (<bold>D</bold>) Quantification of the relative luminescence of subcutaneous xenograft tumor model mice with saline or OTP-BTFPTU liposomes treatment. (<bold>E</bold>) Photographs of HOS derived xenograft model with saline or OTP-BTFPTU liposomes treatment (n = 4). (<bold>F</bold>) Tumor volume of different groups was measured every 7 days after mice were injected with HOS cells. (<bold>G</bold>) The average tumor weight in each group when the mice were sacrificed. (<bold>H</bold>) The expression of c-Myc, E-cadherin and N-cadherin were determined by immunohistochemistry. Scale bars, 400 μm. (<bold>I</bold>) HE staining of heart, kidney, liver, lung and spleen which were obtained from different groups. Scale bars, 300 μm. The data represent the mean ± SD of three independent experiments. *p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001 for a comparison with the control group or as indicated</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>OTP-BTFPTU liposomes exhibit anti-drug resistance and can regulate the tumor immune microenvironment. (<bold>A</bold>) Cell viability of HOS-DDPR (cisplatin-resistant osteosarcoma cell line), 97 H-SR (sorafenib-resistant hepatoma cell line), MDA-MB-231 and BT549 (triple negative breast cancer cell lines) cells with OTP-BTFPTU liposomes treatment for 24 h using Cell Counting Kit-8 assay. (<bold>B</bold>) Schematic illustration of obtaining conditional medium (CM). (<bold>C</bold>) The mRNA level of iNOS, IL-1β, IL-10 and ARG1 in BMMs following M1 or M2 macrophage induction in the presence of 50% control or OTP-BTFPTU liposomes CM. (<bold>D</bold>) DAPI (blue), F4/80 (green) and CD86 (red) immunofluorescence of tumor sections from mice treated with or without OTP-BTFPTU liposomes. Scale bars, 50 μm. (<bold>E</bold>) Quantification of M1 macrophage (F4/80<sup>+</sup>＆CD86<sup>+</sup>) ratio. (<bold>F</bold>) DAPI (blue), F4/80 (green) and CD206 (red) immunofluorescence of tumor sections from mice treated with or without OTP-BTFPTU liposomes. Scale bars, 50 μm. (<bold>G</bold>) Quantification of M2 macrophage (F4/80<sup>+</sup>＆CD206<sup>+</sup>) ratio. The data represent the mean ± SD of three independent experiments. *p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001 for a comparison with the control group or as indicated</p></caption></fig>" ]
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[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Zeyu Zheng, Xiaoan Wei and Yangyang Lin contributed equally to this work.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12951_2023_2270_MOESM1_ESM.docx\"><caption><p><bold>Supplementary Material 1:</bold> Supplementary material of Figs. S1–S7</p></caption></media>" ]
[{"label": ["12."], "surname": ["Lang", "Li", "Dong", "Zhang", "Yang", "Yang", "Deng", "Zhang", "Xu", "Liu"], "given-names": ["C", "W", "Z", "X", "F", "B", "X", "C", "J", "J"], "article-title": ["Biomimetic transmembrane channels with high stability and transporting efficiency from helically folded macromolecules"], "source": ["Angew Chem Int Ed"], "year": ["2016"], "volume": ["55"], "fpage": ["9723"], "lpage": ["7"], "pub-id": ["10.1002/anie.201604071"]}, {"label": ["13."], "surname": ["Lang", "Deng", "Yang", "Yang", "Wang", "Qi", "Zhang", "Zhang", "Dong", "Liu"], "given-names": ["C", "X", "F", "B", "W", "S", "X", "C", "Z", "J"], "article-title": ["Highly selective Artificial Potassium Ion Channels constructed from pore-containing helical oligomers"], "source": ["Angew Chem Int Ed"], "year": ["2017"], "volume": ["56"], "fpage": ["12668"], "lpage": ["71"], "pub-id": ["10.1002/anie.201705048"]}, {"label": ["18."], "surname": ["Zheng", "Huang", "Sun", "Barboiu"], "given-names": ["S-P", "L-B", "Z", "M"], "article-title": ["Self-assembled Artificial Ion-Channels toward Natural selection of functions"], "source": ["Angew Chem Int Ed"], "year": ["2021"], "volume": ["60"], "fpage": ["566"], "lpage": ["97"], "pub-id": ["10.1002/anie.201915287"]}, {"label": ["21."], "surname": ["Busschaert", "Gale"], "given-names": ["N", "PA"], "article-title": ["Small-molecule lipid-bilayer anion transporters for Biological Applications"], "source": ["Angew Chem Int Ed"], "year": ["2013"], "volume": ["52"], "fpage": ["1374"], "lpage": ["82"], "pub-id": ["10.1002/anie.201207535"]}, {"label": ["23."], "surname": ["Lang", "Mohite", "Deng", "Yang", "Dong", "Xu", "Liu", "Keinan", "Reany"], "given-names": ["C", "A", "X", "F", "Z", "J", "J", "E", "O"], "article-title": ["Semithiobambus[6]uril is a transmembrane anion transporter"], "source": ["Chem Commun"], "year": ["2017"], "volume": ["53"], "fpage": ["7557"], "lpage": ["60"], "pub-id": ["10.1039/C7CC04026A"]}, {"label": ["24."], "surname": ["Yang", "Yu", "Sessler", "Shin", "Gale", "Huang"], "given-names": ["J", "G", "JL", "I", "PA", "F"], "article-title": ["Artificial transmembrane ion transporters as potential therapeutics"], "source": ["Chem"], "year": ["2021"], "volume": ["7"], "fpage": ["3256"], "lpage": ["91"], "pub-id": ["10.1016/j.chempr.2021.10.028"]}, {"label": ["25."], "surname": ["Yan", "Zheng", "Liu", "Zou", "Liu"], "given-names": ["T", "X", "S", "Y", "J"], "article-title": ["Ion transporters: emerging agents for anticancer therapy"], "source": ["Sci China Chem"], "year": ["2022"], "volume": ["65"], "fpage": ["1265"], "lpage": ["78"], "pub-id": ["10.1007/s11426-022-1258-4"]}, {"label": ["34."], "surname": ["Lang", "Zhang", "Luo", "Dong", "Xu", "Liu"], "given-names": ["C", "X", "Q", "Z", "J", "J"], "article-title": ["Powerful Bipodal Anion transporters based on scaffolds that Contain different chalcogens"], "source": ["Eur J Org Chem"], "year": ["2015"], "volume": ["2015"], "fpage": ["6458"], "lpage": ["65"], "pub-id": ["10.1002/ejoc.201500997"]}]
{ "acronym": [ "ER", "ROS", "ALP", "TAMs", "OTP", "HPTS", "EYPC", "EMT", "RNA-seq", "UPR", "KEGG", "GO", "OTP-BP-L", "DLS", "LUVs", "PBS" ], "definition": [ "Endoplasmic reticulum", "Reactive oxygen species", "Alkaline phosphatase", "Tumor-associated macrophages", "Osteosarcoma-targeting peptides", "8-hydroxypyrene-1,3,6-trisulfonic acid", "Egg yolk phosphatidylcholine", "Epithelial-mesenchymal transition", "RNA sequencing", "Unfolded protein response", "Kyoto encyclopedia of genes and genomes", "Gene Ontology", "osteosarcoma targeting peptide-BTFPTU supramolecular liposomes", "Dynamic light scattering", "Large unilamellar vesicles", "Phosphate-buffered saline" ] }
51
CC BY
no
2024-01-14 23:43:46
J Nanobiotechnology. 2024 Jan 13; 22:29
oa_package/47/f7/PMC10787436.tar.gz
PMC10787437
38216955
[ "<title>Introduction</title>", "<p id=\"Par5\">As a global public health concern, diabetes mellitus (DM) and its associated complications pose a substantial threat to human well-being [##REF##37037849##1##, ##REF##30171279##2##]. Type 2 DM (T2DM) accounts for more than 90% of DM cases and is characterized by hyperglycemia, insulin resistance, and dysregulated lipid metabolism [##UREF##0##3##]. Patients with T2DM frequently experience microvascular complications, which arise from chronic exposure to hyperglycemia and result in detrimental effects on the microvasculature [##REF##29545773##4##]. Notably, diabetic nephropathy, retinopathy, and neuropathy are common consequences of this damage, significantly impacting both quality of life and life expectancy [##REF##33125468##5##, ##REF##31057114##6##]. The role of endothelial damage in the development of microvascular complications of T2DM is of paramount importance [##REF##37037849##1##].</p>", "<p id=\"Par6\">Vitamin D is an essential nutrient for the human body, and its insufficiency has been found to be associated with T2DM [##REF##27932304##7##]. Recent evidence has indicated that serum 1,25-OH-vitamin D (the biologically active form) is positively correlated with insulin sensitivity and secretion, while a deficiency in vitamin D is negatively linked to glycemic control [##REF##27932304##7##, ##REF##31506836##8##]. Furthermore, recent studies have suggested that individuals with a serum 1,25-OH-vitamin D level below 50 nmol/L have a higher incidence of macrovascular and microvascular events compared to those with a level above 50 nmol/L [##REF##25524951##9##]. The role of vitamin D in the development of microvascular complications in T2DM remains uncertain. Consequently, this study sought to examine the impact and underlying mechanism of vitamin D supplementation on endothelial functions using a model of human umbilical vein endothelial cells (HUVECs) exposed to high glucose conditions.</p>", "<p id=\"Par7\">Specifically, the study focused on the involvement of TIPE1 (Tumor necrosis factor-α-induced protein 8-like 1, TNFAIP8L1), a recently discovered member of the TIPE protein family known to contribute to inflammation, endothelial dysfunction, and atherosclerosis [##REF##31672550##10##]. In this study, it was observed that the downregulation of TIPE1 played a role in mediating the effects of vitamin D in HUVECs (Human umbilical vein endothelial cells) under high glucose conditions.</p>" ]
[ "<title>Methods</title>", "<title>Patients and ethics approval</title>", "<p id=\"Par8\">The Ethics Committee of Suzhou Wuzhong People’s Hospital (KJ-2023-022-01) granted approval for this study. Prior to their participation, all patients were provided with information regarding the objective, content, and significance of the study. Informed consent forms were signed by all patients.</p>", "<title>Measurement of serum vitamin D level</title>", "<p id=\"Par9\">A total of 40 type 2 patients with microvascular complications and 40 type 2 patients without complications were randomly selected for recruitment. Serum vitamin D levels were assessed using chemiluminescence enzyme immunoassay (IDS, Boldon, UK).</p>", "<title>Cell culture and treatment</title>", "<p id=\"Par10\">Human umbilical vein endothelial cells (HUVECs) were purchased from American Type Culture Collection (ATCC, CRL-1730, USA) and cultured in endothelial cell growth medium (ScienCell, USA). Experiments were conducted on cultured HUVECs in their 3rd-6th passage. HUVECs were treated with 35 mM glucose (G8769, Sigma, USA) for 12 h to simulate cells exposed to hyperglycemia. 100 nM vitamin D (1α,25-dihydroxyvitamin D3, D1530, Sigma, USA, dissolved in ethanol) was added in the culture medium of HUVECs for 24 h after pretreatment with 35 mM glucose for 12 h. HUVECs incubated with a normal concentration of glucose (5.6 mM) served as control.</p>", "<title>Cell viability test</title>", "<p id=\"Par11\">Cell counting kit 8 (CCK-8) kit (Vazyme, Nanjing, China) was used to detect HUVECs cell viability with different treatments. The absorbance was measured at 450 nm on a microplate reader after 1.5 h of incubation of 10 µL CCK-8 solution at 37 °C (Molecular Devices, CA, USA).</p>", "<title>Terminal deoxynucleotidyl transferase dUTP nick end labeling staining</title>", "<p id=\"Par12\">Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay kit (Roche Molecular Biochemicals, Mannheim, Germany) was used. The stained cells were imaged with a microscope (Observer D1, Zeiss).</p>", "<title>Cell migration transwell analysis</title>", "<p id=\"Par13\">Cell migration transwell assay was performed to check the migration ability of HUVECs with different treatments. Treated HUVECs were seeded into the upper chamber in serum-free medium, culture medium containing FBS were added to the lower chamber. After 24 h, migrated cells were stained with 0.1% crystal violet reagent solution (Beyotime, China) for 15 min and imaged with a microscope (Observer D1, Zeiss).</p>", "<title>Reverse transcription-quantitative PCR (RT-qPCR)</title>", "<p id=\"Par14\">The expression levels of TIPE1 mRNA were evaluated by RT-qPCR using beta-actin as the internal control following routine procedures. The following primer sequences were used for RT-qPCR: TIPE1 forward, 5’-GGACTTGGCCTCAGTTTTGC-3’, and reverse, 5’-GCCTTGGACGCCATCTTACT-3’; and beta-actin forward, 5’-TCACCATGGATGATGATATCGC-3’, and reverse, 5’-ATAGGAATCCTTCTGACCCATGC-3’.</p>", "<title>Western blot and immunofluorescence staining</title>", "<p id=\"Par15\">The proteins were extracted from indicated treated HUVECs using RIPA lysis buffer containing protease and phosphorylase inhibitors. Then equivalent proteins were separated by SDS-PAGE (sodium dodecyl sulfate polyacrylamide gels) and then transferred to a PVDF (polyvinylidene difluoride) membrane (Millipore, USA). After blocking, the membranes were incubated with TIPE1 antibody (ab85409, Abcam, USA) and then horseradish-peroxidase conjugated secondary antibodies. The membrane was detected using ECL (enhanced chemiluminescence) solution. Beta-ACTIN was used as the internal control.</p>", "<p id=\"Par16\">In immunofluorescence staining, cells were fixed, blocked with 30% goat serum, and incubated with TIPE1 antibody (CSB-PA837859LA01HU, CUSABIO, China). Following PBS washing, cells were incubated with secondary antibody Alexa Fluor 488-congugated AffiniPure Goat Anti-Rabbit IgG(H + L) and counterstained with DAPI. An Olympus optical microscope or confocal laser scanning microscopy was used to detect and analyze images.</p>", "<title>Analysis of cellular reactive oxygen species (ROS) levels</title>", "<p id=\"Par17\">Intracellular reactive oxygen species (ROS) production was quantified by a ROS assay kit (Beyotime, Shanghai, China). Treated HUVECs were incubated with media containing 10 µM DCFH-DA at 37 °C for 15 min. DCFH-DA is converted into dichlorodihydrofluorescein (DCFH) by oxygen free radicals, showing green fluorescence, as imaged using fluorescence microscopy.</p>", "<title>Overexpression of TIPE1</title>", "<p id=\"Par18\">The overexpression plasmids of TIPE1 was constructed by Sangon (Shanghai, China). The vector was used as the negative control. Plasmids were transfected using Lipofectamine 3000 (Thermofisher, USA) according to the manufacture’s protocol.</p>", "<title>Cell apoptosis assay</title>", "<p id=\"Par19\">Apoptosis of HUVECs was quantified using the Annexin V-FITC/propidium iodide assay. Treated HUVECs were digested with 0.25% trypsin, stained with Annexin V-FITC and PI (Vazyme, Nanjing, China) following the manufacturer’s instructions and analysed by flow cytometry (Beckman Coulter, USA) and Kaluza software.</p>", "<title>Autophagy flux and transmission electron microscopy</title>", "<p id=\"Par20\">HUVECs were transfected with mCherry-GFP-LC3B using Lipofectamine 3000 (Thermofisher, USA). After 4 h, cells were incubated with different treated medium overnight. Later, cells were fixed with 4% paraformaldehyde, mounted on slides and analyzed by confocal laser scanning microscope.</p>", "<title>Statistics</title>", "<p id=\"Par21\">Three independent replicates were used to determine the mean and standard deviation. Data analysis and presentation were performed using IBM SPSS 22.0 software (New York, USA) and GraphPad Prism 8.0 (San Diego, CA, USA). Student’s <italic>t</italic> test was used to compare outcomes between two groups. For comparisons of three or more groups, one-way repeated measures (RM) analysis of variance (ANOVA) was performed. <italic>P</italic>-values of 0.05 constituted statistical significance. The association between TIPE1 mRNA and serum vitamin D level was performed using Pearson correlation analysis by GraphPad Prism 8.0.</p>" ]
[ "<title>Results</title>", "<title>Serum vitamin D level was lower in diabetes mellitus patients with microvascular complications</title>", "<p id=\"Par22\">The serum of 40 patients diagnosed with type 2 diabetes without complications and 40 patients diagnosed with type 2 diabetes with microvascular complications, including diabetic cardiomyopathy, nephropathy, retinopathy, and peripheral neuropathy, was collected in a random manner. The clinical information of the patients was recorded in Table ##TAB##0##1##. The measurement of vitamin D level was conducted using routine chemiluminescence enzyme immunoassay. The findings indicated a significant decrease in serum vitamin D level among diabetes mellitus patients with microvascular complications in comparison to those without complications, as illustrated in Fig. ##FIG##0##1##. Based on this phenomenon, it is postulated that a diminished level of serum vitamin D may be linked to the occurrence of microvascular complications in individuals with diabetes mellitus. Consequently, our objective is to investigate the impact and mechanism of vitamin D under conditions of elevated glucose by employing HUVEC cell lines.</p>", "<p id=\"Par23\">\n\n</p>", "<p id=\"Par24\">\n</p>", "<title>Vitamin D reduced cell apoptosis and increased the migration and viability of endothelial cells treated with high glucose</title>", "<p id=\"Par25\">Previous studies have demonstrated that the administration of glucose at a concentration of 35 mM induces notable cytotoxic effects [##REF##18569938##11##–##REF##34989299##14##]. Consequently, we subjected human umbilical vein endothelial cells (HUVECs) to a 12-hour treatment with 35 mM high glucose to simulate the exposure of endothelial cells to hyperglycemia. In the G + VD (Glucose + vitamin D) group, HUVECs were pretreated with 35 mM glucose for 12 h, followed by the addition of 100 nM vitamin D in the culture medium for 24 h. The used concentration of 100 nM vitamin D was previously reported to protect the high glucose induced injury [##REF##16549374##15##, ##REF##25616003##16##]. The TUNEL assay demonstrated that vitamin D reduced apoptosis levels in the presence of high glucose at both 24 and 48 h (Fig. ##FIG##1##2##A). Additionally, transwell migration analysis indicated that vitamin D promoted cell migration (Fig. ##FIG##1##2##B) and enhanced cell viability (Fig. ##FIG##1##2##C) in HUVECs exposed to high glucose.</p>", "<p id=\"Par26\">\n\n</p>", "<title>Vitamin D reduced the protein expression of TIPE1 under high glucose conditions in HUVECs</title>", "<p id=\"Par27\">To investigate the downstream gene of vitamin D in the context of high glucose conditions, our focus was on TIPE1 (tumor necrosis factor α-induced protein 8-like 1, TNFAIP8L-1).</p>", "<p id=\"Par28\">TIPE1, a member of the TNFAIP8 family, has been reported to play a crucial role in various cellular processes including cell death, inflammation, endothelial dysfunction, and atherosclerosis [##REF##31672550##10##]. Notably, our experimental findings using western blot and immunofluorescence analysis demonstrated that vitamin D treatment resulted in a reduction in the protein expression of TIPE1 under high glucose conditions (Fig. ##FIG##2##3##A and B).</p>", "<p id=\"Par29\">\n\n</p>", "<title>Overexpression of TIPE1 reverses the effects of vitamin D under high glucose conditions by increasing ROS production, inflammation, cell apoptosis, and suppressing autophagy, cell migration and viability</title>", "<p id=\"Par30\">Subsequently, we investigated whether the overexpression of TIPE1 could counteract the effects of vitamin D. Our results showed that compared to the glucose treatment group, vitamin D treatment led to a decrease in reactive oxygen species (ROS) production. However, the overexpression of TIPE1 reversed the effects of vitamin D under high glucose conditions by increasing ROS levels (Fig. ##FIG##3##4##A).</p>", "<p id=\"Par31\">\n\n</p>", "<p id=\"Par32\">In this study, the analysis of autophagy flux demonstrated that the overexpression of TIPE1 resulted in a suppression of autophagy flux compared to the vitamin D group under high-glucose conditions (Fig. ##FIG##3##4##B). Additionally, the utilization of transmission electron microscopy revealed that the overexpression of TIPE1 led to a reduction in autophagosome formation compared to the vitamin D group under high-glucose conditions (Fig. ##FIG##3##4##C).</p>", "<p id=\"Par33\">Furthermore, the overexpression of TIPE1 exhibited a reversal of the effects induced by vitamin D under high glucose conditions, as evidenced by the inhibition of cell migration (Fig. ##FIG##4##5##A), the enhancement of cell apoptosis (Fig. ##FIG##4##5##B), the decrease in cell viability (Fig. ##FIG##4##5##C), and the promotion of inflammation (Fig. ##FIG##4##5##D). The upregulation of ET-1 and downregulation of NO were observed when TIPE1 was overexpressed in the presence of vitamin D supplementation (Fig. ##FIG##4##5##E). Additionally, treatment with vitamin D resulted in decreased expression levels of TIPE1 and reduced secretion of the inflammatory cytokine IL-6 in HUVECs exposed to high-glucose conditions.</p>", "<p id=\"Par34\">\n\n</p>", "<title>Serum vitamin D level was negatively associated with TIPE1 level in type 2 diabetes patients</title>", "<p id=\"Par35\">In order to investigate the potential correlation between TIPE1 expression and vitamin D levels in patients, RT-qPCR was performed using serum samples from the same recruited patients depicted in Fig. ##FIG##0##1##. The findings of this study indicate that the relative TIPE1 mRNA expression was significantly elevated in diabetes mellitus patients with microvascular complications in comparison to those without complications, as depicted in Fig. ##FIG##5##6##A. Pearson correlation analysis revealed a negative correlation between TIPE1 mRNA level and serum vitamin D level in patients with diabetes mellitus (Fig. ##FIG##5##6##B).</p>", "<p id=\"Par36\">\n\n</p>", "<p id=\"Par37\">We subsequently endeavor to elucidate the underlying mechanism by which vitamin D influences the expression of TIPE1. Typically, vitamin D engages with the Vitamin D receptor (VDR) to initiate VDR signaling. To accomplish this, we retrieve the 1000 bp upstream promoter sequences of TIPE1 from the ensemble website (Fig. ##FIG##5##6##C) and employ the JASPAR website to scan for potential binding sites of VDR on these promoters. The findings reveal the presence of 12 putative VDR binding sites on the TIPE1 promoter (Fig. ##FIG##5##6##D).</p>", "<p id=\"Par38\">According to the report, TIPE1 exhibits a negative correlation with Rac1 and inhibits various pathways including JNK and NF-kB, cyclin D1/B1, and MMP−2/9. Additionally, TIPE1 upregulates Bax, Bik, Puma, and caspase−8/3, leading to apoptosis and reduced cell growth [##REF##29920292##17##]. Furthermore, TIPE1 disrupts PHB2 mediated mitophagy [##REF##35152003##18##]. Based on these findings, we propose a potential mechanism whereby vitamin D inhibits TIPE1 expression by binding with VDR and recruiting transcriptional repressors to the TIPE1 promoter. TIPE1 exerts its influence on various downstream signaling molecules, including Rac1, JNK, NF-kB, Cyclin D1/B1, MMP-2/9, Bax, Bik, Puma, and Caspase-8/3, thereby modulating the functions of HUVECs in the presence of elevated glucose levels (Fig. ##FIG##5##6##E).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par39\">In recent decades, research has demonstrated the impact of vitamin D deficiency on glucose metabolism, insulin secretion, and the development of type 2 diabetes [##REF##23613602##19##]. Notably, a substantial proportion of individuals with type 2 diabetes exhibit a deficiency in vitamin D [##REF##33745601##20##]. Our study has revealed a significant reduction in serum vitamin D levels among individuals with type 2 diabetes who experience microvascular complications, as compared to those without such complications. This finding suggests a potential association between vitamin D deficiency and the occurrence of microvascular complications in patients with type 2 diabetes.</p>", "<p id=\"Par40\">Recent research indicates that the impact of elevated glucose levels on endothelial cells plays a significant role in the manifestation of clinical complications related to diabetic mellitus [##REF##32398868##21##, ##REF##17924861##22##]. The exposure of human umbilical vein endothelial cells (HUVECs) to high glucose levels results in an upregulation of the ET−1 gene expression and a decrease in cell viability [##REF##37139232##23##]. Furthermore, the induction of apoptosis in vascular endothelial cells is heightened under high glucose conditions [##REF##37009154##24##]. Notably, the administration of vitamin D treatment demonstrates promising outcomes in terms of enhancing cell viability, reducing mitochondrial reactive oxygen species (ROS) production, and suppressing mitophagy and inflammation in the presence of high glucose and particulate matter [##REF##35351169##25##]. The study revealed that elevated glucose levels had a detrimental effect on the viability of HUVEC cells, leading to increased production of reactive oxygen species (ROS) and apoptosis, as well as a decrease in nitric oxide (NO) generation. Consequently, there was a reduction in the levels of antioxidant enzymes and an increase in proinflammatory cytokines. However, the detrimental impact of high glucose-induced endothelial oxidative injury was mitigated by the administration of 1,25(OH)2D3, which resulted in the upregulation of the Nrf2 antioxidant pathway [##REF##33946068##26##]. In our investigation, vitamin D demonstrated a capacity to decrease cell apoptosis and enhance the migration and viability of endothelial cells exposed to high glucose.</p>", "<p id=\"Par41\">The potential mechanisms underlying the effects of vitamin D on diabetes-related complications may involve its antioxidant, anti-inflammatory, and immune modulatory properties [##REF##29951596##27##]. In the present study, we observed that vitamin D supplementation mitigated the damage to human umbilical vein endothelial cells (HUVECs) induced by type 2 diabetes mellitus, likely through the down-regulation of TIPE1. TIPE1 has been implicated in various cellular processes such as survival, migration, necroptosis, apoptosis, and autophagy [##REF##32588529##28##–##REF##33895911##30##]. Furthermore, it has been found to be upregulated in tubular epithelial cells of patients with diabetic nephropathy [##REF##35152003##18##]. In vascular endothelial cells, the up-regulation of TIPE1 resulted in an increase in reactive oxygen species (ROS)-induced oxidative stress, leading to apoptotic cell death and the progression of atherosclerosis [##REF##31672550##10##]. Additionally, the overexpression of TIPE1 reduced the levels of pAMPK and LC3B, thereby inhibiting autophagy in nasopharyngeal carcinoma cells [##REF##32588529##28##]. Furthermore, the upregulation of TIPE1 in renal tubular epithelial cells in a high glucose environment disrupted mitophagy and facilitated the advancement of diabetic nephropathy [##REF##35152003##18##]. In this study, we discovered that the overexpression of TIPE1 counteracted the effects of vitamin D on injury induced by high glucose in HUVECs.</p>", "<p id=\"Par42\">Vitamin D supplementation has the potential to serve as a treatment for diabetes-related periodontitis by reducing oxidative stress and inflammation through the upregulation of Nrf2 signaling [##REF##37021258##31##]. Ampelopsin has been found to protect endothelial cells from oxidative damage caused by hyperglycemia by inducing autophagy through the AMPK signaling pathway [##REF##26644014##32##]. On the other hand, metformin has been shown to alleviate endothelial impairment resulting from hyperglycemia by downregulating autophagy through the Hedgehog pathway [##REF##30653446##33##]. These findings indicate that both the induction and downregulation of autophagy have the ability to reverse injury caused by hyperglycemia. The data presented in our study suggest that vitamin D has the potential to mitigate the oxidative damage to endothelial cells induced by hyperglycemia through the induction of autophagy. In diabetic rats, the administration of vitamin D resulted in a reduction in ET−1 activity and an increase in NO levels [##REF##32233807##34##]. Consistent with this, our investigation using HUVECs exposed to high glucose conditions demonstrated that vitamin D supplementation led to a decrease in ET−1 levels and an increase in NO levels. Additionally, a comprehensive analysis of intervention studies indicated that vitamin D supplementation significantly reduced fasting blood sugar, hemoglobin A1c (HbA1c), insulin concentrations, and homeostatic model assessment for insulin resistance (HOMA-IR) [##REF##37072813##35##].</p>", "<p id=\"Par43\">A subsequent meta-analysis demonstrated that the administration of vitamin D supplements resulted in improved glycemic measures and enhanced insulin sensitivity, thereby potentially serving as a preventive measure against the development of type 2 diabetes [##REF##29951596##27##]. A comprehensive review and meta-analysis further confirmed that the supplementation of vitamin D led to an elevation in serum 25(OH)D levels and a reduction in insulin resistance. Notably, a substantial impact was observed when high doses of vitamin D were administered for a brief period, specifically targeting non-obese individuals of Middle Eastern descent who exhibited vitamin D deficiency or patients with optimal glycemic control at the outset [##REF##29562681##36##]. Paricalcitol, a vitamin D analogue, was found to provide protection against hydrogen peroxide-induced injury in HUVEC by suppressing apoptosis [##REF##36373746##37##]. In this study, we observed that the combination of vitamin D supplementation and insulin treatment resulted in improved diabetes biomarkers in type 2 patients with microvascular complications.</p>", "<p id=\"Par44\">Collectively, our investigation revealed a diminished presence of serum vitamin D in individuals diagnosed with type 2 diabetes mellitus and exhibiting microvascular complications. Additionally, the administration of vitamin D supplements counteracted the detrimental impact of elevated glucose levels on human umbilical vein endothelial cells (HUVECs) by mitigating the expression of TIPE1 protein. Consequently, it can be inferred that vitamin D supplementation holds potential benefits for individuals with type 2 diabetes mellitus and microvascular complications.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Diabetes mellitus (DM) and its associated vascular complications have become a worldwide health concern. The effects and mechanism of vitamin D supplementation on endothelial function under high glucose condition remain elusive.</p>", "<title>Methods</title>", "<p id=\"Par2\">Human umbilical vein endothelial cells (HUVECs) were treated with 35 mM glucose, then 100 nM vitamin D were added. Transwell migration assay, CCK-8, immunofluorescence, flow cytometry, autophagy flux and transmission electric microscope were performed.</p>", "<title>Results</title>", "<p id=\"Par3\">Vitamin D reduced apoptosis, promoted migration and enhanced viability of HUVECs, decreased TIPE1 (Tumor necrosis factor-α-induced protein 8-like 1) under high glucose conditions. Overexpression of TIPE1 reverses the effects of vitamin D by increasing ROS production, inflammation, cell apoptosis, and suppressing autophagy, cell migration and viability. And vitamin D negatively correlated with TIPE1 mRNA level in DM patients.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Vitamin D reverses the harmful effects of high glucose on HUVECs by reducing TIPE1 expression. And vitamin D supplementation could help to alleviate high glucose-induced injury in type 2 diabetes mellitus patients with microvascular complications.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>None.</p>", "<title>Author contributions</title>", "<p>Conceptualization: Zhoujun Liu; Formal Analysis: Haogang Sun, Yu Chen and Jia He; Investigation: Zhoujun Liu, Haogang Sun; Methodology: Lin Zhu, Bing Yang and Wenzhuo Zhao; Writing-Original Draft Preparation: Haogang Sun; Writing-Review and Editing: Zhoujun Liu.</p>", "<title>Funding</title>", "<p>This study was supported by the Youth Fund Project of the First Affiliated Hospital of Shihezi University (QN202220).</p>", "<title>Data availability</title>", "<p>The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par45\">The Ethics Committee of Suzhou Wuzhong People’s Hospital (KJ-2023-022-01) granted approval for this study. Prior to their participation, all patients were provided with information regarding the objective, content, and significance of the study. Informed consent forms were signed by all patients.</p>", "<title>Consent for publication</title>", "<p id=\"Par46\">All authors gave their consent for publication.</p>", "<title>Competing interests</title>", "<p id=\"Par47\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Vitamin D level is significantly lower in type 2 diabetes mellitus patients with microvascular complications. DM without C, diabetes mellitus patients without complications; DM with C, diabetes mellitus patients with microvascular complications. *<italic>P</italic>&lt;0.05</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>?Vitamin D inhibits cell apoptosis, promotes cell migration and viability in human umbilical vein endothelial cells treated by high glucose. (<bold>A</bold>) Cell apoptosis level was detected by TUNEL. (<bold>B</bold>) Cell migration was tested by Transwell assay. (<bold>C</bold>) Cell viability was analysed by CCK-8 assay. Ctrl, a normal concentration of glucose (5.6 mM); G, high glucose treatment; G+VD, high glucose plus vitamin D treatment. **<italic>P</italic>&lt;0.01</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Vitamin D represses the expression of TIPE1 in human umbilical vein endothelial cells treated by high glucose. (<bold>A</bold>) TIPE1 protein expression was checked by Western blot. (<bold>B</bold>) TIPE1 protein expression was determined by immunofluorescence. Ctrl, a normal concentration of glucose (5.6 mM); G, high glucose treatment; G+VD, high glucose plus vitamin D treatment. **<italic>P</italic>&lt;0.01</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>?Overexpression of TIPE1 reverses the effects of Vitamin D in ROS and autophagy in human umbilical vein endothelial cells treated by high glucose. (<bold>A</bold>) ROS level was detected by DCFH-DA. (<bold>B</bold>) Autophagy flux was tested by mCherry-GFP-LC3B assay. (<bold>C</bold>) Transmission microscope was performed to check the autophagosome. Ctrl, a normal concentration of glucose (5.6 mM); G, high glucose treatment; G+VD, high glucose plus vitamin D treatment; G+VD+pc-NC, high glucose plus vitamin D treatment as well as pc-NC transfection; G+VD+pc-TIPE1, high glucose plus vitamin D treatment as well as pc-TIPE1 transfection. *<italic>P</italic>&lt;0.05, **<italic>P</italic>&lt;0.01</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>?Overexpression of TIPE1 reverses the effects of Vitamin D in apoptosis, migration and viability in human umbilical vein endothelial cells treated by high glucose. (<bold>A</bold>) Cell migration was tested by Transwell assay. (<bold>B</bold>) Cell apoptosis level was detected by flowcytometry. (<bold>C</bold>) Cell viability was analysed by CCK-8 assay. (<bold>D</bold>) ELISA was used to determine the level of inflammatory cytokines, (<bold>E</bold>) ELISA was used to test the level of ET-1 and NO. Ctrl, a normal concentration of glucose (5.6 mM); G, high glucose treatment; G+VD, high glucose plus vitamin D treatment; G+VD+pc-NC, high glucose plus vitamin D treatment as well as pc-NC transfection; G+VD+pc-TIPE1, high glucose plus vitamin D treatment as well as pc-TIPE1 transfection. *<italic>P</italic>&lt;0.05, **<italic>P</italic>&lt;0.01</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>?Serum vitamin D level was negatively associated with TIPE1 level in type 2 diabetes patients. (<bold>A</bold>) Relative mRNA level of TIPE1 was detected in type 2 diabetes mellitus patients with or without microvascular complications by RT-qPCR. (<bold>B</bold>) Pearson correlation analysis of the mRNA expression of TIPE1 and serum vitamin D level in type 2 diabetes mellitus patients with or without microvascular complications. (<bold>C</bold>) The 1000 bp upstream promoter sequences of TIPE1 from the Ensemble website. (<bold>D</bold>) Potential binding sites of VDR on 1000 bp upstream promoter sequences of TIPE1 from the JASPAR website. (<bold>E</bold>) Possible function mechanisms of vitamin D on TIPE1 expressions. *<italic>P</italic>&lt;0.05</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Clinical information of patients whose serum vitamin D level were detected</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Clinicopathologic features</th><th align=\"left\">DM without C</th><th align=\"left\">DM with C</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\">Gender (female)</td><td align=\"left\">40 (22)</td><td align=\"left\">40 (26)</td><td align=\"left\">0.49</td></tr><tr><td align=\"left\">Age (years)</td><td align=\"left\">54.37 ± 2.82</td><td align=\"left\">54.85 ± 2.46</td><td align=\"left\">0.42</td></tr><tr><td align=\"left\">BMI (body mass index)</td><td align=\"left\">31.88 ± 1.86</td><td align=\"left\">32.85 ± 1.90</td><td align=\"left\">0.02</td></tr><tr><td align=\"left\">Waist circumference (cm)</td><td align=\"left\">117.31 ± 7.77</td><td align=\"left\">122.51 ± 7.56</td><td align=\"left\">0.003</td></tr><tr><td align=\"left\">Serum vitamin D level (nM)</td><td align=\"left\">56.05 ± 12.80</td><td align=\"left\">49.09 ± 12.60</td><td align=\"left\">0.016</td></tr><tr><td align=\"left\">Diabetic cardiomyopathy (cases)</td><td align=\"left\"/><td align=\"left\">9</td><td align=\"left\"/></tr><tr><td align=\"left\">Diabetic nephropathy (cases)</td><td align=\"left\"/><td align=\"left\">8</td><td align=\"left\"/></tr><tr><td align=\"left\">Diabetic retinopathy (cases)</td><td align=\"left\"/><td align=\"left\">8</td><td align=\"left\"/></tr><tr><td align=\"left\">Diabetic peripheral neuropathy (cases)</td><td align=\"left\"/><td align=\"left\">15</td><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>DM without C, diabetes mellitus patients without complications; DM with C, diabetes mellitus patients with microvascular complications</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Zhoujun Liu and Haogang Sun contributed equally to this work.</p></fn></fn-group>" ]
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[{"label": ["3."], "mixed-citation": ["Jia W, et al. Standards of medical care for type 2 diabetes in China 2019. Diabetes Metab Res Rev. 2019;35(6):e3158."]}]
{ "acronym": [], "definition": [] }
37
CC BY
no
2024-01-14 23:43:46
Diabetol Metab Syndr. 2024 Jan 13; 16:18
oa_package/12/c1/PMC10787437.tar.gz
PMC10787438
38216881
[ "<title>Introduction</title>", "<p id=\"Par5\">Compared with surgical treatment, conservative treatment (foot orthoses and minimalist running interventions) can better restore the biomechanical gait function o in hallux valgus (HV) patients [##REF##35247827##1##], but for cases with obvious symptoms or even transfer metatarsalgia, non-surgical or exercise intervention may not be appropriate [##REF##35063832##2##–##REF##30558948##5##]. Medium to serious hallux valgus abnormity is considered as hallux valgus angle (HVA) over 30 degrees or 1st-2nd-intermetatarsal angle (IMA) over 13 degrees [##UREF##0##6##]. Currently, there are many bone surgeries to treat HV, including open surgeries such as Chevron osteotomy, Scarf osteotomy or Lapidus surgery and minimally invasive surgeries such as Reverdin-Isham osteotomy [##REF##27919259##7##], Intramedullary Nail Device surgery [##REF##33319594##8##]. The above surgical techniques have all achieved satisfactory results, but which technique has the best results has yet to be determined [##REF##34024185##9##]. Scarf osteotomy is the most commonly performed diaphyseal osteotomy for the correction of medium or serious HV and gained a good reputation [##REF##31200616##10##–##REF##36092172##13##].</p>", "<p id=\"Par6\">In TSO, the IMA is reduced by shifting the plantar metatarsal osteotomy bone segment laterally to increase the load on the first metatarsal row [##REF##31997740##14##, ##REF##31653368##15##], and the dorsal metatarsal osteotomy bone segment is shifted medially to correct metatarsal varus [##REF##24878407##16##]. This procedure lengthens or shortens the first metatarsal, and its osteotomy stability allows the patient to bear weight early and return to activity [##REF##31980384##17##, ##REF##35822335##18##]. However, TSO has its own disadvantages [##REF##20976578##19##–##REF##30417612##21##]. The correction capability of this procedure is mainly limited by the width of the metatarsal diaphysis, i.e. the wider the diameter of metatarsal diaphysis, the greater the moving distance and the greater the correction on IMA. Because TSO moves the bone fragments transversely instead of rotating them, the postoperative IMA, DMAA (distal metatarsal articular angle) changes were limited [##REF##29729793##22##]. In addition, the contact between the cortical bone and the cancellous bone after the displacement of the bone fragment makes the cortical bone insert into the cancellous bone in later postoperative term, thus the “troughing effect” [##REF##20976578##19##, ##REF##28479160##23##, ##REF##20706810##24##], which is a common complication by TSO.</p>", "<p id=\"Par7\">Compared with the TSO, the MRSO retains the Z-shape of the osteotomy and applies a rotational movement (Fig. ##FIG##0##1##) instead of lateral movement of the osteotomy shaft, which has been reported to reduce the occurrence of the troughing effect and improve the IMA to a greater extent [##REF##20976578##19##]. Meanwhile, the relevant conclusions need to be further demonstrated. Therefore, the objective of this backward-looking clinic trial was to investigate whether MRSO would improve the outcomes compared with TSO.</p>", "<p id=\"Par8\">\n\n</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par9\">This clinic trial was permitted by the Ethics Panel of our hospital. All patients included in this randomized controlled trial signed the declaration of agreement. From March 2017 to March 2021, 175 patients (247 feet) with MSHV were underwent surgery and were retrospectively evaluated. All procedures were executed by the same senior orthopedic specialist experienced in foot surgery.</p>", "<title>Patient eligibility</title>", "<p id=\"Par10\">Eligible patients were diagnosed as MSHV (HVA &gt; 30° or IMA &gt; 13°) and all of them initially received conservative treatment for over six months. Surgical intervention should only be considered if the patient has failed to respond to conservative treatment for no less than six months. Patients with neurovascular defects, active local infection, previous history of foot and ankle surgery, musculoskeletal inflammatory diseases (gout, rheumatism, etc.) were excluded from the study. Any concomitant surgery on first tarsal metatarsal joint or the lesser metatarsal was excluded. However, procedures performed to the lesser phalanges were not excluding factors. Patients receiving MRSO procedure were assigned to MRSO group or patients receiving TSO procedure were assigned to TSO group, and both were tracked for twenty-four months.</p>", "<title>Modified rotary scarf osteotomy operative technique</title>", "<title>Positioning and application of tourniquet</title>", "<p id=\"Par11\">The patient was set in dorsal recumbent position under spinal anesthesia, the drape was sterilized, and a tourniquet was applied on the upper 1/3 of the thigh after the blood was expelled.</p>", "<title>Incision and osteophyte removal</title>", "<p id=\"Par12\">A long longitudinal incision was made on the medial side of the MTT-1 (first metatarsal). Subcutaneous tissue was cut in to expose the joint capsule, then an “L”-shaped incision was made to expose the MTP-1 (first metatarsophalangeal) joint. The sagittal saw was used to remove the medial osteophyte of the MTT-1 head.</p>", "<title>“Z”-shaped osteotomy and two proximal osteotomy line</title>", "<p id=\"Par13\">A transverse osteotomy line (first proximal osteotomy line) was marked on the plantar side of the MTT-1 bone 5 mm distal to the tarsometatarsal joint. A “Z”-shaped osteotomy was performed with a micro pendulum saw as in traditional Scarf osteotomy (Fig. ##FIG##1##2##a), and then the second proximal osteotomy line (an additional oblique osteotomy line) was made from the outer boundary to the inner boundary of the MTT-1 bone (Fig. ##FIG##1##2##b), forming a “wedge-shaped bone piece”, which was removed for later use (Fig. ##FIG##1##2##d).</p>", "<p id=\"Par14\">\n\n</p>", "<title>Rotation and filling</title>", "<p id=\"Par15\">After the osteotomy is completed, the lateral joint capsule was loosened with a sharp knife through the metatarsal shafts. The center of rotation of angulation (CORA) (i.e., the point where the two proximal osteotomy lines intersect) [##REF##30505417##25##] was used as the fulcrum to rotate plantar shaft to bring the first and second proximal osteotomy lines together. When the metatarsal osteotomy shafts were rotated, a small wedge-shaped gap area appeared on the dorsal medial side of the distal metatarsal, which was filled by the spare wedge-shaped bone piece described above.</p>", "<title>Fixion</title>", "<p id=\"Par16\">After the rotation and filling was completed, 1–2 guide pins were inserted to maintain the reduction (Fig. ##FIG##1##2##e). Next, 1 or 2 hollow compression screws were fixed through the guide pins which was satisfactory under fluoroscopy (Fig. ##FIG##1##2##c).</p>", "<title>Removing excess bone and filling again</title>", "<p id=\"Par17\">The medial excess bone was removed by micro-oscillating saw to make the medial edge tidy, and above-mentioned “wedge-shaped bone piece” was filled into the groove formed by the distal osteotomy surface after rotation.</p>", "<title>Additional Akin osteotomy</title>", "<p id=\"Par18\">Finally, Akin osteotomy was performed in the first proximal phalange bone to improve the first ray alignment [##REF##31200616##10##, ##REF##33596196##26##].</p>", "<title>Postoperative treatment</title>", "<p id=\"Par19\">After the suturing is completed, a loosely wrapped bandage is used to isolate between the 1st and 2nd toes to achieve a slight varus of the toes. Cotton pads and elastic bandages are used for dressing without external fixation with plaster or braces. On the 2nd day after the operation, patients can wear the forefoot decompression shoes and walk with weight on the ground. The walking time is determined according to the wound condition, and the stitches are removed 2 weeks after the operation. From 2 days to 4 or 6 weeks after surgery, the forefoot decompression shoes were worn to walk with weight on the ground to meet the basic needs of daily life. X-ray films were re-examined 1 month after the operation to observe the healing of the osteotomy to decide when to wear normal shoes for activities and systematic rehabilitation training.</p>", "<title>Observation index and curative effect evaluation</title>", "<p id=\"Par20\">After the operation, the patients were followed up in the outpatient clinic, the clinical curative effect was evaluated, and the occurrence of complications was recorded. Basic data including age, gender, Body Mass Index (BMI) and Visual Analogue Scale (VAS) were gathered. Before operation, after operation, six, twelve, and twenty-four months post-surgically anteroposterior and lateral X-ray films of the affected foot were taken, and single person used the same method to accurately measure the position of HVA, IMA, DMAA, MTP-1 ROM (first metatarsophalangeal joint range of motion), AOFAS score and tibial sesamoid (the location of the tibial sesamoid is divided into 7 grades from the tibial border of the metatarsal head neck to the fibular border, 1–4 is normal, and 5–7 is abnormal) [##UREF##1##27##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par21\">Via GraphPad Prism7.0, all statistical analyzes were carried out by an independent statistician. Continuous variables are presented as mean ± standard deviation (SD), and categorical variables (tibial sesamoid, occurrence of complications) are presented numerically. Pre-surgical and post-surgical measurements were compared using a paired-sample t-test. P &lt; 0.05 was regarded as significant difference.</p>" ]
[ "<title>Result</title>", "<p id=\"Par22\">In this study, 100 patients treated with MRSO (138 feet) and 75 patients treated with TSO (109 feet) participated. Both cohorts shared the same baseline characteristics, including mean age (56.66 ± 1.3 and 48.24 ± 1.3 years, p = 0.1386), sex distribution (male: female, n, 13:87 and 11:64, p = 0.7511), BMI (kg/m<sup>2</sup>, 27.2 ± 4.1 and 28.7 ± 4.9, p = 0.4174) and mean VAS pain scores (88.1 and 91.6, p = 0.3959) (Table ##TAB##0##1##). Patients in the MRSO group had significantly lower IMA and higher DMAA at six months (both p &lt; 0.0001), twelve months (both p &lt; 0.0001) and twenty-four months (both p &lt; 0.0001) after surgery compared to TSO group. Patients in the MRSO group had significantly lower Sesamoid grade at six months (p = 0.0171), twelve months (p = 0.0397) and twenty-four months (p = 0.0334) after surgery compared to TSO group. HVA, MTP-1 ROM and AOFAS data at each follow-up time point post-surgically in MRSO group had no significant difference compared to TSO group. Osteotomy healing within 8 weeks was observed in both groups. 4 cases of troughing and 3 cases of hallus varus were observed in TSO group, however delayed healing and non-union complications were not found in both groups (Table ##TAB##1##2##). A typical case is shown in Fig. ##FIG##2##3##.</p>", "<p id=\"Par23\">\n\n</p>", "<p id=\"Par24\">\n\n</p>", "<p id=\"Par25\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par26\">The principal contribution of this clinic trial is that both MRSO and TSO surgery showed the similarly good clinical outcome in terms of HVA, AOFAS score and MTP-1 ROM. Whereas, as seen on the aspect of IMA and sesamoid grade, the MRSO procedure produced remarkably superior radiographic outcomes.</p>", "<p id=\"Par27\">Weil and Borrelli named the Z-shaped MTT-1 osteotomy as the Scarf osteotomy [##REF##34024185##9##, ##REF##31679523##28##] when they studied local vascularization, modified osteotomy, and increased osteotomy length [##REF##24685190##29##]. In the end, Barouk promoted the technology worldwide, especially in Europe [##REF##34024185##9##]. Traditional Scarf osteotomy reduces the IMA and restores the load of the first metatarsal alignment by shifting the plantar osteotomy bone fragment laterally and shifting the dorsal metatarsal osteotomy bone fragment medially [##REF##31881881##30##, ##REF##31103839##31##]. Internal fixation occupies the width of the metatarsal shaft, which makes the movement of bone shafts limited, resulting in limited ability to correct deformities, so that it is suitable for mild to moderate deformities instead of severe deformity. Furthermore, its common postoperative complications are troughing effect [##REF##37097272##32##], in addition to transfer metatarsalgia, undercorrection or recurrence, overcorrection, varus, degenerative arthritis, unstable fixation, and delayed union [##REF##32891491##33##, ##REF##31663288##34##].</p>", "<p id=\"Par28\">The modified rotary Scarf osteotomy uses CORA as the fulcrum to rotate the shaft outward, moving the IMA along the X-axis, raising or sinking the first metatarsal head along the Y-axis, and lengthening or shortening the length of the metatarsal along the Z-axis [##REF##29729798##35##]. Meanwhile, the CORA of the rotational Scarf osteotomy is closer to the proximal end compared to the translational Scarf osteotomy, resulting in a better ability to correct IMA, DMAA [##REF##28405709##36##] (Fig. ##FIG##3##4##). Because of the existence of the wedge-shaped osteotomy, no matter whether the length of the metatarsal is shortened or lengthened, the proximal end of the metatarsal tends to be complete (keep alignment between bone fragments), and the total overlapping area of the osteotomy surface is larger, which makes the biomechanics more stable and the healing speed faster [##UREF##2##37##]. We choose to make two osteotomy lines on the plantar side of the proximal MTT-1 to produce a wedge-shaped bone piece, instead of producing that on the dorsal side of the distal MTT-1, which could result in necrosis or subsidence of the metatarsal head and arthritis of the first metatarsophalangeal [##UREF##3##38##].</p>", "<p id=\"Par29\">\n\n</p>", "<p id=\"Par30\">Establishing X/Y/Z three-axis surgical planning based on foot weight-bearing X-ray films and three-dimensional CT before operation can make the position and degree of MRSO more accurate. According to the establishment of the preoperative Y/Z axis and forefoot metatarsalgia condition, the position of the metatarsal head can be restored during the operation by adjusting the osteotomy direction such as plantarward or dorsarward, inward or outward [##REF##31980384##17##], and the condition of the flat foot or high arch can also be improved [##REF##24878407##16##, ##UREF##4##39##]. Because of the proximal wedge osteotomy and the determination of CORA, this type of operation is flexible, and the three-dimensional adjustment of the metatarsal bone can be performed up and down, forward and backward, and inward and outward. Besides, the “gap area” left by the wedge-shaped osteotomy leaves more buffer for the rotation of the metatarsals during the operation, which could ensure the curative effect.</p>", "<p id=\"Par31\">The long osteotomy line of the metatarsal diaphysis in MRSO can be extended to nearly the full length of the metatarsal bone (Fig. ##FIG##2##3##). Its longer osteotomy line than TSO gives it greater ability to correct deformities. The distal osteotomy line of the MRSO is carried out in the cancellous bone of the metaphysis. As stated in other studies, troughing can be prevented by placing resected cortical bone between the gap sites created by osteotomy [##REF##20976578##19##, ##REF##31630676##40##]. The distal osteotomy line of the MRSO is carried out in the metaphyseal cancellous bone and the “gap” (the dorsal medial side of the distal metatarsal after rotation) was filled by the spare wedge-shaped bone piece, so that the cortical bone at the osteotomy end could be pressed each other to form a “lock” after rotation, which can effectively prevent the troughing effect once the osteotomy is displaced [##REF##20496024##41##]. Meanwhile, the “lock” structure, could ensures the stability after osteotomy. In MRSO group, the distal end of the osteotomy line was about 20 mm from the metatarsophalangeal joint surface; the proximal end was about 5 mm from the tarsometatarsal joint, which ensured the length and stability of the osteotomy shaft. There was no “troughing effect” in this group throughout the follow-up.</p>", "<p id=\"Par32\">In order to achieve better radiological performance, all the MRSO operations were combined with Akin osteotomy for the medium to serious hallux valgus in the MRSO group. The application of Akin osteotomy is increasingly recognized [##REF##35513866##42##–##REF##33167697##45##]. Akin osteotomy can effectively improve the increase of HVA and effectively compensate for the metatarsal osteotomy, thus significantly improving the clinical efficacy and patient satisfaction rate, and fully making up for the shortcomings of rotary Scarf osteotomy in phalanx deformities [##REF##31200616##10##].</p>", "<p id=\"Par33\">MRSO could aid in the recovery of gait biomechanical function post-surgery for the more stable broken ends [##UREF##2##37##] in MRSO allows for more adequate recovery of foot muscle strength during postoperative functional exercises, thereby restoring normal gait. Although there was no statistical difference in the final AOFAS scores between the two groups, the MRSO group was slightly better at final follow-up.</p>", "<p id=\"Par34\">The strength of this study is that the institution to which this study belongs is the foot and ankle center of this city, thus sufficient eligible cases have been accumulated within 4 years. All surgeries in this study were performed by one single senior experienced surgeon who specialized in foot and ankle surgery. However, backward-looking clinic trial was a limitation in our study, and the planning and arrangement are not as detailed as forward-looking clinic trial. In this clinical trial, the standard deviation in the sample data regarding HV especially after surgery is large, and it is inevitable that the intra-observer reliability will decrease. Since data collection was completed by a single researcher, different researchers will be arranged to conduct measurements in future clinical work, and each of them will repeat the measurements multiple times to improve inter-observer and intra-observer reliability. Besides, more and more scholars pay attention to the impact of hypermobility of the first ray (HFR) and instability of the First Metatarsal-Cuneiform Joint (I-MTCJ) on HV [##REF##32555076##46##]. HV patients with similar HVA and IMA angles but different degrees of HFR and I-MTCJ may have different prognosis after the same rotational Scarf surgery. In view of this, our study lacked the evaluation of HFR and I-MTCJ, and we will take these two factors into consideration as observation indicators in future studies. After all, twenty-four months is a short period, and a longer follow-up period would certainly improve the usefulness of the study. In addition, the preoperative, postoperative, and follow-up clinical and radiographic data were evaluated by only one investigator.</p>", "<p id=\"Par35\">Above all, MRSO showed comparable results to TSO in terms of HVA, AOFAS and MTP-1 ROM, but MRSO showed significant advantages in improving IMA, sesamoid grade. In spite of aggravating the DMAA, MRSO can correct hallux valgus deformity in three dimensions, meets the ideal requirements of foot orthosis, and has a low complication rate.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par36\">In summary, MRSO showed comparable results to TSO, and improved IMA and sesamoid grade to a greater extent, with a lower probability of through effect. Despite the increase of DMAA, MRSO still is a reproducible, non-dangerous and efficacious alternative technique for HV treatment.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Traditional Scarf osteotomy (TSO) is an effective procedure with a good record in moderate to severe hallux valgus (MSHV) surgery. In order to overcome shortcomings of TSO, Modified Rotary Scarf osteotomy (MRSO) was introduced in this study, which aimed to compare the clinical and radiological outcome in the patients treated with MRSO or TSO.</p>", "<title>Methods</title>", "<p id=\"Par2\">Of 175 patients (247 feet) with MSHV, 100 patients (138 feet) treated with MRSO and 75 patients (109 feet) treated with TSO were evaluated according to relevant indicators in twenty-four months follow-up. Pre-surgical and post-surgical HVA, IMA, DMAA, MTP-1 ROM, sesamoid grade and AOFAS (American Orthopaedic Foot and Ankle Society) scores and postsurgical complications were evaluated.</p>", "<title>Results</title>", "<p id=\"Par3\">Both groups manifested similar baseline characters. The mean follow-up was of 25.9 (range, 22–37) months. Significantly lower IMA, lower Sesamoid grade and higher DMAA at six months, twelve months and twenty-four months post-surgically had been showed in MRSO group compared to TSO group. There was no significant difference in HVA, MTP-1 ROM and AOFAS data at each follow-up time point post-surgically between the two groups. No major complications occurred in either group.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">MRSO showed comparable results to TSO, and improved IMA and sesamoid grade to a greater extent, with a lower probability of throughing effect. Although DMAA could be increased by MRSO, MRSO could still be a reproducible, non-dangerous and efficacious alternative procedure for treating HV patients which do not have severe DMAA.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>The smooth completion of this work is thanks to the help of the library of Wuhan Forth Hospital.</p>", "<title>Author contributions</title>", "<p>ZL and WY participated in the design of the study; SL and KF carried out data curation; ZL drafted the manuscript. ZF supervised this study and refined the draft and gave several important suggestions. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>Not applicable.</p>", "<title>Data availability</title>", "<p>For data requests, please contact the author Fang Zhenhua.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par38\">This study was performed in accordance with the Declaration of Helsinki, and was approved by the Clinical Research Ethics Committee of Wuhan Puai Hospital. The reference number is KY2023-056-01. Each patient signed a written informed consent before the operation.</p>", "<title>Consent for publication</title>", "<p id=\"Par39\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par37\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Preoperative planning. (<bold>a</bold>) Determine the center of rotation based on the preoperative 3D CT, and establish the X/Y/Z three-axis for preoperative planning. (<bold>b</bold>) The IMA angle that can be achieved after the simulated osteotomy rotation</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Schematic diagram of modified rotary Scarf osteotomy. (<bold>a</bold>) Schematic diagram of medial osteotomy of modified rotary Scarf osteotomy. (<bold>b</bold>) Different from traditional Scarf osteotomy, a second oblique osteotomy line (dotted line in the figure) is added to form proximal wedge-shaped bone piece. (<bold>c</bold>) The wedge-shaped bone piece was taken out and then rotated and moved, and the hollow screw was placed for fixation. (<bold>d</bold>) Schematic diagram of the wedge-shaped bone piece. (<bold>e</bold>) X-ray film after modified rotary Scarf osteotomy and single screw fixation</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>A 47-year-old female patient with severe valgus of her right foot. She underwent surgery on March 5, 2019. Postoperative follow-up showed good squatting activities and no special discomfort. (<bold>a</bold>) Preoperative appearance. (<bold>b</bold>, <bold>c</bold>) Distal lateral rotation after proximal wedge osteotomy. (<bold>d</bold>, <bold>e</bold>) Removal of redundant osteophytes with pendulum saw after cannulated screw fixation (<bold>f</bold>) postoperative fluoroscopy shows obvious changes in HVA, IMA, and DMAA</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Radiological comparison between TSO and MRSO. (<bold>a</bold>–<bold>d</bold>) One person who received TSO, no significant changes in IMA and DMAA before and after operation. However, the HVA was increased one month after TSO, it relapsed four months after TSO. “<bold>a</bold>” represents pre-surgery; “<bold>b</bold>” represents post-surgery; “<bold>d</bold>” represents one month post-surgery; “<bold>d</bold>” represents six months post-surgery. (<bold>e</bold>–<bold>h</bold>) Another person who received MRSO, IMA and DMAA were obvious changed before and after surgery. “<bold>e</bold>” represents pre-surgery; “<bold>f</bold>” represents post-surgery; “<bold>g</bold>” represents one month post-surgery; “<bold>h</bold>” represents six months post-surgery. The osteotomy end heals faster in the person who received TSO compared to another person in TSO. Because of the “lock” structure that formed by the rotation in MRSO, single screw fixation does not affect its stability. Compared with double-screw fixation, the potential correction ability of single-screw is stronger, and its postoperative IMA and HVA are significantly changed</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Patient’s baseline characters</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">MRSO (n = 100)</th><th align=\"left\">TSO (n = 75)</th><th align=\"left\">P value</th></tr></thead><tbody><tr><td align=\"left\">Age, y, mean + SD</td><td align=\"left\">56.66 ± 1.3</td><td align=\"left\">48.24 ± 1.3</td><td char=\".\" align=\"char\">0.1386</td></tr><tr><td align=\"left\">Gender, male: female, n</td><td align=\"left\">13:87</td><td align=\"left\">11:64</td><td char=\".\" align=\"char\">0.7511</td></tr><tr><td align=\"left\">BMI, kg/m<sup>2</sup>, mean + SD</td><td align=\"left\">27.2 ± 4.1</td><td align=\"left\">28.7 ± 4.9</td><td char=\".\" align=\"char\">0.4174</td></tr><tr><td align=\"left\">VAS pain score (0–100), mean</td><td align=\"left\">88.1</td><td align=\"left\">91.6</td><td char=\".\" align=\"char\">0.3959</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Clinical and radiographic results</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">MRSO (138 feet)</th><th align=\"left\">TSO (109 feet)</th><th align=\"left\">P value</th><th align=\"left\">Test</th></tr></thead><tbody><tr><td align=\"left\">HVA before surgery</td><td align=\"left\">34.62 ± 0.68</td><td align=\"left\">33.65 ± 0.75</td><td align=\"left\">0.3420</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">HVA 6 months</td><td align=\"left\">3.17 ± 0.15</td><td align=\"left\">3.10 ± 0.14</td><td align=\"left\">0.5327</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">HVA 12 months</td><td align=\"left\">3.96 ± 0.11</td><td align=\"left\">4.23 ± 0.13</td><td align=\"left\">0.2234</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">HVA 24 months</td><td align=\"left\">4.18 ± 0.17</td><td align=\"left\">4.79 ± 0.14</td><td align=\"left\">0.1657</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">IMA before surgery</td><td align=\"left\">16.86 ± 1.59</td><td align=\"left\">17.01 ± 1.72</td><td align=\"left\">0.6882</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">IMA 6 months*</td><td align=\"left\">5.44 ± 0.08</td><td align=\"left\">8.29 ± 0.10</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">IMA 12 months*</td><td align=\"left\">5.02 ± 0.06</td><td align=\"left\">8.78 ± 0.08</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">IMA 24 months*</td><td align=\"left\">5.40 ± 0.07</td><td align=\"left\">9.06 ± 0.08</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">DMAA before surgery</td><td align=\"left\">20.08 ± 2.21</td><td align=\"left\">19.69 ± 2.66</td><td align=\"left\">0.6684</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">DMAA 6 months*</td><td align=\"left\">30.79 ± 2.44</td><td align=\"left\">17.33 ± 2.87</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">DMAA 12 months*</td><td align=\"left\">22.57 ± 2.19</td><td align=\"left\">16.78 ± 2.84</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">DMAA 24 months*</td><td align=\"left\">17.68 ± 2.47</td><td align=\"left\">13.07 ± 1.93</td><td align=\"left\">&lt; 0.0001</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (dorsiflexion) before surgery</td><td align=\"left\">68.68 ± 3.21</td><td align=\"left\">68.99 ± 3.44</td><td align=\"left\">0.4549</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (dorsiflexion) 6 months</td><td align=\"left\">69.32 ± 2.99</td><td align=\"left\">69.13 ± 2.74</td><td align=\"left\">0.4135</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (dorsiflexion) 12 months</td><td align=\"left\">71.56 ± 2.91</td><td align=\"left\">70.67 ± 2.67</td><td align=\"left\">0.3953</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (dorsiflexion) 24 months</td><td align=\"left\">73.43 ± 2.78</td><td align=\"left\">72.99 ± 3.03</td><td align=\"left\">0.3545</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (plantarflexion) before surgery</td><td align=\"left\">33.45 ± 3.03</td><td align=\"left\">33.95 ± 3.34</td><td align=\"left\">0.4657</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (plantarflexion) 6 months</td><td align=\"left\">35.51 ± 2.93</td><td align=\"left\">34.87 ± 3.25</td><td align=\"left\">0.3824</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (plantarflexion) 12 months</td><td align=\"left\">36.84 ± 2.98</td><td align=\"left\">36.03 ± 2.66</td><td align=\"left\">0.3392</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">MTP-1 ROM (plantarflexion) 24 months</td><td align=\"left\">37.65 ± 2.25</td><td align=\"left\">37.13 ± 3.04</td><td align=\"left\">0.2596</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">AOFAS before surgery</td><td align=\"left\">44.56 ± 3.54</td><td align=\"left\">44.01 ± 3.73</td><td align=\"left\">0.3264</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">AOFAS 6 months</td><td align=\"left\">77.43 ± 0.62</td><td align=\"left\">76.80 ± 0.83</td><td align=\"left\">0.1329</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">AOFAS 12 months</td><td align=\"left\">80.42 ± 1.79</td><td align=\"left\">81.04 ± 2.74</td><td align=\"left\">0.4023</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">AOFAS 24 months</td><td align=\"left\">80.34 ± 0.48</td><td align=\"left\">79.46 ± 0.84</td><td align=\"left\">0.1493</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">Sesamoid grade before surgery</td><td align=\"left\">2.43 ± 0.10</td><td align=\"left\">2.48 ± 0.09</td><td align=\"left\">0.3425</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">Sesamoid grade 6 months*</td><td align=\"left\">1.57 ± 0.05</td><td align=\"left\">2.08 ± 0.05</td><td align=\"left\">0.0171</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">Sesamoid grade 12 months*</td><td align=\"left\">1.45 ± 0.05</td><td align=\"left\">1.99 ± 0.05</td><td align=\"left\">0.0397</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">Sesamoid grade 24 months*</td><td align=\"left\">1.47 ± 0.06</td><td align=\"left\">2.01 ± 0.05</td><td align=\"left\">0.0334</td><td align=\"left\">Unpaired t test</td></tr><tr><td align=\"left\">Complication hallus varus</td><td align=\"left\">0</td><td align=\"left\">3</td><td align=\"left\">0.0886</td><td align=\"left\">Fisher’s exact test</td></tr><tr><td align=\"left\">Complication delayed healing</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\">Complication nonunion</td><td align=\"left\">0</td><td align=\"left\">0</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\">Complication troughing*</td><td align=\"left\">0</td><td align=\"left\">4</td><td align=\"left\">0.0399</td><td align=\"left\">Fisher’s exact test</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>Chi-square test was used to test gender</p></table-wrap-foot>", "<table-wrap-foot><p>100 patients treated with MRSO (138 feet) and 75 patients treated with TSO (109 feet)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Zi Li and Weiwei Yu contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12891_2023_7156_Fig1_HTML\" id=\"d32e276\"/>", "<graphic xlink:href=\"12891_2023_7156_Fig2_HTML\" id=\"d32e333\"/>", "<graphic xlink:href=\"12891_2023_7156_Fig3_HTML\" id=\"d32e870\"/>", "<graphic xlink:href=\"12891_2023_7156_Fig4_HTML\" id=\"d32e970\"/>" ]
[]
[{"label": ["6."], "mixed-citation": ["Kuhn J, Alvi F. Hallux Valgus. StatPearls. Treasure Island (FL): StatPearls Publishing Copyright \u00a9 2023. StatPearls Publishing LLC.; 2023."]}, {"label": ["27."], "mixed-citation": ["Hwang YG, Park KH, Han SH. Medial reduction in sesamoid position after Hallux Valgus correction Surgery showed better outcome in S.E.R.I. Osteotomy than DCMO. J Clin Med. 2023;12(13)."]}, {"label": ["37."], "mixed-citation": ["Li Y, Wang Y, Wang F, Tang K, Tao X. Biomechanical comparison between Rotational Scarf Osteotomy and Translational Scarf Osteotomy: a finite element analysis. Orthop Surg. 2023."]}, {"label": ["38."], "mixed-citation": ["Sieloff MR, Tokarski AR, Elliott AD, Jacobs PM, Borgert AJ. The incidence of Complications following scarf osteotomy for the treatment of Hallux Valgus: a systematic review with Meta-analysis. J Foot Ankle Surg. 2022."]}, {"label": ["39."], "surname": ["Besse", "Metatarsalgia"], "given-names": ["JL"], "source": ["Orthop Traumatol Surg Res"], "year": ["2017"], "volume": ["103"], "issue": ["1s"], "fpage": ["29"], "lpage": ["s39"], "pub-id": ["10.1016/j.otsr.2016.06.020"]}]
{ "acronym": [ "TSO", "MRSO", "MSHV", "HVA", "MTP-1 ROM", "IMA", "DMAA", "AOFAS", "CORA" ], "definition": [ "Traditional Scarf osteotomy", "Modified Rotary Scarf osteotomy", "Moderate to Severe Hallux Valgus", "Hallux Valgus Angle", "first Metatarsophalangeal joint Range of Motion", "Intermetatarsal Angle", "Distal metatarsal articular angle", "American Orthopaedic Foot and Ankle Society", "center of rotation of angulation" ] }
46
CC BY
no
2024-01-14 23:43:46
BMC Musculoskelet Disord. 2024 Jan 13; 25:61
oa_package/ee/4a/PMC10787438.tar.gz
PMC10787439
0
[ "<title>Introduction</title>", "<p id=\"Par20\">Osteoarthritis (OA) is the most prevalent degenerative disease affecting both axial and peripheral joints in the human body [##REF##37037399##1##–##REF##25748615##3##]. It is marked by the gradual deterioration of articular cartilage, bone growth in the articular margin and subchondral area, and abnormal immune inflammation in the synovial microenvironment. Joint pain and swelling, along with dysfunction, are the primary symptoms experienced by patients [##REF##27734845##4##–##REF##32931079##6##]. Currently, the exact cause of OA remains unclear, and there are multiple clinical approaches to treating it. While oral NSAIDs are frequently utilized, their effectiveness cannot be improved through excessive use and may even lead to harmful side effects [##REF##36737426##7##–##REF##30209413##9##]. Thus, it is crucial to continue researching the pathogenesis and potential therapeutic targets of osteoarthritis.</p>", "<p id=\"Par21\">In a joint, the two primary tissues are hyaline cartilage and synovium. Research has demonstrated that synovial inflammation is a significant pathological characteristic in the early stages of OA and is closely linked to the clinical symptoms experienced by patients [##REF##31926267##10##, ##REF##28148295##11##]. The primary manifestation of synovial lesions in OA is chronic and low-grade inflammation, and the microenvironment of synovial inflammation is involved in repairing tissue damage [##REF##27539668##12##, ##REF##31621560##13##]. Fibroblast-like synoviocytes (FLSs) are mesenchymal cells that reside in the synovium. Their abnormal activation and altered biological function are crucial in the formation and development of OA [##REF##34706873##14##, ##REF##33300062##15##]. Recent studies have shown that OA-FLSs share similar biological characteristics with FLSs in rheumatoid arthritis [##REF##30061164##16##, ##REF##26815411##17##]. Changes in their biological phenotype lead to abnormal proliferation and secretion of inflammatory factors in synovium, which accelerates the progression of OA.</p>", "<p id=\"Par22\">In our experiment, we utilized IL-1β to disrupt FLSs and replicate the inflammatory microenvironment of OA. Through transcriptome sequencing, we discovered that the mitogen-activated protein kinase (MAPK) signaling pathway was notably upregulated in the IL-1β-interfered FLSs group relative to the control group. Previous studies have demonstrated that the MAPK signaling pathway, which serves as a vital cell information transmission pathway, plays a critical role in regulating a range of physiological and pathological effects, including cell growth and differentiation, and the inflammatory response. Numerous studies have demonstrated that MAPK signaling cascades play a crucial role in the proliferation and migration of FLSs, as well as the secretion of inflammatory factors [##REF##27433031##18##–##REF##28736247##20##]. Thus, we hypothesize that regulating the MAPK signaling pathway can effectively prevent the expression of FLS-specific biological phenotypes.</p>", "<p id=\"Par23\">Furthermore, it was found that disintegrin and metalloproteinase domain-containing protein 8 (ADAM8) was significantly expressed in both IL-1β-induced FLSs and human synovial tissue. ADAM8 is a gene that codes for a protein. Research has demonstrated that this protein is involved in both calcium ion binding and metallopeptidase activity [##REF##35132956##21##]. ADAM8 has been revealed to play a role in cancer cell invasion through its mediation of the MAPK pathway [##REF##30635388##22##, ##REF##33314720##23##]. Additionally, it has been reported that the expression of ADAM8 remains relatively stable under normal physiological conditions [##REF##19397475##24##]. However, increased ADAM8 expression has been observed in response to inflammatory processes and in different types of cancers. Previously, Awan and colleagues found that ADAM8 plays a crucial role in promoting the proliferation, survival, and migration of hepatocellular carcinoma cells, ultimately leading to metastasis of the cancer [##REF##33814981##25##]. In addition, Liu et al. reported that ADAM8 activates the NF-κB/MMP-13 signaling axis, leading to increased migration and invasion of chondrosarcoma cells [##REF##31305294##26##]. These studies offer valuable insights into the regulation of OA-FLSs proliferation, invasion, and inflammatory factor secretion by ADAM8 in OA, which we can further explore. In our study, we blocked ADAM8 both in vivo and in vitro to observe how it affects the FLSs phenotype mediated by IL-1β and OA synovial inflammation in OA. Collectively, our aim was to offer fresh and valuable perspectives on the management of OA.</p>" ]
[ "<title>Materials and methods</title>", "<title>Chemicals and reagents</title>", "<p id=\"Par24\">Rat IL-1β protein (purity &gt; 90%) was acquired from Sino Biological company (Beijing, China). RNA interference sequences for ADAM8 were purchased from GenePharma in Suzhou, China. Thermo Fisher Scientific (St. Louis, USA) provided DMEM/F12 for cell culture, as well as fetal bovine serum (FBS) and phosphate buffer saline (PBS). Monosodium iodoacetate (MIA) was obtained from Sigma in Gillingham, UK. Antibodies included anti-MMP-13, TNF-α, IL-6, COX2, P-JNK, JNK, P-ERK, ERK, P-P38, P38, and β-actin antibodies were obtained from Abcam, UK. The antibodies included anti-ADAM8 and MMP-1 were obtained from ThermoFisher, USA. BDP-13176, a FSCN1 inhibitor, was purchased from MedChemExpress (New Jersey, USA).</p>", "<title>Cell culture</title>", "<p id=\"Par25\">Rat primary synoviocytes were obtained from Procell Life Science &amp; Technology Company (Procell, Wuhan, China) and cultured in DMEM/F12 medium supplemented with 10% fetal bovine serum. The cells were cultured at 37℃ with 5% CO<sub>2</sub> and cells from passages 4–6 were selected for use in experiments.</p>", "<title>Cell transfection</title>", "<p id=\"Par26\">The transfection process was carried out using GP-transfect-Mate from GenePharma, China, following the manufacturer’s protocol. Initially, FLSs were seeded in a plate at the appropriate density and allowed to adhere overnight. The cells were then transfected with 20 nM siRNA, and the medium was changed to complete DMEM/F12 culture medium overnight, which was maintained for 72 h. Total samples were harvested, and the knockdown efficiency of ADAM8 was detected using immunofluorescence staining and RT-PCR. The siRNA sequences used in this study can be found in Table S##SUPPL##0##1##.</p>", "<title>RNA sequencing</title>", "<p id=\"Par27\">In our studies, we utilized IL-1β as an intervention for FLSs over a period of 6 h. Subsequently, we extracted total RNA by a TRIzol reagent (Beyotime, China). The extracted samples were then sent to OE Biotech in Suzhou, China, for further sequencing. The FPKM of each gene was calculated using Cufflinks, and the read count of the detected gene was obtained. Differential expression genes were analyzed using the R package. And the significance threshold was <italic>P</italic> &lt; 0.05 and the fold change threshold was &gt; 1.5 or &lt; 0.5. To detect ADAM8 downstream, we utilized the same sequencing operation following successful transfection of siADAM8 with high efficiency.</p>", "<title>Quantitative real-time PCR assay</title>", "<p id=\"Par28\">In this study, we isolated total RNA from FLSs subjected to different interventions using TRIzol reagent (Beyotime, China) and quantified the RNA density with a NanoDrop 2000 system (Thermo Fisher Scientific). Then, we extracted complementary DNA (cDNA) from the isolated RNA through reverse transcription. To amplify the reaction system, we combined 10 μl of qPCR Master Mix, 0.5 μl of forward and reverse primers, 2 μl of cDNA, and 7 μl of nuclease-free ddH<sub>2</sub>O. We used the comparative 2<sup>−ΔΔCq</sup> method to determine the folding changes in mRNA expression. The gene primer sequences used in this study are listed in Table S##SUPPL##0##2##.</p>", "<title>Western blotting</title>", "<p id=\"Par29\">After collecting FLSs with different interventions, the cells were rinsed twice with PBS and lysed using RIPA buffer (Beyotime, China). The resulting lysate supernatant lysate was collected, and the protein concentration was determined by the use of a BCA kit (Beyotime, China). Next, all proteins from the various experimental groups were transferred onto a polyvinylidene chloride (PVDF) membrane. After the barrier buffer was sealed in, the membrane was incubated with primary antibody solutions for 12 h. Following this, the membrane was rinsed for 20 min and the corresponding secondary antibody solution was added for another 1 h. Finally, protein band images were visualized and the protein gray was quantified by Image Lab software version 3.0 (Bio-19 Rad, USA).</p>", "<title>Wound-healing assay</title>", "<p id=\"Par30\">In this study, we prepared single-cell suspensions of FLSs under various treatment conditions and inoculated them into 6-well plates at a density of 1 × 10<sup>6</sup> cells per well. We then used a P-200 pipette tip to create a scratch on the surface of the plates, allowing the FLSs to adhere to the walls of the orifice plate. Any shed FLSs cells were washed away by PBS, and the remaining cells were then incubated in serum-free DMEM/F12. We observed the cells at scratch site under an inverted microscope (Carl Zeiss, Germany) after 0 and 24 h.</p>", "<title>Migration and invasion assay</title>", "<p id=\"Par31\">After treating FLSs with IL-1β and siADAM8, we implanted them into the upper chamber of a transwell at a concentration of 2 × 10<sup>4</sup> cells per well, using 100 μl of serum-free DMEM/F12. Simultaneously, we added 600 μl of DMEM/F12 with 20% FBS to the lower lumen of a 24-well plate (BD Bioscience, USA). In contrast to migration analysis, detecting the invasion of FLSs involves an extra layer of matrix glue in the upper chamber of the transwell. Following a 24-h period, the FLSs were fixed with 4% paraformaldehyde for 20 min and rinsed. Subsequently, the upper cells were carefully wiped with a damp cotton swab, while the FLSs in the lower chamber were stained with crystal violet solution for half an hour. Finally, the FLSs in the lower chamber were rinsed with PBS for 5 min. Pictures were taken under an inverted microscope (Carl Zeiss, Germany) and the number of migrating and invading FLSs was evaluated and calculated with ImageJ software (Media Cybernetics, USA).</p>", "<title>Immunofluorescence assay</title>", "<p id=\"Par32\">After treating FLSs with various interventions, the cells were fixed using 4% paraformaldehyde and permeabilized with 0.2% Triton X-100 (Beyotime, China) on ice. Then, cells were blocked with QuickBlock buffer (Beyotime, China) for another hour. The cells were incubated primary antibodies against ADAM8, IL-6, and TNF-α protected from light at 4 °C overnight, followed by incubation with F-actin (Yeasen, China). To stain cell nuclei, DAPI (Beyotime, China) was used for a duration of 10 min. The FLSs were then observed and photographed using a Zeiss laser scanning microscope (LSM 510, Zeiss).</p>", "<title>Management of the synovial tissue in OA patients</title>", "<p id=\"Par33\">All human experiments conducted in this study were in compliance with the ethical standards set by the Hai’an People's Hospital. Synovial tissues were obtained from two groups of patients: those who underwent total knee arthroplasty due to knee OA (OA group, <italic>n</italic> = 5, 4 females, 1 male; median age, 73 years; age range, 62–81 years) and those who got arthroscopic knee surgery because of anterior cruciate ligament injury (ACL group, <italic>n</italic> = 5, 2 females, 3 males; median age, 42 years; age range, 31–49 years). The synovial tissue was excised and sectioned into uniform pieces. which were then washed three times with a PBS solution before being embedded and cut into blocks for subsequent staining.</p>", "<title>Animals and OA model induction</title>", "<p id=\"Par34\">This study was conducted in accordance with the ethical guidelines set forth by the Soochow University Ethics Committee, which approved all animal experiments and procedures. Eighteen 8-week-old male Sprague Dawley rats were chosen as subjects for this study. They were all fed and maintained under standard conditions, which included maintaining a temperature range of 22–25℃, ensuring proper ventilation, and providing a 12-h light and dark cycle. In our study, animals were divided into three groups through random assignment: the sham surgery group, the MIA group, and the ADAM8 intervention group (MIA + siADAM8, joint cavity injection). The OA model group undertook a single intraarticular injection of MIA (Sigma, USA) 50 μl, while the sham operation group got an equivalent amount of saline. In the drug intervention group, rats were injected with 50 μl of siADAM8 at a concentration of 300 μM into their knee joint on the 7th, 14th, and 21st day of modeling. The modeling process lasted for 28 days until the rats were euthanized.</p>", "<title>Immunohistochemical staining</title>", "<p id=\"Par35\">We obtained knee tissues from three groups of rats and subjected them to decalcification for a period of 30 days, utilizing 10% ethylenediaminetetraacetic acid (EDTA, Sigma, USA). Subsequently, we performed gradient dehydration and embedding. The resulting embedded tissue wax blocks were sliced into 7-μm sections and stained with hematoxylin and eosin (H&amp;E), as well as safranin O, in accordance with established protocols. Subsequently, we utilized immunohistochemical (IHC) staining to detect the presence of ADAM8, IL-1β, TNF-α, IL-6, MMP-1, and MMP-13. These primary antibodies were chosen for incubation and staining purposes. To quantify the number of positive cells, we utilized ImageJ software (Media Cybernetics, USA) for analysis.</p>", "<title>Statistical analysis</title>", "<p id=\"Par36\">The data values were expressed as mean ± standard deviation. To determine whether there was a significant difference between the two groups, a <italic>t</italic>-test was utilized for analysis. Additionally, multiple comparisons were determined through the use of a Tukey test following a one-way analysis of variance. GraphPad Prism8 was used for all statistical analysis. A <italic>p</italic>-value of less than 0.05 was considered statistically significant, while a <italic>p</italic>-value of less than 0.01 was deemed highly significant.</p>" ]
[ "<title>Results</title>", "<title>The MAPK signaling cascade is involved in the processes of FLSs treated with IL-1β</title>", "<p id=\"Par37\">To model the synovial inflammatory microenvironment of OA, we utilized IL-1β to intervene FLSs. We report on our sequencing results which indicate the presence of 183 differentially expressed genes (DEGs) in IL-1β-interfered FLSs. Specifically, we found that 81 of these genes were upregulated, while 102 were downregulated (Fig. ##FIG##0##1##A). The volcano diagram illustrates the distribution of unaffected and DEGs in FLSs, both with and without IL-1β intervention. Additionally, the diagram includes the names of the top 10 upregulated and downregulated DEGs (Fig. ##FIG##0##1##B). The expressions of these DEGs were detected using PCR, and the results obtained were consistent with those demonstrated by sequencing (Figure S##SUPPL##0##1##). The gene ontology classification analysis showed that there were differences in the enrichment of FLSs biological processes, intracellular components, and molecular functions following IL-1β intervention (Fig. ##FIG##0##1##C-D). As shown, we observed a significant impact on the biological adhesion function and binding ability of the FLSs. Though KEGG pathway classification, we observed that IL-1β-induced FLSs intervention was associated with the development of infectious diseases, the immune system, and cell growth and death (Fig. ##FIG##0##1##E-F). Upon analyzing the up-regulated signaling pathways, we observed a significant increase in MAP kinase activity. This increase is attributed to the differential genes involved, such as Gper1, ADAM8, and Tert, among others. This observation suggests that the MAPK signaling cascade MAY play a crucial role in IL-1β-induced inflammation models in vitro (Fig. ##FIG##0##1##G).</p>", "<title>ADAM8 is upregulated in FLSs after treatment with IL-1β.</title>", "<p id=\"Par38\">In our study, we conducted an experiment using IL-1β with varying concentrations (0, 5, and 10 ng/ml) to intervene with FLSs. To evaluate cell migration activity in vitro, we utilized a scratch assay, which proved to be an effective simulation. Our findings indicate that IL-1β promotes FLSs migration in a concentration-dependent manner (Fig. ##FIG##1##2##A and D). Upon conducting additional in vitro crystal violet staining, it was observed that IL-1β enhances the invasion and migration of FLSs in a concentration-dependent manner (Fig. ##FIG##1##2##B-C and E-F). Matrix metalloproteinases (MMPs) are enzymes that break down collagen and have various functions, including promoting cell proliferation, migration, and differentiation. Furthermore, western blot results found that the expressions of inflammation-related markers, including IL-6, TNF-α, and COX2 were significantly higher in experimental FLSs compared to the control group (Fig. ##FIG##1##2##G), which was consistent with our PCR results (Fig. ##FIG##1##2##H-J). To further investigate the impact of the MAPK signaling cascade on FLS-specific biological phenotypes, we utilized adezmapimod, a potent inhibitor of MAPK, to intervene in IL-1β-induced FLSs. Based on the CCK8 results, we employed a concentration of 50 μM of adezmapimod for this intervention. Western blot analysis revealed that adezmapimod effectively inhibited the expression of P-ERK and P-P38 in FLSs. Moreover, we observed that the inhibition of MAPK significantly suppressed the invasion, migration, and inflammatory expression of FLSs stimulated by IL-1β (Figure S##SUPPL##0##2##), which further illustrated the role of the MAPK cascade in IL-1β stimulated FLSs. The transcriptome differential gene analysis revealed that IL-1β increased the expression of ADAM8. Additionally, we conducted RT-PCR and observed a gradual upregulation of ADAM8 following the intervention of IL-1β (Fig. ##FIG##1##2##K). Immunofluorescence staining confirmed the upregulation of ADAM8 in FLSs that had been stimulated by IL-1β (Fig. ##FIG##1##2##L).</p>", "<p id=\"Par39\">ADAM8 expression was also detected in synovial tissues of patients with OA. Studies have revealed variations in the biological characteristics of synovial tissue between patients with ACL injuries and patients with OA [##REF##33469085##27##, ##REF##31926672##28##]. In our study, we utilized ACL patients as a model to simulate the condition of individuals without OA as reported in previous studies [##REF##12932288##29##]. Following the acquisition of informed consent from the patients, we surgically procured synovial tissue from ACL patients. This enabled us to distinguish it from postoperative synovium obtained from patients with severe OA. The aim was to observe the genes that exhibit significant changes during the progression of OA. We found that the expressions of inflammatory cytokines TNF-α and IL-1β were significantly increased in the synovium of OA patients compared with ACL (non-OA) patients, as well as the expression of ADAM8, suggesting that ADAM8 may be involved in the synovium progression of OA (Fig. ##FIG##2##3##).</p>", "<title>ADAM8 blockade suppresses FLS migration and invasion by inhibiting MMPs</title>", "<p id=\"Par40\">To further investigate whether ADAM8 regulates the biological behavior of FLSs, we utilized siRNA to manipulate the expression level of ADAM8 in FLSs (Fig. ##FIG##3##4##A). The RT-PCR results indicated that siADAM8 3 had the most significant impact on ADAM8 knockdown in FLSs, which was consistent with the immunofluorescence findings (Fig. ##FIG##3##4##B-C). Furthermore, our results indicate that ADAM8 inhibition led to a significant decrease in the migration of FLSs, as demonstrated by scratch assays and migration analysis (Fig. ##FIG##3##4##D-E and G-H). Additionally, our FLS invasion assays revealed that siADAM8 treatment attenuated the invasive properties of FLSs under IL-1β intervention (Fig. ##FIG##3##4##F and I). Previous research has demonstrated a correlation between the invasion and migration ability of cells and the expression and secretion of MMPs. In this study, we further investigated the impact of siADAM8 intervention on the expression of MMPs in FLSs. Our western blot results indicated ADAM8 silencing inhibited the expression of MMP-1 and MMP-13, which was consistent with the RT-PCR results (Fig. ##FIG##3##4##J-K). Our findings indicate that ADAM8 has the potential to impede the invasion and migration of FLSs by regulating the levels of MMPs.</p>", "<title>ADAM8 blockade suppresses FLS-mediated inflammation by inhibiting MAPK signaling cascades</title>", "<p id=\"Par41\">The development of OA is heavily influenced by inflammatory disorders within the synovial microenvironment [##REF##31550528##30##]. To expand on this, we conducted an investigation into the impact of ADAM8 intervention on the regulation of FLSs inflammation. In our study, we discovered that inhibiting ADAM8 was effective in reducing the expression of various inflammatory cytokines, including TNF-α, IL-6, and COX2 under IL-1β intervention (Fig. ##FIG##4##5##A-B). Furthermore, our RT-PCR analysis revealed that ADAM8 blockade inhibit gene expression of TNF-α, IL-6, COX2, and PGE2 (Fig. ##FIG##4##5##C). Our immunofluorescence results also showed that inhibition of ADAM8 suppressed the expression of TNF-α and IL-6 (Fig. ##FIG##4##5##D-F). The GSEA analysis revealed that the MAPK signaling pathway played a role in the inflammatory response of FLSs induced by IL-1β (Figure S##SUPPL##0##3##). We then investigated the impact of ADAM8 inhibition on the MAPK pathway. The western blot results, as illustrated in Fig. ##FIG##4##5##G-H, indicate that the expression levels of P-JNK, P-ERK, and P-P38 were considerably upregulated following IL-1β intervention. However, after ADAM8 knockdown treatment by FLSs, the expressions of these phosphorylated signaling proteins were significantly inhibited. This finding suggests that ADAM8 may act as an inhibitor of FLS-mediated inflammation through the MAPK signaling pathway.</p>", "<title>ADAM8 blockade prevents IL-1β-stimulated biological phenotypes specific to FLSs by targeting FSCN1</title>", "<p id=\"Par42\">To investigate the molecular mechanism of ADAM8 in regulating the biological behavior of FLSs, RNA sequencing was conducted. In this study, we designated the IL-1β intervention FLSs as the control group and the IL-1β + siADAM8 group as the experimental group for treatment comparison. Our study presents sequencing results that demonstrate the existence of 762 DEGs in FLSs subjected to the siADAM8 intervention compared with FLSs only stimulated by IL-1β. Further analysis revealed that 130 of these genes were upregulated, while 632 were downregulated (Fig. ##FIG##5##6##A). GO enrichment analysis showed that the DEGs were mainly classified in the cell migration signal category, where we observed 34 enriched DEGs (Fig. ##FIG##5##6##B). Among these differentially expressed genes, FSCN1 showed significant downregulation, which has previously been shown to be involved in regulation of the FLS biological phenotype (Fig. ##FIG##5##6##C). Furthermore, we used BDP-13176, a potent inhibitor of FSCN1, in combination with siADAM8 to intervene in the IL-1β-induced FLSs. Our results indicated that siADAM8 significantly inhibited FLS migration and invasion. Interestingly, the inhibitory effect was further enhanced when combined with BDP-13176 (Fig. ##FIG##5##6##D-I). These findings suggest that FSCN1 may play a crucial role downstream of ADAM8 in regulating the biological behavior of FLSs. Our RT‒PCR results indicate that siADAM8 inhibited FSCN1, MMP1, and MMP13 expression. Moreover, when combined with BDP-13176, the gene expression levels of FSCN1, MMP1, and MMP13 were further downregulated (Fig. ##FIG##5##6##J). Furthermore, we investigated the impact of intervening in FSCN1 on the MAPK signaling cascade. Our western blot analysis demonstrated that inhibition of FSCN1 in IL-1β-stimulated FLSs led to a significant reduction in the expression of P-ERK and P-P38 (Figure S##SUPPL##0##4##). These findings suggested that MAPK cascade may play a crucial role in ADAM8/FSCN1-mediated regulation of FLSs.</p>", "<title>Inhibition of ADAM8 alleviates OA progression and synovial inflammation in vivo</title>", "<p id=\"Par43\">As previously reported, we created a rat model of OA by injecting MIA into the joint. In addition, we administered an interventional therapy by injecting siADAM8. The experimental procedure is depicted in Fig. ##FIG##6##7##A. In order to assess inflammation and bone erosion, H&amp;E staining was performed on the knee joints of rats in every group (Fig. ##FIG##6##7##B-C). Additionally, to evaluate cartilage damage, safranin O staining was also conducted (Fig. ##FIG##6##7##D). After conducting our study, we discovered that the knee cartilage experienced severe erosion as a result of MIA modeling. However, we found that ADAM8 treatment was able to effectively reverse this phenomenon and delayed the progression of OA (Fig. ##FIG##6##7##C and E). The results of ADAM8 immunohistochemical staining showed that injecting siRNA into the articular cavity effectively reduced the expression of ADAM8 in the synovium (Fig. ##FIG##6##7##F-G).</p>", "<p id=\"Par44\">Our findings align with the in vitro results, as we observed a significant decrease in the expression of the inflammation-related factors TNF-α, IL-1β, and IL-6 in the synovium of OA rats following ADAM8 inhibition (Fig. ##FIG##7##8##A-F). siADAM8 was injected into the articular cavity of MIA-treated rats, and subsequent immunohistochemical staining revealed a significant decrease in MMP-1 and MMP-13 expressions in the rats’ synovium (Fig. ##FIG##7##8##G-J). These findings align with our in vitro results and suggest that ADAM8 could serve as a potential regulator of synoviocyte invasion and migration activity in OA. Collectively, these results indicate that targeting ADAM8 in the synovium could potentially have a beneficial impact on the treatment of OA.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par45\">OA is a chronic disease characterized by degenerative changes in the knee cartilage, with or without bone hyperplasia and chronic synovitis [##REF##31988808##31##, ##REF##28718060##32##]. In a surveyed population in China, the prevalence of OA was high, reaching up to 8.1%. OA has become the leading cause of disability among middle-aged and elderly individuals in China [##REF##16301755##33##, ##UREF##0##34##]. Unfortunately, this problem is only expected to worsen due to the aging population and increasing levels of obesity. This will inevitably lead to a significant burden on individuals, families, and society as a whole. The first line of treatment for OA in drug therapy is non-steroidal anti-inflammatory drugs. However, long-term use of these drugs can easily cause gastrointestinal reactions [##REF##27007113##35##–##REF##26849131##37##]. Preventing and effectively treating OA has become a significant challenge in the field of national public health management.</p>", "<p id=\"Par46\">The synovium plays a crucial role in maintaining joint cavity homeostasis by communicating with the cartilage through an immune inflammatory network [##REF##35165404##38##, ##REF##22641138##39##]. In cases of OA, chronic and low-grade inflammation are the primary symptoms of synovial lesions [##REF##23516014##40##]. Recent evidence suggests that synovial inflammation is a significant pathological feature in the early stages of OA and is closely linked to the patient’s clinical symptoms [##REF##22387238##41##, ##REF##35679783##42##]. When joints experience stress injuries, such as degeneration or trauma, the synovium is stimulated, leading to an inflammatory response. This results in the secretion of numerous inflammatory factors, such as IL-1, TNF-a, and IL-6, as well as matrix metalloproteinases (MMPs). These factors play a crucial role in the process of repairing articular cartilage injuries. The inflammatory microenvironment is a key pathological feature of tissue repair and is closely linked to tissue regeneration. IL-1β and other pro-inflammatory factors have the potential to disturb the equilibrium of chondrocytes, leading to their demise and gradual depletion of the cartilage matrix [##REF##30340925##43##, ##REF##22063369##44##]. Consequently, synovial inflammation is a crucial factor in the development of the pathological characteristics of OA.</p>", "<p id=\"Par47\">FLSs are mesenchymal cells that reside in synovial tissue [##REF##36359003##45##]. Recent studies have shown that the biological characteristics of FLSs in OA are similar to those in rheumatoid arthritis. This is due to changes in their behavior, which can lead to abnormal synovial hyperplasia [##REF##30582210##46##]. Furthermore, FLSs have been identified as the primary inflammatory infiltrating cells in the synovium in OA [##REF##36175067##47##]. Abnormally activated FLSs can accelerate the destruction of osteoarticular cartilage by releasing inflammatory factors, nitric oxide (NO), PGE2, and MMPs [##REF##15378360##48##, ##REF##22549135##49##]. Moreover, FLSs can activate receptors in the peripheral nervous system through inflammatory networks, which can worsen pain in OA patients [##REF##29194108##50##]. This pain and cartilage damage can then escalate synovial inflammation, creating a vicious cycle that ultimately results in the loss of joint function.</p>", "<p id=\"Par48\">In our experiment, we used IL-1β to interfere with FLSs to simulate the OA synovial inflammatory microenvironment. Transcriptome sequencing analysis revealed that the MAPK signaling pathway was activated during IL-1β-induced FLSs, accompanied by significant upregulation of ADAM8 gene. ADAM8 is a member of the ADAM family, which encodes disintegrin and metalloproteinase structural domains [##REF##30124911##51##]. This protein has been implicated in various biological processes that involve interactions between cells and the extracellular matrix, as well as between cells themselves [##REF##36910158##52##, ##REF##23670189##53##]. These processes include fertilization, muscle development, and neurogenesis. Our study revealed that the expression levels of ADAM8 gradually increased with IL-1β stimulation in vitro. Additionally, we observed a significant increase in synovial ADAM8 expression in OA patients compared with ACL patients.</p>", "<p id=\"Par49\">Previous studies have shown that ADAM8 plays a significant role in neutrophil migration and infiltration, which can help alleviate lung failure associated with acute respiratory distress syndrome [##REF##32048249##54##]. ADAM8 has also been shown to play multiple roles in cancer cell migration, mechanics, and extracellular matrix remodeling. According to Liu et al., the activation of the NF-κB/MMP-13 signaling axis by ADAM8 resulted in the promotion of chondrosarcoma cell migration and invasion [##REF##31305294##26##]. Koller also reported on ADAM8 as a possible emerging drug target treating of inflammatory and aggressive diseases [##REF##19601829##55##]. In our study, we utilized a siRNA to suppress ADAM8 levels in FLS. Our findings indicate that ADAM8 inhibition resulted in a decrease in FLSs migration and invasion, which was accompanied by a significant reduction in MMPs. Additionally, we investigated the impact of ADAM8 inhibition on IL-1β-induced inflammation in FLSs. Our results demonstrate that ADAM8 blockade effectively reduced the expression of TNF-α, IL-6, COX2, and PGE2 in FLSs by regulating the MAPK signaling pathway. To further investigate the impact of ADAM8 knockdown on downstream signaling in IL-1β-stimulated FLSs, we conducted sequencing analysis. Our results revealed that cell migration signals were significantly downregulated, as evidenced by GO enrichment. Interestingly, FSCN1, a highly conserved actin binding protein, was among the downregulated migration-related differences that we identified. FSCN1 has been previously implicated in tumor cell growth and metastasis, further highlighting its potential role in regulating cell migration [##REF##26522130##56##, ##UREF##1##57##]. Previous studies have established that FSCN1 plays a crucial role in regulating the biological function of FLSs [##REF##35595956##58##]. In our research, we employed a potent inhibitor of FSCN1 in combination with siADAM8 as an intervention in IL-1β-stimulated FLSs. Our results indicate that the migration and migration ability of FLSs was further downregulated, indicating that ADAM8 may affect the biological function of FLSs by regulating FSCN1.</p>", "<p id=\"Par50\">In our study, we conducted in vivo animal experiments in which we injected siADAM8 into the articular cavity of an OA rat model. Our findings showed that inhibiting ADAM8 effectively reduced OA progression and bone erosion in rats. Furthermore, our IHC staining revealed that inhibiting ADAM8 significantly reduced the expression level of IL-1β, IL-6, and TNF-α in the synovium of the rat knee. Previous studies conducted by Duan et al. have revealed that the notch1-ADAM8 pathway accelerates the progression of OA by promoting the degradation of chondrocytes through an extracellular mechanism [##REF##31640732##59##]. In our study, we aimed to enhance the potential benefits of ADAM8 as a target in the treatment of OA by inhibiting its activity. Our findings shed new light on the treatment of OA by alleviating synovial inflammation.</p>", "<p id=\"Par51\">Despite the valuable insights gained from our study, there are some limitations that should be acknowledged. One such limitation is that we did not include knockout mice, which could provide a more comprehensive understanding of the role of ADAM8 in regulating synovial biological phenotypes. Additionally, our experiment was conducted solely using the MIA-induced OA model, and further investigation is needed to determine the extent to which ADAM8 contributes to disease progression in older rats with OA. Our study indicates that the ADAM8/FSCN1/MAPK signaling axis may play a crucial role in the progression of OA-related synovitis. However, further investigation is required to verify other targets related to cell migration in the sequencing results and to fully understand the specific biological regulatory mechanism of ADAM8.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par52\">Our study demonstrates the crucial role of MAPK in the inflammatory activation of FLSs, with the involvement of ADAM8. Targeted inhibition of ADAM8 expression inhibits the invasive and migratory ability of FLSs and also suppresses the release of inflammatory cytokines from FLSs. Our sequencing analysis suggests that there may be a potential involvement of FSCN1/MAPK signaling. In vitro, ADAM8 blockade was also observed to alleviate the progression of OA by effectively reducing synovial inflammation and MMP levels. Collectively, our findings indicate that ADAM8 administration could be a beneficial and viable therapeutic approach for treating OA.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">Osteoarthritis (OA) is a degenerative joint disease that affects elderly populations worldwide, causing pain and disability. Alteration of the fibroblast-like synoviocytes (FLSs) phenotype leads to an imbalance in the synovial inflammatory microenvironment, which accelerates the progression of OA. Despite this knowledge, the specific molecular mechanisms of the synovium that affect OA are still unclear.</p>", "<title>Methods</title>", "<p id=\"Par2\">Both in vitro and in vivo experiments were undertaken to explore the role of ADAM8 playing in the synovial inflammatory of OA. A small interfering RNA (siRNA) was targeting ADAM8 to intervene. High-throughput sequencing was also used.</p>", "<title>Results</title>", "<p id=\"Par3\">Our sequencing analysis revealed significant upregulation of the MAPK signaling cascade and ADAM8 gene expression in IL-1β-induced FLSs. The in vitro results demonstrated that ADAM8 blockade inhibited the invasion and migration of IL-1β-induced FLSs, while also suppressing the expression of related matrix metallomatrix proteinases (MMPs). Furthermore, our study revealed that inhibiting ADAM8 weakened the inflammatory protein secretion and MAPK signaling networks in FLSs. Mechanically, it revealed that inhibiting ADAM8 had a significant effect on the expression of migration-related signaling proteins, specifically FSCN1. When siADAM8 was combined with BDP-13176, a FSCN1 inhibitor, the migration and invasion of FLSs was further inhibited. These results suggest that FSCN1 is a crucial downstream factor of ADAM8 in regulating the biological phenotypes of FLSs. The in vivo experiments demonstrated that ADAM8 inhibition effectively reduced synoviocytes inflammation and alleviated the progression of OA in rats.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">ADAM8 could be a promising therapeutic target for treating OA by targeting synovial inflammation.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13075-023-03238-w.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>None.</p>", "<title>Authors’ contributions</title>", "<p>KC, HT and PZ designed the research strategy. KC, HT, MC and XL worked with the animal models and performed immunohistochemical staining. YS, LZ and LH performed the in vitro assays. KC, HT, SL and LH performed the statistical analysis and wrote the manuscript. YX, WH and DG revised the paper. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by the National Natural Science Foundation of China (82072425, 82072498, 82272657), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), Jiangsu Medical Research Project (ZD2022014), the Program of Jiangsu science and technology Department (BE2021650, BE2022737), National and Local Engineering Laboratory of New Functional Polymer Materials (SDGC2205) and the Program of Suzhou Health Commission (GSWS2022002, SZXK202111).</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par53\">All animal experiments and tests were guided and approved by the Ethics Committee of the Soochow University.</p>", "<title>Consent for publication</title>", "<p id=\"Par54\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par55\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The MAPK signaling cascade is involved in the processes in FLSs treated with IL-1β. <bold>A</bold> Differentially expressed mRNAs in FLSs in response to IL-1β are illustrated as a heat map. <bold>B</bold> Volcano map showing differentially expressed mRNAs. <bold>C-D</bold> Gene ontology classification. <bold>E</bold> KEGG pathway classification. <bold>F</bold> Bubble map of KEGG enrichment analysis (Total). <bold>G</bold> Bubble map of KEGG enrichment analysis (Up) and correlational heatmap of different samples and MAP kinase activity and bone resorption-related markers in different samples</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>ADAM8 is up-regulated in FLSs after treatment with IL-1β. <bold>A</bold>, <bold>D</bold> Wound healing assays and quantitative analysis of the migration abilities of FLSs with different concentrations of IL-1β. <bold>B</bold>, <bold>E</bold> Transwell assays and quantitative analysis of the migration ability of FLSs with different concentrations of IL-1β. <bold>C</bold>, <bold>F</bold> Transwell assays and quantitative analysis of the invasion abilities of FLSs with different concentrations of IL-1β. <bold>G</bold> Western blot and quantitative analysis of IL-6, TNF-α, and COX-2 in FLSs after treatment with IL-1β. <bold>H-J</bold> qRT-PCR analysis of the mRNA expression levels of IL-6, TNF-α, and COX2. <bold>K</bold> qRT-PCR analysis of the mRNA expression levels of ADAM8. <bold>L</bold> Immunofluorescence staining of ADAM8 in FLSs. Scale bar = 200 µm. *<italic>P</italic> &lt; 0.05; **<italic>P</italic> &lt; 0.01</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>The expression of ADAM8 was found to be increased in the synovium of patients with OA. <bold>A</bold> H&amp;E staining of synovial tissues in ACL injury and OA patients. <bold>B-D</bold> TNF-α, IL-1β, and ADAM8 IHC staining of synovial tissues in ACL injury and OA patients. <bold>E–G</bold> Quantification of IHC staining for TNF-α, IL-1β, and ADAM8. Scale bars, 100 µm. **<italic>P</italic> &lt; 0.01</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>ADAM8 blockade suppresses FLS migration and invasion by inhibiting MMPs. <bold>A</bold> qRT-PCR analysis of the mRNA expression levels of ADAM8. <bold>B</bold> ADAM8 transfection efficiency was detected by fluorescence assay. <bold>C</bold> Immunofluorescence staining of ADAM8. <bold>D</bold>, <bold>G</bold> Wound healing assays and quantitative analysis of the migration ability of FLSs. <bold>E</bold>, <bold>H</bold> Transwell assays and quantitative analysis of the migration ability of FLSs. <bold>F</bold>, <bold>I</bold> Transwell assays and quantitative analysis of the invasion ability of FLSs with different concentrations of IL-1β. <bold>J</bold> Western blot and quantitative analysis of MMP-1 and MMP-13. <bold>K</bold> qRT-PCR analysis of the mRNA expression levels of MMP-1 and MMP-13. Scale bar = 200 µm. *<italic>P</italic> &lt; 0.05; **<italic>P</italic> &lt; 0.01</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>ADAM8 blockade suppresses FLS inflammation by inhibiting MAPK signaling cascades. <bold>A</bold> Western blot and quantitative analysis of TNF-α, IL-6 and COX2 after treatment with siADAM8. <bold>H</bold> qRT-PCR analysis of the mRNA expression levels of TNF-α, IL-6, COX2, and PGE2. <bold>D-F</bold> Immunofluorescence staining and quantitative analysis of TNF-α and IL-6 after treatment with siADAM8. <bold>G</bold> Western blot of P-JNK, JNK, P-ERK, ERK, P-P38, and P38 after treatment with siADAM8. <bold>H</bold> Quantitative analysis of P-JNK/JNK, P-ERK/ERK, and P-P38/P38. *<italic>P</italic> &lt; 0.05; **<italic>P</italic> &lt; 0.01</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>ADAM8 blockade prevent IL-1β-stimulated biological phenotypes specific of FLSs by targeting FSCN1. <bold>A</bold> The differentially expressed mRNAs in FLSs between IL-1β group and IL-1β + siADAM8 are illustrated as a heat map. <bold>B</bold> Gene ontology classification. <bold>C</bold> The heat map shows the detected differential genes associated with cell migration. <bold>D</bold>, <bold>G</bold> Wound healing and quantitative analysis of the migration ability of FLSs. <bold>E</bold>, <bold>H</bold> Transwell assays and quantitative analysis of the migration ability of FLSs. <bold>F</bold>, <bold>I</bold> Transwell assays and quantitative analysis of the invasion ability of FLSs with different concentrations of IL-1β.<bold> J</bold> qRT-PCR analysis of the mRNA expression levels of FSCN1, MMP-1, and MMP-13. Scale bar = 200 µm. *<italic>P</italic> &lt; 0.05; **<italic>P</italic> &lt; 0.01</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Inhibition of ADAM8 alleviates OA progression in vivo. <bold>A</bold> Schematic diagram of the in vivo experiments. <bold>B</bold>-<bold>C</bold> H&amp;E staining and OARSI score of rat knee joint. <bold>D</bold>-<bold>E</bold> Safranin O staining of rat knee joint. <bold>F</bold>-<bold>G</bold> Immunohistochemical staining and quantitative analysis for ADAM8 of decalcified bone sections. Scale bars, 200 µm. *<italic>P</italic> &lt; 0.05; **<italic>P</italic> &lt; 0.01</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>Inhibition of ADAM8 alleviates synovitis and MMPs in vivo. <bold>A</bold>, <bold>B</bold> IL-1β IHC staining and quantitative analysis of synovial tissues in OA rats. <bold>C</bold>, <bold>D</bold> IL-6 IHC staining and quantitative analysis of synovial tissues in OA rats. <bold>E</bold>, <bold>F</bold> TNF-α IHC staining and quantitative analysis of synovial tissues in OA rats. <bold>G</bold>, <bold>H</bold> MMP-1 IHC staining and quantitative analysis of synovial tissues in OA rats. <bold>I</bold>, <bold>J</bold> MMP-13 IHC staining and quantitative analysis of synovial tissues in OA rats. Scale bars, 200 µm. *<italic>P</italic> &lt; 0.05; **<italic>P</italic> &lt; 0.01</p></caption></fig>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Kai Chen, Huaqiang Tao, Pengfei Zhu, and Miao Chu contributed equally to this work.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"13075_2023_3238_MOESM1_ESM.zip\"><caption><p><bold>Additional file 1: Table S1.</bold> siRNA sequences of rat genes. <bold>Table S2.</bold> Primers used in qRT-PCR. <bold>Figure S1.</bold> qRT-PCR analysis of the mRNA expression levels of TULP2, DNAH6, CTRC, HIPK4, BEX1, CPA2, ARG2, BIN2A, MYCN and GNAL in FLSs after intervention with IL-1β. *<italic>P</italic>&lt;0.05; **<italic>P</italic>&lt;0.01. <bold>Figure S2.</bold> MAPK inhibitor Adezmapimod inhibited invasion, migration and inflammatory expression of IL-1β-stimulated FLSs. (A) CCK-8 results showing cytotoxicity of Adezmapimod on FLSs. (B) Western blot and quantitative analysis of P-JNK/JNK, P-ERK/ERK and P-P38/P38 in IL-1β-stimulated FLSs after treatment with Adezmapimod. (C, F) Wound healing assays and quantitative analysis of the migration ability of FLSs. (D, G) Transwell assays and quantitative analysis of the migration ability of FLSs. (E, H) Transwell assays and quantitative analysis of the invasion ability of FLSs with different concentrations of IL-1βin IL-1β-stimulated FLSs after treatment with Adezmapimod. (I) Western blot and quantitative analysis of IL-6, TNF-α and COX2 in IL-1β-stimulated FLSs after treatment with Adezmapimod. Scale bar = 200 µm. *<italic>P</italic>&lt;0.05; **<italic>P</italic>&lt;0.01. <bold>Figure S3.</bold> The GSEA analysis revealed that the MAPK signaling pathway was significantly enriched in FLSs after treatment with IL-1β. <bold>Figure S4.</bold> Western blot and quantitative analysis of P-JNK/JNK, P-ERK/ERK and P-P38/P38 in FLSs after treatment with BDP13176. ns, non-significant, **<italic>P</italic>&lt;0.01.</p></caption></media>" ]
[{"label": ["34."], "surname": ["Buckwalter", "Saltzman", "Brown"], "given-names": ["JA", "C", "T"], "article-title": ["The impact of osteoarthritis: implications for research"], "source": ["Clin Orthop Relat Res"], "year": ["2004"], "volume": ["427 Suppl"], "fpage": ["S6"], "lpage": ["15"], "pub-id": ["10.1097/01.blo.0000143938.30681.9d"]}, {"label": ["57."], "surname": ["Xiao", "Liu", "Zhou"], "given-names": ["P", "W", "H"], "article-title": ["[Retracted] miR-200b inhibits migration and invasion in non-small cell lung cancer cells via targeting FSCN1"], "source": ["Mol Med Rep"], "year": ["2021"], "volume": ["24"], "issue": ["2"], "fpage": ["1"], "pub-id": ["10.3892/mmr.2021.12218"]}]
{ "acronym": [ "OA", "FLS", "siRNA", "MMPs", "MAPK", "ADAM8", "FBS", "PBS", "ACL", "EDTA", "IHC", "H&E", "DEGs", "GO", "KEGG" ], "definition": [ "Osteoarthritis", "Fibroblast-like synoviocytes", "Small interfering RNA", "Matrix metallomatrix proteinases", "Mitogen-activated protein kinase", "A disintegrin and metalloproteinase domain-containing protein 8", "Fetal bovine serum", "Phosphate buffer saline", "Anterior cruciate ligament injury", "Ethylenediaminetetraacetic acid", "Immunohistochemical", "Hematoxylin and eosin", "Differentially expressed genes", "Gene ontology", "Kyoto encyclopedia of genes and genomes" ] }
59
CC BY
no
2024-01-14 23:43:46
Arthritis Res Ther. 2024 Jan 13; 26:20
oa_package/ff/1a/PMC10787439.tar.gz
PMC10787440
0
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[ "<p id=\"Par1\">Chen et al. recently related the skin autofluorescence (SAF) of Advanced Glycation End-products to subclinical cardiovascular disease in the 3001 participants from the general population (Rotterdam study), with a particularly close relationship for the 413 subjects with diabetes. Because conventional vascular risk factors do not capture the risk in diabetes very well, this relationship may help to select high-risk individuals for the screening of silent myocardial ischemia, which has yet to prove its benefit in randomized controlled trials. Among 477 patients with uncontrolled and/or complicated Type 2 Diabetes, we measured the SAF ten years ago, and we registered new revascularizations during a 54-months follow-up. The patients with SAF &gt; 2.6 Arbitrary units (AUs), the median population value, experienced more revascularizations of the coronary (17/24) and lower-limb arteries (13/17) than patients with a lower SAF, adjusted for age, sex, diabetes duration, vascular complications, and smoking habits: HR 2.17 (95% CI: 1.05–4.48), p = 0.035. The SAF has already been reported to predict cardiovascular events in three cohorts of people with diabetes. We suggest that its measurement may help to improve the performance of the screening before vascular explorations and revascularizations.</p>", "<title>Keywords</title>" ]
[ "<p id=\"Par6\">We were interested in the recent article from Jinluan Chen et al., who related the skin autofluorescence (SAF) to markers of subclinical cardiovascular disease in the Rotterdam study [##REF##38017418##1##]: carotid plaques and intima-media thickness, coronary artery calcifications (CAC), and pulse wave velocity. Besides the scientific interest in the role of Advanced Glycation End-products in cardiovascular disease in the general population, their results may have practical implications for subjects with diabetes.</p>", "<p id=\"Par7\">As mentioned by the authors, the relationship between SAF and subclinical cardiovascular disease was especially close for their 413/3001 participants with diabetes. In Type 2 Diabetes (T2D), the intima-media thickness [##REF##22028278##2##], the pulse wave velocity [##REF##36397444##3##], and the CAC scores [##UREF##0##4##] are predictive of later cardiovascular events, whereas conventional risk factors do not well capture this risk. They may help to identify high-risk individuals with T2D for the screening of myocardial ischemia, as proposed for the CAC score in a position article of the French Societies of Cardiology and Diabetology: screen patients with CAC scores &gt; 400 Arbitrary units (AUs) [##REF##33309203##5##].</p>", "<p id=\"Par8\">Myocardial ischemia is often silent in people with T2D, arguing for this screening. However, randomized controlled trials that tested it have not yet detected a benefit [##REF##33714278##6##]. The selection of high-risk subjects seems therefore critical, and the relationship to subclinical cardiovascular disease makes SAF an interesting candidate as its measurement is simple and non-invasive. As an important objective of the screening is to select subjects who could benefit from a revascularization to prevent a cardiovascular event, the article from Chen prompted us to test whether the SAF related to later revascularizations in our cohort of subjects with T2D, that recently allowed us to show that the SAF predicted Diabetic Foot Ulcers [##REF##37647711##7##].</p>", "<p id=\"Par9\">The characteristics of the 477 subjects are presented in the Table ##TAB##0##1##. They were hospitalized in our diabetology unit from 2009 to 2017 for uncontrolled and/or complicated T2D. All were interviewed, had a clinical examination, and blood and urine samples. To participate in the study, which was approved by the local ethics committee, all the subjects gave their informed consent to the measurement of SAF, the anonymized collection of variables and outcomes from their medical records, and their analysis. As expected, due to our hospital setting, our patients were poorly controlled (HbA1c 8.7 ± 1.8% or 72 ± 14.9 mmol/mol), with high rates of vascular complications.</p>", "<p id=\"Par10\">Forty-one revascularizations were registered during the 54 ± 27 months of follow-up: 24 coronary and 17 lower-limbs. The revascularized patients differed from others for higher rates of vascular complications at baseline, whereas no difference for conventional risk factors (arterial hypertension, dyslipidemia) was significant, except for more frequent smoking habits. The SAF were higher for later revascularized patients than non-revascularized patients (p &lt; 0.001).</p>", "<p id=\"Par11\">The Fig. ##FIG##0##1## depicts revascularization-free survival curves according to a SAF higher vs lower than the median value (2.6 AUs), that differed (Log-Rank: p &lt; 0.001). They similarly differed for coronary (Log-Rank: p = 0.005) and lower-limbs (Log-Rank: p = 0.007) revascularizations. For the 319 subjects without macroangiopathy (defined as previous myocardial infarction, stroke, peripheral revascularization) at baseline, 5 revascularizations were performed and all were in subjects with SAF &gt; 2.6 AUs (Log-Rank: p = 0.008). By Cox regression analysis, a SAF &gt; 2.6 AUs was related to later revascularizations: HR 2.17 (95% CI: 1.05–4.48) p = 0.035, adjusted for age, sex, diabetes duration, smoking, and diabetic vascular complications defined as macroangiopathy, retinopathy and Diabetic Kidney Disease (glomerular filtration rate &lt; 60 ml/min/1.73m<sup>2</sup> and/or albumin excretion rate 30 &gt; mg/24H).</p>", "<p id=\"Par12\">The higher rate of revascularizations among T2D patients with high SAF is well-accorded with its relationship to subclinical cardiovascular disease as reported by Chen. Higher risk of cardiovascular events related to SAF were already reported in three cohort studies [##REF##19274450##8##–##REF##33435948##10##], but they did not specifically address revascularization procedures. Advanced glycation endproducts (AGEs) score measured at the fingertip in patients with cardiovascular disease have been associated with major adverse cardiovascular and cerebrovascular events [##REF##37592261##11##]. Elevated SAF was recently associated with subclinical atherosclerosis in coronary and carotid arteries independently of conventional risk factors [##REF##35196628##12##]. Moreover, both advanced glycation expressed by higher skin autofluorescence or soluble receptor for AGEs (sRAGE) and impaired microvascular reactivity are involved in the pathogenesis of vascular complications in diabetes [##REF##35644724##13##]. We hope that the Rotterdam study team will follow their participants during the next years, to confirm whether the SAF may help to select subjects for further coronary and lower-limbs vascular explorations, and revascularizations if necessary.</p>" ]
[ "<title>Author contributions</title>", "<p>FA researched data and wrote the manuscript. No conflict of interest. GB researched data and reviewed the manuscript. No conflict of interest. NF researched data and reviewed the manuscript. No conflict of interest. AL researched data and reviewed the manuscript. No conflict of interest. LB researched data and reviewed the manuscript. No conflict of interest. M-AB-M researched data and reviewed the manuscript. No conflict of interest. AF researched data and reviewed the manuscript. No conflict of interest. CD researched data and reviewed the manuscript. No conflict of interest. KM researched data and reviewed the manuscript. No conflict of interest. SF researched data and reviewed the manuscript. No conflict of interest. TC researched data and reviewed the manuscript. No conflict of interest. VR is the corresponding author, researched data, performed all the statistical analyses and wrote the manuscript. No conflict of interest. Pr VR is the guarantor of this work.</p>", "<title>Funding</title>", "<p>Dr Ninon Foussard is supported by the Société Francophone du Diabète, the European Foundation for the Study of Diabetes and the Fondation de l’Université de Bordeaux FGLMR/AVAD for her project on the skin autofluorescence “GLYCAGEST”.</p>", "<title>Availability of data and materials</title>", "<p>No datasets were generated or analysed during the current study.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par13\">All the participants gave an informed consent to participate in the study, which was approved by the Comité de Protection des Personnes Sud-Ouest et Outre-Mer III (number: DC 2014/102).</p>", "<title>Consent for publication</title>", "<p id=\"Par14\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par15\">No competing financial interests exist. No conflict of interest and no disclosure exist.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Revascularization-free survival curves in 477 subjects with T2D, according to their SAF higher vas below the median (2.6 AUs). Log-Rank: p &lt; 0.000</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics of the patients with later revascularizations vs patients without</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Whole population</th><th align=\"left\">Indemn of revascularization</th><th align=\"left\">New revascularization</th><th align=\"left\">p</th></tr></thead><tbody><tr><td align=\"left\">N</td><td align=\"left\">477</td><td align=\"left\">436</td><td align=\"left\">41</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Sex (% men)</td><td align=\"left\">56.8%</td><td align=\"left\">55.4%</td><td align=\"left\">71.4%</td><td char=\".\" align=\"char\">0.051</td></tr><tr><td align=\"left\">Age (years)</td><td align=\"left\">62 ± 9</td><td align=\"left\">61 ± 9</td><td align=\"left\">64 ± 9</td><td char=\".\" align=\"char\">0.062</td></tr><tr><td align=\"left\">Duration of diabetes (years)</td><td align=\"left\">14 ± 10</td><td align=\"left\">14 ± 9</td><td align=\"left\">17 ± 10</td><td char=\".\" align=\"char\">0.050</td></tr><tr><td align=\"left\">HbA1c (%)</td><td align=\"left\">8.7 ± 1.8%</td><td align=\"left\">8.7 ± 1.8%</td><td align=\"left\">8.6 ± 1.7%</td><td char=\".\" align=\"char\">0.826</td></tr><tr><td align=\"left\">BMI (kg/m2)</td><td align=\"left\">32.7 ± 6.1</td><td align=\"left\">32.6 ± 6.2</td><td align=\"left\">33.4 ± 5.5</td><td char=\".\" align=\"char\">0.439</td></tr><tr><td align=\"left\"><p>Triglycerides</p><p>(mg/dL, median, IQR)</p></td><td align=\"left\"><p>158</p><p>(112–226)</p></td><td align=\"left\"><p>159</p><p>(113–223)</p></td><td align=\"left\"><p>154</p><p>(106–290)</p></td><td char=\".\" align=\"char\">0.810</td></tr><tr><td align=\"left\">HDL-cholesterol (mg/dL)</td><td align=\"left\">44 ± 13</td><td align=\"left\">44 ± 14</td><td align=\"left\">42 ± 10</td><td char=\".\" align=\"char\">0.309</td></tr><tr><td align=\"left\">LDL-cholesterol (mg/dL)</td><td align=\"left\">105 ± 43</td><td align=\"left\">105 ± 43</td><td align=\"left\">99 ± 38</td><td char=\".\" align=\"char\">0.422</td></tr><tr><td align=\"left\">Treated by a statin (%)</td><td align=\"left\">65.2%</td><td align=\"left\">64.1%</td><td align=\"left\">76.2%</td><td char=\".\" align=\"char\">0.122</td></tr><tr><td align=\"left\">Arterial hypertension (%)</td><td align=\"left\">64.8%</td><td align=\"left\">63.9%</td><td align=\"left\">73.8%</td><td char=\".\" align=\"char\">0.238</td></tr><tr><td align=\"left\">Smoking (%)</td><td align=\"left\">23.1%</td><td align=\"left\">21.4%</td><td align=\"left\">40.5%</td><td char=\".\" align=\"char\">0.011</td></tr><tr><td align=\"left\"><p>Albumin Excretion Rate</p><p>(mg/24H, median, IQR)</p></td><td align=\"left\"><p>15</p><p>(4–62)</p></td><td align=\"left\"><p>14</p><p>(4–47)</p></td><td align=\"left\"><p>53</p><p>(8–360)</p></td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\">Estimated GFR (mL/min/1.73m2)</td><td align=\"left\">82 ± 25</td><td align=\"left\">83 ± 24</td><td align=\"left\">72 ± 28</td><td char=\".\" align=\"char\">0.006</td></tr><tr><td align=\"left\">Macroangiopathy (%)</td><td align=\"left\">31.4%</td><td align=\"left\">27.8%</td><td align=\"left\">69.0%</td><td char=\".\" align=\"char\">0.000</td></tr><tr><td align=\"left\">Retinopathy (%)</td><td align=\"left\">25.8%</td><td align=\"left\">24.4%</td><td align=\"left\">40.5%</td><td char=\".\" align=\"char\">0.027</td></tr><tr><td align=\"left\">Diabetic kidney disease (%)</td><td align=\"left\">43.8%</td><td align=\"left\">41.4%</td><td align=\"left\">69.0%</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\">Skin autofluorescence (AU)</td><td align=\"left\">2.67 ± 0.64</td><td align=\"left\">2.64 ± 0.62</td><td align=\"left\">3.00 ± 0.73</td><td char=\".\" align=\"char\">0.000</td></tr></tbody></table></table-wrap>" ]
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[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2024_2121_Fig1_HTML\" id=\"MO1\"/>" ]
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[{"label": ["4."], "surname": ["Kramer", "Zinman", "Gross", "Canani", "Rodrigues", "Azevedo"], "given-names": ["CK", "B", "JL", "LH", "TC", "MJ"], "article-title": ["Coronary artery calcium score prediction of all cause mortality and cardiovascular events in people with type 2 diabetes: systematic review and meta-analysis"], "source": ["BMJ"], "year": ["2013"], "volume": ["25"], "issue": ["346"], "fpage": ["f1654"], "pub-id": ["10.1136/bmj.f1654"]}]
{ "acronym": [ "AU", "CAC", "SAF", "T2D" ], "definition": [ "Arbitrary Units", "Coronary Artery Calcifications", "Skin autofluorescence", "Type 2 Diabetes" ] }
13
CC BY
no
2024-01-14 23:43:46
Cardiovasc Diabetol. 2024 Jan 13; 23:32
oa_package/a6/fc/PMC10787440.tar.gz
PMC10787441
0
[ "<title>Introduction</title>", "<p id=\"Par7\">Congestive heart failure (CHF) is a leading cause of hospitalization, imposing a substantial burden on the global healthcare system [##REF##33069326##1##]. CHF patients face a high mortality rate, with 30–50% succumbing or requiring rehospitalization within 60 days of admission, and a subsequent 40–50% mortality within 5 years [##REF##22009099##2##]. CHF is characterized by fluid accumulation in systemic or pulmonary circulation and reduced effective circulating volume, resulting in inadequate organ perfusion. In this context, the occurrence of acute kidney injury (AKI) in CHF patients is not uncommon, with more than 40% of CHF patients manifesting coexisting renal dysfunction [##REF##27573728##3##]. Notably, AKI significantly increases the risk of both in-hospital and one-year mortality by 5–7 times when compared to CHF patients without AKI [##REF##24164864##4##, ##REF##25951761##5##]. Recognizing CHF patients at high AKI risk early is crucial for timely interventions and vigilant care.</p>", "<p id=\"Par8\">Stress hyperglycemia, denoting a transient increase in blood glucose levels induced by physiological or psychological stress, is frequently observed in individuals experiencing acute HF [##REF##35901906##6##]. Previous studies have demonstrated that stress hyperglycemia serves as a significant risk factor of adverse outcomes [##REF##25534479##7##, ##UREF##0##8##]. However, ABG levels can be influenced by chronic glycemic conditions, limiting their ability to differentiate an acute rise in blood glucose. To better gauge a patient’s actual blood glucose status, the stress hyperglycemia ratio (SHR) has been proposed [##REF##26485219##9##]. It calculates the ABG while considering the individual’s average glycemic status. Several studies have suggested that SHR is highly associated with an increased risk of mortality in patients with acute HF [##REF##37495967##10##], coronary artery disease [##REF##36261839##11##], and stroke [##REF##35084107##12##]. Furthermore, SHR exhibited a significant association with AKI in critically ill patients. Ülger’s study reported that an SHR greater than 1.47 independently served as a risk factor for AKI [##REF##37160486##13##]. However, it remains uncertain whether the SHR is linked to AKI in patients with CHF. This study is designed to explore the relationship between SHR and in-hospital AKI among CHF patients admitted to critical care units.</p>" ]
[ "<title>Methods</title>", "<title>Data resource</title>", "<p id=\"Par9\">Data of this study were collected from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.0), a comprehensive US-based database. MIMIC-IV comprises extensive health-related data from 76,943 ICU admissions, patients received critical care at the Beth Israel Deaconess Medical Center between 2008 and 2019 [##REF##36596836##14##]. The author (Le Li) had authorized access to the database with a designated Record ID of 35,965,741. To ensure patient privacy protection, all personally identifiable information has been de-identified. Since our study involved the analysis of a third-party, anonymized, publicly available database that had previously obtained institutional review board (IRB) approval, our institution’s IRB approval was considered exempt.</p>", "<title>Study design and participants</title>", "<p id=\"Par10\">This is a retrospective observational cohort study based on a large-scale critical care database. Patients admitted to hospital due to CHF were included in this study. In the present study, congestive HF was diagnosed by clinicians based on the guideline of HF [##REF##16160202##15##]. Based on the medical history, patients were divided into acute HF, chronic HF, and acute exacerbation in chronic HF. Patients were excluded if they were under 18 years old, without data of blood glucose or glycosylated hemoglobin A1c (HbA1c). Ultimately, a total of 8268 patients were included in the analysis (Fig. ##FIG##0##1##). Patients were stratified into seven groups based on their SHR levels, with intervals of 0.25, spanning from &lt; 0.50 to ≥ 1.75.</p>", "<p id=\"Par11\">\n\n</p>", "<title>Data collection</title>", "<p id=\"Par12\">In this study, we gathered data on patient demographics (age, sex, weight), prevalent comorbidities (including diabetes mellitus [DM], hypertension, atrial fibrillation [AF], myocardial infarction [MI], chronic kidney disease [CKD], non-ischemic cardiomyopathy [NICM], and others), laboratory parameters (such as serum creatinine [SCr], blood urea nitrogen [BUN]), medication and interventions (comprising insulin, vasopressors, diuretics, mechanical ventilation [MV], replace renal treatment [RRT]), and various pertinent variables. The diagnosis of AKI adhered to clinical practice guidelines, which include criteria such as a ≥ 0.3 mg/dL (or ≥ 26.5 µmol/L) increase in SCr within 48 h, a rise in SCr to 1.5 times the baseline level within 7 days, and a patient urine output (UO) ≤ 0.5 mL/kg/h for 6 h. Further details about AKI stage definitions can be referenced in the guidelines [##REF##22890468##16##]. The SHR was calculated using the formula: SHR = ABG (mg/dL) / (28.7 × HbA1c (%)-46.7). Glucose and HbA1c values were sourced from the initial records post-ICU admission. Comorbidities were determined via ICD-9 or ICD-10 codes. Information regarding hospitalization within the first 24 h after ICU admission was meticulously extracted from the MIMIC-IV database through PostgreSQL (version 14.0). This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational studies [##REF##18064739##17##].</p>", "<title>Endpoints</title>", "<p id=\"Par13\">The primary endpoint in this study was the occurrence of AKI during the hospitalization period. Secondary endpoints encompassed in-hospital mortality and one-year mortality.</p>", "<title>Statistical analysis</title>", "<p id=\"Par14\">Statistical analyses were executed using R software (version 4.1.0), with statistical significance set at a two-sided <italic>P</italic>-value of less than 0.05. Categorical variables were represented as proportions, while continuous variables were delineated as mean (standard deviation, SD) or median (interquartile range, IQR). Continuous variables were compared using the Wilcoxon test, while categorical variables were analyzed using the chi-square test.</p>", "<p id=\"Par15\">To explore the relationships between different levels of SHR and the probabilities of AKI and in-hospital mortality, multivariate logistic models were employed. Cox regression models were utilized to investigate the association between various SHR levels and one-year mortality. Effect sizes were quantified as odds ratios (ORs) or hazard ratios (HRs), accompanied by their respective 95% confidence intervals (CIs) for logistic or Cox models, respectively. In addition, Kaplan-Meier survival analysis was conducted to assess one-year mortality rates within SHR-defined groups, with inter-group disparities assessed using the log-rank test. Furthermore, the connection between SHR levels and mortality risk was elucidated through the application of restricted cubic spline (RCS) curves, with the reference group defined as the SHR interval demonstrating the lowest incidence rate.</p>", "<p id=\"Par16\">The multivariate logistic and Cox regression analyses were adjusted for pertinent baseline factors, encompassing demographic parameters (age, sex), urine output, medical history (hypertension, DM, AF, acute HF, AMI, old myocardial infarction [OMI], stroke, NICM, and CKD), laboratory tests (Nt-pro BNP, SCr, BUN and HbA1c), and interventions (history of insulin use, vasopressors, loop diuretics, MV, and RRT). Furthermore, subgroup analyses were conducted to delve deeper into the data, stratifying outcomes based on age, gender, and the presence of comorbidities, such as DM, hypertension, CKD, acute HF, AMI, and NICM. These subgroup analyses were performed using comprehensive regression models adjusted for potential confounding factors.</p>" ]
[ "<title>Results</title>", "<title>Baseline characteristics</title>", "<p id=\"Par17\">A total of 8268 CHF patients were enrolled in this study, with a median age of 72.4 years (interquartile range, 62.9–81.5), and 4,665 (56.4%) were male. Among these patients, 5564 (67.3%) presented with acute heart failure. Moreover, 4687 (56.7%) were diagnosed with type 2 diabetes mellitus, and 3632 (43.9%) received insulin therapy. The participants were stratified into seven distinct groups (groups 1–7) based on their SHR levels: &lt; 0.50 (n = 286), 0.50–0.74 (n = 1,018), 0.75–0.99 (n = 2854), 1.00-1.24 (n = 1904), 1.25–1.49 (n = 996), 1.50–1.74 (n = 530), and ≥ 1.75 (n = 680). The baseline characteristics of these seven groups are summarized in Table ##TAB##0##1##. Furthermore, for additional context, Table ##SUPPL##0##S1## provides a comparison of baseline characteristics between patients with AKI and those without AKI during the in-hospital period.</p>", "<p id=\"Par18\">\n\n</p>", "<title>Clinical outcomes</title>", "<p id=\"Par19\">In this study, AKI occurred in 5,221 (63.1%) patients during their hospitalization. Group 3 (SHR: 0.75–0.99) exhibited the lowest AKI rate at 56.9%, and was thus chosen as the reference group. In the unadjusted model, the remaining groups had a heightened risk of AKI, with ORs of 3.85 (95% CI: 2.79–5.30), 1.66 (95% CI: 1.43–1.94), 1.16 (95% CI: 1.04–1.31), 1.22 (95% CI: 1.05–1.42), 1.57 (95% CI: 1.29–1.92), and 2.67 (95% CI: 2.20–3.25) for Groups 1, 2, 4, 5, 6, and 7, respectively. This U-shaped association persisted even after adjusting for confounding variables, resulting in ORs of 1.97 (95% CI: 1.35–2.88), 1.21 (95% CI: 1.01–1.44), 1.14 (95% CI: 0.99–1.31), 1.14 (95% CI: 0.96–1.35), 1.32 (95% CI: 1.05–1.66), and 2.34 (95% CI: 1.86–2.93) for Groups 1, 2, 4, 5, 6, and 7, respectively (Fig. ##FIG##1##2##). Given the distinct management and clinical outcomes associated with AKI stage 1 and stage 2–3, we conducted logistic regressions to assess the relationship between SHR and AKI stage 2/3. Our analysis confirmed a U-shaped association between them (Figure ##SUPPL##0##S1##). Furthermore, we observed a strong association between SHR and in-hospital mortality, with adjusted ORs of 1.56 (95% CI: 1.04 − 2.35), 1.33 (95% CI: 1.03–1.71), 1.10 (95% CI: 0.89–1.36), 1.34 (95% CI: 1.04–1.72), 1.41 (95% CI: 1.03–1.94), and 1.93 (95% CI: 1.48 − 2.52) for Groups 1, 2, 4, 5, 6, and 7, respectively. This relationship was similarly observed in the case of one-year mortality (Table ##TAB##1##2##). The Kaplan–Meier curves in Fig. ##FIG##2##3## illustrate that patient with an SHR falling within the 0.75–0.99 range experienced the lowest one-year mortality rate (Log-rank <italic>P</italic> &lt; 0.001).</p>", "<p id=\"Par20\">\n\n</p>", "<p id=\"Par21\">\n\n</p>", "<p id=\"Par22\">\n\n</p>", "<p id=\"Par23\">Additionally, we conducted the RCS analysis to provide a comprehensive examination of the continuous relationship between SHR and the occurrence of AKI. As depicted in Fig. ##FIG##3##4##, this graphical representation illustrates the U-shaped pattern in the association between SHR and AKI. This pattern is consistently observable in both the unadjusted and adjusted models. Notably, the optimal point in this curve, indicative of the lowest risk for all-cause mortality, was precisely identified at a specific SHR level of 0.98, aligning with the 0.75–0.99 interval (which was designated as the reference group). Upon standardizing SHR, we observed that when SHR falls below 0.98, the odds ratio for predicting AKI per standard deviation increase was 0.58 (95% CI: 0.45 to 0.75). Conversely, when SHR exceeded 0.98, the odds ratio for predicting AKI per standard deviation increase was 1.32 (95% CI: 1.22 to 1.46) based on the adjusted model. The RCS analysis of SHR and AKI stage 2/3 also illustrated the U-shaped association (Figure ##SUPPL##0##S2##).</p>", "<p id=\"Par24\">\n\n</p>", "<title>Subgroup analysis</title>", "<p id=\"Par25\">Extensive analyses were conducted to investigate the intricate association between the SHR and the development of AKI within diverse subpopulations. Rigorously adjusted for potential confounding factors, our investigation consistently revealed a recurrent U-shaped relationship across all the subgroups examined, as comprehensively presented in Table ##TAB##2##3##. Significantly, our examination unveiled notable interactions between SHR and specific variables, including gender, DM, CKD, and acute HF (all P for interaction &lt; 0.05). For instance, it is noteworthy that non-diabetic patients exhibited a relatively elevated risk of in-hospital mortality compared to patients with CKD. Furthermore, we expanded our exploration by conducting meticulous RCS analyses within these subgroups, taking into consideration gender, DM, CKD, and acute HF. Impressively, our thorough investigation consistently disclosed a U-shaped relationship between SHR, evaluated on a continuous scale, and the incidence of AKI in all the scrutinized subgroups (Figure ##SUPPL##0##S3##-##SUPPL##0##6##).</p>", "<p id=\"Par26\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par27\">To the best of our knowledge, this study marks the first comprehensive investigation into the association between SHR and AKI in patients with CHF. Our findings have revealed a distinctive U-shaped correlation between SHR and the occurrence of AKI within this patient cohort. Specifically, both elevated and reduced SHR values demonstrate a significant connection with an increased susceptibility to AKI during hospitalization, with a turning point for SHR at 0.98. Furthermore, our research has illuminated SHR as a potential risk factor for all-cause mortality in this particular patient population.</p>", "<p id=\"Par28\">The concept of SHR underscores a relative acute increase in glycemia when compared to the individual’s previous glycemic status in response to a stress reaction or critical illness [##REF##26485219##9##]. Recently, we have demonstrated the strong association of SHR and all-cause mortality in patients with critical illness [##REF##37833697##18##]. In the study, we enrolled 8,978 patients with critical illness and identified a U-shaped relationship between SHR and mortality. Notably, the SHR falling within the range of 0.75 to 0.99 exhibited the lowest mortality rates. For each increment of 0.25 in the SHR within this range, the risk of in-hospital mortality increased by 1.34-fold (OR: 1.34, 95% CI: 1.25–1.44). Conversely, a decrease of 0.25 in SHR within the same 0.75–0.99 range elevated the risk by 1.38-fold (OR: 1.38, 95% CI: 1.10–1.75). In addition, Wei et al. suggested that SHR was significantly associated with an increased risk of in-hospital death and all-cause mortality in ST-element myocardial infarction patients treated with percutaneous coronary intervention [##REF##37046267##19##]. In this study, we also found that SHR was highly associated with all-cause mortality in CHF patients. However, the relationship between SHR and AKI in this population remains unclear.</p>", "<p id=\"Par29\">CHF is characterized by the presence of congestion within the systemic or pulmonary circulation, which results in a reduction in effective circulating volume, ultimately leading to inadequate organ perfusion. Conversely, a decline in the glomerular filtration rate, as seen in AKI, augments the cardiac volume load and exacerbates cardiac dysfunction. These intricate and reciprocal interactions between the kidney and heart are collectively referred to as cardiorenal syndrome [##REF##30852913##20##]. Multiple studies have provided evidence that acute hyperglycemia independently predicts the occurrence of AKI in specific patient populations [##REF##15939812##21##, ##REF##10711923##22##]. Recently, Gao et al. suggested that the novel index SHR serves as a superior predictor of AKI compared to ABG in a cohort of 1,215 diabetic patients with AMI [##REF##33781208##23##]. In this study, we have firstly provided the report highlighting a robust association between the SHR and the occurrence of AKI in patients with CHF. This association, marked by a U-shaped pattern, not only emphasizes critical clinical implications but also provides vital insights for optimizing personalized risk assessment strategies, directing targeted interventions, and laying the groundwork for future research to unravel underlying mechanisms. The underlying mechanisms of the U-shaped association remains unclear. Some findings may help to explain the mechanisms. Firstly, stress hyperglycemia is driven by the hypothalamic-pituitary-adrenal axis and the sympathoadrenal system to reestablish homeostasis amidst intense stress [##REF##23470218##24##]. Some studies suggested that mild-to-moderate stress hyperglycemia is a protective factor during stress [##REF##23470218##24##]. McNamara et al. have discovered that stress hyperglycemia may enhance cardiac output and contribute to improved survival [##REF##5410974##25##]. Additionally, stress hyperglycemia has the capacity to increase the expression of cell survival factors, notably vascular endothelial growth factor and hypoxia-inducible factor-1α. Consequently, this results in a decrease in cellular apoptosis, a reduction in infarction size, and improvements in cardiac systolic function within a rat model of MI [##REF##20406798##26##]. Furthermore, stress hyperglycemia leads to the establishment of a new glucose equilibrium, creating a heightened blood glucose diffusion gradient that optimizes cellular glucose uptake, particularly in the presence of microvascular flow disturbances. Consequently, moderate hyperglycemia maximizes cellular glucose uptake while mitigating the risk of hyperosmolarity [##REF##20727232##27##].</p>", "<p id=\"Par30\">Furthermore, we identified the inflection point of SHR for poor prognosis to be 0.98. Consequently, an SHR greater than 0.98 is indicative of stress hyperglycemia. In contrast, SHR values below 0.98 suggest the presence of chronic hyperglycemia (as indicated by high HbA1c) with either effective current glycemic control or the potential for glycemic control that exceeds the target levels set by ABG. This U-shaped association suggested that the risk increases in all situations that depart from the linear correlation between ABG and HbA1c in both directions.</p>", "<title>Limitations</title>", "<p id=\"Par31\">While we have provided the initial evidence of a U-shaped association between SHR and AKI in CHF patients, it is essential to acknowledge certain limitations in our study. Firstly, this was a retrospective observational study conducted at a single center, which precludes us from establishing a definitive causal association between this factor and clinical outcomes. Secondly, the data for this study were derived from a third-party public database, which led to the exclusion of certain covariates, including left ventricular ejection fraction, from the multivariable regression models. Thirdly, while our primary focus was on the CHF population, it is worth noting that the patients in this cohort were primarily hospitalized for critical illness, which may limit the generalizability of our findings to the broader population. Therefore, the findings of this study should be interpreted with caution.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par32\">In conclusion, our study has unveiled a U-shaped association between SHR and AKI in patients with CHF. Notably, both low and high SHR values exhibited significant associations with AKI and mortality in this specific patient population, underscoring the paramount importance of maintaining optimal glycemic control in this clinical context. Furthermore, the inflection point for SHR concerning AKI was precisely identified at 0.98, marking a critical threshold for risk assessment and intervention. Future research endeavors should aim for larger-scale, multicenter, and prospective investigations to further substantiate our findings.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The stress hyperglycemia ratio (SHR) has been demonstrated as an independent risk factor for acute kidney injury (AKI) in certain populations. However, this relationship in patients with congestive heart failure (CHF) remains unclear. Our study sought to elucidate the relationship between SHR and AKI in patients with CHF.</p>", "<title>Methods</title>", "<p id=\"Par2\">A total of 8268 patients with CHF were included in this study. We categorized SHR into distinct groups and evaluated its association with mortality through logistic or Cox regression analyses. Additionally, we applied the restricted cubic spline (RCS) analysis to explore the relationship between SHR as a continuous variable and the occurrence of AKI. The primary outcome of interest in this investigation was the incidence of AKI during hospitalization.</p>", "<title>Results</title>", "<p id=\"Par3\">Within this patient cohort, a total of 5,221 (63.1%) patients experienced AKI during their hospital stay. Upon adjusting for potential confounding variables, we identified a U-shaped correlation between SHR and the occurrence of AKI, with an inflection point at 0.98. When the SHR exceeded 0.98, for each standard deviation (SD) increase, the risk of AKI was augmented by 1.32-fold (odds ratio [OR]: 1.32, 95% CI: 1.22 to 1.46). Conversely, when SHR was below 0.98, each SD decrease was associated with a pronounced increase in the risk of AKI.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Our study reveals a U-shaped relationship between SHR and AKI in patients with CHF. Notably, we identified an inflection point at an SHR value of 0.98, signifying a critical threshold for evaluating AKI in this population.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02105-x.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>None.</p>", "<title>Author contributions</title>", "<p>This study was designed by LL and LGD. LHZ, LMW, ZCH, LML were responsible for data collation and statistical analysis. LL wrote the first draft. YY reviewed and checked the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study was supported by Medical and Health Technology Innovation Project of Chinese Academy of Medical Sciences (2021-CXGC09-1).</p>", "<title>Data availability</title>", "<p>The datasets used during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par34\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par35\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par33\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow chart. CHF: congestive heart failure</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The relationship between SHR and AKI. OR: odd ratio; CI: confidence interval</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Kaplan–Meier analysis for 1-year mortality of distinct groups</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Restricted cubic spline analysis. The U-shaped association between SHR and acute kidney injury was observed in both (<bold>A</bold>) unadjusted model and (<bold>B</bold>) adjusted model</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics grouped according to SHR levels</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variables</th><th align=\"left\" rowspan=\"2\">Total</th><th align=\"left\" colspan=\"7\">Groups (group 1–7) divided by SHR</th><th align=\"left\" rowspan=\"2\"><italic>P</italic> value</th></tr><tr><th align=\"left\">&lt; 0.50</th><th align=\"left\">0.50–0.74</th><th align=\"left\">0.75–0.99</th><th align=\"left\">1.00–1.24</th><th align=\"left\">1.25–1.49</th><th align=\"left\">1.50–1.74</th><th align=\"left\">≥ 1.75</th></tr></thead><tbody><tr><td align=\"left\">Sample, %</td><td align=\"left\">8268 (100)</td><td align=\"left\">286 (3.5)</td><td align=\"left\">1018 (12.3)</td><td align=\"left\">2854 (34.5)</td><td align=\"left\">1904 (23.0)</td><td align=\"left\">996 (12.0)</td><td align=\"left\">530 (6.4)</td><td align=\"left\">680 (8.2)</td><td align=\"left\"/></tr><tr><td align=\"left\">Age, year</td><td align=\"left\">72.4 (62.9–81.5)</td><td align=\"left\">68.1 (58.2–76.1)</td><td align=\"left\">72.3 (62.5–81.4)</td><td align=\"left\">73.3 (63.3–82.1)</td><td align=\"left\">72.8 (63.4–41.7)</td><td align=\"left\">72.9 (63.6–82.2)</td><td align=\"left\">72.1 (65.1–80.1)</td><td align=\"left\">70.5 (61.2–79.4)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Male, %</td><td align=\"left\">4665 (56.4)</td><td align=\"left\">163 (57.0)</td><td align=\"left\">579 (56.9)</td><td align=\"left\">1646 (57. 7)</td><td align=\"left\">1079 (56. 7)</td><td align=\"left\">535 (53.7)</td><td align=\"left\">281 (53.0)</td><td align=\"left\">382 (56.2)</td><td align=\"left\">0.279</td></tr><tr><td align=\"left\">Vital Signs</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> SBP, mmHg</td><td align=\"left\">114 (106–127)</td><td align=\"left\">116 (106–131)</td><td align=\"left\">114(105–126)</td><td align=\"left\">114 (1056 − 125)</td><td align=\"left\">115 (106–126)</td><td align=\"left\">115(106–129)</td><td align=\"left\">115 (107–128)</td><td align=\"left\">115 (106–128)</td><td align=\"left\">0.121</td></tr><tr><td align=\"left\"> Heart rate, bpm</td><td align=\"left\">82 (73–92)</td><td align=\"left\">81 (71–91)</td><td align=\"left\">81(72–91)</td><td align=\"left\">81 (72–90)</td><td align=\"left\">82 (73–92)</td><td align=\"left\">83 (74–93</td><td align=\"left\">85 (76–95)</td><td align=\"left\">84 (73–94)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> Temperature, ℃</td><td align=\"left\">36.7 (36.5–37.0)</td><td align=\"left\">36.7 (36.4–36.9)</td><td align=\"left\">36.7 (36.5–36.9)</td><td align=\"left\">36.7 (36.5–37.0)</td><td align=\"left\">36.7 (36.5–37.0)</td><td align=\"left\">36.8 (36.6–37.0)</td><td align=\"left\">36.8 (36.6–37.0)</td><td align=\"left\">36.8 (36.6–37.0)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> RR, bpm</td><td align=\"left\">19 (17–21)</td><td align=\"left\">18 (16–20)</td><td align=\"left\">18 (17–21)</td><td align=\"left\">19 (17–21)</td><td align=\"left\">19 (17–22)</td><td align=\"left\">19 (17–22)</td><td align=\"left\">19 (17–22)</td><td align=\"left\">20 (17–22)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Comorbidities</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Acute HF, %</td><td align=\"left\">5564 (67.3)</td><td align=\"left\">205 (71.7)</td><td align=\"left\">708 (69.6)</td><td align=\"left\">1787 (62.6)</td><td align=\"left\">1281 (67.3)</td><td align=\"left\">703 (70.6)</td><td align=\"left\">382 (72.1)</td><td align=\"left\">498 (73.2)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> Hypertension,%</td><td align=\"left\">5708 (69.0)</td><td align=\"left\">195 (68.2)</td><td align=\"left\">726 (71.3)</td><td align=\"left\">1974 (69.2)</td><td align=\"left\">1323 (69.5)</td><td align=\"left\">668 (67.1)</td><td align=\"left\">369 (69.6)</td><td align=\"left\">453 (66.6)</td><td align=\"left\">0.367</td></tr><tr><td align=\"left\"> AF, %</td><td align=\"left\">4669 (56.5)</td><td align=\"left\">148 (51.8)</td><td align=\"left\">589 (57.9)</td><td align=\"left\">1681 (58.9)</td><td align=\"left\">1078 (56.6)</td><td align=\"left\">537 (53.9)</td><td align=\"left\">295 (55.7)</td><td align=\"left\">341 (50.2)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> AMI, %</td><td align=\"left\">1823 (22.1)</td><td align=\"left\">63 (22.0)</td><td align=\"left\">207 (20.3)</td><td align=\"left\">491 (17.2)</td><td align=\"left\">422 (22.2)</td><td align=\"left\">253 (25.4)</td><td align=\"left\">160 (30.2)</td><td align=\"left\">227 (33.4)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> OMI, %</td><td align=\"left\">2518 (30.5)</td><td align=\"left\">108 (37.8)</td><td align=\"left\">325 (31.9)</td><td align=\"left\">815 (28.6)</td><td align=\"left\">557 (29.3)</td><td align=\"left\">299 (30.0)</td><td align=\"left\">182 (34.3)</td><td align=\"left\">232 (34.1)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> NICM, %</td><td align=\"left\">1171 (14.16)</td><td align=\"left\">42 (14.7)</td><td align=\"left\">166 (16.3)</td><td align=\"left\">383 (13.4)</td><td align=\"left\">249 (13.1)</td><td align=\"left\">141 (14.2</td><td align=\"left\">79 (14.9)</td><td align=\"left\">111 (16.3)</td><td align=\"left\">0.129</td></tr><tr><td align=\"left\"> T2DM, %</td><td align=\"left\">4687 (56.7)</td><td align=\"left\">272 (95.1)</td><td align=\"left\">703 (69.1)</td><td align=\"left\">1252 (43.9)</td><td align=\"left\">970 (51.0)</td><td align=\"left\">596 (60.0)</td><td align=\"left\">374 (70.6)</td><td align=\"left\">520 (76.5)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> Stroke, %</td><td align=\"left\">2764 (33.4)</td><td align=\"left\">90 (31.5)</td><td align=\"left\">344 (33.8)</td><td align=\"left\">969 (33.9)</td><td align=\"left\">625 (32.8)</td><td align=\"left\">340 (34.1)</td><td align=\"left\">167 (31.5)</td><td align=\"left\">229 (33.7)</td><td align=\"left\">0.886</td></tr><tr><td align=\"left\"> CKD, %</td><td align=\"left\">4211 (50.9)</td><td align=\"left\">228 (79.7)</td><td align=\"left\">598 (58.7)</td><td align=\"left\">1326 (46.5)</td><td align=\"left\">899 (47.2)</td><td align=\"left\">472 (47.4)</td><td align=\"left\">286 (54.0)</td><td align=\"left\">402 (59.1)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Laboratory tests</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> NT-pro BNP, pg/mL</td><td align=\"left\"><p>2482</p><p>(821–6745)</p></td><td align=\"left\"><p>3061</p><p>(922-10085)</p></td><td align=\"left\"><p>2465</p><p>(787–6743)</p></td><td align=\"left\"><p>2538</p><p>(874–6712)</p></td><td align=\"left\"><p>2372</p><p>(833–6138)</p></td><td align=\"left\"><p>2464</p><p>(834–7020)</p></td><td align=\"left\"><p>2424</p><p>(720–7906)</p></td><td align=\"left\"><p>2575</p><p>(750–7428)</p></td><td align=\"left\">0.490</td></tr><tr><td align=\"left\"> SCr, mg/dL</td><td align=\"left\">1.1 (0.8–1.5)</td><td align=\"left\">1.30 (0.9–2.1)</td><td align=\"left\">1.1 (0.9–1.6)</td><td align=\"left\">1.1 (0.8–1.4)</td><td align=\"left\">1.1 (0.8–1.4)</td><td align=\"left\">1.1 (0.8–1.5)</td><td align=\"left\">1.1 (0.9–1.6)</td><td align=\"left\">1.3 (0.9–1.8)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> BUN, mg/dL</td><td align=\"left\">21 (15–32)</td><td align=\"left\">25 (17–39)</td><td align=\"left\">22 (15–33)</td><td align=\"left\">20 (15–30)</td><td align=\"left\">21 (15–31)</td><td align=\"left\">21 (15–32)</td><td align=\"left\">23 (16–35)</td><td align=\"left\">25 (17–39)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> Glucose, mg/dL</td><td align=\"left\">128 (103–176)</td><td align=\"left\">75 (60–97)</td><td align=\"left\">94 (83–116)</td><td align=\"left\">108 (98–124)</td><td align=\"left\">136 (121–160)</td><td align=\"left\">171 (149–206)</td><td align=\"left\">211 (183–254)</td><td align=\"left\">303 (246–382)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> HbA1c, %</td><td align=\"left\">6.1 (5.6-7.0)</td><td align=\"left\">8.6 (7.2–10.6)</td><td align=\"left\">6.6 (6.0–8.0)</td><td align=\"left\">5.9 (5.6–6.5)</td><td align=\"left\">5.9 (5.5–6.7)</td><td align=\"left\">6.0 (5.5–6.9)</td><td align=\"left\">6.2 (5.6–7.1)</td><td align=\"left\">6.4 (5.7–7.4)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Medical History</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Insulin use, %</td><td align=\"left\">3445 (41.7)</td><td align=\"left\">222 (77.6)</td><td align=\"left\">546 (53.6)</td><td align=\"left\">931 (32.6)</td><td align=\"left\">697 (36.6)</td><td align=\"left\">419 (42.1)</td><td align=\"left\">260 (49.1)</td><td align=\"left\">370 (54.4)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> LD use, %</td><td align=\"left\">7565 (91.5)</td><td align=\"left\">266 (93.0)</td><td align=\"left\">944 (92.7)</td><td align=\"left\">2631 (92.2)</td><td align=\"left\">1728 (90.8)</td><td align=\"left\">905 (90.9)</td><td align=\"left\">482 (90.9)</td><td align=\"left\">609 (89.6)</td><td align=\"left\">0.128</td></tr><tr><td align=\"left\">  Vasopressor, %</td><td align=\"left\">3632 (43.9)</td><td align=\"left\">111 (38.8)</td><td align=\"left\">429 (42.1)</td><td align=\"left\">1324 (46.4)</td><td align=\"left\">801 (42.1)</td><td align=\"left\">442 (44.4)</td><td align=\"left\">220 (41.5)</td><td align=\"left\">305 (44.9)</td><td align=\"left\">0.016</td></tr><tr><td align=\"left\">  MV, %</td><td align=\"left\">6741 (81.5)</td><td align=\"left\">222 (77.6)</td><td align=\"left\">806 (79.2)</td><td align=\"left\">2331 (81.7)</td><td align=\"left\">1557 (81.8)</td><td align=\"left\">829 (83.2)</td><td align=\"left\">434 (81.9)</td><td align=\"left\">562 (82.7)</td><td align=\"left\">0.158</td></tr><tr><td align=\"left\"> RRT 1st 24 h, %</td><td align=\"left\">491 (5.9)</td><td align=\"left\">45 (15.7)</td><td align=\"left\">71 (7.0)</td><td align=\"left\">125 (4.4)</td><td align=\"left\">102 (5.4)</td><td align=\"left\">50 (5.0)</td><td align=\"left\">40 (7.6)</td><td align=\"left\">58 (8.5)</td><td align=\"left\">&lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Cox regression and logistic regression analyses for different end points</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" rowspan=\"2\">Events/total</th><th align=\"left\" colspan=\"2\">Model 1</th><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"2\">Model 2</th><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"2\">Model 3</th></tr><tr><th align=\"left\">Effect size<break/>(95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">Effect size<break/>(95% CI)</th><th align=\"left\"><italic>P</italic> value</th><th align=\"left\">Effect size<break/>(95% CI)</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\">\n<bold>In-hospital mortality</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 0.50</td><td align=\"left\">36/286</td><td align=\"left\">1.71 (1.17 − 2.48)</td><td align=\"left\">0.005</td><td align=\"left\"/><td align=\"left\">1.87 (1.28 − 2.73)</td><td align=\"left\">0.001</td><td align=\"left\"/><td align=\"left\">1.56 (1.04 − 2.35)</td><td align=\"left\">0.033</td></tr><tr><td align=\"left\">0.50–0.74</td><td align=\"left\">107/1018</td><td align=\"left\">1.39 (1.09–1.77)</td><td align=\"left\">0.007</td><td align=\"left\"/><td align=\"left\">1.42 (1.11–1.81)</td><td align=\"left\">0.005</td><td align=\"left\"/><td align=\"left\">1.33 (1.03–1.71)</td><td align=\"left\">0.029</td></tr><tr><td align=\"left\">0.75–0.99</td><td align=\"left\">222/2854</td><td align=\"left\">Ref</td><td align=\"left\">–</td><td align=\"left\"/><td align=\"left\">Ref</td><td align=\"left\">–</td><td align=\"left\"/><td align=\"left\">Ref</td><td align=\"left\">–</td></tr><tr><td align=\"left\">1.00–1.24</td><td align=\"left\">165/1904</td><td align=\"left\">1.12 (0.91–1.39)</td><td align=\"left\">0.273</td><td align=\"left\"/><td align=\"left\">1.13 (0.91–1.39)</td><td align=\"left\">0.272</td><td align=\"left\"/><td align=\"left\">1.10 (0.89–1.36)</td><td align=\"left\">0.378</td></tr><tr><td align=\"left\">1.25–1.49</td><td align=\"left\">103/996</td><td align=\"left\">1.37 (1.07–1.75)</td><td align=\"left\">0.013</td><td align=\"left\"/><td align=\"left\">1.37 (1.07–1.75)</td><td align=\"left\">0.012</td><td align=\"left\"/><td align=\"left\">1.34 (1.04–1.72)</td><td align=\"left\">0.024</td></tr><tr><td align=\"left\">1.50–1.74</td><td align=\"left\">59/530</td><td align=\"left\">1.49 (1.10 − 2.01)</td><td align=\"left\">0.011</td><td align=\"left\"/><td align=\"left\">1.52 (1.12 − 2.06)</td><td align=\"left\">0.007</td><td align=\"left\"/><td align=\"left\">1.41 (1.03–1.94)</td><td align=\"left\">0.030</td></tr><tr><td align=\"left\">≥ 1.75</td><td align=\"left\">100/680</td><td align=\"left\">2.04 (1.59 − 2.63)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.87 (1.28 − 2.73)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.93 (1.48 − 2.52)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">\n<bold>One-year mortality</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">&lt; 0.50</td><td align=\"left\">160/286</td><td align=\"left\">2.19 (1.71 − 2.80)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">2.70 (2.10–3.48)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.69 (1.28 − 2.24)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">0.50–0.74</td><td align=\"left\">483/1018</td><td align=\"left\">1.56 (1.35–1.80)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.65 (1.42–1.92)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.37 (1.17–1.61)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">0.75–0.99</td><td align=\"left\">1047/2854</td><td align=\"left\">Ref</td><td align=\"left\">–</td><td align=\"left\"/><td align=\"left\">Ref</td><td align=\"left\">–</td><td align=\"left\"/><td align=\"left\">Ref</td><td align=\"left\">–</td></tr><tr><td align=\"left\">1.00–1.24</td><td align=\"left\">719/1904</td><td align=\"left\">1.05 (0.93–1.18)</td><td align=\"left\">0.451</td><td align=\"left\"/><td align=\"left\">1.05 (0.93–1.19)</td><td align=\"left\">0.450</td><td align=\"left\"/><td align=\"left\">1.00 (0.87–1.13)</td><td align=\"left\">0.946</td></tr><tr><td align=\"left\">1.25–1.49</td><td align=\"left\">414/996</td><td align=\"left\">1.23 (1.06–1.42)</td><td align=\"left\">0.006</td><td align=\"left\"/><td align=\"left\">1.24 (1.06–1.44)</td><td align=\"left\">0.006</td><td align=\"left\"/><td align=\"left\">1.16 (0.99–1.36)</td><td align=\"left\">0.075</td></tr><tr><td align=\"left\">1.50–1.74</td><td align=\"left\">236/530</td><td align=\"left\">1.39 (1.15–1.67)</td><td align=\"left\">0.001</td><td align=\"left\"/><td align=\"left\">1.45 (1.20–1.76)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.24 (1.01–1.52)</td><td align=\"left\">0.042</td></tr><tr><td align=\"left\">≥ 1.75</td><td align=\"left\">346/680</td><td align=\"left\">1.79 (1.51 − 2.12)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">2.00 (1.68 − 2.39)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\"/><td align=\"left\">1.64 (1.36–1.97)</td><td align=\"left\">&lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Subgroup analysis evaluating the association between SHR and AKI by means of odds ratios</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variables</th><th align=\"left\" colspan=\"7\">Groups (group 1–7) divided by SHR</th><th align=\"left\" rowspan=\"2\">P for interaction</th></tr><tr><th align=\"left\">&lt; 0.50</th><th align=\"left\">0.50–0.74</th><th align=\"left\">0.75–0.99</th><th align=\"left\">1.00–1.24</th><th align=\"left\">1.25–1.49</th><th align=\"left\">1.50–1.74</th><th align=\"left\">≥ 1.75</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.054</td></tr><tr><td align=\"left\"> ≥ 65</td><td align=\"left\">2.04 (1.23–3.39)</td><td align=\"left\">1.30 (1.05–1.62)</td><td align=\"left\">Ref</td><td align=\"left\">1.09 (0.92–1.28)</td><td align=\"left\">1.02 (0.83–1.25)</td><td align=\"left\">1.16 (0.88–1.51)</td><td align=\"left\">2.24 (1.68–2.97)</td><td align=\"left\"/></tr><tr><td align=\"left\"> &lt; 65</td><td align=\"left\">1.79 (1.01–3.20)</td><td align=\"left\">0.97 (0.70–1.35)</td><td align=\"left\">Ref</td><td align=\"left\">1.28 (0.99–1.66)</td><td align=\"left\">1.52 (1.09–2.11)</td><td align=\"left\">1.83 (1.17–2.86)</td><td align=\"left\">2.49 (1.69–3.66)</td><td align=\"left\"/></tr><tr><td align=\"left\">Sex</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.014</td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">2.50 (1.48–4.22)</td><td align=\"left\">1.23 (0.96–1.57)</td><td align=\"left\">Ref</td><td align=\"left\">1.08 (0.90–1.29)</td><td align=\"left\">1.16 (0.91–1.46)</td><td align=\"left\">1.65 (1.19–2.28)</td><td align=\"left\">2.97 (2.16–4.08)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Female</td><td align=\"left\">1.51 (1.01–2.77)</td><td align=\"left\">1.18 (0.90–1.55)</td><td align=\"left\">Ref</td><td align=\"left\">1.22 (0.99–1.51)</td><td align=\"left\">1.11 (0.86–1.43)</td><td align=\"left\">1.07 (0.77–1.48)</td><td align=\"left\">1.75 (1.26–2.43)</td><td align=\"left\"/></tr><tr><td align=\"left\">DM</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">1.74 (1.17–2.60)</td><td align=\"left\">1.16 (0.91–1.47)</td><td align=\"left\">Ref</td><td align=\"left\">1.02 (0.83–1.25)</td><td align=\"left\">0.92 (0.72–1.16)</td><td align=\"left\">1.23 (0.91–1.65)</td><td align=\"left\">1.81 (1.38–2.40)</td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">3.05 (0.80–11.7)</td><td align=\"left\">1.14 (0.86–1.52)</td><td align=\"left\">Ref</td><td align=\"left\">1.23 (1.02–1.49)</td><td align=\"left\">1.42 (1.10–1.82)</td><td align=\"left\">1.37 (0.94–2.01)</td><td align=\"left\">3.49 (2.33–5.23)</td><td align=\"left\"/></tr><tr><td align=\"left\">Hypertension</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.152</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">2.22 (1.32–3.74)</td><td align=\"left\">1.37 (1.10–1.71)</td><td align=\"left\">Ref</td><td align=\"left\">1.22 (1.03–1.44)</td><td align=\"left\">1.20 (0.97–1.49)</td><td align=\"left\">1.36 (1.02–1.80)</td><td align=\"left\">2.05 (1.54–2.71)</td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">1.72 (0.98–3.01)</td><td align=\"left\">0.95 (0.70–1.30)</td><td align=\"left\">Ref</td><td align=\"left\">1.00 (0.79–1.28)</td><td align=\"left\">1.04 (0.78–1.40)</td><td align=\"left\">1.22 (0.82–1.81)</td><td align=\"left\">2.82 (1.94–4.13)</td><td align=\"left\"/></tr><tr><td align=\"left\">CKD</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.002</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">1.88 (1.11–3.18)</td><td align=\"left\">1.06 (0.80–1.42)</td><td align=\"left\">Ref</td><td align=\"left\">0.94 (0.75–1.20)</td><td align=\"left\">1.15 (0.85–1.56)</td><td align=\"left\">1.33 (0.89–1.98)</td><td align=\"left\">1.71 (1.19–2.47)</td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">1.99 (1.12–3.54)</td><td align=\"left\">1.29 (1.02–1.62)</td><td align=\"left\">Ref</td><td align=\"left\">1.25 (1.05–1.48)</td><td align=\"left\">1.14 (0.92–1.41)</td><td align=\"left\">1.27 (0.95–1.69)</td><td align=\"left\">2.60 (1.94–3.41)</td><td align=\"left\"/></tr><tr><td align=\"left\">Acute HF</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.017</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">2.11 (1.25–3.58)</td><td align=\"left\">1.37 (1.09–1.74)</td><td align=\"left\">Ref</td><td align=\"left\">1.14 (0.96–1.36)</td><td align=\"left\">1.22 (0.98–1.51)</td><td align=\"left\">1.28 (0.96–1.71)</td><td align=\"left\">2.06 (1.55–2.73)</td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">1.82 (1.04–3.17)</td><td align=\"left\">1.02 (0.77–1.36)</td><td align=\"left\">Ref</td><td align=\"left\">1.14 (0.92–1.42)</td><td align=\"left\">1.02 (0.76–1.36)</td><td align=\"left\">1.33 (0.91–1.95)</td><td align=\"left\">3.10 (2.11–4.54)</td><td align=\"left\"/></tr><tr><td align=\"left\">AMI</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.429</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">1.47 (0.62–3.49)</td><td align=\"left\">1.00 (0.64–1.57)</td><td align=\"left\">Ref</td><td align=\"left\">0.91 (0.66–1.26)</td><td align=\"left\">0.76 (0.53–1.10)</td><td align=\"left\">1.29 (0.81–2.06)</td><td align=\"left\">1.73 (1.13–2.65)</td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">2.07 (1.36–3.16)</td><td align=\"left\">1.25 (1.02–1.52)</td><td align=\"left\">Ref</td><td align=\"left\">1.20 (1.03–1.39)</td><td align=\"left\">1.26 (1.04–1.54)</td><td align=\"left\">1.27 (0.97–1.65)</td><td align=\"left\">2.52 (1.92–3.31)</td><td align=\"left\"/></tr><tr><td align=\"left\">NICM</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.312</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">2.41 (0.69–8.47)</td><td align=\"left\">1.26 (0.75–2.13)</td><td align=\"left\">Ref</td><td align=\"left\">1.11 (0.73–1.67)</td><td align=\"left\">0.95 (0.58–1.57)</td><td align=\"left\">1.07 (0.54–2.12)</td><td align=\"left\">1.66 (0.88–3.13)</td><td align=\"left\"/></tr><tr><td align=\"left\"> No</td><td align=\"left\">1.92 (1.29–2.85)</td><td align=\"left\">1.18 (0.98–1.43)</td><td align=\"left\">Ref</td><td align=\"left\">1.14 (0.98–1.32)</td><td align=\"left\">1.16 (0.96–1.39)</td><td align=\"left\">1.35 (1.06–1.72)</td><td align=\"left\">2.43 (1.91–3.10)</td><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>SHR: stress hyperglycemia ratio; SBP: systolic blood pressure; RR: respiratory rate; HF: heart failure; AF: atrial fibrillation; AMI: acute myocardial infarction; OMI: old myocardial infarction; NICM: non-ischemic cardiomyopathy; T2DM: type 2 diabetes mellitus; CKD: chronic kidney injury; Nt-pro BNP: N-terminal forebrain natriuretic peptide; SCr: serum creatinine; BUN: blood urea nitrogen; HbA1c: glycosylated hemoglobin A1c; LD: loop diuretics; MV: mechanical ventilation; RRT: renal replacement treatment</p></table-wrap-foot>", "<table-wrap-foot><p>Model 1: unadjusted model; Model 2: adjusted by age and sex; Model 3: adjusted by age, sex, urine output, hypertension, DM, AF, acute HF, MI, OMI, stroke, non-ischemic cardiomyopathy, CKD, Nt-pro BNP, SCr, BUN, HbA1c, history of insulin use, vasopressors, loop diuretics, MV, and RRT.</p></table-wrap-foot>", "<table-wrap-foot><p>The abbreviations are as same in Table ##TAB##0##1##</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Le Li and Ligang Ding contributed equally to this study.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2105_Fig1_HTML\" id=\"d32e272\"/>", "<graphic xlink:href=\"12933_2023_2105_Fig2_HTML\" id=\"d32e992\"/>", "<graphic xlink:href=\"12933_2023_2105_Fig3_HTML\" id=\"d32e1362\"/>", "<graphic xlink:href=\"12933_2023_2105_Fig4_HTML\" id=\"d32e1387\"/>" ]
[ "<media xlink:href=\"12933_2023_2105_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>" ]
[{"label": ["8."], "mixed-citation": ["Huang H, Liu J, Li Q et al. Relationship between stress hyperglycemia and worsening Heart Failure in patients with significant secondary mitral regurgitation. Atherosclerosis. 2023:117306."]}]
{ "acronym": [], "definition": [] }
27
CC BY
no
2024-01-14 23:43:46
Cardiovasc Diabetol. 2024 Jan 13; 23:29
oa_package/0a/70/PMC10787441.tar.gz
PMC10787442
0
[ "<title>Introduction</title>", "<p id=\"Par23\">Disease cognition, or disease perception, refers to the arousal of one’s psychological coping response through the individual’s cognitive evaluation and emotional expression of the disease when the disease state leads to threatened health status [##REF##12136498##1##]. Studies have found that patients’ cognition of the disease will affect their coping and adjustment, such as health behaviour toward treatment, treatment compliance, and emotion [##REF##25456999##2##, ##REF##24630175##3##]. This negative effect may directly or indirectly influence the prognosis of the illness, the patient's quality of life, and their capacity for social interaction [##UREF##0##4##, ##REF##2189997##5##].</p>", "<p id=\"Par24\">Cancer patients, irrespective of the specific cancer type, often experience various emotions stemming from their diagnosis and treatment journey, including fear, anxiety, and uncertainty [##REF##15992569##6##, ##REF##20142735##7##]. The depth of their knowledge and cognitive understanding of cancer significantly shapes their coping strategies and emotional responses. With the advancement of cancer diagnosis and treatment, the survival rate of cancer patients has increased significantly, and the survival period has been prolonged [##REF##26108168##8##]. In cancer rehabilitation, understanding and measuring disease cognition play a pivotal role [##REF##6629788##9##]. Therefore, investigating and measuring disease cognition in cancer patients is crucial.</p>", "<p id=\"Par25\">Two commonly used tools for assessing patients' cognition perception and cognition of their illness are the Brief Illness Perception Questionnaire (B-IPQ) and the Illness Cognition Questionnaire (ICQ). IPQ is based on Weinman et al. (1996) self-regulatory model (SRM) theory [##REF##28056835##10##]. SRM divides patients' cognition of disease into five aspects: disease identity, disease continuity, disease control, pathogenic factors, and serious consequences [##REF##28056835##10##]. IPQ has been widely used in patients with various chronic diseases and has good reliability and validity in breast cancer patients [##REF##24444351##11##]. While the Illness Perception Questionnaire-Revised (IPQ-R) consists of 80 items which is not suitable to assess cancer patients who are symptomatic and in physical distress as well as those who are short of time. B-IPQ is a much shorter version of the original IPQ which consists of 9 items rated from Likert scale of 0 (minimum) to 10 (maximum) [##REF##27317335##12##]. ICQ was compiled by Evers et al. (2001). It is used to assess patients' cognition of the stress and disgust characteristics of the disease at the psychological and behavioural level within three dimensions: helplessness, acceptance, and perceived benefits [##REF##19757084##13##]. The questionnaire has good reliability and validity among patients with chronic diseases, such as chronic pain, fatigue, and rheumatoid arthritis [##REF##26108168##8##, ##REF##19757084##13##]. The differences between B-IPQ and ICQ include: (1) B-IPQ has 9 items, while ICQ has 18 items; (2) the B-IPQ items assess cognitive perceptions of illness, emotional aspect of illness, degree of understanding of illness and causes of illness; while the ICQ assess acceptance, perceived benefits and helplessness concerning the illness experienced; and (3) the B-IPQ is intended for use in groups and hence it is more suitable for use in research, whereas the ICQ is good for use in groups as well as in individuals and therefore suitable for use in research and clinical setting [##REF##27317335##12##, ##REF##19757084##13##]. Aa a result of wider application of the ICQ, it is more crucial to translate and validate the ICQ compared with B-IPQ. At present, there is a lack of data regarding the reliability and validity of the ICQ when used with cancer patients in Malaysia.</p>", "<p id=\"Par26\">Nevertheless, conducting cultural adaptation and validation studies is crucial to ensure the ICQ's relevance and accuracy across diverse cultural contexts. Given Malaysia's distinct sociocultural background and rising cancer rates, it presents a compelling context to validate the ICQ among cancer patients. Validating a Malay version of the ICQ is highly significant as it offers a culturally relevant and linguistically valid tool to evaluate perceived social support among Malay-speaking cancer patients in Malaysia. Therefore, it is essential to translate the ICQ into the Malay version. Firstly, translating the ICQ into Malay improves accessibility and promotes a better understanding of illness cognition among individuals who primarily speak Malay. Secondly, cultural relevance is essential to consider. Translating the questionnaire into Malay ensures that the questions and scales are culturally appropriate for individuals in Malaysia who may hold different beliefs, attitudes, and practices related to health and illness. Furthermore, a Malay version of the ICQ enables clinicians and health professionals to effectively address cognitive distortions associated with illness in Malay-speaking patients, who form a significant population in Malaysia. Additionally, the availability of a Malay version of the ICQ facilitates research on illness cognition within the Malay-speaking population, contributing to a deeper understanding of cultural factors influencing illness beliefs and coping strategies in Malaysia. Translating the ICQ into Malay enhances research outcomes on illness cognition, thereby improving the quality of healthcare for cancer patients in Malaysia. As a result, this validation study translated the original English language version of the ICQ into the Malay language version, modified it for use in cancer patients, and evaluated the reliability and validity of the Malay version of the ICQ (ICQ-M) in a cohort of cancer patients with mixed diagnoses in Malaysia to fill the research gap.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study design and study sample</title>", "<p id=\"Par27\">The validation study took place from December 2022 to March 2023. The study focused on cancer patients registered under the oncology unit of the Advanced Medical and Dental Institute (AMDI). It is a tertiary medical facility for oncology in Peninsular Malaysia, covering states like Pulau Pinang, Kedah, Perlis, and Perak. The AMDI, USM oncology unit currently has approximately 900 to 1000 registered oncology patients with various cancer diagnoses.</p>", "<p id=\"Par28\">The required sample size for this validation research was established using a sample size calculator. Using an online sample size calculator (<ext-link ext-link-type=\"uri\" xlink:href=\"https://wnarifin.github.io/ssc/ssalpha.html\">https://wnarifin.github.io/ssc/ssalpha.html</ext-link>), the estimated sample size needed for meaurement of internal consistency by Cronbach’s α was carried out: the minimum acceptable Cronbach's alpha was 0.7, the estimated Cronbach's alpha was 0.8 [##REF##26108168##8##], the type I error was 0.05, the power was 0.8, and the number of questionnaire items was 18. Therefore, 130 participants (with 20% dropout) were deemed the minimum required to evaluate internal consistency. Finally, the estimated sample size required for confirmatory factor analysis was calculated using an A priori sample size calculator for the structural equation model (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.danielsoper.com/statcalc/calculator.aspx?id=89\">https://www.danielsoper.com/statcalc/calculator.aspx?id=89</ext-link>), whereby the type I error of 0.05, a power of 0.8, three latent variables, eighteen observable variables, and the effect size was 0.22 [##UREF##1##14##]. The estimated sample size required for the study was determined to be 318 subjects, taking into account a 20% anticipated dropout rate. This sample size was determined based on the requirement to assess confirmatory factor analysis, which yielded the largest estimated sample size among all the calculations. Thus, the final sample size required for the study was established at 318 subjects. The sample size required for CFA assessment of instrument may depends on the number of indicators per factor. A CFA model with 6—12 indicator variables per factor would required a sample size of at least 50 subjects. A CFA model with 3 to 4 indicators per factor would need a sample size of at least 100 subjects. While a CFA model with only 2 indicators per factor would required more than 400 subjects [##UREF##2##15##]. The original ICQ has 6 indicators per factor and hence, a sample size of 318 subjects is deemed as sufficient.</p>", "<p id=\"Par29\">The subject recruitment for the study was carried out using consecutive sampling [##REF##29808508##16##]. The research team explained the investigation by interviewing cancer patients who attended the outpatient clinic and in-patient ward of the AMDI, USM oncology unit. Then, potential subjects were screened with the eligibility criteria of the study. The inclusion criteria were: (1) patients with any cancer with a diagnosis confirmed by the histopathological report and at any stage and any duration since diagnosis, (2) those with age from 18 years old and above, (3) those who could read and write in Malay, (4) those who were cognitively sound to answer questionnaires and (5) those who are physically capable of answering the questionnaire. Participants in the research must fulfill all inclusion criteria to be invited.</p>", "<title>Translation and back translation of the ICQ-M and content validity</title>", "<p id=\"Par30\">Two independent language specialists who are multilingual native Malay speakers from the School of Language and Literacy at one institution translated the ICQ's original English edition into Malay. Subsequently, a bilingual language expert from the same institution, fluent in English without seeing the original version of the ICQ, performed a back-translation from the Malay language into English. To establish the content validity of the translated Malay version, a team of experts made up of a psychiatrist, two psychologists, and two community health professionals evaluated the translation and back-translation draughts of the ICQ (the two community health professionals were included in the panel of experts as their area of research also focus on the mental health aspect of cancer patients in the community). The selection criteria for the panel of experts were: (1) engaged in mental health research in cancer patients for at least 5 years after completion of postgraduate qualification, (2) academic qualification with Master of Medicine or PhD, and (3) voluntary participation in the study. The panel's experts were individually asked to assess the relevance of each item to the ICQ's domains using the available answer choices. The response options are: (1) the item is not relevant to the measured domain, (2) the item is partially relevant to the measured domain, (3) the item is relevant to the measured domain, and (4) the item is very relevant to the measured domain. Those who rated an item with response option (3) and (4) was given a score of 1, while those who placed an item with response option (1) and (2) was assigned a score of 0. By dividing the total number of experts in the panel by the number of assessors who received a score of 1, it will produce the item-level content validity index (I-CVI). An I-CVI value of &gt; 0.83 was acceptable [##REF##16977646##17##, ##REF##17654487##18##]. An item’s universal agreement (UA) is equal to 1 if all the experts in the panel agree that the item is either “relevant to the domain measured” or “very relevant to the domain measured”; otherwise, its UA is scored 0. The scale level content validity index (S-CVI/UA) is calculated as the total sum of UA divided by the complete items of the ICQ, in which a value of &gt; 0.8 is considered as high [##UREF##3##19##]. At the same time, I-CVI is added together and divided by the total number of ICQ items to get the average scale-level content validity index(S-CVI/Ave), whereby &gt; 0.9 is deemed to be high [##REF##37550733##20##]. After the panel of experts examined the drafted translations and back-translated copies of the ICQ, the drafted Malay language version of the ICQ (ICQ-M) was constructed.</p>", "<p id=\"Par31\">The draft of the ICQ-M was then given to twenty Malay-speaking cancer patients to evaluate the face validity. All the twenty subjects were interviewed individually for their assessment of the semantic quality, the comprehensibility of the words and sentences used in the instructions and items, any repetition or redundance of terms and sentences, and the duration of the administration. Their responses to each of the four factors mentioned above were coded as “inappropriate,” “appropriate,” and “very appropriate” after the interview.</p>", "<title>Measures</title>", "<p id=\"Par32\">The participants enrolled in the study were administered the socio-demographic and clinical characteristics questionnaire, the ICQ-M, and the Malay language version of the acceptance and action questionnaire II (AAQ-II).</p>", "<title>Socio-demographic and clinical characteristics questionnaire</title>", "<p id=\"Par33\">The socio-demographic and clinical characteristics questionnaire gathered information on various variables, such as gender, age, religion, monthly family income, ethnicity, marital status, level of education, types of cancer, duration since diagnosis, and cancer stage.</p>", "<p id=\"Par34\">The response options to the age of the participants were coded as “18–25 years”, “26–45 years”, “46–65 years”, and “more than 65 years”. The response options to gender were coded as “male” and “female.” The response options to ethnicity were coded as “Malay,” “Chinese,” “Indian,” and “others.” The response options to religion were coded as “Islam,” “Buddhism,” “Hindu,” and “Christian.” The response options to monthly household income were coded into “less than RM 4500”, “between RM 4500 to RM 11000”, and “more than RM 11000”. The response options to the participants’ marital status were coded as “married” as well as “single/divorced/widow/widower.” For the education status options, the answer possibilities were \"tertiary education and above,\" \" up to secondary education,\" and \"primary education and below.\"</p>", "<p id=\"Par35\">Regarding the clinical characteristics, the types of cancer were coded as \"breast cancer,\" \"lung cancer,\" \"head and neck cancer,\" \"colorectal cancer,\" and \"others.\" The time since diagnosis options were coded as \"less than three months,\" \"3–6 months,\" \"6–12 months,\" \"1–2 years,\" and \"more than two years.\" The stage of cancer options included \"stage 1,\" \"stage 2,\" \"stage 3,\" and \"stage 4.\"</p>", "<title>Illness Cognitive Questionnaire (ICQ)</title>", "<p id=\"Par36\">The ICQ, which is self-administered tool which is used to evaluate how people with different chronic conditions perceive themselves [##REF##11777106##21##]. It comprises of 18 items allocated to three domains: acceptance, perceived benefits, and helplessness. Each domain consists of 6 items, each scored on a Likert scale of 1 = not at all to 4 = completely. Hence, the domain score varies between 6 and 24. The degree of the assessed domain increases with increasing domain score. The domains of the ICQ have good to excellent internal consistency with Cronbach’s α between 0.84 and 0.91.</p>", "<title>Acceptance and Action Questionnaire II (AAQ-II)</title>", "<p id=\"Par37\">The AAQ-II is a self-administered tool to assess experiential avoidance or psychological inflexibility. Psychological inflexibility is the lack of ability to accept and adapt to difficult life situations by fully experiencing the present moment and consciously selecting value-consistent behaviour in response, regardless of the person's internal experience. The AAQ II is the second version, improved from the first edition. It is shorter (7 items) and has good psychometric properties. The seven items were added together to determine the scores. With higher scores came more psychological rigidity [##REF##22035996##22##]. The Malay version of the AAQ-II [AAQ-II (M)] was validated, and results showed that it was a unidimensional scale that examined psychological inflexibility/experiential avoidance among cancer patients in Malaysia. Cronbach's alpha was 0.91, and the instrument had great internal consistency [##REF##30807594##23##]. This research evaluated the concurrent validity of the ICQ-M using the AAQ-II (M) as a gold standard comparator.</p>", "<title>Ethical consideration</title>", "<p id=\"Par38\">This study was approved by the Human Research Ethics Committee of Universiti Sains Malaysia (ethics code: USM/JEPeM/22080569), adhering to the Helsinki Declaration of 1964 regulations and its subsequent amendments. A comprehensive explanation of the study's objectives, procedures, potential benefits and risks, participants' right to withdraw at any time, and the assurance of data anonymity was provided. Participants signed informed consent to join the study after receiving this information, with the understanding that their collected data would be discarded after completion of the study.</p>", "<title>Statistical analysis</title>", "<p id=\"Par39\">We used SPSS version 26 (SPSS Inc., Chicago, IL, USA) for data analysis, except confirmatory factor analysis (CFA), which was performed using SPSS Amos version 26 software. Descriptive statistics were reported for sociodemographic and clinical characteristics, while mean scores were calculated for the ICQ domains. Continuous data were reported as mean, standard deviation (SD), skewness and kurtosis; whereas categorical variables were provided as frequency and percentage. The continous data (total and domain scores of ICQ-M) were normally distributed. There was no missing data in this study.</p>", "<p id=\"Par40\">Construct validity was evaluated using confirmatory factor analysis (CFA). The method employed to estimate parameters in CFA was maximum likelihod method. In this method, the measurement model for CFA is a multivariate regression model which describe the relationship between a set of observed dependent variables and a set of continous latent variables. Here, the observed dependent variables were factor indicators, while the continous latent variables were factors. Several parameters were compared across several ICQ-M models to find the model that best suited the ICQ-M (such as: (a) 3-factor model with item allocation and factor structure similar to the original English version of the ICQ; (b) 2-factor model with merging of the acceptance and perceived benefit domains into a single domain, while the helplessness domain as another domain of the ICQ-M and all 18 items included; and (c) with merging of the acceptance and perceived benefit domains into a single domain, while the helplessness domain as another domain of the ICQ-M and item 7 omitted). The chi-square to degrees of freedom ratio (\n<sup>2</sup>/df) of 2.0 with a <italic>p</italic>-value &gt; 0.05, the Tucker-Lewis index (TLI) of 0.95, the comparative fit index (CFI) of 0.95, the goodness of fit index (GFI) of 0.90, and the root mean square error of approximation (RMSEA) of 0.06 were the parameters used to evaluate the model fit [##REF##37550733##20##, ##REF##32369820##24##]. During the CFA evaluation, the above criteria were considered acceptable in determining the most suitable factor model for the ICQ-M.</p>", "<p id=\"Par41\">The convergent and discriminant validity of the ICQ-M were evaluated using the confirmatory factor analysis (CFA) best-fitting model. Convergent validity was assessed by calculating the average variance extracted (AVE), which required adding up the squared factor loadings of items within a certain domain and dividing it by the total number of indicators. An AVE value greater than 0.5 indicated that the ICQ-M demonstrated convergent validity [##REF##37550733##20##, ##UREF##4##25##]. The square root of the AVE for a specific domain and the inter-construct correlation coefficients across domains were compared to evaluate the model's discriminant validity. The ICQ-M had gained discriminant validity if the square root of the AVE was greater than all the inter-construct correlation coefficients.</p>", "<p id=\"Par42\">Finally, for evaluation of the concurrent validity of the ICQ-M, the Pearson’s correlation coefficient between the domains and total ICQ-M score and the total AAQ-II (M) score was computed, and a significantly higher correlation between the ICQ-M and the AAQ-II (M) score indicates good concurrent validity of the ICQ-M as the AAQ-II measures psychological inflexibility when facing negative life event, such as having cancer.</p>" ]
[ "<title>Results</title>", "<title>Participants</title>", "<p id=\"Par43\">Table ##TAB##0##1## lists each participant's sociodemographic information, clinical characteristics, and mean total ICQ-M scores. More than half of the participants (<italic>n</italic> = 185, 53.3%) were middle-aged, between 46 and 65 years old, and 75% were females (<italic>n</italic> = 267, 76.9%). The low-income group (<italic>n</italic> = 269, 77.5%), which included individuals who made less than RM4500 per month, included around three-quarters of the participants. Clinically, over half of the individuals (<italic>n</italic> = 163, 47%) had breast cancer, and more than one-third (<italic>n</italic> = 140, 40.3%) were in stage II.\n</p>", "<p id=\"Par44\">The mean total ICQ-M was 54.96 (standard deviation (SD) = 9.14), while the skewness and kurtosis were -0.24 (SD = 0.13) and -0.20 (SD = 0.10), respectively. The mean acceptance and perceived benefit domain score was 37.78 (SD = 7.87), while the skewness and kurtosis were -0.39 (SD = 0.13) and -0.30 (SD = 0.10), respectively. Finally, the mean helplessness domain score was 17.19 (SD = 4.05), while the skewness and kurtosis were -0.33 (SD = 0.13) and -0.55 (SD = 0.17), respectively.</p>", "<title>Content validity index of ICQ-M</title>", "<p id=\"Par45\">Table ##TAB##1##2## provides an overview of the content validity index of the ICQ-M. All of the ICQ-M items' I-CVI values felt between 0.83 and 1.00. The ICQ-M had an S-CVI/Ave of 0.97. Last but not least, the ICQ-M's S-CVI/UA was 0.83.\n</p>", "<title>The face validity of the ICQ-M</title>", "<p id=\"Par46\">When questioned about the semantic quality, comprehensibility of the words and phrases used and the instructions given, any redundancy of words used, and timing of the ICQ-M administration, 75% of the participants in the pilot study rated the criteria above as \"appropriate.\" This was done while interviewing 20 native Malay-speaking cancer patients. A further 25% of respondents thought it was \"very appropriate.\" There were no complaints regarding any deficiency in the above four factors assessed. Therefore, the expert group decided against making changes to the ICQ-M draft.</p>", "<title>Confirmatory factor analyses of the ICQ-M</title>", "<p id=\"Par47\">In terms of the ICQ-M CFA assessment, a 2-factor model of the ICQ-M with merging of the acceptance and perceived benefit domains into a single domain, while the helplessness domain as another domain of the ICQ-M and all 18 items included, was not fitting (\n<sup>2</sup>/df = 3.007 with <italic>p</italic> &lt; 0.001, CFI = 0.918, GFI = 0.896, TLI = 0.896, and RMSEA = 0.079). Then, a 3-factor model of the ICQ-M with item allocation similar to the original English language version of the ICQ was also not fitting (\n<sup>2</sup>/df = 3.723 with <italic>p</italic> &lt; 0.001, CFI = 0.880, GFI = 0.863, TLI = 0.895, and RMSEA = 0.092). Finally, a 2-factor model of the ICQ-M with merging of the acceptance and perceived benefit domains into a single domain, while the helplessness domain as another domain of the ICQ-M and item 7 omitted was the best fitting model of the ICQ-M (\n<sup>2</sup>/df = 2.000 with <italic>p</italic> &lt; 0.001, CFI = 0.958, GFI = 0.905, TLI = 0.955, and RMSEA = 0.059). Table ##TAB##2##3## provides an overview of the CFA results of the ICQ-M.\n</p>", "<title>The convergent and discriminant validity of the ICQ-M</title>", "<p id=\"Par48\">Table ##TAB##3##4## provides the results of assessing the convergent and discriminant validity of the ICQ-M, based on the 2-factor model of the ICQ-M that fitted the data the best. The AVE of the helplessness domain of the ICQ-M was 0.523, while the square root of the AVE was 0.723, which was greater than the interconstruct correlation coefficient between helplessness and acceptance and perceived benefit of 0.060. While for the acceptance and perceived benefit domain of the ICQ-M, the AVE was at 0.517, the square root of the AVE was at 0.719, which was larger than the interconstruct correlation coefficient between helplessness and acceptance and the perceived benefit of 0.060.\n</p>", "<title>Concurrent validity of the ICQ-M</title>", "<p id=\"Par49\">When the domains of the ICQ-M's Pearson's correlation coefficient and the overall AAQ-II score were evaluated, the helplessness domain of the ICQ-M was significantly moderate positively correlated with the total AAQ-II score (<italic>r</italic> = 0.435, <italic>p</italic> &lt; 0.001). While the acceptance and perceived benefits domain of the ICQ-M was also significantly moderately positively correlated with the total AAQ-II score (<italic>r</italic> = 0.452, <italic>p</italic> &lt; 0.001). Finally, the total ICQ-M score significantly positively correlated with the total AAQ-II score (<italic>r</italic> = 0.495, <italic>p</italic> &lt; 0.001).</p>", "<title>Reliability of the ICQ-M</title>", "<p id=\"Par50\">In the context of internal consistency of the ICQ-M, the Cronbach's alpha of the total score was 0.858, while that of the helplessness and acceptance and perceived benefits domains were 0.742 and 0.927, respectively.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par51\">Our study represents a noteworthy development in the realm of illness cognition research, with a specific focus on cancer patients in Malaysia. Through developing and validating the ICQ-M, we have introduced a valuable instrument for gaining insights into individuals' perceptions and thought processes concerning their illness. This innovative tool has profound implications for clinical practice and research, as it offers a culturally tailored means to assess illness cognition across a diverse ethnic population as in Malaysia. The ICQ-M has adequate content validity, as shown by the I-CVI of all its items being at least 0.83, the S-CVI/UA being higher than 0.8, and the S-CVI/Ave being higher than 0.9 [##REF##17654487##18##–##REF##37550733##20##, ##REF##26161370##26##]. Twenty native Malay-speaking cancer patients participated in a pilot study to evaluate the ICQ-M's face validity. Of the respondents, 75% rated the semantic quality, comprehensibility, and administration time as \"appropriate,\" and 25% rated it as \"very appropriate,\" with no respondents criticising the use of redundant wording or sentences. This proved the ICQ-M's strong face validity.</p>", "<p id=\"Par52\">In the context of its construct validity, the CFA performed confirmed the two-factor model of the ICQ-M, whereby the acceptance and perceived benefit domains were merged into a single domain, while the helplessness domain was maintained with item 7 omitted (Table ##TAB##2##3##). The differences in the language and cultures may explain the discrepancies between the factor structures of the original English and Malay version of the ICQ. Hence, the translated wordings in the ICQ-M may have a different meaning than the original English version. In the ICQ-M, item 7 was omitted as there were enormous similarities between the meaning of item 7 and item 15. When item 7 was omitted from the ICQ-M, the fitting of the 2-factor model was greatly improved (Table ##TAB##2##3##). When we inspected the best-fitting 2-factor model of the ICQ-M, the best-fit indicators were all acceptable (GFI, CFI, TFI, and RMSEA) except for the chi-square (\n<sup>2</sup>), in which the p-value was &lt; 0.001. One of the limitations of chi-square statistics in CFA is that it is sensitive to sample size, whereby a large sample size will lead to the chi-square remaining statistically significant. The adequate sample size for CFA can be estimated as a cut-off of 200 subjects, or the sample size ratio to model variables should be at least 10:1 [##UREF##5##27##]. Our sample size in this validation study was 346 participants, and the ratio of sample size to model variables was 19:1. Hence, it is more appropriate to use the ratio of the chi-square to the degree of freedom (\n<sup>2</sup>/df) as a best-fit indicator rather than the chi-square itself. Moreover, it was suggested that a set of combined indices should be reported in assessing the best-fitting model in CFA, such as the chi-square, RMSEA, CFI, and SRMSR, rather than depending on chi-square statistics alone [##UREF##5##27##].</p>", "<p id=\"Par53\">The ICQ-M had also achieved convergent validity as indicated by the AVE of the helplessness (0.523) and acceptance and perceived benefit (0.517) domains, which were greater than 0.5. In addition, the ICQ-M had also achieved discriminant validity as the square root of AVE for the helplessness (0.723) and acceptance and perceived benefit (0.719) domains were greater than their inter-construct correlation coefficient (0.06) (Table ##TAB##3##4##).</p>", "<p id=\"Par54\">Regarding the concurrent validity of the ICQ-M, the AAQ-II was used as the comparator instrument. It was designed and validated to measure psychological inflexibility when facing a life event like cancer [##REF##30807594##23##]. Our study reported that the domains and total score of the ICQ-M moderately correlated to the total AAQ-II score, indicating that the ICQ-M and its domains have similarities in their capability to measure acceptance of negative life event occurrence.</p>", "<p id=\"Par55\">The internal consistency of the ICQ-M and its domains showed satisfactory to exceptional internal consistency (Cronbach's range from 0.742 to 0.927). It has been suggested that Cronbach’s α value between 0.70 to 0.95 is acceptable [##REF##28029643##28##]. Regarding internal consistency, the ICQ-M domains and the original English ICQ were comparable (the latter's Cronbach's α ranges from 0.84 to 0.91) [##REF##11777106##21##]. Similarly, the internal consistency of the ICQ-M was also comparable to that of the Korean version of the ICQ (Cronbach’s α range from 0.79 to 0.86), and that of the ICQ adapted for use to assess illness perception and cognition in parents of children with cancer [##REF##26108168##8##, ##REF##33314524##29##].</p>", "<p id=\"Par56\">There were a few limitations of this validation research. First, the research sample's gender distribution and cancer types were not indicative of Malaysia's overall cancer population. Hence, this has an impact on how generalizable the research results are. Similarly, the cancer patient recruitment only involved a single center which may again affect the applicability and generalizability of the study findings to be representative of the Malaysian cancer population.</p>", "<p id=\"Par57\">Despite its limitations, this study effectively translated, adapted, and validated the ICQ-M to manage cancer patients in Malaysia. Now, patients with cancer may use the ICQ-M to gauge the illness perception of cancer patients, which is an essential determinant of the mental state of the patient and their compliance with cancer treatment, quality of life, and prognosis. Psychotherapy or other effective psychosocial interventions can be administered to cancer patients if their poor illness acceptance and a high degree of helplessness affect their mental state and disrupt their compliance with cancer treatment to improve the outcome of their cancer management. Moreover, the translated and validated ICQ-M can also be adapted and validated in future studies to be applied for measuring illness perception of other chronic illnesses in the Malaysian population.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par58\">The original English version of the ICQ has been successfully translated to Malay, and the ICQ-M exhibited good reliability, such as internal consistency, and decent validity, such as the face, content, convergent, discriminant, construct, and concurrent validity. The CFA of the ICQ-M confirmed that the ICQ-M consists of 17 items designated to two domains. The ICQ-M is now available to measure the illness perception and cognition among cancer patients in Malaysia.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">The Illness Cognition Questionnaire (ICQ) was translated from its original English version to the Malay version for this research, adapted the Malay language version of the ICQ (ICQ-M) for use in cancer patients, and assessed the internal consistency, content, face, construct, convergent, discriminant and concurrent validity of the ICQ-M among a cohort of cancer patients with mixed cancer types in Malaysia.</p>", "<title>Method</title>", "<p id=\"Par2\">Initially, the ICQ was translated into Malay and back-translated, and its content and face validity were evaluated. Then, 346 cancer patients with various cancer types received the ICQ-M, and its internal consistency, convergent, discriminant, construct, and concurrent validity were evaluated.</p>", "<title>Results</title>", "<p id=\"Par3\">The ICQ-M and its domains had acceptable internal consistency with Cronbach’s α ranging from 0.742 to 0.927. Construct validity assessment demonstrated that the ICQ-M consists of 17 items designated in two domains with good convergent and discriminant validity. The ICQ-M and its domains also had moderate correlations with the Acceptance and Action Questionnaire II, which denotes that the ICQ-M had acceptable concurrent validity.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The ICQ-M had good psychometric properties and is now available to measure the illness cognition of cancer patients in Malaysia.</p>", "<title>Keywords</title>" ]
[ "<title>Relevance for clinical practice</title>", "<p id=\"Par59\">ICQ-M holds significant relevance for the clinical practice among cancer patients in Malaysia. The ICQ-M helps healthcare workers to get insight into patients' mental states and attitudes toward cancer by offering a trustworthy and valid instrument to evaluate disease perception and cognition. These results can inform personalized treatment plans, help to understand patients, and guide the implementation of psychotherapeutic interventions to improve illness acceptance and reduce helplessness. Ultimately, the ICQ-M improves patient outcomes and overall cancer management in clinical settings.</p>" ]
[ "<title>Acknowledgements</title>", "<p>The authors would like to thank Dr. Noor Mastura Mohd Mujar for suggestions on content validity and the staff nurses of Advanced Medical and Dental Institute, Universiti Sains Malaysia, for their assistance in data collection.</p>", "<title>Authors’ contributions</title>", "<p>Conceptualization of the study by MFILBA and RZ. Validation, resources, software and methodology of the study by MFILBA, WS, NSM, NIS, and RZ. The first draft of the study was written by MFILBA and WS. All authors commented on the previous manuscript versions. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study is funded by the Xinxiang Social Science Federation (grant number: SKL- 2022–120, URL = <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.xxmu.edu.cn/\">https://www.xxmu.edu.cn/</ext-link>). The funder plays no role in the design of the study and collection, analysis, interpretation of data and in writing the manuscript, and submission for publication.</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding authors on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par60\">This study was approved by the Human Research Ethics Committee of Universiti Sains Malaysia (code:USM/JEPeM/22080569), adhering to the Helsinki Declaration of 1964 regulations and its subsequent amendments. Participants signed informed consent to join the study only after receiving this information, understanding that their collected data would be discarded.</p>", "<title>Consent for publication</title>", "<p id=\"Par61\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par62\">The authors declare no competing interests.</p>" ]
[]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Socio-demographic and clinical characteristics of the participants</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Number of participants(n)</th><th align=\"left\">Percentage (%)</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"3\"><bold>Age:</bold></td></tr><tr><td align=\"left\"> 18–25 years old</td><td align=\"left\">6</td><td align=\"left\">1.7</td></tr><tr><td align=\"left\"> 26–45 years old</td><td align=\"left\">97</td><td align=\"left\">28</td></tr><tr><td align=\"left\"> 46–65 years old</td><td align=\"left\">185</td><td align=\"left\">53.5</td></tr><tr><td align=\"left\"> &gt; 65 years</td><td align=\"left\">58</td><td align=\"left\">16.8</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Gender:</bold></td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">79</td><td align=\"left\">22.8</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">267</td><td align=\"left\">77.2</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Ethnicity:</bold></td></tr><tr><td align=\"left\"> Malays</td><td align=\"left\">279</td><td align=\"left\">80.6</td></tr><tr><td align=\"left\"> Chinese</td><td align=\"left\">40</td><td align=\"left\">11.6</td></tr><tr><td align=\"left\"> Indians</td><td align=\"left\">23</td><td align=\"left\">6.6</td></tr><tr><td align=\"left\"> others</td><td align=\"left\">4</td><td align=\"left\">1.2</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Religion:</bold></td></tr><tr><td align=\"left\"> Islam</td><td align=\"left\">279</td><td align=\"left\">80.6</td></tr><tr><td align=\"left\"> Buddhism</td><td align=\"left\">39</td><td align=\"left\">11.4</td></tr><tr><td align=\"left\"> Hindu</td><td align=\"left\">23</td><td align=\"left\">6.6</td></tr><tr><td align=\"left\"> Christian</td><td align=\"left\">5</td><td align=\"left\">1.4</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Monthly household income:</bold></td></tr><tr><td align=\"left\"> &lt; RM 4,500</td><td align=\"left\">269</td><td align=\"left\">77.8</td></tr><tr><td align=\"left\"> RM 4500-RM 11000</td><td align=\"left\">72</td><td align=\"left\">20.8</td></tr><tr><td align=\"left\"> &gt; RM 11000</td><td align=\"left\">5</td><td align=\"left\">1.4</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Marital status:</bold></td></tr><tr><td align=\"left\"> Married</td><td align=\"left\">283</td><td align=\"left\">81.8</td></tr><tr><td align=\"left\"> Single/divorcee/widow/widower</td><td align=\"left\">63</td><td align=\"left\">18.2</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Education status:</bold></td></tr><tr><td align=\"left\"> Primary education or below</td><td align=\"left\">37</td><td align=\"left\">10.7</td></tr><tr><td align=\"left\"> Up to secondary education</td><td align=\"left\">189</td><td align=\"left\">54.6</td></tr><tr><td align=\"left\"> Tertiary education and above</td><td align=\"left\">120</td><td align=\"left\">34.7</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Time since diagnosis</bold></td></tr><tr><td align=\"left\"> 3 months</td><td align=\"left\">61</td><td align=\"left\">17.6</td></tr><tr><td align=\"left\"> 3–6 month</td><td align=\"left\">65</td><td align=\"left\">18.8</td></tr><tr><td align=\"left\"> 6 months- 1 year</td><td align=\"left\">59</td><td align=\"left\">17.1</td></tr><tr><td align=\"left\"> 1–2 year</td><td align=\"left\">58</td><td align=\"left\">16.8</td></tr><tr><td align=\"left\"> More than 2 years</td><td align=\"left\">103</td><td align=\"left\">29.8</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Types of cancer:</bold></td></tr><tr><td align=\"left\"> Breast cancer</td><td align=\"left\">163</td><td align=\"left\">47.1</td></tr><tr><td align=\"left\"> Lung cancer</td><td align=\"left\">9</td><td align=\"left\">2.6</td></tr><tr><td align=\"left\"> Head and neck cancer</td><td align=\"left\">84</td><td align=\"left\">24.3</td></tr><tr><td align=\"left\"> Colon cancer</td><td align=\"left\">34</td><td align=\"left\">9.8</td></tr><tr><td align=\"left\"> Others</td><td align=\"left\">56</td><td align=\"left\">16.2</td></tr><tr><td align=\"left\" colspan=\"3\"><bold>Stage of cancer:</bold></td></tr><tr><td align=\"left\"> Stage 1</td><td align=\"left\">51</td><td align=\"left\">14.7</td></tr><tr><td align=\"left\"> Stage 2</td><td align=\"left\">140</td><td align=\"left\">40.5</td></tr><tr><td align=\"left\"> Stage 3</td><td align=\"left\">116</td><td align=\"left\">33.5</td></tr><tr><td align=\"left\"> Stage 4</td><td align=\"left\">39</td><td align=\"left\">11.3</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Content validity index (CVI) of the ICQ-M</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Items</th><th align=\"left\">Expert 1</th><th align=\"left\">Expert 2</th><th align=\"left\">Expert 3</th><th align=\"left\">Expert 4</th><th align=\"left\">Expert 5</th><th align=\"left\">Expert 6</th><th align=\"left\">Expert in agreement</th><th align=\"left\">I-CVI</th><th align=\"left\">UA</th></tr></thead><tbody><tr><td align=\"left\">Item 1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 2</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 3</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 4</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 5</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 6</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 7</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 8</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 9</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 10</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 11</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 12</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 13</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">5</td><td align=\"left\">0.83</td><td align=\"left\">0</td></tr><tr><td align=\"left\">Item 14</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">5</td><td align=\"left\">0.83</td><td align=\"left\">0</td></tr><tr><td align=\"left\">Item 15</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 16</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 17</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">6</td><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Item 18</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">5</td><td align=\"left\">0.83</td><td align=\"left\">0</td></tr><tr><td align=\"left\">Proportion relevance</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\">0.22</td><td align=\"left\">1</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" rowspan=\"2\">The average proportion of items judged as relevant across the six experts</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">S-CVI/Ave:</td><td align=\"left\">0.97</td><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">S-CVI/UA:</td><td align=\"left\"/><td align=\"left\">0.83</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Confirmatory factor analysis of the Malay version of the Illness Cognitive Questionnaire (ICQ-M)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">variables</th><th align=\"left\"><bold>2-factor model of the ICQ-M</bold><sup><bold>a</bold></sup></th><th align=\"left\"><bold>2-factor model of the ICQ-M</bold><sup><bold>b</bold></sup></th><th align=\"left\">3-factor model which follows the original ICQ</th></tr></thead><tbody><tr><td align=\"left\">Chi-square/degree of freedom (χ2/df)</td><td char=\".\" align=\"char\">2.000*</td><td char=\".\" align=\"char\">3.007*</td><td char=\".\" align=\"char\">3.723*</td></tr><tr><td align=\"left\">Comparative fit index (CFI)</td><td char=\".\" align=\"char\">0.958</td><td char=\".\" align=\"char\">0.918</td><td char=\".\" align=\"char\">0.880</td></tr><tr><td align=\"left\">The goodness of fit index (GFI)</td><td char=\".\" align=\"char\">0.905</td><td char=\".\" align=\"char\">0.896</td><td char=\".\" align=\"char\">0.863</td></tr><tr><td align=\"left\">Tucker-Lewis Index (TLI)</td><td char=\".\" align=\"char\">0.955</td><td char=\".\" align=\"char\">0.896</td><td char=\".\" align=\"char\">0.895</td></tr><tr><td align=\"left\">Root mean square error of approximation (RMSEA)</td><td char=\".\" align=\"char\">0.059</td><td char=\".\" align=\"char\">0.079</td><td char=\".\" align=\"char\">0.092</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Convergent and discriminant validity of the Malay version of the Illness Cognitive Questionnaire (ICQ-M) according to the best fitting 2-factor model of the ICQ-M in confirmatory factor analysis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Indicator variables</th><th align=\"left\">Latent variables</th><th align=\"left\">Standardized loading</th><th align=\"left\">Square of standardized loading</th><th align=\"left\">The sum of squared of standardized loading</th><th align=\"left\">Number of indicators</th><th align=\"left\">AVE</th><th align=\"left\">The square root of AVE</th><th align=\"left\">Inter-construct correlation</th></tr></thead><tbody><tr><td align=\"left\"><bold>Item 1</bold></td><td align=\"left\">HLP</td><td char=\".\" align=\"char\">0.680</td><td char=\".\" align=\"char\">0.462</td><td align=\"left\" rowspan=\"5\">2.614</td><td align=\"left\" rowspan=\"5\">5</td><td align=\"left\" rowspan=\"5\">0.523</td><td align=\"left\" rowspan=\"5\">0.723</td><td align=\"left\" rowspan=\"5\">HLP\n\nAPB = 0.060\n</td></tr><tr><td align=\"left\"><bold>Item 5</bold></td><td align=\"left\">HLP</td><td char=\".\" align=\"char\">0.672</td><td char=\".\" align=\"char\">0.452</td></tr><tr><td align=\"left\"><bold>Item 9</bold></td><td align=\"left\">HLP</td><td char=\".\" align=\"char\">0.663</td><td char=\".\" align=\"char\">0.440</td></tr><tr><td align=\"left\"><bold>Item 12</bold></td><td align=\"left\">HLP</td><td char=\".\" align=\"char\">0.908</td><td char=\".\" align=\"char\">0.824</td></tr><tr><td align=\"left\"><bold>Item 15</bold></td><td align=\"left\">HLP</td><td char=\".\" align=\"char\">0.660</td><td char=\".\" align=\"char\">0.436</td></tr><tr><td align=\"left\"><bold>Item 2</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.620</td><td char=\".\" align=\"char\">0.384</td><td align=\"left\" rowspan=\"12\">6.201</td><td align=\"left\" rowspan=\"12\">12</td><td align=\"left\" rowspan=\"12\">0.517</td><td align=\"left\" rowspan=\"12\">0.719</td><td align=\"left\" rowspan=\"12\">HLP \n\nAPB = 0.060\n</td></tr><tr><td align=\"left\"><bold>Item 3</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.614</td><td char=\".\" align=\"char\">0.377</td></tr><tr><td align=\"left\"><bold>Item 10</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.587</td><td char=\".\" align=\"char\">0.345</td></tr><tr><td align=\"left\"><bold>Item 13</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.789</td><td char=\".\" align=\"char\">0.623</td></tr><tr><td align=\"left\"><bold>Item 14</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.661</td><td char=\".\" align=\"char\">0.437</td></tr><tr><td align=\"left\"><bold>Item 17</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.693</td><td char=\".\" align=\"char\">0.480</td></tr><tr><td align=\"left\"><bold>Item 4</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.745</td><td char=\".\" align=\"char\">0.555</td></tr><tr><td align=\"left\"><bold>Item 6</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.780</td><td char=\".\" align=\"char\">0.608</td></tr><tr><td align=\"left\"><bold>Item 8</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.779</td><td char=\".\" align=\"char\">0.607</td></tr><tr><td align=\"left\"><bold>Item 11</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.784</td><td char=\".\" align=\"char\">0.615</td></tr><tr><td align=\"left\"><bold>Item 16</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.763</td><td char=\".\" align=\"char\">0.582</td></tr><tr><td align=\"left\"><bold>Item 18</bold></td><td align=\"left\">APB</td><td char=\".\" align=\"char\">0.767</td><td char=\".\" align=\"char\">0.588</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>I-CVI</italic> Item-level content validity index, <italic>UA</italic> Universal agreement, <italic>S-CVI/Ave</italic> Average of the scale-level content validity index, <italic>S-CVI/UA</italic> Average of the scale-level content validity index across universal agreement among experts</p></table-wrap-foot>", "<table-wrap-foot><p><sup>*</sup> = <italic>p</italic> &lt; 0.001</p><p><sup>a</sup>a 2-factor model with merging of the acceptance and perceived benefit domains into a single domain, with the helplessness domain as another domain of the ICQ-M and item 7 omitted</p><p><sup>b</sup>a 2-factor model with merging of the acceptance and perceived benefit domains into a single domain, with the helplessness domain as another domain of the ICQ-M and all 18 items included</p></table-wrap-foot>", "<table-wrap-foot><p><italic>HLP</italic> Helplessness, <italic>APB</italic> Acceptance and perceived benefit, <italic>AVE</italic> Average variance extracted</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["4."], "mixed-citation": ["Postolica R, Iorga M, Petrariu FD, Azoicai D. Cognitive-behavioral coping, illness perception, and family adaptability in oncological patients with a family history of cancer. BioMed Res Int. 2017;2017:8104397."]}, {"label": ["14."], "mixed-citation": ["Gallagher\u00a0MW, Brown TA. Introduction to confirmatory factor analysis and structural equation modeling. In Teo T, editor. Handbook of quantitative methods for educational research. Rotterdam: SensePublishers; 2013. p. 287\u2013314."]}, {"label": ["15."], "surname": ["Kyriazos"], "given-names": ["TA"], "article-title": ["Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general"], "source": ["Psychology"], "year": ["2018"], "volume": ["9"], "fpage": ["2207"], "lpage": ["2230"], "pub-id": ["10.4236/psych.2018.98126"]}, {"label": ["19."], "surname": ["Shi", "Mo", "Sun"], "given-names": ["J", "X", "Z"], "article-title": ["Content validity index in scale development"], "source": ["Zhong nan da xue xue bao. Yi xue ban= J Central South Univ Med Sci"], "year": ["2012"], "volume": ["37"], "issue": ["2"], "fpage": ["152"], "lpage": ["155"]}, {"label": ["25."], "surname": ["Ahmad", "Zulkurnain", "Khairushalimi"], "given-names": ["S", "N", "F"], "article-title": ["Assessing the validity and reliability of a measurement model in Structural Equation Modeling (SEM)"], "source": ["Br J Math Comp Sci"], "year": ["2016"], "volume": ["15"], "issue": ["3"], "fpage": ["1"], "lpage": ["8"], "pub-id": ["10.9734/BJMCS/2016/25183"]}, {"label": ["27."], "surname": ["Alavi", "Visentin", "Thapa", "Hunt", "Watson", "Cleary"], "given-names": ["M", "DC", "DK", "GE", "R", "ML"], "source": ["Chi-square for model fit in confirmatory factor analysis"], "year": ["2020"]}]
{ "acronym": [ "ICQ-M", "B-IPQ", "SRM", "AMDI", "EFA", "I-CVI", "UA", "S-CVI", "AAQ-II", "CFA", "AVE", "RM", "SPSS", "\n2/df", "TLI", "CFI", "GFI", "RMSEA" ], "definition": [ "Malay version of the Illness Cognition Questionnaire", "Brief Illness Perception Questionnaire", "Self-regulatory model", "Advanced Medical and Dental Institute", "Exploratory factor analysis", "Item-level content validity index", "Universal agreement", "Scale-level content validity index", "Acceptance and action questionnaire version 2", "Confirmatory factor analysis", "Average variance extracted", "Ringgit Malaysia", "Statistical Package for Social Sciences", "Chi square to degree of freedom ratio", "Tucker-Lewis index", "Comparative fit index", "Goodness of fit index", "Root mean square error of approximation" ] }
29
CC BY
no
2024-01-14 23:43:46
BMC Public Health. 2024 Jan 13; 24:173
oa_package/1e/c3/PMC10787442.tar.gz
PMC10787443
38216883
[ "<title>Introduction</title>", "<p id=\"Par9\"><italic>ras</italic> gene is the first oncogene isolated from human bladder cancer cells [##REF##6283357##1##]. The ras gene has three main subtypes, namely N-ras, H-ras, and K-ras, encoding four Ras proteins: N-Ras, H-Ras, K-Ras4A, and K-Ras4B, respectively. Among them, K-Ras4A and K-Ras4B are different splicing forms of K-Ras protein. These proteins all exist in two forms: the activated state bound to GTP (Ras GTP) and the inactivated state bound to GDP (Ras-GDP). Ras protein(p21Ras) regulates cell differentiation, proliferation, and survival through the “on/off” cycle of activated Ras GTP and deactivated Ras GDP. Under physiological conditions, this state change is balanced. Once the balance is lost, such as point mutations at codons 12, 13, or 61, the hydrolysis rate of GTP in Ras GTP will decrease, meaning that Ras protein continues to exist in the activated state as Ras-GTP style, which will promote cell proliferation and lead to the occurrence of cancer [##REF##22393783##2##]. Research has found that about 30% of human tumors harboured ras gene mutations [##REF##31832517##3##]. Every year, more than 3 million cancer patients worldwide are caused by ras mutations. Such as pancreatic cancer, colorectal cancer, lung cancer, peritoneal cancer, bladder cancer cancer, bile duct cancer and melanoma [##REF##32289276##4##]. In recent years it was found that overexpression of wild type p21Ras could lead occurence of cancer [##REF##28259994##5##]. Therefore, p21Ras is a potential therapeutic target for <italic>ras</italic> gene driven tumors, and the development of drugs against p21Ras is of great significance for the diagnosis and treatment of ras gene driven tumors.</p>", "<p id=\"Par10\">The drugs development for the p21Ras itself are currently mainly focused on two directions: small molecule inhibitors and therapeutic antibodies. At present, a few small molecule inhibitors have entered the clinical trial stage, and Sotorasib (AMG510) and Adagrasib (MRTX849) are approved for clinical practise [##REF##33138715##7##–##REF##31822538##9##]. However, anti-p21Ras antibody drugs have not yet been available.</p>", "<p id=\"Par11\">As early as the 1980s, anti-p21Ras antibodies, Y13-259 and RASK1-16 etc. were reported, but they could not penetrate cell to bind p21Ras within cytoplasm [##REF##6287003##10##, ##REF##3046740##11##]. Previously, we prepared anti-p21Ras single chain antibodies(p21Ras-scFv) based on phage display library technology [##REF##26897358##12##]. We inserted the p21Ras scFv gene into the adenovirus vector and infected tumor cells, achieving intracellular expression of the p21Ras-scFv. In vitro and in vivo experiments have shown that the anti-p21Ras-scFv has unexpected anti-tumor activity [##REF##26780944##13##–##REF##33535808##19##].</p>", "<p id=\"Par12\">In order to gain anti-p21Ras-scFv which can penetrate tumor cell, we linked the RGD transmembrane peptide gene to the p21Ras-scFv gene and expressed the RGD-p21Ras-scFv through a prokaryotic expression system. In vitro experiments have shown that it can enter tumor cells and has anticipated anti-tumor activity [##REF##33765976##20##–##REF##34338241##22##]. However, the above study obtained recombinant antibodies through small-scale expression in laboratory shaking bottles. To convert recombinant antibodies into clinical anti-tumor drugs, it is necessary to explore the conditions for large-scale preparation and determine that the recombinant antibodies prepared on a large scale have the same immunoreactivity and anti-tumor activity. Therefore, this study established a pilot scale expression process to prepare “gram level” RGD-p21Ras-scFv protein, and verified its immunoreactivity and anti-tumor activity. The purpose of this study is to explore the possibility of further industrial development of the recombinant antibody, laying the foundation for the commercial production of RGD-p21Ras-scFv protein.</p>" ]
[ "<title>Materials and methods</title>", "<title>Cell cultures and reagents</title>", "<p id=\"Par13\">The Kunming Cell Bank of the Chinese Academy of Sciences, including human cell lines CCD841, A549, AGS, AsPC-1, HePG-2, MDB-MB-231, MIApaca-1, PANC-1, U251, HT29, SW837, LS180, SW480, and HCT116 all cells; and human embryonic kidney cell line 293T. The growth of cells was made in the corresponding medium (DMEM: SW480, SW837, 293T; RPMI 1640: HCT116, HT29; MEM EAGLE: LS180) added with 10% fetal bovine serum (Excell Bio) and 1% penicillin/streptomycin (Basic Medium) at 37 °C in a 5% carbon dioxide incubator. The KRAS (G12C) inhibitor was dissolved in DMSO.</p>", "<title>Construction of expression plasmid</title>", "<p id=\"Par14\">The gene encoding RGD-p21Ras-scFv was obtained by PCR amplification using the paired primer with the RGD-p21Ras-scFv in the pet28a plasmid (preserved at our laboratory) as a template [##REF##33765976##20##]. The primers were synthesized by TsingKe Biological Technology Inc. (Kunming, China), and PCR products were subcloned into the pClone 7 plasmid between Hind III and Kpn I and transfected into DH5α strain. Then, the pClone 7 plasmid and the PET-28a (+) were digested with Hind III and NdeI, the pClone 7 plasmid and the PET-32a (+) were digested with Hind III and KpnI, the pClone 7 plasmid and the PET-22b were digested with NdeI and Hind III to acquired fusion gene. The fragments of RGD-p21Ras-scFv were recovered from the agarose gel(Promega), purified, and ligated by T4 DNA ligase, so the RGD-p21Ras-scFv gene was inserted into different expression vectors and then transfected into DH5α according to the standard protocol [##REF##33528691##23##]. Using the PCR and DNA sequencing to identify the RGD-p21Ras-scFv gene fragment insert in the correct position.</p>", "<p id=\"Par15\">The research adopted the primer pairs as below: 5’-CCTCCCAGCTCTGGTATTGC-3’(Forward) and 5’-AGGGTTCTGTGAGTTTGATT-3’(Reverse) for T7 sequence using in plcone7 plasmid identification. The 5’-CATATGGCATGTGATTGTCG-3’(Forward) and 5’-AAGCTTTTATCACCGTTTGA-3’(Reverse) for RGD-p21Ras-scFv sequence using in expression plasmid identification. The PCR reaction program was: 94 °C, 5 min; 94 °C, 50s; 55 °C, 1 min; 72 °C, 45 S; 72 °C, 10 min; 32 cycles.</p>", "<title>Selection and optimization of expression condition</title>", "<p id=\"Par16\">The expression vector was transformed into E.coil Origami(DE3), Origami B (DE3) and BL21(DE3). After recovery, 200µL of the cells were spread on a LB solid medium (1% peptone, 1% yeast extract, and 0.5% sodium chloride, 1.5% agar, pH 7.0) a) containing 100 µg /ml ampicillin and 50 µg/ml Kanamycin. The plate was upside down and incubated at 37℃ overnight. The inserted RGD-p21Ras-scFv gene was confirmed by PCR and DNA sequencing. Identified single clones were placed in 5ml LB medium(1% peptone, 1% yeast extract, and 0.5% sodium chloride, pH 7.0) containing 100 µg /ml ampicillin and 50 µg/ml Kanamycin shaking at 37℃, 200 rpm overnight.To optimize the highest level of RGD-p21Ras-scFv recombinant antibody expression, the comparison between the different strains, different cultures (LB and Isopropyl-β-Dthiogalactopyranoside, ZYM5052), and expression form in soluble or inclusion body were evaluated. Briefly, the isopropyl-β-Dthiogalactopyranoside (IPTG) induced methods: The bacteria were inoculated into a 200ml shake flask containing 30ml LB containing 100 µg /ml ampicillin and 50 µg/ml Kanamycin, culturing with proportion of bacteria involved was at ratio of 1/100 and incubated at 37 °C, 200 rpm in a shaker until the OD value (at 600 nm) reached 0.6–0.8. At this time point, different concentration of IPTG from 0.2mM to 1.6mM was added to the LB culture followed by shaking at 37 °C, and 200 rpm for 5 h, respectively. Then, after the most suitable concentration of IPTG was chosen, the induced time was from 4 to 20 h to be selected.</p>", "<p id=\"Par17\">The self-inducing methods: This method was using ZYM-5052 culture which contains 1% Tryptone, 0.5% Yeast extract, 25mM Na<sub>2</sub>HPO<sub>4</sub>, 25mM KH2PO4, 50mM NH<sub>4</sub>Cl, 5 m MNa<sub>2</sub>SO<sub>4</sub>, 0.5% Glycerol, 0.05% Glucose, 0.2% α-lactose, 2 m Mg<sub>2</sub>SO<sub>4</sub>, 0.2x Trace elements [##REF##15915565##24##]. The bacteria were inoculated into a 200ml shake flask containing 30ml LB containing 100 µg /ml ampicillin and 50 µg/ml Kanamycin and culture with the proportion of bacteria involved was at a ratio of 1/100 at 37 °C, 200 rpm shaking until the OD value reached 0.6–0.8, then reducing the temperature to 20 °C with 200 rpm shaking 20 h. Recombinant bacteria was harvested by centrifugation, and lysed by sonication into the buffer. The supernatants were harvested by centrifugation at 12,000 rpm for 30 min at 4 °C. Both soluble and insoluble bodies were analyzed by 12% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE).</p>", "<title>Recombinant protein expression and pilot-scale fermentation</title>", "<p id=\"Par18\">Small-scale expression in the laboratory: The bacteria were inoculated into a 1 L shake flask containing 500ml LB containing 100 µg /ml ampicillin and 50 µg/ml Kanamycin and cultured under the condition of self-inducing method.</p>", "<p id=\"Par19\">Pilot-scale fermentation: Before inoculation in bioreactors, the seed strain cultures were prepared in a total volume of 1 L. Briefly, inoculating 1ml <italic>E. Coli</italic> Orignami (DE3) cells into a 1 L baffled shake flask containing 400 mL of LB medium with 100 µg /ml ampicillin and 50 µg/ml Kanamycin 200 rpm shaking until the OD (600 nm) value reached 0.6-0.8 nm. The seed culture was transferred to a 100 L bioreactor containing 60 L of ZYM-5052 medium with lactose doubled and the rest unchanged. The temperature and stirring were started at 37 °C and 200 rpm, respectively. When the OD (600 nm)value reaches 0.6–0.8, the temperature drops to 20℃ continuing cultures for 16–18 h. The pH was maintained at 7.0-7.1 by the addition of 30% H<sub>3</sub>PO<sub>4</sub> and NaOH. The concentration of dissolved oxygen was maintained at 30-35% of air saturation. When the DO (dissolved oxygen) level could not be maintained by increasing oxygen, the feed rate was controlled by adding medium (yeast 40 g/L, peptone 80 g/L, MgSO<sub>4</sub>·7H<sub>2</sub>O 10 g/L, lactose 100 g/L). A DO control feed approach was used to control the feeding rate. After fermentation, pellets were harvested by using continuous flow centrifuges centrifugation at 12,000 ×g, 4 °C, and the pellet was frozen at − 70 °C.</p>", "<title>RGD-p21Ras-scFv recombinant antibody purification, refolding</title>", "<p id=\"Par20\">The RGD-p21Ras-scFv was purified by affinity chromatography and ion exchange chromatography. After fermentation, the cells were harvested. The 31 g cell pellets were ultrasonically disrupted and centrifuged as 12,000 g for 20 min. The inclusion bodies were dissolved with binding buffer, they were filtered using a 0.45 nm filter membrane and following purification. Firstly, the recombinant protein purification with Ni Sepharose 6 Fast Flow (GE Healthcare,) under the denaturation condition. The Ni-NTA resin was washed with binding buffer I (20 mM phosphate, containing 10 mM imidazole and 500 mM NaCl, 8 M urea, and pH 7.4) until OD280 of effluent reached the baseline. Contaminating proteins were eluted from the column with wash buffer II l containing (20 mM phosphate,20 mM imidazole 500 mM NaCl, 8 M urea, and pH 7.4). Finally, the protein was eluted with elution buffer (20 mM phosphate,250 mM imidazole, 500 mM NaCl, 8 M urea, and pH 7.4). Then, the proteins were refolded under the refolding condition as the prior description [##REF##33765976##20##]. By using a urea gradient for refolding, the dialysis sequence starts with reversion solution I for 6 h with 6 M urea. Dialysis refolding is performed at low temperature using a magnetic stirrer, and dialysis refolding is completed when dialysis reversion solution IV is ready with 0 M urea, and finally, RGD-p21Ras-scFv recombinant antibody is dialyzed in 0.01 M PBS (containing 10% glycerol) buffer. In the last, the DEAE Sepharose FF column chromatography purification was performed. The eluted with buffer containing different concentrations of NaCl (0.3 mol/L, pH 8.0). The purity of fusion protein was assessed using SDS-PAGE, and its concentration was evaluated with the BCA Protein Assay Kit.</p>", "<title>ELISA to identify RGD-p21Ras-scFv immunoreactivity</title>", "<p id=\"Par21\">Respectively, dilute K-p21RAS, N-p21RAS and H-p21RAS antigens to a final concentration of 5ug/ml using pH 9.6 substrate buffer, incubation at 4 °C overnight; add 1% BSA-PBS for closure, incubate at 37 °C for 1 h and wash with TBST; respectively, add RGD-p21Ras-scFv recombinant antibodies at 1:50, 1:100, 1:200, 1:400, 1:800, 1:1600, 1:3200 and conduct 1-hour incubation at 37 °C and wash by TBST; add diluted anti-His tag antibody, make 1-hour incubation at 37 °C and washed; add diluted anti-His tag antibody(1:4000), make 1-hour incubation at 37 °C and washed; add diluted secondary antibody(1:200) of enzyme standard, incubate at 37 °C for 1 h and perform TMB color development. An enzyme marker was adoptedto measure the absorbance value at a wavelength of 450 nm.</p>", "<title>Counting Kit-8 assay to determine IC50</title>", "<p id=\"Par22\">After being seeded into 96-well culture plates with 5000 cells per well, HT29, SW837, LS180, SW480 and HCT116 cells were treated with different doses (0 μm, 2.5 μm, 5 μm, 10 μm, 20 μm, 40 μm, 80 and 160 μm)) of the drug for 48 h. Cell viability was checked with the Cell Counting Kit-8 assay (CCK8, APExBIO, Lot: K101816122EF5E) based on the manufacturer’s protocol, and IC50 values were calculated.</p>", "<title>SDS-PAGE</title>", "<p id=\"Par23\">Add 5×loading buffer with protein samples to make the final concentration of buffer to 1X. mix well using a vortex shaker before loading, and microcentrifuge in a centrifuge, heat the EP tubes in a preheated metal bath at 98 °C for 10 min. load the samples separately according to the experimental order, first run 85 V to the separation gel and then adjust the voltage to 110 V. after electrophoresis, put the separation gel into Komas Brilliant Blue After staining for half an hour, the separation gel was decolorized by boiling with distilled water until clear protein bands could be observed, stopped decolorization and photographed and recorded.</p>", "<title>Immunofluorescence colocalization</title>", "<p id=\"Par24\">HT29, SW837, LS180, SW480 and HCT116 cells were inoculated at approximately 50% density on microscope slides and allowed to adhere overnight. The cells were co-cultured with 30 µM RGD-p21Ras-scFv for 5 h. The 30-minute fixation of cells was made with 4% paraformaldehyde, followed by washing with PBS; the 10-minute permeabilization of cells was made with 0.2% Triton X-100. After 1-hour incubation with primary anti-Pan-Ras mouse monoclonal antibody (sc-166,691, Santa Cruz) and His-tag rabbit monoclonal antibody (#12,698, CST) at 37 °C, the 1-hour incubation of secondary anti-Goat anti-mouse IgG/TRITC (1: 200, 113,608, ZSGB-BIO) and Goat anti-rabbit IgG/FITC (1 :200, 135,850, ZSGB-BIO) was made at 37 °C in the dark. Then, 7 µl of DAPI (Solarbio, C0065) was put to every slide, and the slides were sealed and protected from light. Images were taken with a fluorescent camera (OLYMPUS, BX51).</p>", "<title>Pull-down assay</title>", "<p id=\"Par25\">The RGD-p21Ras-scFv with FLAG tag, wild-type p21Ras gene with MYC tag and p21Ras<sup>G12C</sup> gene mutation with MYC tag plasmids were synthesized by Shanghai Jikai Gene Medical Technology Co., Ltd. Single colonies were selected by the plate scribing method, inoculated into liquid medium containing antibiotics, and shaken at 220 rpm at 37 ℃ for 12–16 h. Finally, the extraction of plasmid was made based on the standard experimental step using the EndoFree Mini Plasmid Kit II (Cat. #DP118-02) from TIANGEN BIOTECH (Beijing) Co., Ltd., and stored at -20 °C until use. Finally, using a Lipofectamine™ 3000 Transfection Kit (Thermo, 2,413,975, USA), the plasmid was transfected into 293T cells. The RGD-p21Ras-scFv plasmid with FLAG and the wild-type p21Ras plasmid with MYC were transfected into 293T cells. RGD-p21Ras-scFv with FLAG and p21Ras<sup>G12C</sup> with Myc were grouped, and blank plasmids with FLAG and RGD-p21Ras-scFv with FLAG were transfected into 293T cells (human embryonic kidney cells) for 36 h and then lysed in lysis buffer. A FLAG-labeled protein immunoprecipitation kit (magnetic bead method) and BeyoMag™ Anti-Flag Magnetic Beads (Beyotime, P2181S, P2118-2ml) were used, and 500 µl protein samples were incubated with 20 µl magnetic bead suspension at 4 °C overnight, magnetically separated for 10 s and washed. Finally, the protein samples obtained from these samples were eluted by the 3X FLAG competitive elution method. Proteins were detected by western blotting with an anti-FLAG tag mouse monoclonal antibody (1:1000, Proteintech, 66008-4-lg), anti-MYC tag mouse monoclonal antibody (1:1000, Proteintech, 60003-2-lg) and the appropriate goat anti-mouse IgG/HRP secondary antibody (1:10000, ZSGB-BIO, ZB-5305).</p>", "<title>Molecular Docking</title>", "<p id=\"Par26\">Build the RGD-p21Ras-scFv model using Piper (Clus Pro 2.0), save the PDB file. Download the PDB files (K-p21Ras, ID: 4LDJ; H-p21Ras, ID: 6E6P; N-p21Ras, ID: 3CON) at <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.rcsb.org/\">https://www.rcsb.org/</ext-link>. Open the antibody docking mode of the Piper for antigen-antibody docking. Import the pdb of K-p21Ras; H-p21Ras; N-p21Ras; in separate steps for optimization (hydrogen addition, charge calculation, etc.). Import RGD-p21Ras-scFv.pdb. Close the non-CDR regions. Fourier-transformed surface fit search using CDR regions with antigens (Note: find the most appropriate antigen-antibody docking model among 70,000 conformations combined with the actual situation) [##REF##23053206##25##].</p>", "<title>Molecular dynamics simulation</title>", "<p id=\"Par27\">Gromacs (version 2022.3) software [##UREF##0##26##, ##REF##16211538##27##] was adopted for the molecular dynamics simulation. First, the molecularly docked pdb was imported and the pdb was converted to the protein format of Gromacs, and the amber99sb-ildn force field and the tip3p water model were specified. Then, add the periodic bounding box shaped as a vertical square at a distance of 1.2 nm from the protein, and add the just-set tip3p water in the box after the following two lines are added Na ions to neutralize the charge in the system to make it electrically neutral. After performing the energy minimization process the system is subjected to NVT equilibrium and NPT equilibrium. Finally, start the simulation.</p>", "<title>Western blotting</title>", "<p id=\"Par28\">After different doses (described above) of drug treatment for 48 h, cells (HT29, SW837, LS180, SW480 and HCT116) were lysed in RIPA lysis and extraction buffer (Cat# 89,900, Thermo, USA). BCA protein assay kits (Beyotime, China) were used for collection and quantification of proteins. Electrophoresed by 10% SDS‒PAGE, proteins were moved to a PVDF membrane (Bio-Rad, USA) with transfer buffer. The 1-hour blocking of membranes was made with 5% nonfat milk powder, followed by incubation with primary antibodies (1:1000) against β-actin (Cell Signaling Technology (CST), #3700), PI3K (Proteintech, 60225-1-Ig), P-PI3K (CST, #17,366), ERK1/2 (Proteintech, 67170-1-Ig); P-P44/42MAPK (ERK1/2) (CST, #4370), AKT (CST, #4691), P-AKT (CST, #4060), MEK1/2 (Proteintech, 110499-1-AP), and P-MEK1/2 (CST, 9154) overnight at 4 °C. The next day, the 1-hour incubation of membranes was made with the appropriate secondary antibodies (goat anti-rabbit IgG/HRP (1:10000, ZSGB-BIO, ZB-2301) or goat anti-mouse IgG/HRP (1:10000, ZSGB-BIO, ZB-5305)) at room temperature. A western blotting detection system (Bio-Rad, USA) was adopted to visualize protein bands.</p>", "<title>Ras pull-down assay</title>", "<p id=\"Par29\">Ras pull-down assays were made by the Active Ras pull-down kit (Thermo, 16,117). First, cells were lysed using lysis buffer to obtain the protein. Second, by 15-minute incubation of the supernatant of the total cell lysate with guanosine triphosphate labeled with S (GTPγS) on a gamma phosphate base at room temperature, the target protein (p21Ras-GTP, Total p21Ras) [##REF##32459053##28##] was obtained. Finally, the protein samples were subject to resuspending using the agarose beads from the kit, washing with 400 µl of wash buffer, and 30-second centrifugal at 6000 g. Primary antibody anti-Ras antibody (1:250, Thermo) and secondary antibodies (goat anti-Rabbit IgG/HRP (1:10000, ZSGB-BIO, ZB-2301)) were adopted to make western blotting.</p>", "<title>Tumor xenograft animal experiments</title>", "<p id=\"Par30\">The Laboratory Animal Ethics Committee of 920th Hospital, Yunnan, China approved animal experiments. Healthy BALB/c nude mice (male, N = 30, 5–6 weeks old, and weighing 15–18 g) were offered by China Hunan Slake Jingda Experimental Animal Co., Ltd. After being housed under specific pathogen-free (SPF) situations at 25 °C with 50% humidity, all animals can access to food and water freely. The inoculation of HT29 and SW48 cells (1 × 10<sup>6</sup> cells/mouse) in 0.15 ml of serum-free DMEM was made into the left armpits of the nude mice. After 7 days, the tumor volume was 50–100 mm<sup>3</sup> and the random division of mice was made into 5 groups (n = 6 for each group): RGD-p21Ras-scfv treatment group (150 µg/pc/2 days), PBS (150 µg/pc/2 days), RGD (150 µg/pc/2 days), DMSO (150 µg/pc/2 days), KRAS(G12C) inhibitor (150 µg/pc/2 days). The mouse body weight and the length (a) and width (b) of the tumor were supervised every two days with calipers. The calculation of tumor volume (V) was made below: V = ab<sup>2</sup>/2. The tumor tissues were collected, and the tumor was weighed after the mice were anesthetized with persistent isoflurane on Day 21.</p>", "<title>Hematoxylin and eosin staining and histology</title>", "<p id=\"Par31\">After 21 days of treatment, the mice were killed. The heart, liver, spleen, lung, kidney, brain, intestine, stomach tissues, and a part of the tumor were isolated, fixed in 10% paraformaldehyde buffer for HE staining. The freezing of some tumors and normal tissues was made in liquid nitrogen for other research.</p>", "<title>Immunohistochemistry (IHC)</title>", "<p id=\"Par32\">Paraffin sections of tumor tissue were stained immunohistochemically with anti-Ki67 antibody (ZSGB-BIO, 1:200, ZM-0166), anti-His-tag mouse monoclonal antibody (1:10000, Proteintech, 66005-1-lg), anti-LCK antibody (ZSGB-BIO, 1:200, ZM-0329), anti-villin antibody (ZSGB-BIO, 1:200, ZM-0261), and anti-vimentin antibody (ZSGB-BIO, 1:200, ZM-0261) followed by incubation with the secondary antibody and DAB color development. The number of Ki67-positive cells divided by the total number of resting cells [##REF##21366896##29##] was used to calculate the proliferation index (PI).</p>", "<title>Statistical analysis</title>", "<p id=\"Par33\">Data were shown as the mean ± SD of three repeated tests. The statistical significance was compared with Student’s t-test and one-way ANOVA by GraphPad Prism 8.0 (San Diego, CA, USA). *<italic>P</italic> &lt; 0.05 were considered significant.</p>" ]
[ "<title>Results</title>", "<title>Construction and identification of the recombinant expression plasmid</title>", "<p id=\"Par34\">Through the standard procedure for molecular cloning, the RGD-p21Ras-scFv recombinant antibody gene fragment was double-digested from the plcone7 vector. The gene fragment was inserted into three expression plasmids pET32a, pET28a, and pET22b using T4 ligase, and named the recombinant plasmid pET32a-RRS (Fig. ##FIG##0##1##A), pET28a-RRS (Supplementary Fig. ##SUPPL##0##1##A), and pET22B-RRS (Supplementary Fig. ##SUPPL##0##1##B), respectively. The PCR and DNA sequencing also identified the gene fragments were all correctly and inserted correctly in the pET32a-RRS (Fig. ##FIG##0##1##B), pET28a-RRS (Supplementary Fig. ##SUPPL##0##1##C), pET22B-RRS (Supplementary Fig. ##SUPPL##0##1##D).</p>", "<p id=\"Par35\">Expression and fermentation of RGD-p21Ras-scFv recombinant antibody.</p>", "<p id=\"Par36\">Three expression plasmids were transferred into different expression bacteria BL21(DE3), Origami (DE3), and Origami B(DE3). At 37℃ and induced by 1mM IPTG for 5 h, the recombinant proteins expressed in soluble and inclusion body form were screened by SDS-PAGE. Among the three expressing bacteria, inclusion body expression was more than soluble expression (Fig. ##FIG##0##1##C, supplementary Fig. ##SUPPL##0##1##E-F), and most proteins are expressed in the form of inclusion bodies in Origami (DE3) (Fig. ##FIG##0##1##C). The molecular weight of the recombinant antibody was in the range of 35–45 kDa, which was consistent with the predicted results. To increase the expression level, we further screened the concentration and induction time of IPTG and the use of different media. The experimental results showed that the inclusion body expression was the highest at 37℃ and 0.6mMIPTG for 10 h of induction (Fig. ##FIG##0##1##D-E). Moreover, compared with the IPTG-induced expression of traditional LB medium and ZYM-5052 self-induced medium, we found that ZYM-5052 medium could express more inclusion bodies, much higher than that of IPTG induced expression (Fig. ##FIG##0##1##F).</p>", "<p id=\"Par37\">After controlled fermentation by dissolved oxygen feedback and continuous feed feeding, the optimal production conditions were preliminarily determined, and 1863.84 g total of bacteria cell pellets could be obtained by 60 L fermentation, and the average yield was 31.064 g /L (Wet weight of bacteria). At the same time, most proteins are still expressed in the form of inclusion bodies. Compared with the laboratory wet weight of 10.6 g/L of bacteria, fermentation by the dissolved oxygen feedback method greatly increased the yield of bacteria (Fig. ##FIG##0##1##J).</p>", "<title>Two-step of purification of RGD-p21Ras-scFv recombinant antibody</title>", "<p id=\"Par38\">After fermentation, 14.3 g inclusion bodies were obtained from the cell pellets by ultrasonic crushing of 31 g bacteria cell pellets. Under denaturation conditions, Ni-NTA fast flow affinity chromatography was performed first. Protein elution was performed with 250 mM imidazole. The target protein 286.7 mg was obtained from 14.3 g dissolved inclusion body protein solution by Ni column affinity chromatography. Then, urea gradient refolding is performed at low temperatures, and the refolding loss protein is about 3-7% of the total refolding protein (Fig. ##FIG##0##1##G). DEAE ion exchange chromatography was performed after renaturation. DEAE is a commonly used weak anion exchange filler whose adsorption affinity is affected by pH value. DEAE column chromatography results showed that most of the target proteins were eluted by 0.3 mol/L NaCl. The protein with low binding to the DEAE column had a loss of about 40% (Fig. ##FIG##0##1##I). In addition, soluble proteins were purified by Ni-NTA affinity chromatography. The results showed that more target proteins were obtained from inclusion bodies than from soluble proteins by affinity chromatography (Fig. ##FIG##0##1##H). SDS-PAGE identification showed that the target protein size was consistent. The results also showed that the purity of the obtained recombinant protein could reach more than 85%.</p>", "<title>RGD-p21Ras-scFv binds stably to the p21Ras protein and is structurally stable upon binding</title>", "<p id=\"Par39\">To determine the immunoreactivity of the RGD-p21Ras-scFv recombinant antibody with K-p21RAS, H-p21RAS, and N-p21RAS, we examined the immunobinding ability of the purified scFv with K-p21RAS, H-p21RAS, and N-p21RAS using ELISA, and the results showed that 1 mg/ml of RGD-p21Ras-scFv binds to K-p21Ras, H-p21Ras, and N-p21Ras proteins with an immunoreactive activity of 1:800 (Fig. ##FIG##1##2##A). In addition, we verified the binding activity of RGD-p21Ras-scFv with K-p21Ras, H-p21Ras and N–p21Ras by molecular docking, and the results showed that RGD-p21Ras-scFv binds to amino acid residues of K-p21Ras, H-p21Ras and N-p21Ras proteins mainly through hydrogen bonding and salt bridges, with the total binding free energies were − 48.81 kcal/mol, -39.27 kcal/mol and − 35.13 kcal/mol, respectively. (Fig. ##FIG##1##2##B and D).</p>", "<p id=\"Par40\">Finally, our study further explored the stability of RGD-p21Ras-scFv binding to K-p21Ras, H-p21Ras and N-p21Ras proteins by molecular dynamics simulations. Our simulation process has a total of 5,000,000 steps with a step size of 2 fs and a total time of 100ns. Through simulations, we found that the RMSF value of RGD-p21Ras-scFv fluctuated between 0.15 and 0.75 nm, the RMSF value of K-p21Ras fluctuated between 0.15 and 0.60 nm, the RMSF value of H-p21Ras fluctuated between 0.15 and 0.85 nm, and the RMSF value of N-p21Ras fluctuated between 0.15 and 0.58 nm, indicating that RGD-p21Ras-scFv and K-p21Ras, H-p21Ras, and N-p21Ras proteins had minimal fluctuations in the root mean square displacement and average conformation per amino acid, and had good mutual binding activity (Fig. ##FIG##1##2##E and G). The RMSD values of RGD-p21Ras-scFv with K-p21Ras protein complex fluctuated between 0.2 and 0.6 nm, the RMSD values of RGD-p21Ras-scFv with H-p21Ras protein complex fluctuated between 0.15 and 0.6 nm, the RMSD values of RGD-p21Ras-scFv with N-p21Ras protein complex fluctuated between 0.15 and 0.82 nm indicating that the complex fluctuated very little throughout the kinetic simulation and remained stable within a suitable range. The RMSD values of RGD-p21Ras-scFv complex with N-p21Ras protein fluctuated between 0.15 and 0.82 nm indicating that the complexes fluctuated very little throughout the kinetic simulation, were in equilibrium, and remained stable within a suitable range (Fig. ##FIG##1##2##H J). Also, we analyzed the Rg (radius of gyration) of RGD-p21Ras-scFv in complex with K-p21Ras, H-p21Ras, and N-p21Ras proteins by molecular dynamics simulations, and we found that the Rg values of RGD-p21Ras-scFv in complex with K-p21Ras protein fluctuated between 2. 15 and 2.25 nm, the RGD- p21Ras-scFv fluctuated between 2.10 and 2.25 nm for the Rg value of the RGD-p21Ras-scFv with the H-p21Ras protein complex, and 2.15–2.35 nm for the RGD-p21Ras-scFv with the N-p21Ras protein complex, suggesting that the Rg values of RGD-p21Ras-scFv with the K-p21Ras, H- p21Ras and N-p21Ras proteins formed a stable complex (Fig. ##FIG##1##2##K and M). During the simulations, RGD-p21Ras-scFv formed an average of 6–10 hydrogen bonds upon binding to K-p21Ras, H-p21Ras, and N-p21Ras, which represents a strong interaction of the complex (Fig. ##FIG##1##2##N and P).</p>", "<title>RGD-p21Ras-scFv significantly inhibits the growth of multiple ras-derived Tumor cell lines</title>", "<p id=\"Par41\">To determine the antitumor activity of RGD-p21Ras-scFv in vitro, we used 30 µM PBS, RGD peptide, and 0.32 µM RGD-p21Ras-scFv with Ras-derived tumor cell lines (A549, AGS, AsPC-1, HePG-2, MDB-MA-321, MIApaca-2, PANC- 1, U 251, SW480, HT29 and SW480) and a normal colon epithelial cell line (CCD841) were co-cultured for a period of time, and cell proliferation was analyzed by CCK-8 assay. The results showed that neither PBS, RGD nor RGD-p21Ras-scFv inhibited the growth of the normal colon epithelial cell line CCD841 (Fig. ##FIG##2##3##A); however, RGD-p21Ras-scFv significantly inhibited the growth of all the Ras-associated tumor cell lines we included (Fig. ##FIG##2##3##B L). Importantly, it is evident from our results that RGD-p21Ras-scFv inhibited colorectal cancer cell lines most significantly and showed a more statistically significant difference (Fig. ##FIG##2##3##J L). Therefore in the following study we used the tumor cell lines expressing the most common KRAS origin in colorectal cancer as our in-depth study, and also included more KRAS mutated types of colorectal cancer cell lines.</p>", "<title>RGD-p21Ras-scFv enters KRAS wild-type and mutant Colorectal cancer cell to bind to p21Ras</title>", "<p id=\"Par42\">To determine the localization and distribution of RGD-p21Ras-scFv in KRAS wild-type and (KRAS<sup>G12C</sup>, KRAS<sup>G12D</sup>, KRAS<sup>G12V</sup>, KRAS<sup>G13D</sup>) mutant colorectal cancer cell lines, we performed analysis by immunofluorescence co-localization and showed that RGD-p21Ras-scFv could enter into the cancer cell membrane and co-localize with p21Ras co-localization (Fig. ##FIG##3##4##A). Meanwhile, we further validated that RGD-p21Ras-scFv interacts with KRAS wild-type and KRAS<sup>G12C</sup> mutant in cells using a pull-down assay. By co-transfecting RGD-p21Ras-scFv with FLAG tag and blank plasmid with FLAG tag, RGD-p21Ras-scFv with FLAG tag and KRAS wild-type with MYC tag, and RGD-p21Ras-scFv with FLAG tag and KRAS<sup>G12C</sup> mutant with MYC tag into 293T cells, respectively, after successful transfection, cell proteins were collected and FLAG- and MYC-tagged magnetic beads were added for IP experiments. The results showed that RGD-p21Ras-scFv could directly have a mutual effect with wild-type K-p21Ras and mutant K-p21Ras<sup>G12C</sup>. Finally, when we used FLAG and MYC antibodies for detection, we found that in IP-treated proteins we were able to detect RGD-p21Ras-scFv using FLAG antibody to detect RGD-p21Ras-scFv as well as MYC antibody; and at the same time, we were able to detect p21Ras-scFv using MYC antibody as well as RGD-p21Ras-scFv using FLAG antibody (Fig. ##FIG##3##4##B, ##FIG##3##4## C).</p>", "<title>RGD-p21Ras-scFv reduced p21Ras-GTP expression and inhibited MEK-ERK/PI3K-AKT phosphorylation</title>", "<p id=\"Par43\">To elucidate the potential mechanism by which RGD-p21Ras-scFv inhibits the activity of colorectal cancer cell lines after stable binding to p21Ras. This study performed Ras pull-down assays using the KRAS wild-type colorectal cancer cell line HT29 and KRAS mutant colorectal cancer cell lines SW837<sup>G12C</sup>, LS180<sup>G12D</sup>, SW480<sup>G12V</sup>, and HCT116<sup>G13D</sup>. The results showed that RGD-p21Ras-scFv reduced p21Ras-GTP expression in all of the above colorectal cancer cell lines, while KRAS (G12C) inhibitor only reduced p21Ras-GTP expression in KRAS<sup>G12C</sup> mutant colorectal cancer cells (Fig. ##FIG##4##5##A); after analyzing relative protein expression for quantification, our results proved to be statistically significance (Figure Supplementary ##SUPPL##0##3## A).</p>", "<p id=\"Par44\">The MEK-ERK and PI3K-AKT signaling paths downstream of Ras are the classical pathways that promote tumor progression. To further explore the effect of RGD-p21Ras-scFv on downstream signaling pathways after inhibition of Ras activity, we analyzed the changes of MEK-ERK and PI3K-AKT signaling molecules in the above KRAS wild and KRAS mutant colorectal cancer cell lines by WB. The results showed that RGD-p21Ras-scFv significantly reduced the phosphorylation of MEK-ERK/PI3K-AKT and inhibited the activation of MEK-ERK/PI3K-AKT signaling pathway in KRAS wild-type and mutant colorectal cancer cell lines, and KRAS (G12C) inhibitors only inhibited KRAS<sup>G12C</sup> mutant colorectal cancer cell lines (Fig. ##FIG##4##5##B F, Supplementary Fig. ##SUPPL##0##2##B-F).</p>", "<title>RGD-p21Ras-scFv inhibits Tumor growth in nude mice</title>", "<p id=\"Par45\">To decide the antitumor activity of RGD-p21Ras-scFv in nude mice, we selected the KRAS wild-type colorectal cancer cell line HT29 and the KRAS<sup>G12V</sup> mutant colorectal cancer cell line SW480 with low IC50 values to establish nude mouse xenograft model and administered the drug for treatment. Reduced growth rate of xenografts volume in RGD-p21Ras-scFv treated nude mice was found by plotting the tumor volume growth curve (Fig. ##FIG##5##6##A and D). At the end of the administration, individual organs and xenografts were collected and the xenografts were weighed and found that the weight of xenografts in RGD-p21Ras-scFv treated nude mice was significantly lower than other treatment groups (Fig. ##FIG##5##6##B and E), while we observed the smallest xenografts in the RGD-p21Ras-scFv treated group (Fig. ##FIG##5##6##C, ##FIG##5##6## F).</p>", "<p id=\"Par46\">Finally, we verified whether RGD-p21Ras-scFv could target nude mice xenografts cells and inhibit their cell proliferation, and we collected xenografts from each treatment group of nude mice for Ki67 staining and analyzed other organs of nude mice for HE staining. Ki-67 results showed that RGD-p21Ras-scFv effectively inhibited the proliferation index of xenografts established in human colorectal cancer cell lines in nude mice (Fig. ##FIG##5##6##G, ##FIG##5##6## H). HE staining showed that RGD-p21Ras-scFv treatment did not cause pathological damage to the major organs of nude mice (Supplementary Fig. ##SUPPL##0##3##A, ##SUPPL##0##3##B). Moreover, we analyzed the distribution of RGD-p21Ras-scFv in the organs of nude mice, and immunohistochemical results showed that RGD-p21Ras-scFv was present only in xenograft (Fig. ##FIG##5##6##I), while the same results were obtained by WB assay (Supplementary Fig. ##SUPPL##0##4##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par47\">In previous studies, we constructed RGD-p21Ras scFv recombinant antibody and expressed them in small amounts in E. coli in the laboratory. It was found that the RGD-p21Ras scFv could enter the tumor cells that has integrin αvβ3 expression on the surface and bind to intracellular p21Ras to inhibit the proliferation of tumor cells. However, the key to clinical translational application of p21Rras recombinant antibody is to scale expression and maintain their biological effects of penetrating into tumor cells and binding to intracellular p21Ras.</p>", "<p id=\"Par48\">In this study, we optimized the conditions for the expression of recombinant proteins to solve the problem of obtaining large amounts of proteins. It can conduct in vivo experiments and prepare for future preclinical studies to scale up protein production. When RGD peptide conjugated with proteins, they may result in low production. For example, Curnis et al [##REF##14744770##30##]. used RGD to modify TNF, resulting in getting 2 mg of RGD-MTNF from 1 L of <italic>E. coli.</italic> In our study, through the selection of different plasmids and bacteria, we screened the best expression plasmid and bacteria combination. ZYM-5052 culture medium can further improve the expression level of target protein, and the result was demonstrated that the self-induced expression of ZYM-5052 is much higher than that of the traditional IPTG-induced expression. Through the fermentation culture of 60 L in a 100 L bioreactor, we can finally get 31.064 g/L wet-weight bacteria. Compared with 10.6 g/L under laboratory conditions, it is significantly improved. Compared with the 30 g/L wet bacteriophage obtained from the pilot-scale preparation process established by the SA-hGM-CSF bifunctional fusion protein, our recombinant antibody was able to meet the requirements of the pilot-scale preparation [##REF##31017543##31##].</p>", "<p id=\"Par49\">In <italic>E. coli.</italic> expression systems, purification and renaturation are essential to obtain biologically active proteins. Moreover, the greatest loss of protein occurs usually in these two steps. Unlike other studies [##REF##19823948##32##], a two step purification method was used in our study. Firstly, we used affinity chromatography under denaturation conditions, and by gradient refolding to remove urea and imidazole. Then, DEAE ion exchange chromatography resin was used to further purify the protein after refolding, which was beneficial to improve the purity. After refolding and DEAE purification, the protein with low binding affinity was flow-through, and about 60% of the protein was obtained. Finally, Our protein purity is higher than 85%. The purity was in the same range as other antibody purification obtained from other reports [##REF##24519456##33##, ##REF##33718141##34##], which proved that our purification was effective.</p>", "<p id=\"Par50\">It is certain that our preparation of RGD-p21Ras-scFv has strong immunoreactivity with p21Ras (K-p21Ras, N-p21Ras, H-p21Ras) and can bind to them to exert anti-tumor effects. We visualized that scale expression of RGD-p21Ras-scFv entered KRAS wild and KRAS mutant colorectal cancer cell lines and co-localized with p21Ras protein by immunofluorescence. Second, the analysis of performing pull-down tests also directly illustrates that our RGD-p21Ras-scFv interacts with wild K-p21Ras and mutant K-p21Ras proteins. Further, we also used molecular docking and molecular dynamics simulations to demonstrate that RGD-p21Ras-scFv has strong binding ability with wild K-p21Ras and mutant K-p21Ras proteins, and the bound protein complexes remain stable for a longer period of time. Here, we can clarify that scale expression of RGD-p21Ras-scFv enters tumor cells and binds to p21Ras by multiple forces including hydrogen bonding, and the bound complex remains stable for a long time.</p>", "<p id=\"Par51\">As it is known that p21Ras switches between binding to GDP (inactive) and GTP (active), we have clarified that scale expression of RGD-p21Ras-scFv can bind to p21Ras protein with a very significant interaction, it was observed that RGD-p21Ras-scFv can reduce the expression of active p21Ras (p21Ras-GTP) protein after binding to p21Ras protein by Ras pull down assay. Also, considering that active p21Ras activates MEK phosphorylation, which activates downstream ERK phosphorylation [##UREF##1##35##], activation of PI3K/AKT phosphorylation also promotes RAS-dependent tumor growth and exerts a complementary effect on the MEK/ERK signaling cascade [##REF##17496923##36##]. Thus, this study also demonstrated that RGD-p21Ras-scFv reduced activity of p21Ras after downregulating the phosphorylation of MEK-ERK/PI3K-AKT signaling pathway downstream of Ras. Based on these results, we elucidated for the first time the specific mechanism by which RGD-p21Ras-scFv exerts its antitumor activity: RGD-p21Ras-scFv enters tumor cells and binds to p21Ras, reduces the expression of active p21Ras (p21Ras-GTP) protein, and further inhibits the phosphorylation of MEK-ERK/PI3K-AKT signaling pathway.</p>", "<p id=\"Par52\">We found that scale expression of RGD-p21Ras-scFv have anti-tumor activity in vitro, since many drugs were developed with good in vitro effects but poor in vivo effects and poor safety [##REF##15796152##37##], we selected the KRAS wild-type colorectal cancer cell line HT29 and the KRAS<sup>G12V</sup> mutant colorectal cancer cell line SW480 with good in vitro effects to establish a nude mouse xenograft tumor model and treated with RGD-p21Ras-scFv administration. We found that scale expression of RGD-p21Ras-scFv greatly stopped the development of xenograft tumors while ensuring a certain safety profile, specifically targeting xenograft tumors and reducing the proliferation of tumor cells.</p>", "<p id=\"Par53\">In conclusion, we screened the combination of recombinant plasmids and expression bacteria as well as optimized the induction expression conditions and successfully established the pilot-scale prokaryotic expression of RGD-p21Ras-scFv recombinant antibody. Furthermore, we elucidated for the first time that scale expression of RGD-p21Ras-scFv enters KRAS wild and mutant colorectal cancer cell lines to stably bind to p21Ras and reduce the expression of active p21Ras protein, and consequently inhibits phosphorylation of the MEK-ERK/PI3K-AKT signaling pathway downstream of Ras, providing safety while effectively inhibiting RAS-dependent tumor growth. Our outcomes offer a theoretical basis for the clinical translation and usage of RGD-p21Ras-scFv for the treatment of Ras-derived tumors.</p>", "<p id=\"Par35007\">\n\n</p>", "<p id=\"Par2307\">\n\n</p>", "<p id=\"Par50507\">\n\n</p>", "<p id=\"Par33507\">\n\n</p>", "<p id=\"Par3507\">\n\n</p>", "<p id=\"Par58\">\n\n</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Ras gene mutation and/or overexpression are drivers in the progression of cancers, including colorectal cancer. Blocking the Ras signaling has become a significant strategy for cancer therapy. Previously, we constructed a recombinant scFv, RGD-p21Ras-scFv by linking RGD membrane-penetrating peptide gene with the anti-p21Ras scFv gene. Here, we expressed prokaryotically RGD-p21Ras-scFv on a pilot scale, then investigated the anti-tumor effect and the mechanism of blocking Ras signaling.</p>", "<title>Methods</title>", "<p id=\"Par2\">The <italic>E. coli</italic> bacteria which could highly express RGD-p21Ras-scFv was screened and grown in 100 L fermentation tank to produce RGD-p21Ras-scFv on optimized induced expression conditions. The scFv was purified from <italic>E. coli</italic> bacteria using His Ni-NTA column. ELISA was adopted to test the immunoreactivity of RGD-p21Ras-scFv against p21Ras proteins, and the IC50 of RGD-p21Ras-scFv was analyzed by CCK-8. Immunofluorescence colocalization and pull-down assays were used to determine the localization and binding between RGD-p21Ras-scFv and p21Ras. The interaction forces between RGD-p21Ras-scFv and p21Ras after binding were analyzed by molecular docking, and the stability after binding was determined by molecular dynamics simulations. p21Ras-GTP interaction was detected by Ras pull-down. Changes in the MEK-ERK /PI3K-AKT signaling paths downstream of Ras were detected by WB assays. The anti-tumor activity of RGD-p21Ras-scFv was investigated by nude mouse xenograft models.</p>", "<title>Results</title>", "<p id=\"Par3\">The technique of RGD-p21Ras-scFv expression on a pilot scale was established. The wet weight of the harvested bacteria was 31.064 g/L, and 31.6 mg RGD-p21Ras-scFv was obtained from 1 L of bacterial medium. The purity of the recombinant antibody was above 85%, we found that the prepared on a pilot scale RGD-p21Ras-scFv could penetrate the cell membrane of colon cancer cells and bind to p21Ras, then led to reduce of p21Ras-GTP (active p21Ras). The phosphorylation of downstream effectors MEK-ERK /PI3K-AKT was downregulated. In vivo antitumor activity assays showed that the RGD-p21Ras-scFv inhibited the proliferation of colorectal cancer cell lines.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">RGD-p21Ras-scFv prokaryotic expressed on pilot-scale could inhibited Ras-driven colorectal cancer growth by partially blocking p21Ras-GTP and might be able to be a hidden therapeutic antibody for treating RAS-driven tumors.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12885-023-11686-5.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank all the team members who participated in the study.</p>", "<title>Author contribution</title>", "<p>Conceptualization, JLY, QF and PL; Investigation, PL, CCH and JQ; Resources, WMX, YYW, ZRG, SQZ, PW, and DQJ; Writing–Original Draft, PL; Supervision, QF, and JLY; Funding Acquisitions, JLY.</p>", "<title>Funding</title>", "<p>The Major Science and Technology Project of the Yunnan Science and Technology Plan [2018ZF009] supported this work.</p>", "<title>Data Availability</title>", "<p>The protein structure data analyzed in this study can be found in the RCSB Protein Data Bank at <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.rcsb.org/\">https://www.rcsb.org/</ext-link> PDB files are (K-p21Ras, ID: 4LDJ; H-p21Ras, ID: 6E6P; N-p21Ras, ID: 3CON). Also, information supporting the results of this study can be found in the article or in the supplementary material and is available from the corresponding author on request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par67\">All methods in this paper are based on the ARRIVE guidelines report (<ext-link ext-link-type=\"uri\" xlink:href=\"https://arriveguidelines.org\">https://arriveguidelines.org</ext-link>) for the study in question, while this study was approved by the ethics committee of the Kunming University of Technology and is also based on the Declaration of Helsinki of 1975. The animals in the study were raised according to institutional guidelines. None of the cell lines used in this study required ethical approval.</p>", "<title>Consent to publish</title>", "<p id=\"Par68\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par269\">No potential conflicts of interest in terms of the study, authorship, and/or publication of this article were declared.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Expression and purification of RGD-p21Ras-scFv recombinant antibody in E.coil system. <bold>(A)</bold>The recombinant expression plasmids pET32a-RRS were set up by inserting the RGD-p21Ras-scFv gene into the corresponding enzyme cleavage site of the plasmid vector. <bold>(B)</bold> PCR showed the RGD-p21Ras-scFv gene was successfully transferred into pET32a plasmid. <bold>(C)</bold> The highest expression of RGD-p21Ras-scFv was detected in Origami(DE3) and Origami B(DE3) inclusion bodies by SDS-PAGE. The red arrow showed the target protein. <bold>(D)</bold> The RGD-p21Ras-scFv was expression in different concentration of IPTG from 0.2mM to 1.6mM. The red arrow shows the optimum inducible expression conditions. <bold>(E)</bold> After the suitable concentration of IPTG was chosen(0.6mM), the induced time was investigated from 4 to 20 h. The red arrow shows the optimum inducible expression conditions. <bold>(F)</bold> SDS-PAGE showed theRGD-p21Ras-scFv was more highly expressed in the self-induction system than in IPTG as detected by SDS-PAGE analysis. The red arrow shows the target protein. <bold>(G)</bold> Affinity chromatogram (left) and SDS-PAGE (right) of RGD-p21Ras-scFv recombinant antibody from Ni2 + affinity resin. The wash fraction contains 20 mM imidazole, and the elution fraction contains 250 mM imidazole. <bold>(H)</bold> RGD-p21Ras-scFv recombinant antibody was more highly expressed in inclusion bodies than in soluble proteins as detected by SDS-PAGE analysis. <bold>(I)</bold> Ion-exchange chromatography of RGD-p21Ras-scFv from DEAE resin (left) and SDS-PAGE (right). The refolding protein to loading up after adjusted the pH at 8.0 and the elution fraction with 0.3 mol/L NaCl in elution buffer. <bold>(J)</bold> Comparison of the wet weight of bacteria expressed in small scale shaker in laboratory and fermentation. Fermentation can significantly increase the yield (cell wet weight)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>RGD-p21Ras-scFv could bind stably to K-p21Ras, H-p21Ras and N-p21Ras proteins. <bold>(A)</bold> RGD-p21Ras-scFv was immunoreactive with K-p21Ras, H-p21Ras and N-p21Ras at 1:800 by ELISA. <bold>(B, C, D)</bold> The molecular docking model of RGD-p21Ras-scFv to K-p21Ras, H-p21Ras and N-p21Ras proteins, The RGD-p21Ras-scFv binds to p21Ras through hydrogen bonding and salt bridges et al. <bold>(E-P)</bold> Molecular dynamics simulated the interaction and stability of RGD-p21Ras-scFv upon binding to p21Ras. The complexes formed by RGD-p21Ras-scFv with K-p21Ras, H-p21Ras and N-p21Ras fluctuated very little and were highly stable during the simulation process, and the graphs demonstrated RMSF; RMSD; Rg; and the number of hydrogen bonding from left to right, respectively</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>RGD-p21Ras-scFv significantly inhibits the growth of Ras-derived tumor cell lines. Eleven Ras-derived-associated tumor cell lines and one normal epithelial cell lines were co-cultured with RGD-p21Ras-scFv, PBS, and RGD peptide in 96-well plates for 24, 48, and 72 h, and then cellular activity was assayed using the CCK-8 time. rgd-p21Ras-scFv inhibited the growth of the incorporated Ras-derived tumor cells but had no normal colon epithelial cell effects. <bold>(A)</bold> CCD841; <bold>(B)</bold> A549, <bold>(C)</bold> AGS, <bold>(D)</bold> AsPC-1, <bold>(E)</bold> HePG-2, <bold>(F)</bold> MDB-MA-321, <bold>(G)</bold> MIApaca-2, <bold>(H)</bold> PANC- 1, <bold>(I)</bold> U251, <bold>(J)</bold> SW480, <bold>(K)</bold> HT29 and (L) SW480 Data are expressed as the mean of three independent experiments expressed, Mean ± SD. *<italic>p</italic> &lt; 0.05; **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001, ****<italic>p</italic> &lt; 0.0001</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>RGD-p21Ras-scFv enters tumor cells to bind directly to p21Ras. <bold>(A)</bold> Immunofluorescence assay showed that RGD-p21Ras-scFv(green) entered tumor cells and co-localized with p21Ras(red) in colorectal cancer cell lines HT29, SW837, LS180, SW480, HCT116. Nuclei were stained with DAPI (blue). <bold>(B, C)</bold> Pull-down assay revealed that RGD-p21Ras-scFv could directly bind with wild-type K-p21Ras and mutant K-p21Ras. Plasmids of RGD-p21Ras-scFv with Flag (scFv-Flag), blank with Flag (Flag), wild-type KRAS with MYC (K-p21RasW-Myc), and mutant KRAS with MYC (K-p21RasM-Myc) were transfected into 293T cells. No-IP: whole-cell lysate; Flag-IP: eluate by anti-Flag beads, Myc-IP: eluate by anti-Myc beads. No-IP, Flag-IP, and Myc-IP by WB detection</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>The binding between RGD-p21Ras-scFv and p21Ras protein could reduce p21Ras-GTP (active Ras) and inhibit phosphorylation of the downstream pathway MEK-ERK/PI3K-AKT in colorectal cancer. <bold>(A)</bold> RGD-p21Ras-scFv reduces p21Ras-GTP by western-blot analysis. The colorectal cancer cell lines were cocultured with RGD-p21Ras-scFv, KRAS(G12C) inhibitor, PBS, RGD or DMSO for 48 h. The proteins p21Ras-GTP and total p21Ras were enriched in the cell lysates by an RAS pull-down kit. <bold>(B-F)</bold> The RGD-p21Ras-scFv inhibits the phosphorylation of the MEK-ERK/PI3K-AKT signaling pathway. Colorectal cancer cell lines were cocultured with RGD-p21Ras-scFv, KRAS(G12C) inhibitor, PBS, RGD or DMSO for 48 h. Cells were lysed, and proteins were extracted for western blot analysis Ras changes in downstream signaling pathways. β-actin was adopted as the control</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>RGD-p21Ras-scFv inhibited the growth of xenografts in nude mice. <bold>(A, D)</bold> All the nude mice were weighed and divided into the following five groups: PBS, RGD, RGD-p21Ras-scFv, DMSO and K-Ras(G12C) inhibitor group. The tumor growth curves were drawn according to the tumor sizes. The tumor volume growth was inhibited by the RGD-p21Ras-scFv. <bold>(B, E)</bold> RGD-p21Ras-scFv treatment group had the lowest tumor weight compared to the other groups. <bold>(C, F)</bold> Tumor tissues from each group were dissected and examined by general observation. <bold>(G, H)</bold> IHC showed there were less Ki67-positive cells in the RGD-p21Ras-scFv treatment group. Ki67 index (PI) was calculated and scored from the number of Ki67-positive cells to the total number of tumor cells, Mean ± SD. *<italic>P</italic> &lt; 0.05, **<italic>P</italic> &lt; 0.01. <bold>(I)</bold> After 24 days of treatment, RGD-p21Ras-scFv was only presented in xenograft tumor tissues rather than in any other major organs by IHC analysis</p></caption></fig>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Peng Lin, Jing Qian and Chengcheng Huang have contributed equally to this work.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12885_2023_11686_MOESM1_ESM.docx\"><caption><p>Supplementary Material 1</p></caption></media>" ]
[{"label": ["26."], "surname": ["Abraham", "Murtola", "Schulz", "P\u00e1ll", "Smith", "Hess", "Lindahl"], "given-names": ["MJ", "T", "R", "S", "JC", "B", "E"], "article-title": ["GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers"], "source": ["SoftwareX"], "year": ["2015"], "volume": ["1\u20132"], "fpage": ["19"], "lpage": ["25"], "pub-id": ["10.1016/j.softx.2015.06.001"]}, {"label": ["35."], "mixed-citation": ["Tsubaki M, Takeda T, Noguchi M, Jinushi M, Seki S, Morii Y, Shimomura K, Imano M, Satou T, Nishida S. Overactivation of akt contributes to MEK inhibitor primary and Acquired Resistance in Colorectal Cancer cells. Cancers (Basel) 2019, 11(12)."]}]
{ "acronym": [], "definition": [] }
37
CC BY
no
2024-01-14 23:43:46
BMC Cancer. 2024 Jan 12; 24:71
oa_package/25/33/PMC10787443.tar.gz
PMC10787444
0
[ "<title>Background</title>", "<p id=\"Par4\">Poly C binding protein (PCBP) generally refers to an RNA binding protein belongs to the heterogeneous nuclear ribonucleoprotein family with a molecular weight of about 38 kDa [##REF##33058239##1##]. There are four members in PCBP family, PCBP1–4, also known as α-CPs or hnRNP E 1–4 [##REF##12003487##2##]. Three highly conserved hnRNP K homology (KH) domains and poly(C)-binding specificity are common features of the PCBP family [##REF##12003487##2##, ##UREF##0##3##]. The KH domain is critical for PCBP1 to recognize and bind poly(C) DNA and RNA sequences in mammalian cells [##UREF##1##4##–##UREF##3##6##].</p>", "<p id=\"Par5\">PCBP1 is highly expressed in a variety of human tissues and organs [##UREF##4##7##]. It is mainly located in the nucleus and distributed in the cytoplasm. A variety of biological processes, such as transcription, translation, protein interaction, and shuttling of mRNA between the nucleus and cytosol, are contributed by PCBP1 [##REF##20584894##8##–##UREF##6##12##]. In addition, PCBP1 is involved in cell cycle regulation [##UREF##7##13##], and loss of PCBP1 can arrest cells in the G1 phase [##UREF##8##14##, ##UREF##9##15##]. PCBP1 can induce apoptosis, and Shi et al. confirmed that PCBP1 increased p27 expression by stabilizing p27 mRNA, further promoting apoptosis [##UREF##10##16##]. PCBP1 is involved in autophagy, and its overexpression can weaken the stability of microtubule-associated protein light chain 3 (LC3 B) mRNA, inhibit LC3 B expression, and lead to autophagy inhibition [##REF##26880484##17##].</p>", "<p id=\"Par6\">Pigs are an important species in the animal breeding industry, and virus invasion is one of the key issues for animal health and business development. In recent years, a variety of emerging and re-emerging infectious diseases have jeopardized the healthy development of the animal breeding industry. The development of targeted therapeutic drugs to improve porcine autoimmunity has become one of the methods to solve this problem. Innate immunity is the body’s first line of defense against infection by foreign pathogenic microorganisms. Pathogenic microorganisms are recognized through their specific molecular structures, called pathogen-related molecular patterns, by pattern recognition receptors of the host, which produce a series of signal cascades that play an antiviral role. In the course of virus propagation and evolution, viruses have evolved various adaptations to evade the cellular immune system and successfully proliferate. PCBP1 was first cloned from a human lymphocyte cDNA library in 1994 [##UREF##11##18##]. Over the next three decades, its structure and function have been well studied, and new studies are still under way. In particular, a series of studies have suggested that PCBP1 may be involved in immune responses through different pathways. PCBP1 participates in several virus-related signaling pathways, and its expression is closely related to viral replication. PCBP1 is involved in antiviral innate immunity. PCBP1 can not only participate in STAT3 (Signal transducer and activator of transcription 3) mediated inhibition of NF-κB (nuclear factor κB) activity [##UREF##12##19##, ##UREF##13##20##], but also participate in antiviral innate immune regulation through cGAS (cyclic GMP-AMP synthase) protein [##UREF##14##21##]. PCBP1 is also involved in MAVS (mitochondrial antiviral signaling) pathways for tuning antiviral immunity and preventing inflammation [##UREF##15##22##]. Therefore, we intend to conduct in-depth research on porcine PCBP1, hoping to find new directions for the prevention and control of porcine viral diseases.</p>", "<p id=\"Par7\">The porcine kidney cells 15(PK-15) used in this study were derived from adult porcine kidney PK-2a cells established in 1955 and subsequently collected by the ATCC. Today it is one of the most commonly used porcine passageway cell lines and has been widely used in many research fields [##REF##35729483##23##–##UREF##17##25##]. In this study, the porcine PCBP1 gene was cloned from PK-15 cells and bioinformatics analysis was performed to predict the structure and possible function of its protein. In addition, the subcellular location and differential expression of PCBP1 gene in various tissues were analyzed. Finally, the effects of PCBP1 on apoptosis and cell cycle were analyzed. Our results suggest that PCBP1 plays an important role in apoptosis and cell cycle regulation in PK-15 cells and possibly in pigs.</p>" ]
[ "<title>Methods</title>", "<title>Strains, plasmids, and antibodies</title>", "<p id=\"Par28\">PK-15 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco, USA) supplemented with 10% fetal bovine serum (FBS, Gibco, USA) at 37 °C in a humidified atmosphere containing 5% CO<sub>2</sub>. <italic>Escherichia</italic> coli TOP10 (Invitrogen, Beijing, China) was used for plasmid amplification and was grown in LB medium at 37 °C. The plasmid pMD 18-T vector (Invitrogen, Beijing, China) was used to clone the PCBP1 gene and the plasmid pCAGGS-HA was used to produce HA-tagged PCBP1 proteins. Anti-PCBP1, anti-HA and anti-β-Actin antibodies were purchased from Proteintech (Wuhan, China).</p>" ]
[ "<title>Results</title>", "<title>Molecular cloning of porcine PCBP1</title>", "<p id=\"Par8\">To clone porcine PCBP1, cDNA generated from PK-15 cells was used as a template for PCR, and an amplified fragment was obtained (Fig. ##FIG##0##1##A); the fragment had a clear and bright band, which was consistent with the expected result. After ligation, transformation and bacterial selection, PCR identification of the bacterial plasmids was performed. Positive colonies were verified by sequencing. The coding sequence (CDs) of PCBP1 showed 100% similarity to a previously predicted sequence (XM_003125057.4). The length of the PCBP1 CDs is 1071 bp, and the CDs encodes a protein containing 356 amino acids. The structure of PCBP1 was predicted using the SWISS-MODEL [##UREF##18##26##], and porcine PCBP1 was found to be mainly composed of α-helices and β-folds (Fig. ##FIG##0##1##B).</p>", "<p id=\"Par9\">\n\n</p>", "<title>Sequence analysis and phylogenetic tree construction of porcine PCBP1</title>", "<p id=\"Par10\">To analyze the similarity and phylogenetic relationships of PCBP1 to its homologous proteins from other species, a multiple sequence alignment was established for these cDNA sequence with Clustal W [##REF##7984417##27##], and a phylogenetic tree was constructed with MEGA 7.0 (Fig. ##FIG##1##2##A). The results of the similarity comparison showed that the PCBP1 gene was highly conserved in different species. The similarity between the sequence of porcine PCBP1 and other species was 93.7–99.1% (Fig. ##FIG##1##2##B). At the protein level, the amino acid sequence of PCBP1 between pigs and humans were identical (Fig. ##FIG##1##2##C).</p>", "<p id=\"Par11\">\n\n</p>", "<title>Expression abundance of PCBP1 in different tissues from 30-day-old pigs</title>", "<p id=\"Par12\">To characterize the expression level of PCBP1 mRNA in different tissues, several tissues (heart, liver, spleen, lung, kidney, brain, and lymph nodes) from 30-day-old pigs were examined by RT-qPCR. The results showed that porcine PCBP1 mRNA could be detected in all seven tissues, and the lowest expression abundance was detected in brain, while PCBP1 mRNA expression in liver and lymph nodes were significantly higher than that in other tissues (Fig. ##FIG##2##3##). This finding suggests that PCBP1 protein may play a more important role in the liver and lymph nodes than in other tissues.</p>", "<p id=\"Par13\">\n\n</p>", "<title>Subcellular localization of PCBP1 in PK-15 cells</title>", "<p id=\"Par14\">To examine the subcellular localization of porcine PCBP1, subcellular staining was performed. Immunofluorescence assay was used to detect the subcellular localization of porcine PCBP1 protein, and the results are shown in Fig. ##FIG##3##4##. Under the laser confocal microscope, the outline of PK-15 cells was clearly visible, and the cytoplasm and nucleus were clearly stained. Specifically, the PCBP1 protein was distributed in both the cytoplasm and nucleus, with more protein present in the nucleus than in the cytoplasm. In the cytoplasm, PCBP1 was scattered and concentrated on the perinuclear side and near the cell membrane. This result is consistent with the subcellular localization of human PCBP1 [##REF##14612387##28##].</p>", "<p id=\"Par15\">\n\n</p>", "<title>Overexpression and knockdown of PCBP1 in PK-15 cells</title>", "<p id=\"Par16\">In this study, the PCBP1 expression vector pCAGGS-HA -PCBP1 was successfully constructed. As confirmed by western blotting, PCBP1 was successfully expressed (Fig. ##FIG##4##5##A). Three small interfering RNAs (siRNAs ) were designed and synthesized, two of which can inhibit PCBP1 expression in PK-15 cells (Fig. ##FIG##4##5##B).</p>", "<p id=\"Par17\">\n\n</p>", "<title>Effect of PCBP1 on cell apoptosis</title>", "<p id=\"Par18\">To detect the effect of PCBP1 on apoptosis of PK-15 cells, PCBP1 was overexpressed in PK-15 cells and apoptosis was detected by flow cytometry. PK-15 cells were transfected with pCAGGS-HA-PCBP1 overexpression plasmid and pCAGGS-HA empty plasmid. Twenty-four hours after transfection, cells were collected and detected by flow cytometry. The results showed that there was no significant difference in cell apoptosis ratio between the mock group and the PCBP1 overexpression group (Fig. ##FIG##5##6##A and B). The effect of PCBP1 knockdown on cell apoptosis in PK-15 cells was also examined. Interestingly, when PCBP1 expression was suppressed, the proportion of apoptotic cells increased, especially in the proportion of late apoptotic cells (Fig. ##FIG##5##6##C and D).</p>", "<p id=\"Par19\">\n\n</p>", "<title>Effect of PCBP1 on cell cycle</title>", "<p id=\"Par20\">Similarly, to detect the effect of PCBP1 on cell cycle, we overexpressed and inhibited PCBP1 expression in PK-15 cells. Cell cycle analysis was performed on cells treated for 24 h. The results showed that when PCBP1 was overexpressed in PK-15 cells, the number of cells in G0/G1 phase decreased, while the number of cells in G2/M phase did not change significantly (Fig. ##FIG##6##7##A and B). When PCBP1 expression was inhibited, cells were blocked in the G0/G1 phase, and the number of cells decreased in G2/M phase (Fig. ##FIG##6##7##C and D). The results showed that when PCBP1 protein expression decreased, cells were arrested in the G0/G1 phase.</p>", "<p id=\"Par21\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par23\">In this study, the CDs of PCBP1 gene in PK-15 cells was successfully cloned, which was 1071 bp, could encode 356 amino acids and was consistent with the predicted sequence (XM_003125057.4) in NCBI (national center for biotechnology information). The CDs of porcine PCBP1 was compared with several other species, and the results showed that PCBP1 was highly conserved in animals. These results indicated that PCBP1 may be an important protein that is highly conserved during evolution.</p>", "<p id=\"Par24\">Subcellular localization showed that PCBP1 protein was present in both the cytoplasm and nucleus, consistent with the reported distribution of human PCBP1 [##REF##14612387##28##]. In PK-15 cells, PCBP1 expression is mainly located in the nucleus, which is consistent with the localization of human PCBP1 protein. In addition, PCBP1 in the cytoplasm was mainly located on the perinuclear side and near the cell membrane, suggesting that PCBP1 may association with membrane structures. In mouse, depletion of PCBP1 induced mitochondrial dysfunction, demonstrated by reduction of Mitofusin 2 and ATP levels in liver [##REF##34455040##29##]. PCBP1 regulated Enterovirus 71 replication in the host specialized membrane-associated replication complex [##REF##24489926##30##].</p>", "<p id=\"Par25\">We selected 30-day-old pigs, dissected several different tissues, and tested the expression level of PCBP1 mRNA. The results showed that PCBP1 had the lowest expression level in the brain, and relatively high in the liver and lymph nodes. It is well known that the liver’s functions include metabolism, detoxification, and hematopoiesis; especially in young animals, the liver is an important hematopoiesis organ [##REF##20696076##31##]. It has also been reported that PCBP1 is associated with hematopoietic function [##REF##36452487##32##]. As an important immune organ, lymph nodes play a critical role in the immune system. The high expression of PCBP1 in lymph nodes suggests that PCBP1 may have some immune function. There are reports that PCBP1 is a novel mediator of antiviral innate immunity and has been shown to increase replication of Classical swine fever virus [##REF##23221550##33##]. Furthermore, PCBP1 has recently been shown to reduce IFN induction by degradation of MAVS [##UREF##15##22##]. Moreover, ChenYang Liao, CaoQi Lei and HongBing Shu confirmed that PCBP1 plays an important role in cGAS-mediated innate immune response to DNA virus infection by promoting cGAS binding to viral DNA [##UREF##14##21##]. These results suggest that PCBP1 is an important multi-functional protein, involved in a variety of life processes.</p>", "<p id=\"Par26\">Finally, we investigated the effect of PCBP1 on apoptosis and cell cycle. In terms of cell apoptosis, PCBP1 overexpression did not affect cell apoptosis rate, but it was significantly increased when PCBP1 was inhibited. PCBP1 has been reported to bind heavily oxidized RNA, inhibiting apoptosis under oxidative conditions [##REF##32647012##34##]. Moreover, long noncoding RNA SNHG1 (small nucleolar RNA host gene 1) inhibits apoptosis by up regulating GNAI2 (G protein alpha inhibiting activity polypeptide 2) and PCBP1 [##REF##32536864##35##]. Under starvation conditions, PCBP1 promoted apoptosis of tumor cells through the autophagy pathway [##REF##26880484##17##]. However, there are also reports that PCBP1 overexpression elicits cycle arrest, apoptosis induction, and p73 splicing in human cervical carcinoma cells [##REF##36583744##36##]. In most cases, viral infection induces apoptosis [##UREF##19##37##–##UREF##21##39##], but although the mechanism is unclear, PCBP1 may be a potential target for initial investigation.PCBP1 overexpression had little effect on cell cycle in PK-15 cells. However, PK-15 cells were arrested in G0/G1 phase when PCBP1 expression was inhibited. A comprehensive analysis of the effects of PCBP1 on cell cycle and apoptosis showed that the lack of PCBP1 would affect the normal physiological function of cells. Moreover, previous investigations have shown consistent results [##UREF##9##15##, ##REF##36583744##36##], similar to the current study on the effect of human PCBP1 on the cell cycle. This result indicates that PCBP1 is an important cellular protein in the cell cycle and deserves further study.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par27\">In this study, we cloned porcine PCBP1, studied its subcellular localization and tissue expression level in different tissues, and characterized its effect on cell cycle and apoptosis. This study provides a basis for further research on the functions of porcine PCBP1.</p>", "<title>Methods</title>", "<title>Strains, plasmids, and antibodies</title>", "<p id=\"Par28\">PK-15 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco, USA) supplemented with 10% fetal bovine serum (FBS, Gibco, USA) at 37 °C in a humidified atmosphere containing 5% CO<sub>2</sub>. <italic>Escherichia</italic> coli TOP10 (Invitrogen, Beijing, China) was used for plasmid amplification and was grown in LB medium at 37 °C. The plasmid pMD 18-T vector (Invitrogen, Beijing, China) was used to clone the PCBP1 gene and the plasmid pCAGGS-HA was used to produce HA-tagged PCBP1 proteins. Anti-PCBP1, anti-HA and anti-β-Actin antibodies were purchased from Proteintech (Wuhan, China).</p>", "<title>Cloning and sequencing of porcine PCBP1</title>", "<p id=\"Par29\">Total RNA was isolated from PK-15 cells using TRIzol reagent (Invitrogen, Beijing, China). The cDNA was generated using a HiScriptII 1st Strand cDNA Synthesis Kit (Vazyme, Nanjing, China) according to the manufacturer’s instructions. PCBP1 CDs was amplified using the following primers designed based on the previously predicted PCBP1 cDNA sequence (Accession Number: XM_003125057.4). The forward primer was 5’-ATGGATGCCGGTGTGACTG-3’ and the reverse primer was 5’-CTGCACCCCATGCCCTTC-3’. After the amplified DNA fragment was purified using the Gel Extraction Kit (TransGen, Beijing, China), it was ligated into the pMD18-T vector and transformed into the <italic>E. coli</italic> TOP10 strain. Positive colonies were verified by sequencing.</p>", "<title>Similarity comparison and phylogenetic tree construction</title>", "<p id=\"Par30\">SWISS-MODEL (<ext-link ext-link-type=\"uri\" xlink:href=\"https://swissmodel.expasy.org\">https://swissmodel.expasy.org</ext-link>) was used for PCBP1 homology modeling. PCBP1 gene sequences in various species, including <italic>Homo sapiens</italic> (NM_006196.4), <italic>Mus musculus</italic> (NM_011865.4), <italic>Rattus norvegicus</italic> (XM_006236844), <italic>Bos Taurus</italic> (NM_001015565.1), <italic>Equus caballus</italic> (NM_001256921.2), <italic>Capra hircus</italic> (predicted, XM_005686838.3), <italic>Bubalus bubalis</italic> (predicted, XM_006079627.2), and <italic>Equus asinus</italic> (XM_014836701.1), were downloaded from NCBI (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ncbi.nlm.nih.gov/\">https://www.ncbi.nlm.nih.gov/</ext-link>), followed by amino acid multiple sequence alignment with DNAStar. The phylogenetic tree was constructed using the neighbor-joining (NJ) method in MEGA 7.0 software, and 1 000 self-spreading analyses were performed.</p>", "<title>Tissue specific expression analysis</title>", "<p id=\"Par31\">Based on the sequencing results, primers for PCBP1 qPCR detection were selected. The forward primer was 5’-CAGTCTGTCACCGAGTGTGT-3’ and the reverse primer was 5’-GTCATGACTCTCCCTTGCGG-3’. The relative mRNA expression of PCBP1 in pig tissues (heart, liver, spleen, lung, kidney, brain, and lymph nodes) was detected by RT-qPCR. The tissues were derived from healthy 30-day-old piglets (2 females and 1 male) purchased from a commercial pig farm (Xiongfeng Sige, Zhengzhou, China). No obvious clinical signs or significant temperature changes were observed in these piglets. Animal experiments comply with the ethical standards of animal experiments and the relevant provisions of animal welfare. Briefly, piglets were anaesthetized with 30 g/L sodium barbiturate, and euthanized through i.v. application of 0.5mL/kg of 10% KCl via the ear vein. After euthanized, piglets were dissected for tissue collection. The tissues were ground on ice and total RNA was extracted from each tissue and complementary DNA was synthesized. RT-qPCR was performed using Power SYBR Green PCR Master Mix (Vazyme, Nanjing, China). Each sample was triplicated. β-actin was used as the internal control. The relative expression levels of PCBP1 in different tissues were analyzed by -2<sup>△△T</sup>. Data are expressed as the mean ± SEM (standard deviation).</p>", "<title>IFA assay</title>", "<p id=\"Par32\">PK-15 cells seeded on coverslips were fixed with 4% paraformaldehyde (Servicebio, Wuhan, China) for 10 min at 4 °C, blocked with 3% BSA for 30 min at room temperature and then incubated with primary antibodies against PCBP1 (Proteintech, Wuhan, China) at 4 °C overnight. The secondary antibody used was FITC-conjugated anti-rabbit IgG (Proteintech, Wuhan, China). The cells were treated with phalloidin (Servicebio, Wuhan, China) which labeled cytoskeleton. In addition, the cells were stained with DAPI (Servicebio, Wuhan, China) to visualize the nuclei. Images were obtained by fluorescence microscope (Zeiss, Oberkochen, Germany).</p>", "<title>Overexpression of PCBP1 in PK-15 cells</title>", "<p id=\"Par33\">The verified pMD18-T-PCBP1 was used as a template to amplify the cDNA fragment encoding the mature PCBP1 protein (without the signal peptide) by PCR and then ligated into the pCAGGS-HA vector. The pCAGGS-HA-PCBP1 plasmid was transfected into PK-15 cells by ExFect®2000 Transfection Reagent (Vazyme, Nanjing, China) according to the manufacturer’s instructions. Cell samples were collected 24 h after transfection for Western blot analysis.</p>", "<title>RNA interference of PCBP1 expression</title>", "<p id=\"Par34\">Three small interfering RNA sequences targeting porcine PCBP1 (siRNA345, siRNA894 and siRNA1012) and one irrelevant interference sequence were designed separately according to PCBP1 sequence. The sequences of these siRNAs were siRNA345 (5’-GCGGCUGUAAGAUCAAAGATT-3’), siRNA894 (5’-GCGCCAACAUUAAUGAGAUTT-3’) and siRNA1012 (5’-GGCCCAAUAUCUAAUCAAUTT-3’). These sequences were synthesized by GenePharma Company. PK-15 cells were transfected with siRNA using ExFect®2000 Transfection Reagent and cell samples were collected 24 h after transfection for Western blot analysis.</p>", "<title>Western blotting</title>", "<p id=\"Par35\">Western blotting was used to identify PCBP1 expression. Total protein was isolated by adding lysis buffer (Beyotime, Shanghai, China) to the cells. Cell extracts were separated by SDS-PAGE and electro blotted onto a polyvinylidene difluoride (PVDF) membrane (Millipore, Billerica, USA). Then, the membranes were incubated with specific primary antibodies, followed by incubation with appropriate horseradish peroxidase (HRP)-conjugated secondary antibodies. Signals were detected using an enhanced chemiluminescence detection kit (Millipore, Billerica, USA).</p>", "<title>Cell apoptosis analysis</title>", "<p id=\"Par36\">Annexin V/PI double staining was used to detect phosphatidylserine valgus to evaluate apoptosis. The cells were stained with an Annexin V-FITC/PI Apoptosis Detection Kit (Solarbio, Beijing, China) and apoptosis was detected by flow cytometry. Cell apoptosis data were analyzed using CytExpert software (Beckman Coulter, USA). All experiments were performed in triplicate.</p>", "<title>Cell cycle analysis</title>", "<p id=\"Par37\">When PK-15 cells reached 60% confluence in the well, the plasmids pCAGGS-HA-PCBP1 and pCAGGS-HA were transfected for 24 h. In another group, non-targeting siRNA and PCBP1 siRNA were also transfected into PK-15 cells for 24 h. The cells were then harvested, washed twice with ice-cold PBS, and fixed with 95% ethanol overnight. Afterward, cells were stained with 50 µg/ml propidium iodide (PI) at 37 °C in the dark for 30 min. Then, the cells were analyzed by flow cytometry.</p>", "<title>Statistical analysis</title>", "<p id=\"Par38\">Statistical analysis was performed using GraphPad Prism 6 (GraphPad Software). Differences between groups were evaluated for significance by one-way analysis of variance with Dunnett’s post-comparison test for multiple groups. All experimental groups were compared to the control group. * indicates <italic>p</italic> &lt; 0.05; ** indicates <italic>p</italic> &lt; 0.01; and *** indicates <italic>p</italic> &lt; 0.001. Experimental data are presented as mean ± SEM, and differences with <italic>p</italic> values &lt; 0.05 were considered statistically significant.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Poly C Binding Protein 1 (PCBP1) belongs to the heterogeneous nuclear ribonucleoprotein family. It is a multifunctional protein that participates in several functional circuits and plays a variety of roles in cellular processes. Although PCBP1 has been identified in several mammals, its function in porcine was unclear.</p>", "<title>Results</title>", "<p id=\"Par2\">In this study, we cloned the gene of porcine PCBP1 and analyzed its evolutionary relationships among different species. We found porcine PCBP1 protein sequence was similar to that of other animals. The subcellular localization of PCBP1 in porcine kidney cells 15 (PK-15) cells was analyzed by immunofluorescence assay (IFA) and revealed that PCBP1 was mainly localized to the nucleus. Reverse transcription-quantitative PCR (RT-qPCR) was used to compare PCBP1 mRNA levels in different tissues of 30-day-old pigs. Results indicated that PCBP1 was expressed in various tissues and was most abundant in the liver. Finally, the effects of PCBP1 on cell cycle and apoptosis were investigated following its overexpression or knockdown in PK-15 cells. The findings demonstrated that PCBP1 knockdown arrested cell cycle in G0/G1 phase, and enhanced cell apoptosis.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">Porcine PCBP1 is a highly conserved protein, plays an important role in determining cell fate, and its functions need further study.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12917-023-03861-4.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>L.W. conceived and designed research. Y. S., Y. W. and X. L. conducted experiments. M. X., Y. S. and X. L. analyzed data. Y. S. wrote the original manuscript. L. W. and L. Z. reviewed the manuscript. All authors read and approved the manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by the Natural Science Foundation of Henan Province, China [grant numbers 222300420586]; and the Key Scientific Research Projects of Henan Education Department [grant numbers 21A230018 and 23B230008]. The funding body played no role in the design of the study and collection, analysis, interpretation of data, and in writing the manuscript.</p>", "<title>Data Availability</title>", "<p>The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. DNA sequences have been deposited in GenBank (accession numbers: OR037304).</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par451\">The study was reviewed and approved by Academic Ethics and Moral Construction Committee of Zhengzhou Normal University. All methods were carried out in accordance with relevant guidelines and regulations. The studies were reported in accordance with ARRIVE guidelines.</p>", "<title>Consent for publication</title>", "<p id=\"Par461\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par471\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Cloning and sequencing of porcine PCBP1. (<bold>A</bold>) The full-length coding sequence of porcine PCBP1 gene was amplified by PCR. Lane 1, PCR products; Lane M, DNA marker. (<bold>B</bold>) Prediction of the 3D structure of porcine PCBP1 (based on SWISS-MODEL).</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Sequence analysis of porcine PCBP1. (<bold>A</bold>) Phylogenetic tree analysis of PCBP1 CDs. (<bold>B</bold>) Homology analysis of PCBP1 in <italic>Homo sapiens</italic>, <italic>Mus musculus</italic>, <italic>Rattus norvegicus</italic>, <italic>Bos taurus</italic>, <italic>Equus caballus</italic>, <italic>Capra hircus</italic>, <italic>Bubalus bubalis</italic>, <italic>Equus asinus</italic> and <italic>Sus scrofa</italic>. (<bold>C</bold>) Comparison of PCBP1 amino acid sequences between <italic>Sus scrofa</italic> and <italic>Homo sapiens</italic></p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Relative expression of PCBP1 mRNA in pig tissues. RT-qPCR analysis was performed. β-actin was used as the internal control against which the PCBP1 mRNA expression was normalized</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Localization of PCBP1 by immunofluorescence assay. Red fluorescence signals show samples stained with phalloidin. Blue fluorescence signals show samples stained with DAPI. Green fluorescence signals show samples stained with anti-PCBP1 antibody and FITC-conjugated goat anti-rabbit IgG. Scale bar, 10 μm</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Overexpression and knockdown of PCBP1 in PK-15 cells. PK-15 cells were transfected with vector or siRNA for overexpression or knockdown of PCBP1. Expression levels of PCBP1 protein were determined by Western blotting. β-actin was used as a protein control. (<bold>A</bold>) The control vector (pCAGGS-HA) and expression vector (pCAGGS-HA-PCBP1) were transfected into PK-15 cells for 24 h. (<bold>B</bold>) Control and PCBP1 siRNAs were transfected into PK-15 cells for 24 h</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Effect of PCBP1 on apoptosis in PK-15 cells. The cells were stained with Annexin V-FITC/PI. Cell apoptosis analysis was performed by flow cytometry. A, B) pCAGGS-HA-PCBP1 and pCAGGS-HA were transfected into PK-15 cells for 24 h. The cells were stained and analyzed by flow cytometry (<bold>A</bold>) and presented as a percentage of apoptotic cells (<bold>B</bold>). (<bold>C, D</bold>) Mock siRNA and PCBP1 siRNAs were transfected into PK-15 cells for 24 h, the cells were stained, and the flow cytometry data (<bold>C</bold>) is presented as a percentage of apoptotic cells (<bold>D</bold>)</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Effect of PCBP1 on cell cycle in PK-15 cells. The cells were stained with Annexin PI. Cell cycle analysis was performed by flow cytometry. (<bold>A, B</bold>) The plasmids pCAGGS-HA-PCBP1 and pCAGGS-HA were transfected into PK-15 cells for 24 h, and cells were stained and analyzed by flow cytometry (<bold>A</bold>) and presented as the percentage of G0/G1 and G2/M stages (<bold>B</bold>). (<bold>C, D</bold>) MOCK siRNA and PCBP1 siRNA were transfected into PK-15 cells for 24 h, and cells were stained and analyzed by flow cytometry (<bold>C</bold>) and presented as a percentage of G0/G1 and G2/M stages (<bold>D</bold>)</p></caption></fig>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Yue Song and Linqing Wang contributed equally to this work.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12917_2023_3861_MOESM1_ESM.pdf\"><caption><p>Supplementary Material 1</p></caption></media>" ]
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{ "acronym": [ "PCBP1", "IFA", "RT-qPCR", "PK-15", "LC3 B", "STAT3", "NF-κB", "cGAS", "MAVS", "CDs", "siRNA", "NCBI", "SNHG1", "DMEM", "FBS", "PVDF", "PI" ], "definition": [ "Poly C Binding Protein 1", "Immunofluorescence assay", "Reverse transcription-quantitative PCR", "Porcine kidney cells 15", "Microtubule-associated protein light chain 3", "Signal transducer and activator of transcription 3", "Nuclear factor κB", "Cyclic GMP-AMP synthase", "Mitochondrial antiviral signaling", "Coding sequence", "Small interfering RNA", "National center for biotechnology information", "Small nucleolar RNA host gene 1", "Dulbecco’s modified Eagle’s medium", "Fetal bovine serum", "Polyvinylidene difluoride", "Propidium iodide" ] }
39
CC BY
no
2024-01-14 23:43:46
BMC Vet Res. 2024 Jan 13; 20:25
oa_package/2d/e5/PMC10787444.tar.gz
PMC10787445
38216905
[ "<title>Background</title>", "<p id=\"Par6\">Musculoskeletal (MSK) conditions are highly prevalent and represent a considerable burden on the society as well as for the individual [##REF##29875522##1##]. Among these conditions, low back pain (LBP) is the highest rated cause of years lived with disability globally [##REF##30496104##2##], with 70–85% of the population estimated to experience an episode of low back pain (LBP) at some point in their lives [##UREF##0##3##]. However, most previous research has focused on younger people, often in their productive ages [##REF##19158540##4##, ##REF##14710506##5##]. The anatomical and physiological explanations and functional consequences of LBP in the older population are not comparable to those in the working population [##REF##34021388##6##]. Some studies have reported that the geriatric population has a higher prevalence of severe, persistent and disabling pain [##REF##16547119##7##, ##REF##20591572##8##] compared to the younger adults, with low back pain being one of the most frequently reported symptoms causing functional limitations and disability [##REF##29224696##9##]. Consequently, with a decline in physical activity and function, back pain may represent a major health burden for older individuals. Considering the ageing of the population globally, this expanding problem represents a considerable challenge for health care systems in the future.</p>", "<p id=\"Par7\">Back pain is predominantly managed in primary care by first contact clinicians such as general practitioners (GP), physiotherapists (PT) and chiropractors (DC). Personal factors (age, sex, educational level and employment status) [##REF##32763791##10##–##REF##21978663##13##], pain characteristics [##REF##25436149##11##, ##REF##27639556##14##, ##REF##26955969##15##], functional level [##REF##32763791##10##], and psychological and behavioral characteristics (fear avoidance and expectations) [##REF##25436149##11##] are factors found to be associated with which health care provider the patient seeks for their back pain. However, previous research has found demographic differences among patients seeking care depending on their first point of contact. Patients seeking chiropractic care are well educated, working, and report better health related quality of life, while individuals seeing their family physician have lower socioeconomic status [##REF##21654096##16##]. This is, however, not investigated extensively among the elderly [##REF##34535487##17##].</p>", "<p id=\"Par8\">A plethora of treatment options are provided [##REF##28640822##18##], but in terms of reducing pain and improving function, the effectiveness of these various treatment options remains moderate at best [##REF##28640822##18##]. Management is complicated by heterogeneity among patients [##REF##29573870##19##]. Identifying homogeneous patient groups could be useful in developing targeted interventions to improve treatment outcomes. Previous research have classified patients according to diagnosis [##REF##24661395##20##–##REF##22644216##26##], a single variable like e.g. pain-site [##REF##23042697##27##, ##REF##24925881##28##], or psychological dimensions [##REF##26889613##25##]. Recently, researchers have called for studies subgrouping patients across multidimensional factors (i.e. psychological, behavioral, and social) in the population experiencing MSK pain [##REF##32040225##29##].</p>", "<p id=\"Par9\">Latent Class Analysis (LCA) has the potential to identify subgroups that are homogenous in their baseline clinical presentation based on similar patterns of responses to the questionnaire items [##REF##27914733##30##]. Such subgrouping has shown promise in populations with MSK pain, and these subgroups might facilitate better prognostic estimates and more targeted treatment [##REF##32040225##29##]. A study among patients with low back pain found LCA classes with prognostic capacity [##REF##36970061##31##], but a recent Danish study found that LCA-derived subgroups provided little prognostic value [##REF##28793903##24##]. Few studies have investigated if there are hidden patterns or underlying subgroups among MSK patients based on a broad set of prognostic factors across the biopsychosocial domains, and to the best of our knowledge, none has investigated the elderly.</p>", "<p id=\"Par10\">This study aimed to identify homogenous subgroups among patients aged 55 or older seeking primary care for a new episode of back pain. The variables chosen for the analysis were based on previous prognostic research, and included pain characteristics [##REF##33981936##32##–##UREF##1##34##], psychosocial factors [##REF##33981936##32##, ##REF##28356140##35##, ##REF##15834343##36##], beliefs [##REF##19808766##33##, ##UREF##1##34##] and attitudes about back pain [##REF##12406524##37##], function [##REF##19808766##33##], and comorbidities [##UREF##1##34##]. A second aim was to investigate if the identified classes differed in terms of type of health care provider (i.e. GP, PT, or DC) the patients first contacted for their back pain.</p>" ]
[ "<title>Method</title>", "<title>Design and setting</title>", "<p id=\"Par11\">This study used cross-sectional (baseline) data from the Back Complaints in the Older adult -Norway (BACE-N); a prospective observational cohort study of older adults seeking primary health care in primary care in Norway for a new episode of back pain [##REF##21854620##38##]. The Norwegian Social Science Data Service approved this study (reference no. 42419) and this study did not need ethics approval as treatment was not affected by participation (Norwegian Regional Committee for Medical Research Ethics, ref. no 2014/1634/REK vest).</p>", "<title>Study sample and recruitment</title>", "<p id=\"Par12\">Eligible patients for the BACE-N study were women and men, 55 years of age or older who sought primary care (GP, PT or DC) with a new episode of back pain between April 2015 and March 2020. Back pain was defined as pain located in the region from the top of the scapulae to the first sacral vertebrae. A new episode was defined as being preceded by 6 months without visiting a primary care provider for a similar complaint. Patients were excluded from the study if they had a cognitive impairment which precluded them from completing the study questionnaires or if they had difficulties speaking and writing Norwegian. Patients who had severe mobility impairments (i.e., were wheelchair bound) were excluded as they would not be able to complete the physical examination.</p>", "<p id=\"Par13\">Participants were recruited from primary care practices across Mid- and Southern Norway, including both cities and rural areas. The patients were invited to participate in the study by their health care practitioner. Those who fit the eligibility criteria and completed an informed consent to participate-form, responded to a comprehensive questionnaire and underwent a standardized physical examination at baseline by one of the study coordinators were included. We did not collect data on eligible individuals who were not included. The study coordinators were physiotherapists or chiropractors given standardized training in the examination procedure.</p>", "<title>Data collection</title>", "<p id=\"Par14\">The questionnaire and history taking during the inclusion (baseline) visit included questions on patient characteristics, characteristics of the back complaint, medication consumption, function, psychological factors and comorbidities. A selection of these variables was used for this analysis (Fig. ##FIG##0##1##). The physical examination comprised general examination of the body, range of motion of the back and hips and additional orthopedic and neurological tests. Details of additional data can be found elsewhere. Follow-up questionnaires were sent at 3, 6, 12, and 24 months after inclusion, but paper versions were available for participants who were unfamiliar with electronic data collection. While the study was ongoing, patients received care as usual.</p>", "<title>Variables in the latent class modelling</title>", "<p id=\"Par15\">Based on previous research, eleven indicator variables were extracted from the dataset and used in the analysis (Fig. ##FIG##0##1##). These include (1) pain characteristics: intensity (measured by the Numeric Rating Scale (NRS, range 0–10, higher scores indicate higher pain intensity), duration of current complaint (0–14 days, 15–90 days, 91–365 days or ≥ 366 days), widespread pain (measured by the pain drawing from McGill Pain Questionnaire and the revised criteria from Wolfe et al. for widespread pain [##REF##31596726##39##]), medication consumption for back pain (yes or no); (2) function: disability (measured by Roland-Morris Disability Questionnaire (RMDQ, range 0–24, higher scores indicate more back-related disability); (3) comorbidities: number of comorbidities (measured by Self-administered Comorbidity Questionnaire, range 0–7); (4) psychological factors: kinesiophobia (measured by the physical activity subscale of the Fear-Avoidance Beliefs Questionnaire, range 0–24, higher score indicates higher levels of kinesiophobia), pain catastrophizing (measured by Pain Catastrophizing Scale, range 0–52, higher score indicates more pain catastrophizing), back beliefs (measured by Back Beliefs Questionnaire, range 9–45, where that a high score indicates more pessimistic beliefs regarding the consequences of back pain), symptoms of depression (measured by Centre for Epidemiologic Studies-Depression questionnaire, range 0–60, higher scores indicates the presence of more symptomatology) and expectations (expectations of their back pain in three months, better/much better or no change/worse).</p>", "<p id=\"Par16\">\n\n</p>", "<title>Statistical analysis</title>", "<p id=\"Par18\">Descriptive statistics were performed in IBM SPSS Statistics Version 26 for Windows [##UREF##2##40##]. A single-stage LCA, modelling all variables simultaneously, was conducted in MPlus version 8.3 [##UREF##3##41##]. The model with the best fit was selected by comparing several fit indices and making a choice based on multiple aspects. For descriptive model comparisons the information criteria (BIC, AIC) were explored, where lower values indicate better model fit [##UREF##4##42##, ##UREF##5##43##]. Furthermore, mean posterior probability values were examined. These should be equal to or larger than 0.8, indicative of low levels of misclassification. The quality of the classification in the models was additionally inspected by the entropy value, where values close to 1 indicate good classification accuracy and little ‘fuzziness’ [##UREF##6##44##]. After the choice for the final model was made, patients were allocated to their best fitting class.</p>", "<title>Transformation of data</title>", "<p id=\"Par19\">The variable “duration” was categorized into the following categories: 0–14 days, 15–90 days, 91–365 days, and “366 days and more”. No data were imputed as the likelihood approach used in LCA includes a procedure for handling missing values and does not require complete data [##UREF##6##44##, ##REF##23836191##45##].</p>", "<title>Model selection</title>", "<p id=\"Par20\">An explorative and common, forward approach to the model specification was performed [##UREF##7##46##], i.e., classes were added to the model until the model did not improve any further. The clinical interpretability between the classes was also inspected.</p>", "<p id=\"Par21\">First, the models were compared using information criteria (IC)-based fit statistics. These include the Bayesian Information Criteria (BIC; [##UREF##5##43##]), Akaike Information Criteria (AIC; [##UREF##4##42##]), and Adjusted BIC [##UREF##8##47##]. Second, entropy statistics were used as a marker of the accuracy with which models classified individuals into their most likely class. Patients´ subgroup membership was assessed by the average posterior probabilities. Lastly, the preferred models were compared by inspecting the clinical interpretability and the respective number of individuals in each subgroup [##UREF##9##48##] and then labeled according to their distinct characteristics.</p>", "<title>Health care providers</title>", "<p id=\"Par22\">To explore if individuals in the identified classes sought different health care providers as their first point-of-contact, a cross-table was constructed, and X<sup>2</sup>-tests performed to compare the observed and expected proportions of patients who were seeking care with GPs, PTs and DCs across classes. The results are presented as the estimated proportions of patients seeking a given type of first point-of-contact for each class. All the point estimates are presented with 95% confidence intervals (CI).</p>" ]
[ "<title>Results</title>", "<title>Description of the Sample</title>", "<p id=\"Par23\">In total, 435 patients were included in this study, 28% were recruited from GPs, 29% from PTs and 43% from DCs. The median age was 66 (IQR: 59–72) and around half of the patients were women (53.1%). The vast majority, 94.6%, had experienced back pain before this current episode. The majority of the sample reported pain in the lumbar/ lower spinal region only (85%), 4% had pain only in the thoracic level and 43% reported having radiating (uni- or bilateral) leg pain the previous week.</p>", "<p id=\"Par24\">For the total sample, all scores of the psychological variables were below the cut-off values for clinical symptoms. For example, the median score of the CES-D for depressive symptomatology was 8.0 (IQR; 3–13), whereas the cut-off point of 16 or above are considered identifying those at risk of clinical depression [##REF##9189988##49##]. Also, three out of four had high expectations of recovery, expecting to be fully recovered or much better within 3 months.</p>", "<p id=\"Par25\">The latent class analysis identified a model with four classes as the optimal fit. The average posterior probabilities for classes 1 to 4 were 0.905, 0.858, 0.961, and 0.877 respectively. The characteristics of the classes are shown in Table ##TAB##0##1## and Fig. ##FIG##1##2##.</p>", "<p id=\"Par26\">In class 1 (<italic>n</italic> = 169, 39%), labeled the “positive” class, the mean age was 66 years and half were men, and the group had the highest proportion of employed individuals. The mean pain intensity level for this group was 3.92/10, and less than one out of five were taking pain medication for their back pain. This class also showed lower functional disability, kinesiophobia, pain catastrophizing, and symptoms of depression and high positive beliefs about back pain compared to the other classes.</p>", "<p id=\"Par27\">For class 2 (<italic>n</italic> = 31, 7%), labeled the “fearful” class, the mean age was the highest among the groups, 72.3 years, and a high proportion (71%) were women. The individuals in this group had the most comorbidities of all classes. The mean pain intensity was 6.9/10, and nearly two out of three took pain medication for their back pain. The median disability score (14.50) of this group was the second highest of all groups. They also scored the second highest on symptoms of depression and pain catastrophizing.</p>", "<p id=\"Par28\">Class 3 (<italic>n</italic> = 33, 8%), labeled the “distressed” class, had a mean age of 62.8 years and a high proportion (70%) were women. The mean pain intensity score was 6.1/10, and nearly three out of four took pain medication for their back pain. This class had the highest proportion of individuals with widespread pain (18.2%) and the highest score on functional disability of the classes. For symptoms of depression, the median score of this subgroup was 26.0 on the CES-D scale, well above the cut-off point for symptoms of clinical depression. Out of all four classes, this class also had the highest score of pain catastrophizing and the most negative back pain beliefs.</p>", "<p id=\"Par29\">Class 4 (<italic>n</italic> = 202, 46%), labeled the “hopeful” class, was the largest class by number, making up nearly half of our sample (46,4%), and had a mean age of 66.6 years. Half of the group were women, and just under half of the individuals had higher education. This class had the lowest number of comorbidities. The mean pain intensity score was 6.1/10, and their pain related disability was 12/24 on the RMDQ. Over 80% of the individuals in this group believed their back pain would improve in the next three months.</p>", "<p id=\"Par30\">\n\n</p>", "<p id=\"Par31\">\n\n</p>", "<p id=\"Par32\">In Table ##TAB##1##2##, the first point-of-contact for individuals in each class is reported. The proportions of patients suggest that the fearful and distressed were mainly consulting a GP, the classes were evenly distributed for patients consulting a PT and patients in the positive and hopeful classes were mainly consulting a DC. The only statistically significant association between type of first point-of-contact and a given class was found for the “positive” class where the proportion of patients visiting a chiropractor was significantly higher compared to the proportions of patients seeking GPs and PTs.</p>", "<p id=\"Par33\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par34\">This study identified four distinct classes among individuals aged 55 or older seeking primary care for their back pain, based on 11 key prognostic factors, including pain characteristics, comorbidities, disability and psychological factors. The classes were distinctly different in terms of severity of symptoms (pain intensity, functional disability, use of medication), comorbidities, and psychological characteristics, and a higher proportion of “positive” patients visited a chiropractor as first point-of-contact.</p>", "<p id=\"Par35\">The majority of individuals (classes 1 and 4, 371 individuals, 85%) may be labelled as having favorable psychological and behavioral characteristics, according to our selected variables. Thus the sample seemed to be in good shape in terms of pain, psychological and behavioral characteristics.</p>", "<p id=\"Par36\">The largest class, number 4, the “hopeful” patients, were characterized by high expectations to pain improvements in the upcoming months. Despite relatively high pain intensity (6.1/10), these patients had high expectations for improvement. This was echoed in the second-largest class, number 1, the “positive” class, consisting of individuals who reported low scores on all the variables, except expectations for a positive outcome, thus they did not have any predictors for a negative outcome.</p>", "<p id=\"Par37\">Classes 2 and 3 were considerably smaller, with 31 and 33 individuals, respectively. Despite the group sizes, they were supported by the statistical model selection values/criteria (among others AIC, BIC, posterior probabilities and entropy). Individuals classified in classes 2 and 3 generally had poor scores on all the variables measured, thus were clearly “unhealthier” than the majority of individuals in classes 1 and 4. Class 3 stands out from group 2 by its higher scores on symptoms of depression and pain catastrophizing, which are well known prognostic factors for persistent back pain [##REF##33981936##32##].</p>", "<p id=\"Par38\">Most of the individuals in this study were recruited from chiropractors’ offices, but this does not necessarily reflect the pattern of first point-of-contact for back pain among the elders. Overall, GPs, PTs and DCs see the same proportion of positive, distressed, fearful and hopeful older adult patients with back pain, with the only difference being a higher proportion of the “positive” patients sought a chiropractor as their first point-of-contact compared to the proportions of patients who sought a GP or PT.</p>", "<p id=\"Par39\">To the best of our knowledge, no previous studies have investigated classes among the older adult seeking care for back pain. A Norwegian study on people of working ages (up to 67 years) on patients seeking care for musculoskeletal pain identified five latent classes, also based on pain and psychological factors [##REF##32040225##29##]. These five classes showed, in line with our study, a “graded” approach, from the very severely affected to the lightly affected patients. However, our sample (apart from being older) suffered from pain of shorter duration and of higher intensity, possibly reflecting the inclusion criteria of not having sought care the previous six months, thus not including individuals with persistent pain.</p>", "<p id=\"Par40\">In a Danish study, adults (up to 65 years) seeking chiropractic care for low back pain were included if not having needed more than one previous appointment for their pain in the previous three months [##REF##28793903##24##]. This study used a single-stage and a two-stage approach and identified seven and nine classes, respectively, based on a wide range of pain, psychological, functional, participatory and impairment factors. The resulting classes were described in terms of pain characteristics (duration, intensity and radiation) as well as impact on work and sleep and are therefore not easily comparable.</p>", "<p id=\"Par41\">In a German study, patients receiving multimodal treatment for chronic pain, aged between 18 and 86 years, were included [##REF##32523372##50##]. Four classes, based on pain characteristics and health data, were identified. As in our study, these ranged from a group with “high pain burden” to a group with “low pain burden”, with the severely affected representing the majority of the sample. Thus, it is likely that these classes are common across ages, but that the proportion severe/lightly affected differs between populations. However, for the older population, we need to explore if these challenges translate into a poorer outcome. If so, interventions could be directed towards specific classes.</p>", "<p id=\"Par42\">In a previous publication with data from the same cohort, differences between individuals seeking care with a GP, PT or DC were explored [##REF##34535487##17##]. It was found that patients with more severe pain (longer duration and higher intensity) were likely to visit the GP or PT, whilst those with high expectations of recovery and widespread pain were likely to visit the DC. We found that among the “positive” a higher proportion sought chiropractic care compared to the proportions of patients seeking a GP or PT. However, for the people in the “hopeful” class the probabilities of seeking the three types of first contact point were similar. In the latent classes, the highest proportion of widespread pain was found in the “hopeful” class. These differences are likely due to the fact that our classes were based on many variables. Thus, the identified classes encompass a broader picture of the pain experience as well as patient characteristics.</p>", "<p id=\"Par43\">This study has some strengths. We recruited patients from multiple primary care clinics in both urban and rural parts of Norway, strengthening the external validity of our results. We also had a relatively large sample size and good quality data, few missing datapoints, as we used validated questionnaires. The method, LCA, is data-driven, but based on previously identified prognostic variables for back pain outcome. We a priori included variables that cover the most expected factors for treatment outcomes in this patient group [##REF##33981936##32##–##REF##15834343##36##]. To decide the number of groups, we utilized statistical criteria alongside clinical knowledge, further strengthening the relevance of the identified classes.</p>", "<p id=\"Par44\">Some limitations should be considered. The classes were based on variables that were selected according to existing prognostic research. It cannot be ruled out that the classes may have looked different if we had included other variables or had used prospective data instead of cross-sectional. However, the similarity of the identified classes with those of other studies of younger individuals, which have included slightly different selections of variables, suggests that this is not the case.</p>", "<p id=\"Par45\">We did not have information regarding excluded patients mainly to minimize the burden on the recruiting clinicians, as previously described [##REF##34535487##17##]. Likely, this has resulted in selection bias, as many individuals with persistent pain were excluded due to the criterion of not having sought care the past six months, leaving us with a cohort with favorable psychological and behavioral characteristics, not necessarily representative of the older adult population at large. We have previously compared the BACE-N sample to a representative general population sample with musculoskeletal disorders and found that the BACE-N sample is likely over-represented by men, those with higher education, and those in paid work [##REF##34535487##17##], which may explain why the majority of our sample had favorable psychological and behavioral characteristics. Further, we have not performed an external validation of our classes, thus we don’t know if the classes would have been generalizable. However, a Norwegian study on common musculoskeletal disorders somewhat similar to our study found low classification error and comparable classes when performing an external validation [##REF##32040225##29##].</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par46\">This study identified four classes among individuals aged 55 or older seeking primary care for their back pain; named the “positive”, “fearful”, “distressed” and “hopeful”. The classes were distinctly different in terms of severity of symptoms (pain intensity, functional disability, and use of medication), comorbidities, and psychological characteristics. The patients in the “positive” class were more likely to use chiropractors as their first point-of-contact compared to the other classes.</p>", "<p id=\"Par47\">Even though the identified classes appear to have clinical relevance, it remains to be explored if the individuals also develop differently over time.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Back pain is the number one condition contributing to years lived with disability worldwide, and one of the most common reasons for seeking primary care. Research on this condition in the ageing population is sparse. Further, the heterogeneity of patients with back pain complicates the management in clinical care. It is possible that subgrouping people with similar characteristics would improve management. This paper aimed to identify latent classes based on demographics, pain characteristics, psychosocial behavior, and beliefs and attitudes about back pain, among older patients seeking primary care with a new episode of back pain, and to examine if there were differences regarding the classes’ first point-of-contact.</p>", "<title>Methods</title>", "<p id=\"Par2\">The study was part of the international BACE (Back complaints in elders) consortium and included 435 patients aged ≥ 55 years seeking primary care (general practitioners, physiotherapists, and chiropractors) in Norway from April 2015 to March 2020. A latent class analysis was performed to identify latent classes. The classes were described in terms of baseline characteristics and first point-of-contact in primary care.</p>", "<title>Results</title>", "<p id=\"Par3\">Four latent classes were identified. The mean age was similar across groups, as were high expectations towards improvement. Class 1 (<italic>n</italic> = 169, 39%), the “positive” class, had more positive attitudes and beliefs, less pain catastrophizing and shorter duration of current pain episode. Class 2 (<italic>n</italic> = 31, 7%), the “fearful” class, exhibited the most fear avoidance behavior, and had higher mean pain intensity. Class 3 (<italic>n</italic> = 33, 8%), the “distressed” class, had the highest scores on depression, disability, and catastrophizing. Finally, class 4 (<italic>n</italic> = 202, 46%), the “hopeful” class, showed the highest expectations for recovery, although having high pain intensity. The identified four classes showed high internal homogeneity, sufficient between-group heterogeneity and were considered clinically meaningful. The distribution of first point-of-contact was similar across classes, except for the positive class where significantly more patients visited chiropractors compared to general practitioners and physiotherapists.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The identified classes may contribute to targeting clinical management of these patients. Longitudinal research on these latent classes is needed to explore whether the latent classes have prognostic value. Validation studies are needed to evaluate external validity.</p>", "<title>Trial registration</title>", "<p id=\"Par5\">Clinicaltrials.gov NCT04261309.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12891-024-07163-0.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We would like to thank all study participants, participating physiotherapists, chiropractors and GP’s and their assistants for their significant contribution. We thank the primary care providers assisting with the clinical examinations and providing baseline questionnaires to study participants; Kerstin Ulrich, Lise Lothe, Tim Raven, Andreas Hoff Nordvik, Christoffer Børsheim, Steinar Forshei, Mette Brekke, Daniel Major, Jan Harald Lønn, Agnes Mordt, Andrea Kolstad, Mathias Svanevik, Alexander Diesen, Lars Gullestad, Ida Svalstuen, Joakim Ordahl, Mona Øversveen, Jørgen Kongtorp, Are Hansen, Geir Haram, Palwinder Singh, Svein Erik Sandelien, Bent Ulseth, Harald Nordheim, Ola Sand, Ragnhild Perstølen, Jorun Salater, Anna AllenUnhammer, Morten Nilsen, Haakon Lilleeng Asmyhr, Philip Wilkens, Ane Klevberg, Eli Magnesen, Aleksander Killingmo, Bjørn Tore Bjørkedal, Stina Lund, Daniel Ekeberg, Berte Marie Enger, Johan Edvard Tellum, Morten de la Cruz, Bård Kvam, Marte Paulsen, Astrid Figger, Christian Mayer, Trond Magne Aasberg, Thea Tømmervåg, Jørgen Øyen, Håvard Nordås, Tore Viste Ollestad, Olav Aase, Renate Meier, Bjørn Røe, Jørgen Øyen, Jack Johnson, Carl-Erik Høgquist, Ingrid Hystad, Mats Thorbeck, Elisabeth Barø, Kaja McCormick, Lars Martin Fischer, Martin Haagensen, Cathrine Rossland, Marianne Storberget, Nora Helk, Grete Bråten, Annecken Lister Haugen, Hege Herstad, Cathrine Natland, Frøydis Blaker Åsbø, Ola Klaastad, Thorleif Henning Monsen, Geir Wiik, Jørn Christian Halvorsen, Tonje Høgdahl Mysen, Tine Tandberg, Eir Marie Bergan, Rune Solheim, Ole Kristoffer Larsen. We thank the BACE-N scientific board, and the BACE Consortium.</p>", "<title>Author contributions</title>", "<p>LKG: study design, data collection, data analyses, manuscript draft. IA: study design, data interpretation, manuscript draft. SS: study design, data interpretation, manuscript draft. TH: statistical advisor, data interpretation, critical revision. ØVN: data collection, data interpretation, critical revision. RMK: data collection, data interpretation, critical revision. KS: study design, data interpretation, critical revision. MG: principal investigator, study design, data interpretation, critical revision.</p>", "<title>Funding</title>", "<p>This study was supported by Oslo Metropolitan University, the Norwegian Fund for Post-Graduate Training in Physiotherapy (grant number 90749) and “Et liv i bevegelse” (A life in movement) – the Norwegian chiropractors’ research foundation. Funding organisations had no part in the planning, performing, or reporting of the study.</p>", "<title>Data availability</title>", "<p>All data relevant to the study are included in the article or uploaded as online supplemental information.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent</title>", "<p id=\"Par49\">The Norwegian Social Science Data Service approved this study (reference no. 42419) and this study did not need ethics approval as treatment was not affected by participation (Norwegian Regional Committee for Medical Research Ethics, ref. no 2014/1634/REK vest). All included patients completed an informed consent to participate-form.</p>", "<title>Consent for publication</title>", "<p id=\"Par50\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par48\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Overview of the variables in the latent class analysis. NRS, Numeric Rating Scale; SCQ, Self-administered Comorbidity Questionnaire; RMDQ, Roland-Morris Disability Questionnaire; FABQ-PA, Fear-Avoidance Beliefs Questionnaire-Physical Activity subscale; PCS, Pain Catastrophizing Scale; BBQ, Back Beliefs Questionnaire; CES-D, Centre for Epidemiological Studies-Depression</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Mean scores of each class’ questionnaire values, class size in brackets. NRS, Numeric Rating Scale; SCQ, Self-administered Comorbidity Questionnaire; RMDQ, Roland Morris Disability Questionnaire; FABQ, Fear-Avoidance Beliefs Questionnaire; BBQ, Back Beliefs Questionnaire; CES-D, Centre for Epidemiologic Studies-Depression questionnaire; PCS, Pain Catastrophizing Scale</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Characteristics of the full sample and stratified by class</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Total sample (<italic>n</italic> = 435)</th><th align=\"left\">The positive (<italic>n</italic> = 169), 39%</th><th align=\"left\">The fearful (<italic>n</italic> = 31), 7%</th><th align=\"left\">The distressed (<italic>n</italic> = 33), 8%</th><th align=\"left\">The hopeful (<italic>n</italic> = 202), 46%</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"6\">\n<bold>Sociodemographics</bold>\n</td></tr><tr><td align=\"left\">Age (y), mean (SD)</td><td align=\"left\">66.0 (13.0)</td><td align=\"left\">66.0 (7.7)</td><td align=\"left\">72.3 (9.6)</td><td align=\"left\">62.8 (8.4)</td><td align=\"left\">66.6 (8.3)</td></tr><tr><td align=\"left\">Women, n (%)</td><td align=\"left\">231 (53.1)</td><td align=\"left\">84 (49.7)</td><td align=\"left\">22 (71.0)</td><td align=\"left\">23 (69.7)</td><td align=\"left\">102 (50.5)</td></tr><tr><td align=\"left\">Educational level, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Low</td><td align=\"left\">244 (56.5)</td><td align=\"left\">87 (51.5)</td><td align=\"left\">14 (45.2)</td><td align=\"left\">22 (68.8)</td><td align=\"left\">121 (60.5)</td></tr><tr><td align=\"left\"> High</td><td align=\"left\">188 (43.5)</td><td align=\"left\">82 (48.5)</td><td align=\"left\">17 (54.8)</td><td align=\"left\">10 (31.3)</td><td align=\"left\">79 (39.5)</td></tr><tr><td align=\"left\">Employed, n (%)</td><td align=\"left\">201 (46.2)</td><td align=\"left\">87 (51.5)</td><td align=\"left\">7 (22.6)</td><td align=\"left\">10 (30.3)</td><td align=\"left\">97 (48.0)</td></tr><tr><td align=\"left\">Comorbidities, &gt; 4, N (%)</td><td align=\"left\">34 (10.2)</td><td align=\"left\">6 (3.6)</td><td align=\"left\">24 (77.4)</td><td align=\"left\">3 (10.3)</td><td align=\"left\">1(0.6)</td></tr><tr><td align=\"left\">Intake of medications for back pain, n (%)</td><td align=\"left\">165 (39.9)</td><td align=\"left\">28 (17.6)</td><td align=\"left\">20 (64.5)</td><td align=\"left\">23 (74.2)</td><td align=\"left\">94 (48.7)</td></tr><tr><td align=\"left\" colspan=\"6\">\n<bold>Pain characteristics</bold>\n</td></tr><tr><td align=\"left\">Pain intensity, mean (SD)</td><td align=\"left\">5.3 (2.30)</td><td align=\"left\">3.9 (2.3)</td><td align=\"left\">6.9 (2.1)</td><td align=\"left\">6.1 (1.7)</td><td align=\"left\">6.1 (2.0)</td></tr><tr><td align=\"left\">Duration of current back pain episode, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 0–14 days</td><td align=\"left\">150 (39.9)</td><td align=\"left\">68 (47.2)</td><td align=\"left\">9 (37.5)</td><td align=\"left\">13 (44.8)</td><td align=\"left\">60 (33.5)</td></tr><tr><td align=\"left\"> 25-90 days</td><td align=\"left\">151 (40.2)</td><td align=\"left\">54 (37.5)</td><td align=\"left\">4 (16.7)</td><td align=\"left\">8 (27.6)</td><td align=\"left\">85 (47.5)</td></tr><tr><td align=\"left\"> 91-365</td><td align=\"left\">46 (12.2)</td><td align=\"left\">15 (10.4)</td><td align=\"left\">7 (29.2)</td><td align=\"left\">4 (13.8)</td><td align=\"left\">20 (11.2)</td></tr><tr><td align=\"left\"> ≥366 days</td><td align=\"left\">29 (7.7)</td><td align=\"left\">7 (4.9)</td><td align=\"left\">4 (16.7)</td><td align=\"left\">4 (13.8)</td><td align=\"left\">14 (7.8)</td></tr><tr><td align=\"left\">Widespread Pain, n (%)</td><td align=\"left\">30 (6.9)</td><td align=\"left\">7 (4.1)</td><td align=\"left\">4 (12.9)</td><td align=\"left\">6 (18.2)</td><td align=\"left\">13 (6.4)</td></tr><tr><td align=\"left\" colspan=\"6\">\n<bold>Disability</bold>\n</td></tr><tr><td align=\"left\">RMDQ score, median (IQR)</td><td align=\"left\">9.0 (4–13)</td><td align=\"left\">4.0 (2–6)</td><td align=\"left\">14.5 (12–17)</td><td align=\"left\">16.0 (12–19)</td><td align=\"left\">12.0 (8–14)</td></tr><tr><td align=\"left\" colspan=\"6\">\n<bold>Psychological factors and pain related behavior</bold>\n</td></tr><tr><td align=\"left\">FABQ score, median (IQR)</td><td align=\"left\">9.0 (5–13)</td><td align=\"left\">5.0 (0.5-9)</td><td align=\"left\">17.0 (14–20)</td><td align=\"left\">14.0 (10-17.5)</td><td align=\"left\">11.0 (7–14)</td></tr><tr><td align=\"left\">CES-D score, median (IQR)</td><td align=\"left\">8.0 (3–13)</td><td align=\"left\">4.0 (1-7.3)</td><td align=\"left\">13.0 (10–18)</td><td align=\"left\">26.0 (20–30)</td><td align=\"left\">9.0 (5–13)</td></tr><tr><td align=\"left\" colspan=\"6\">\n<bold>Back pain related beliefs and attitudes</bold>\n</td></tr><tr><td align=\"left\">PCS score, median (IQR)</td><td align=\"left\">9.0 (4–15)</td><td align=\"left\">4.0 (1-6.5)</td><td align=\"left\">14.0 (10–19)</td><td align=\"left\">29.0 (23-37.5)</td><td align=\"left\">12.0 (7–16)</td></tr><tr><td align=\"left\">BBQ score, mean (SD)</td><td align=\"left\">23.8 (7.1)</td><td align=\"left\">19.7 (5.4)</td><td align=\"left\">29.5 (6.8)</td><td align=\"left\">33.1 (7.2)</td><td align=\"left\">25.3(5.9)</td></tr><tr><td align=\"left\">Expectations, n (%)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Fully recovered or much better</td><td align=\"left\">328 (75.7)</td><td align=\"left\">122 (72.2)</td><td align=\"left\">21 (70.0)</td><td align=\"left\">23 (69.7)</td><td align=\"left\">162 (80.6)</td></tr><tr><td align=\"left\">No change or worse</td><td align=\"left\">105 (24.3)</td><td align=\"left\">47 (27.8)</td><td align=\"left\">9 (30.0)</td><td align=\"left\">10 (30.3)</td><td align=\"left\">39 (19.4)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>First point-of-contact for the sample and each class, reported as numbers and proportions to investigate if the identified classes differed in terms of type of health care provider</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Professional</th><th align=\"left\">Full sample, N (%)</th><th align=\"left\">The positive, N</th><th align=\"left\">The estimated proportion, % (95% CI)</th><th align=\"left\">The fearful, N</th><th align=\"left\">The estimated proportion, % (95% CI)</th><th align=\"left\">The distressed, N</th><th align=\"left\">The estimated proportion, % (95% CI)</th><th align=\"left\">The hopeful, N</th><th align=\"left\">The estimated proportion, % (95% CI)</th></tr></thead><tbody><tr><td align=\"left\">GP</td><td char=\".\" align=\"char\">123 (28.4)</td><td align=\"left\">32</td><td align=\"left\">19.2 (13.5 to 26.1)</td><td char=\".\" align=\"char\">14</td><td align=\"left\">45.2 (27.3 to 64.1)</td><td char=\".\" align=\"char\">14</td><td align=\"left\">42.4 (25.5 to 60.8)</td><td char=\".\" align=\"char\">63</td><td align=\"left\">31.2 (24.9 to 38.1)</td></tr><tr><td align=\"left\">PT</td><td char=\".\" align=\"char\">126 (29.1)</td><td align=\"left\">45</td><td align=\"left\">26.9 (20.4 to 34.3)</td><td char=\".\" align=\"char\">9</td><td align=\"left\">29.0 (14.2 to 48.0)</td><td char=\".\" align=\"char\">11</td><td align=\"left\">33.3 (18.1 to 51.8)</td><td char=\".\" align=\"char\">61</td><td align=\"left\">30.2 (24.1 to 37.0)</td></tr><tr><td align=\"left\">DC</td><td char=\".\" align=\"char\">184 (42.5)</td><td align=\"left\">90*</td><td align=\"left\">53.9 (46.0 to 61.6)</td><td char=\".\" align=\"char\">8</td><td align=\"left\">25.8 (11.9 to 44.6)</td><td char=\".\" align=\"char\">8</td><td align=\"left\">24.2 (11.1 to 42.3)</td><td char=\".\" align=\"char\">78</td><td align=\"left\">38.6 (31.9 to 45.7)</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>RMDQ, Roland Morris Disability Questionnaire; FABQ, Fear-Avoidance Beliefs Questionnaire; CES-D, Centre for Epidemiologic Studies-Depression questionnaire; PCS, Pain Catastrophizing Scale; BBQ, Back Beliefs Questionnaire</p></table-wrap-foot>", "<table-wrap-foot><p>The confidence level for the class distribution is reported as lower and upper bounds</p><p>GP, General Practitioner; PT, Physiotherapist; DC, Chiropractor; CI, confidence interval</p><p>*Statistically significant at the 0.05 level</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12891_2024_7163_Fig1_HTML\" id=\"d32e460\"/>", "<graphic xlink:href=\"12891_2024_7163_Fig2_HTML\" id=\"d32e937\"/>" ]
[ "<media xlink:href=\"12891_2024_7163_MOESM1_ESM.docx\"><caption><p><bold>Supplementary table 1</bold>: Fit-indices, entropy and PPs for all the tested models.</p></caption></media>" ]
[{"label": ["3."], "surname": ["de Souza", "Sakaguchi", "Yuan", "Matsutani", "do Espirito-Santo", "Pereira"], "given-names": ["IMB", "TF", "SLK", "LA", "AS", "CAB"], "article-title": ["Prevalence of low back pain in the elderly population: a systematic review"], "source": ["Clin (Sao Paulo)"], "year": ["2019"], "volume": ["74"], "fpage": ["e789"], "pub-id": ["10.6061/clinics/2019/e789"]}, {"label": ["34."], "mixed-citation": ["Scheele J, Enthoven WT, Bierma-Zeinstra SM, Peul WC, van Tulder MW, Bohnen AM et al. Course and prognosis of older back pain patients in general practice: a prospective cohort study. Pain. 2013."]}, {"label": ["40."], "mixed-citation": ["SPSS. SPSS [Available from: "], "ext-link": ["http://www.spss.com/software/statistics/stats-standard/"]}, {"label": ["41."], "mixed-citation": ["Muth\u00e9n M. Mplus Statistical Analysis With Latent Variables. Los Angeles, CA; 1998\u20132017."]}, {"label": ["42."], "surname": ["Akaike"], "given-names": ["H"], "article-title": ["Factor analysis and AIC"], "source": ["Psychometrika"], "year": ["1987"], "volume": ["52"], "fpage": ["317"], "lpage": ["32"], "pub-id": ["10.1007/BF02294359"]}, {"label": ["43."], "surname": ["Schwarz"], "given-names": ["G"], "article-title": ["Estimating the dimension of a model"], "source": ["The Annals of Statistics"], "year": ["1978"], "volume": ["6"], "fpage": ["461"], "lpage": ["4"], "pub-id": ["10.1214/aos/1176344136"]}, {"label": ["44."], "surname": ["Geiser"], "given-names": ["C"], "source": ["Data analysis with Mplus"], "year": ["2012"], "publisher-loc": ["New York"], "publisher-name": ["NY Guilford"]}, {"label": ["46."], "surname": ["Jung", "Wickrama"], "given-names": ["T", "K"], "article-title": ["An introduction to latent class groowth analysis and growth mixture modelling"], "source": ["Social and Persinality Psychology Compass"], "year": ["2008"], "volume": ["2"], "issue": ["1"], "fpage": ["302"], "lpage": ["17"], "pub-id": ["10.1111/j.1751-9004.2007.00054.x"]}, {"label": ["47."], "surname": ["Sclove"], "given-names": ["S"], "article-title": ["Application of model-selection criteria to some problems in multivariate analysis"], "source": ["Psychometrika"], "year": ["1987"], "volume": ["52"], "fpage": ["333"], "lpage": ["43"], "pub-id": ["10.1007/BF02294360"]}, {"label": ["48."], "surname": ["Lubke", "Neale"], "given-names": ["G", "MC"], "article-title": ["Distinguishing between latent classes and continuous factors: resolution by Maximum Likelihood?"], "source": ["Multivar Behav Res"], "year": ["2006"], "volume": ["41"], "issue": ["4"], "fpage": ["499"], "lpage": ["532"], "pub-id": ["10.1207/s15327906mbr4104_4"]}]
{ "acronym": [ "MSK", "BACE", "LBP", "LCA", "GP", "PT", "DC", "NRS", "RMDQ", "FABQ", "PCS", "BBQ", "CES" ], "definition": [ "musculoskeletal", "Back complaints in elders", "low back pain", "Latent Class Analysis", "general practitioner", "physiotherapist", "doctor of chiropractic", "numeric rating scale", "Roland-Morris Disability Questionnaire", "Fear-Avoidance Beliefs Questionnaire", "Pain Catastrophizing Scale", "Back Beliefs Questionnaire", "D-Centre for Epidemiologic Studies-Depression questionnaire" ] }
50
CC BY
no
2024-01-14 23:43:46
BMC Musculoskelet Disord. 2024 Jan 13; 25:60
oa_package/78/4e/PMC10787445.tar.gz
PMC10787446
38216908
[ "<title>Introduction</title>", "<p id=\"Par12\">Malnutrition causes nutrient deficiencies that have both physical and clinical consequences in severe acute malnutrition children. Stunting is a form of undernutrition that is characterized by a child’s height for age Z score (SD ≤ 2) [##UREF##0##1##]. Wasting is characterized by low weight for height and poses a greater risk than stunting [##UREF##1##2##]. Wasting and stunting are often described as “acute” and “chronic” undernutrition, respectively. Underweight is characterized as a low weight-for-age. Underweight children might be stunted, wasted, or both [##REF##22623393##3##]. Globally, there were 47 million wasted children under the age of five in 2019. One in four were located in sub-Saharan Africa, with half being in South Asia. South Asia had almost two out of every five stunted children [##UREF##2##4##].</p>", "<p id=\"Par13\">Malnutrition still affects young children under the age of five in developing countries such as Pakistan. In Pakistan, 12 million children are stunted, with a national average of 40.2%. Stunting rates in Pakistan remain globally critical, with a slow reduction rate. Wasting among young children is increasing and had a prevalence of 17.7% in 2017, leading to a nutrition emergency in Pakistan [##UREF##3##5##]. Malnutrition is a major cause of intergenerational starvation, destroying the future productivity of nations and raising the economic burden [##REF##22106755##6##]. Studies conducted in low-income countries have shown that male children are more likely to be stunted than their female counterparts, with a high prevalence in sub-Saharan Africa. Some studies conducted in Asia have documented that female children are more vulnerable [##REF##12578296##7##, ##REF##15548346##8##].</p>", "<p id=\"Par14\">Malnutrition is caused by several interrelated variables and has both acute and chronic negative health effects [##REF##30935382##9##]. The key factors contributing to child undernutrition are political unpredictability, poverty, and a lack of education that leads to inadequate dietary intake. The most typical causes of undernutrition in children are conditions such as diarrhea and inflammatory bowel syndrome, which have an impact on children’s development and growth [##REF##24708711##10##, ##REF##22675542##11##]. Child malnutrition can be influenced by several variables, such as fetal growth retardation, a lack of exclusive breastfeeding, incorrect complementary feeding, recurrent illnesses, food scarcity, and vitamin deficiencies [##REF##24708711##10##, ##REF##25385920##12##].</p>", "<p id=\"Par15\">Malnutrition is the main cause of morbidity and mortality in children under five, and Pakistan ranks 22nd in the world for underfive child mortality [##UREF##4##13##]. Pakistan has recently faced natural disasters such as floods, famine/drought, and earthquakes [##UREF##5##14##]. A study of 656 households in the flood-affected areas of Pakistan found that 40.5% of children suffer from stunting, with factors such as age, maternal age, family type, water quality, and toilet facilities [##UREF##6##15##]. Similarly, a study in Khyber Pakhtunkhwa, Pakistan, revealed that 46% of children suffer from MUAC-based malnutrition, highlighting the need for targeted community-based nutrition awareness programs [##REF##33472422##16##]. The most concerning effect of these catastrophes is the rise in childhood malnutrition. Previous studies have focused on explaining poverty and low socioeconomic status as the main cause of malnutrition in Pakistan.</p>", "<p id=\"Par16\">The present study used the Boruta algorithm, a novel approach to studying malnutrition determinants, to fill a gap in the literature by focusing on southern Punjab, Pakistan. The algorithm’s ability to handle high-dimensional data and its ability to identify key determinants could guide more effective policies. This study is critical for comprehending the current situation with undernutrition among children under 5 years. The integration of diverse data sources, such as socioeconomic, health, and environmental data, could provide a more holistic understanding of malnutrition and undernutrition in particular. The possible contributions of the study to policy might highlight its importance.</p>", "<p id=\"Par17\">Malnutrition can be caused by a variety of variables and requires creating an effective response strategy. The policy environment significantly influences the implementation and efficacy of nutrition interventions. Understanding the malnutrition framework is crucial for policy formulation and strategic actions, but its translation depends on a strong local understanding of subcomponents and their interactions. Previous research has typically used only univariate methods to identify the determinants of malnutrition [##REF##35059381##17##, ##REF##32984245##18##]. Recent research has employed the Boruta relevant feature selection wrapper algorithm to identify the key predictive determinants for undernutrition [##UREF##7##19##]. The Boruta algorithm compares the original attributes’ importance with random, permuted copies and eliminates irrelevant features [##UREF##8##20##].</p>", "<p id=\"Par18\">Undernutrition in children under five requires a comprehensive public health approach, addressing factors such as illiteracy, poverty, and poor living standards through policies and awareness. Undernutrition treatments still cause significant morbidity and mortality, necessitating effective interventions to prevent millions of child deaths annually and contribute to sustainable development goals. This study aims to apply the Boruta algorithm to identify the important predictors of undernutrition among children under five living in Dera Ghazi Khan, which is one of the marginalized districts of the densely populated Punjab province in Pakistan.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study design and setting</title>", "<p id=\"Par19\">A multicenter cross-sectional study was carried out for data collection during March 2021 to June 2022. The “National Program for Family Planning and Primary Health Care” operated four functional outpatient therapeutic program centers (OTPs) at basic health units (BHUs), including Samina, Jhokutra, and Aaliwala, and one OTP at a rural health center (RHC), Kotchutta, of Dera Ghazi Khan, Punjab, Pakistan, for the collection of children with severe acute malnutrition. These four centers were selected because they were more active than the others, with an appropriate number of workers, patients, and therapeutic food. Participants in the study were selected from these government-designated centers for the treatment of malnutrition. These chosen areas of Dera Ghazi Khan District are underdeveloped, with poor socioeconomic situations, poverty, insecure housing tenure, overpopulation, and unclean living conditions.</p>", "<title>Study population</title>", "<p id=\"Par20\">A purposive sampling technique was used to recruit children aged 6–59 months living in district Dera Ghazi Khan diagnosed with “severe acute malnutrition” without chronic comorbidities. A mid-upper arm circumference (MUAC) of ≤ 11.5 cm, a weight for height Z score of -3, or bilateral edema of grades 1–2 were used as the World Health Organization-suggested inclusion criteria for severe acute malnutrition [##UREF##9##21##]. All of the children had good general health, and they shared the same racial and language background. Parents/caregivers were informed of the study’s purpose and provided with a written consent form to participate in the study. Children with severe malnutrition-related problems such as severe hypoglycemia, severe anemia, severe pitting edema, anorexia, hypothermia, or high pyrexia were excluded.</p>", "<title>Sample size</title>", "<p id=\"Par21\">The cross-sectional study formula was used to determine the sample size, with the error term (d) set at 0.05 and the prevalence of severe malnutrition (p) at 11%. A sample size of 151 was calculated using the following formula (Eq. ##FORMU##0##1##), and this number was raised to 185 to increase study precision, strength, and accuracy. A total of 252 children were screened for participation in this study, with 67 being excluded due to not satisfying the inclusion criteria (Fig. ##FIG##0##1##).</p>", "<p id=\"Par22\">\n\n</p>", "<p id=\"Par23\">\n\n</p>", "<title>Data collection</title>", "<p id=\"Par24\">Parents were interviewed at OTP centers using a structured questionnaire that had been pretested to gather information about family sociodemographics (income, parental education, occupation, household size, and family structure), infant and young child feeding (IYCF), anthropometric measurements (height, weight, and MUAC) and healthcare characteristics (child medical history, immunization record, and access to healthcare). Income from all sources in Pakistani rupees (PKR) was used to estimate the monthly income of the family.</p>", "<p id=\"Par25\">In accordance with WHO recommendations, complementary feeding practices (amount, variety, and frequency) and exclusive breastfeeding were evaluated [##UREF##10##22##]. The vaccination record served as evidence that the Expanded Program of Immunization (EPI) schedule for child immunization had been followed [##UREF##11##23##]. The child’s medical history was assessed to identify wasting, stunting, and underweight. Parents/caregivers provided a history to identify seizure disorders and neurological deficits in children; sick children were excluded.</p>", "<p id=\"Par26\">For children who had hospital deliveries, the gestational age was derived from the antenatal record; in cases of home deliveries, it was based on the mother’s narrative. The number of lost gestational weeks was deducted from the present age to account for premature birth in children up to 24 months of age (37 weeks gestation).</p>", "<p id=\"Par27\">Nutritional supervisors conducted anthropometric measurements, recording double anthropometric values if they differed from one another. Children’s weight was assessed without clothing or in light outfits using SECA 336 baby scales, while children 2 years or older were weighted using SECA 874 Electronic Scale. Infant/child weights were calculated as the difference between these two measures and were close to 10 g.</p>", "<p id=\"Par28\">A length-measuring board with a fixed headrest and an adjustable foot piece (SECA GmbH &amp; Co. KG, Hamburg, Germany) was used to measure the recumbent length of children under 87 cm in height to the nearest 0.1 cm. Children who were taller than 87 cm were measured by having them stand with their heels touching a flat horizontal plate attached to the measurement board. The WHO Child Growth Standards were used to generate the weight-for-height Z scores and the height-for-age Z scores [##UREF##0##1##]. WHO ANTHRO, version 3.2.2, was used to classify the nutritional status of the children.</p>", "<title>Data analysis</title>", "<p id=\"Par29\">The demographic and household characteristics are presented as categorical variables to show the frequency distribution by using IBM SPSS 25.0. In addition, for statistical analyses, we used the Boruta package, which is available from the comprehensive R archive network at <ext-link ext-link-type=\"uri\" xlink:href=\"https://cran.r-project.org/web/packages/Boruta/index.html\">https://cran.r-project.org/web/packages/Boruta/index.html</ext-link>. The determinants were identified using the Boruta feature selection, and the variables’ importance scores were calculated for weight-for-height, weight-for-age, and undernutrition. Undernutrition data generated from the Boruta outcome are presented in the graphs. Blue boxplots represent a shadow attribute’s minimum, average, and maximum Z scores for the undernutrition determinants. Z scores of qualities that were rejected are presented in red and confirmed are presented in green boxplots. The attStats function also generates a data frame with Z score statistics for each attribute.</p>", "<title>Ethics approval</title>", "<p id=\"Par30\">The provincial and district health departments of Punjab, Pakistan, gave their approval for the study to be conducted. The University of Punjab in Pakistan’s Ethical Review and Advanced Study Research Board (ref-9/2352-ACAD) gave its approval to all procedures involving human subjects during this study, which was carried out following the Declaration of Helsinki’s principles [##REF##24141714##24##]. All subjects provided written consent to participate in the study.</p>" ]
[ "<title>Results</title>", "<p id=\"Par31\">This study included 185 children, with a mean age of 15.36 ± 10.23 months, who had a MUAC of 10.19 ± 0.96 cm. In terms of gender, the study included 81 male participants (43.8%) and 104 female participants (56.2%). When considering monthly income, the majority of participants (69.2%) had an income of ≤ 15,000 PKR, while 30.8% had an income ranging from 15,000 to 35,000 PKR. Among the study participants, 22.7% reported a history of a parasite, whereas the majority (77.3%) had no such history. In terms of TB, 43.8% of the participants had a history of TB. Additionally, 15.1% of the participants reported a history of measles. The participants experienced varying numbers of illness episodes, with 54.1% reporting 1–7 episodes and 45.9% having 8–15 episodes. Only 19.5% of the mothers exclusively breastfed their infants, whereas the majority (80.5%) did not. In addition, 89.2% of the subjects had inadequate complementary feeding practices, as shown in Table ##TAB##0##1##.</p>", "<p id=\"Par32\">\n\n</p>", "<p id=\"Par33\">\n\n</p>", "<p id=\"Par34\">The Boruta analysis was conducted to identify the determinants that have significant importance in predicting weight-for-height among children under five years. The analysis revealed several key findings and suggested that age (D1) emerged as the most important determinant, consistently demonstrating high importance scores across multiple iterations. Mid-upper arm circumference (D3) also exhibited significant importance and was consistently identified as important in all iterations. Additionally, weaning practices (D10) and the immunization status of the children (D11) were found to be important determinants, as shown in Fig. ##FIG##0##1##a; Table ##TAB##1##2##.</p>", "<p id=\"Par35\">However, income per month (D4) displayed a moderate importance score and was labelled tentative, requiring further investigation for confirmation. On the other hand, determinants such as gender (D2), history of a parasite (D5), history of measles (D6), history of scabies (D7), history of TB (D8), exclusive breastfeeding (D9), father’s education (D12), mother’s education (D13), hygiene (D14), under five siblings (D15), and household size (D16) were rejected as unimportant, as shown in Fig. ##FIG##1##2##a; Table ##TAB##1##2##. These findings provide valuable insights into the factors influencing weight-for-height and can inform future research and modelling efforts in this domain.</p>", "<p id=\"Par36\">\n\n</p>", "<p id=\"Par37\">The study also aimed to determine the important determinants for predicting weight-for-age using the Boruta algorithm. Determinants MUUAC and income per month emerged as confirmed determinants, consistently demonstrating significant importance in multiple iterations. A history of scabies also showed consistent importance and was confirmed as a significant determinant. On the other hand, age, sex, exclusive feeding and immunization displayed moderate importance and were labelled tentative, indicating the need for further investigation. The study found that factors such as history of parasites (D5), measles (D6), tuberculosis (D8), weaning practices (D10), parents’ education (D12, D13), hygiene (D14), under5-siblings (D15), and household size (D16) were not significant in predicting weight-for-age, as shown in Fig. ##FIG##1##2##b; Table ##TAB##2##3##. The Boruta analysis identified age, income per month, exclusive feeding, and immunization as significant determinants for predicting underweight, with gender and history of tuberculosis as tentative determinants. Rejected determinants had little influence, as shown in Fig. ##FIG##1##2##c; Table ##TAB##3##4##.</p>", "<p id=\"Par38\">\n\n</p>", "<p id=\"Par39\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par40\">The present study aimed to identify the important determinants for predicting weight-for-height, weight-for-age, and underweight using the Boruta algorithm. The findings from the Boruta analysis provided valuable insights into the factors influencing these anthropometric measurements. The Boruta algorithm was chosen for this analysis due to its robustness in handling multiple features, capturing nonlinear pattern relationships, and providing more robust discriminant power than classical statistics. For weight-for-height, the Boruta analysis identified age, MUAC, weaning practices, and immunization as confirmed determinants. Age, with the highest importance score, consistently demonstrated its significance across multiple iterations. For weight-for-age, the Boruta analysis revealed MUAC, income per month, and history of scabies as confirmed determinants. MUAC and income per month consistently displayed significant importance scores, highlighting their influence on weight-for-age prediction. In the case of undernutrition, the Boruta analysis confirmed age, income per month, exclusive feeding, and immunization as important determinants. Age, income per month, and immunization consistently demonstrated significant importance, suggesting their strong association with underweight.</p>", "<p id=\"Par41\">Children of poor families with a monthly income less than 15,000 PKR were more prone to wasting than those with a relatively higher monthly income (15,000–35,000 PKR). This result is consistent with previous research that highlights a strong relationship between poverty and malnutrition [##UREF##12##25##]. Monthly family income can impact food intake, malnutrition, and limited resources for low-income families [##REF##26971598##26##]. Financial limitations often make it difficult for people to obtain nutritious food, medical care, and a healthy standard of living, which affects the nutrition of children [##UREF##13##27##].</p>", "<p id=\"Par42\">Undernutrition has been strongly associated with complementary feeding practices. A higher rate of undernutrition was observed in children who received inadequate complementary feeding. This finding is in alignment with other research emphasizing the need for adequate and timely introduction of complementary foods in promoting optimal growth and development [##REF##18289157##28##]. Inappropriate complementary feeding and weaning practices lead to chronic malnutrition in children.</p>", "<p id=\"Par43\">Improving infant and young child feeding practices is crucial for improving nutrition, health, and development in children aged 0–22 months, ultimately impacting child survival [##UREF##14##29##]. The WHO’s guidelines recommend complementary feeding for infants and young children aged 6–22 months in low-, middle-, and high-income countries [##UREF##15##30##]. Breast milk or infant formula alone is insufficient to meet the infant’s energy needs or offer enough amounts of specific nutrients such as protein, zinc, iron, and fat-soluble vitamins from that age [##REF##11236735##31##]. The WHO Global Strategy for Infant and Young Child Feeding recommends introducing solid, semisolid, and soft foods at six months of age, while continuing breastfeeding, to prevent malnutrition [##UREF##16##32##].</p>", "<p id=\"Par44\">Children who have a balanced diet or enough food have a positive tendency towards healthy development and growth. Malnutrition results from inappropriate weaning procedures and can significantly impair nutritional status [##UREF##2##4##]. Breastfeeding for the first 24 months of a child’s life, together with complementary feeding, ensures that they receive a sufficient amount of nutrients and a balanced diet, both of which are essential to the child’s growth and the prevention of malnutrition [##UREF##10##22##]. Mother’s milk alone cannot meet the nutritional requirements of growing children, so breastfeeding should start at birth and continue until the child’s second birthday in combination with complementary feeding to prevent acute and chronic malnutrition [##UREF##10##22##, ##REF##32153979##33##, ##UREF##17##34##]. Due to the lack of vital nutrients needed for children’s healthy growth and development, continuing to breastfeed without complementary feeding after six months of age may increase the risk of malnutrition [##UREF##10##22##].</p>", "<p id=\"Par45\">Malnutrition, both acute and chronic, can result from inappropriate and nonexclusive breastfeeding. According to research conducted in Pakistan, 45.8% of mothers started breastfeeding their children as soon as they were born, and 48.4% of infants were exclusively breastfed [##UREF##3##5##]. Because the mother’s milk contains an appropriate proportion of the nutrients the infant needs, exclusive nursing should begin within the first hour of delivery [##UREF##10##22##, ##REF##30923753##35##]. Malnutrition in children caused by infectious diseases could also affect their growth and development [##UREF##18##36##, ##UREF##19##37##]. Inflammation increased the likelihood of stunting and malnutrition in children with a history of TB [##UREF##18##36##].</p>", "<p id=\"Par46\">Compared to children with one or two siblings, children with three or more siblings are more likely to be stunted. Increased family size may affect food availability, resulting in underweight or stunted children [##UREF##2##4##, ##REF##32153979##33##, ##UREF##17##34##]. Acute or chronic malnutrition is more likely to develop in children with birth intervals of less than two years [##REF##32153979##33##]. The resources needed to appropriately feed every child become more scarce as the number of children under five in a family increases [##UREF##2##4##, ##UREF##19##37##, ##REF##24604035##38##].</p>", "<p id=\"Par47\">The healthy growth and development of newborns and young children are significantly influenced by the education of mothers. The majority of the mothers in the present study were uneducated, and the children they raised had higher nutrient deficiencies. Stunting and wasting may be avoided by an educated mother, as she will be more aware of her child’s nutritional requirements [##REF##30923753##35##].</p>", "<p id=\"Par48\">The cross-sectional design of this study has certain drawbacks. The study’s small sample size and limited coverage in one district limit its potential for strong results, suggesting the need for longitudinal research across multiple districts. Anthropometric measurements were carried out by qualified individuals, which supports the integrity of the data. A deeper understanding of the dynamic nature of a child’s growth and development could be achieved by carefully examining children’s nutritional status.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par49\">The study reveals that age and mid-upper arm circumference are key determinants of weight-for-height and weight-for-age in children under five years, emphasizing the need for interventions targeting specific age groups and practical measures to assess nutritional status. Weaning practices and immunization status are crucial determinants of child development, emphasizing the need for comprehensive health and nutrition programs. Income per month’s importance varies, suggesting that economic context may influence child undernutrition and requires further investigation.</p>", "<p id=\"Par50\">The Boruta analysis revealed that factors such as gender, parasite history, and exclusive breastfeeding are less influential in predicting undernutrition in children. These findings can guide policymakers, healthcare professionals, and researchers in developing targeted strategies to combat undernutrition in children.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Malnutrition causes nutrient deficiencies that have both physical and clinical consequences in severe acute malnutrition children. Globally, there were 47 million wasted children under the age of five in 2019. One in four were located in sub-Saharan Africa, with half being in South Asia. This study aims to apply the Boruta algorithm to identify the determinants of undernutrition among children under five living in Dera Ghazi Khan, one of the marginalized districts of densely populated Punjab Province in Pakistan.</p>", "<title>Methods</title>", "<p id=\"Par2\">A multicenter cross-sectional study design was used to collect data from 185 children with severe acute malnutrition aged under five years visiting the OTPs centers located in Dera Ghazi Khan, Punjab, Pakistan. A purposive sampling technique was used to collect data using a pretested structured questionnaire from parents/caregivers regarding family sociodemographic characteristics, child nutrition, and biological and healthcare characteristics. Anthropometric measurements, including height, weight, and mid-upper arm circumference, were collected. The Boruta models were used to incorporate the children’s anthropometric, nutritional, and household factors to determine the important predictive variables for undernutrition using the Boruta package in R studio.</p>", "<title>Results</title>", "<p id=\"Par3\">This study included 185 children, with a mean age of 15.36 ± 10.23 months and an MUAC of 10.19 ± 0.96 cm. The Boruta analysis identifies age, mid-upper arm circumference, weaning practices, and immunization status as important predictors of undernutrition. Income per month, exclusive breastfeeding, and immunization status were found to be key factors of undernutrition in children under the age of five.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">This study highlights age, mid-upper arm circumference, weaning practices, and immunization status as key determinants of weight-for-height and weight-for-age in children under five years. It also suggests that economic context may influence undernutrition. The findings can guide targeted strategies for combating undernutrition.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>Conceptualization: J.S., R.Z. and MI; Data curation: Z.A. and MSB; Formal analysis: Z.A, and MSB; Writing– original draft: J.S and MSB; Writing– reviewing &amp; editing: R.Z., R.M.A., M.S.B., Z.A., G.M.J.B., MI and F.F.; supervision: R.Z. G.M. J.B. and F.F. All authors read and approved the final version of the manuscript.</p>", "<title>Funding</title>", "<p>This research received no supporting funds from any funding agency in the public, commercial, or not-for-profit sector.</p>", "<title>Data availability</title>", "<p>Data are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to participate</title>", "<p id=\"Par51\">The provincial and district health departments of Punjab, Pakistan, gave their approval for the study to be conducted. The study was conducted after the approval of the Ethical Review and Advanced Study Research Board of the University of Punjab, Pakistan (ref-9/2352-ACAD). It followed the Declaration of Helsinki’s principles. Written informed consent was obtained from the parents of the participants after introducing them to the purpose of the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par52\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par53\">RZ and FF are Associate Editors at BMC Public Health. All the other authors declare no conflict of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flowchart of sample selection</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p><bold>a-c</bold>: Variable importance scores from the Boruta algorithm for (<bold>a</bold>) weight-for-height, (<bold>b</bold>) weight-for-age, and (<bold>c</bold>) underweight. Blue boxplots represent a shadow attribute’s minimum, average, and maximum Z scores. Z scores of qualities that were rejected and confirmed, respectively, are represented by red and green boxplots</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Characteristics of the study participants</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Determinant code</th><th align=\"left\">Variable</th><th align=\"left\">Category</th><th align=\"left\">n (%)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">D1</td><td align=\"left\" rowspan=\"3\"><p>Age</p><p>(15.36 ± 10.23 Months)</p></td><td align=\"left\">≤ 12 months</td><td char=\".\" align=\"char\">112 (60.5)</td></tr><tr><td align=\"left\">13–24 Months</td><td char=\".\" align=\"char\">45 (24.3)</td></tr><tr><td align=\"left\">≥ 25 Months</td><td char=\".\" align=\"char\">28 (15.1)</td></tr><tr><td align=\"left\" rowspan=\"2\">D2</td><td align=\"left\" rowspan=\"2\">Gender</td><td align=\"left\">Male</td><td char=\".\" align=\"char\">81 (43.8)</td></tr><tr><td align=\"left\">Female</td><td char=\".\" align=\"char\">104 (56.2)</td></tr><tr><td align=\"left\" rowspan=\"2\">D3</td><td align=\"left\" rowspan=\"2\">Mid Upper Arm Circumference (MUAC) (10.19 ± 0.95 cm)</td><td align=\"left\">≤ 10 cm</td><td char=\".\" align=\"char\">99 (53.5)</td></tr><tr><td align=\"left\">≥ 10.1 cm</td><td char=\".\" align=\"char\">86 (46.5)</td></tr><tr><td align=\"left\" rowspan=\"2\">D4</td><td align=\"left\" rowspan=\"2\">Income per month</td><td align=\"left\">≤ 15,000 PKR</td><td char=\".\" align=\"char\">128 (69.2)</td></tr><tr><td align=\"left\">15,000–35,000 PKR</td><td char=\".\" align=\"char\">57 (30.8)</td></tr><tr><td align=\"left\" rowspan=\"2\">D5</td><td align=\"left\" rowspan=\"2\">History of parasite</td><td align=\"left\">Yes</td><td char=\".\" align=\"char\">42 (22.7)</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">143 (77.3)</td></tr><tr><td align=\"left\" rowspan=\"2\">D6</td><td align=\"left\" rowspan=\"2\">History of measles</td><td align=\"left\">Yes</td><td char=\".\" align=\"char\">28 (15.1)</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">157 (84.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">D7</td><td align=\"left\" rowspan=\"2\">History of scabies</td><td align=\"left\">Yes</td><td char=\".\" align=\"char\">28 (15.1)</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">157 (84.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">D8</td><td align=\"left\" rowspan=\"2\">History of TB</td><td align=\"left\">Yes</td><td char=\".\" align=\"char\">81 (43.8)</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">104 (56.2)</td></tr><tr><td align=\"left\" rowspan=\"2\">D9</td><td align=\"left\" rowspan=\"2\">Exclusive breastfeeding</td><td align=\"left\">Yes</td><td char=\".\" align=\"char\">36 (19.5)</td></tr><tr><td align=\"left\">No</td><td char=\".\" align=\"char\">149 (80.5)</td></tr><tr><td align=\"left\" rowspan=\"2\">D10</td><td align=\"left\" rowspan=\"2\">Weaning practices</td><td align=\"left\">Adequate</td><td char=\".\" align=\"char\">45 (24.3)</td></tr><tr><td align=\"left\">Nonadequate</td><td char=\".\" align=\"char\">140 (75.7)</td></tr><tr><td align=\"left\" rowspan=\"2\">D11</td><td align=\"left\" rowspan=\"2\">Immunization</td><td align=\"left\">Incomplete</td><td char=\".\" align=\"char\">46 (24.9)</td></tr><tr><td align=\"left\">Complete</td><td char=\".\" align=\"char\">139 (75.1)</td></tr><tr><td align=\"left\" rowspan=\"2\">D12</td><td align=\"left\" rowspan=\"2\">Father’s education</td><td align=\"left\">Primary &amp; above</td><td char=\".\" align=\"char\">73 (39.5)</td></tr><tr><td align=\"left\">No education</td><td char=\".\" align=\"char\">112 (60.5)</td></tr><tr><td align=\"left\" rowspan=\"2\">D13</td><td align=\"left\" rowspan=\"2\">Mother’s education</td><td align=\"left\">Primary &amp; above</td><td char=\".\" align=\"char\">52 (28.1)</td></tr><tr><td align=\"left\">No education</td><td char=\".\" align=\"char\">133 (71.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">D14</td><td align=\"left\" rowspan=\"2\">Hygiene</td><td align=\"left\">Good</td><td char=\".\" align=\"char\">20 (10.8)</td></tr><tr><td align=\"left\">Poor</td><td char=\".\" align=\"char\">165 (89.2)</td></tr><tr><td align=\"left\" rowspan=\"2\">D15</td><td align=\"left\" rowspan=\"2\">Underfive siblings</td><td align=\"left\">≤ 2</td><td char=\".\" align=\"char\">144 (77.8)</td></tr><tr><td align=\"left\">≥ 3</td><td char=\".\" align=\"char\">41 (22.2)</td></tr><tr><td align=\"left\" rowspan=\"2\">D16</td><td align=\"left\" rowspan=\"2\">Household size</td><td align=\"left\">1–10</td><td char=\".\" align=\"char\">23 (12.4)</td></tr><tr><td align=\"left\">≥ 10</td><td char=\".\" align=\"char\">162 (87.6)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Determinants importance scores from Boruta algorithm for weight-for-height</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Determinants</th><th align=\"left\">Meanimp</th><th align=\"left\">Medianimp</th><th align=\"left\">Minimp</th><th align=\"left\">Maximp</th><th align=\"left\">Normhits</th><th align=\"left\">Decision</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td char=\".\" align=\"char\">7.11</td><td char=\".\" align=\"char\">7.02</td><td char=\".\" align=\"char\">2.20</td><td char=\".\" align=\"char\">11.61</td><td char=\".\" align=\"char\">0.93</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Gender</td><td char=\".\" align=\"char\">1.56</td><td char=\".\" align=\"char\">1.28</td><td char=\".\" align=\"char\">-0.71</td><td char=\".\" align=\"char\">4.08</td><td char=\".\" align=\"char\">0.03</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">MUAC</td><td char=\".\" align=\"char\">15.69</td><td char=\".\" align=\"char\">15.88</td><td char=\".\" align=\"char\">9.99</td><td char=\".\" align=\"char\">21.18</td><td char=\".\" align=\"char\">1.00</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Income per month</td><td char=\".\" align=\"char\">2.56</td><td char=\".\" align=\"char\">2.37</td><td char=\".\" align=\"char\">-1.31</td><td char=\".\" align=\"char\">6.62</td><td char=\".\" align=\"char\">0.43</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">History of Parasites</td><td char=\".\" align=\"char\">-0.97</td><td char=\".\" align=\"char\">-1.08</td><td char=\".\" align=\"char\">-2.83</td><td char=\".\" align=\"char\">0.66</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of Measles</td><td char=\".\" align=\"char\">-0.45</td><td char=\".\" align=\"char\">-0.48</td><td char=\".\" align=\"char\">-1.93</td><td char=\".\" align=\"char\">1.27</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of Scabies</td><td char=\".\" align=\"char\">-0.11</td><td char=\".\" align=\"char\">0.68</td><td char=\".\" align=\"char\">-3.82</td><td char=\".\" align=\"char\">1.46</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of TB</td><td char=\".\" align=\"char\">0.00</td><td char=\".\" align=\"char\">-0.22</td><td char=\".\" align=\"char\">-0.80</td><td char=\".\" align=\"char\">1.15</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Exclusive feeding</td><td char=\".\" align=\"char\">-0.63</td><td char=\".\" align=\"char\">-0.48</td><td char=\".\" align=\"char\">-3.22</td><td char=\".\" align=\"char\">0.78</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Weaning practices</td><td char=\".\" align=\"char\">4.70</td><td char=\".\" align=\"char\">4.74</td><td char=\".\" align=\"char\">0.20</td><td char=\".\" align=\"char\">9.41</td><td char=\".\" align=\"char\">0.73</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Immunization</td><td char=\".\" align=\"char\">4.16</td><td char=\".\" align=\"char\">4.08</td><td char=\".\" align=\"char\">-0.09</td><td char=\".\" align=\"char\">8.22</td><td char=\".\" align=\"char\">0.70</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Father Education</td><td char=\".\" align=\"char\">0.11</td><td char=\".\" align=\"char\">-0.02</td><td char=\".\" align=\"char\">-2.12</td><td char=\".\" align=\"char\">1.82</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Mother Education</td><td char=\".\" align=\"char\">0.72</td><td char=\".\" align=\"char\">0.65</td><td char=\".\" align=\"char\">-2.17</td><td char=\".\" align=\"char\">4.04</td><td char=\".\" align=\"char\">0.02</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Hygiene</td><td char=\".\" align=\"char\">1.93</td><td char=\".\" align=\"char\">1.95</td><td char=\".\" align=\"char\">-1.05</td><td char=\".\" align=\"char\">4.52</td><td char=\".\" align=\"char\">0.07</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Under5-siblings</td><td char=\".\" align=\"char\">1.22</td><td char=\".\" align=\"char\">1.17</td><td char=\".\" align=\"char\">-1.16</td><td char=\".\" align=\"char\">3.06</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Household size</td><td char=\".\" align=\"char\">0.00</td><td char=\".\" align=\"char\">0.05</td><td char=\".\" align=\"char\">-1.61</td><td char=\".\" align=\"char\">1.52</td><td char=\".\" align=\"char\">0.00</td><td align=\"left\">Rejected</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Determinants importance scores from the Boruta algorithm for weight-for-age</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Determinants</th><th align=\"left\">Meanimp</th><th align=\"left\">Medianimp</th><th align=\"left\">Minimp</th><th align=\"left\">Maximp</th><th align=\"left\">Normhits</th><th align=\"left\">Decision</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\">3.85</td><td align=\"left\">3.75</td><td align=\"left\">-0.21</td><td align=\"left\">7.64</td><td align=\"left\">0.61</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">Gender</td><td align=\"left\">3.44</td><td align=\"left\">3.19</td><td align=\"left\">-1.40</td><td align=\"left\">7.87</td><td align=\"left\">0.58</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">MUAC</td><td align=\"left\">5.97</td><td align=\"left\">5.88</td><td align=\"left\">2.33</td><td align=\"left\">10.78</td><td align=\"left\">0.92</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Income per month</td><td align=\"left\">4.68</td><td align=\"left\">4.74</td><td align=\"left\">1.24</td><td align=\"left\">8.82</td><td align=\"left\">0.77</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">History of Parasites</td><td align=\"left\">-0.58</td><td align=\"left\">-1.02</td><td align=\"left\">-2.30</td><td align=\"left\">2.26</td><td align=\"left\">0.01</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of Measles</td><td align=\"left\">1.58</td><td align=\"left\">1.97</td><td align=\"left\">-1.85</td><td align=\"left\">3.84</td><td align=\"left\">0.02</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of Scabies</td><td align=\"left\">4.47</td><td align=\"left\">4.55</td><td align=\"left\">0.55</td><td align=\"left\">9.44</td><td align=\"left\">0.71</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">History of TB</td><td align=\"left\">-0.65</td><td align=\"left\">-0.85</td><td align=\"left\">-2.94</td><td align=\"left\">1.92</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Exclusive feeding</td><td align=\"left\">2.35</td><td align=\"left\">2.03</td><td align=\"left\">-0.97</td><td align=\"left\">7.01</td><td align=\"left\">0.41</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">Weaning practices</td><td align=\"left\">-0.23</td><td align=\"left\">-0.40</td><td align=\"left\">-1.77</td><td align=\"left\">1.86</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Immunization</td><td align=\"left\">3.89</td><td align=\"left\">4.03</td><td align=\"left\">-1.35</td><td align=\"left\">8.38</td><td align=\"left\">0.63</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">Father Education</td><td align=\"left\">-0.14</td><td align=\"left\">0.02</td><td align=\"left\">-2.26</td><td align=\"left\">1.45</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Mother Education</td><td align=\"left\">-0.27</td><td align=\"left\">-0.13</td><td align=\"left\">-2.12</td><td align=\"left\">1.61</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Hygiene</td><td align=\"left\">0.92</td><td align=\"left\">0.90</td><td align=\"left\">-1.13</td><td align=\"left\">4.66</td><td align=\"left\">0.02</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Under5-siblings</td><td align=\"left\">-0.04</td><td align=\"left\">-0.18</td><td align=\"left\">-1.02</td><td align=\"left\">0.95</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Household size</td><td align=\"left\">1.19</td><td align=\"left\">1.41</td><td align=\"left\">-1.70</td><td align=\"left\">4.07</td><td align=\"left\">0.03</td><td align=\"left\">Rejected</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Determinants importance scores from the Boruta algorithm for underweight</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Determinants</th><th align=\"left\">Meanimp</th><th align=\"left\">Medianimp</th><th align=\"left\">Minimp</th><th align=\"left\">Maximp</th><th align=\"left\">Normhits</th><th align=\"left\">Decision</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\">4.60</td><td align=\"left\">4.57</td><td align=\"left\">1.56</td><td align=\"left\">8.90</td><td align=\"left\">0.72</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Gender</td><td align=\"left\">3.23</td><td align=\"left\">3.01</td><td align=\"left\">-0.45</td><td align=\"left\">9.43</td><td align=\"left\">0.46</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">MUAC</td><td align=\"left\">0.09</td><td align=\"left\">0.36</td><td align=\"left\">-1.44</td><td align=\"left\">2.33</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Income per month</td><td align=\"left\">5.02</td><td align=\"left\">4.97</td><td align=\"left\">-0.19</td><td align=\"left\">11.35</td><td align=\"left\">0.75</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">History of Parasites</td><td align=\"left\">-0.31</td><td align=\"left\">-0.08</td><td align=\"left\">-3.27</td><td align=\"left\">1.85</td><td align=\"left\">0.02</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of Measles</td><td align=\"left\">0.78</td><td align=\"left\">0.67</td><td align=\"left\">-1.78</td><td align=\"left\">3.19</td><td align=\"left\">0.03</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of Scabies</td><td align=\"left\">2.03</td><td align=\"left\">1.89</td><td align=\"left\">-2.33</td><td align=\"left\">5.52</td><td align=\"left\">0.14</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">History of TB</td><td align=\"left\">3.45</td><td align=\"left\">3.54</td><td align=\"left\">0.20</td><td align=\"left\">7.13</td><td align=\"left\">0.54</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">Exclusive feeding</td><td align=\"left\">5.63</td><td align=\"left\">5.70</td><td align=\"left\">0.91</td><td align=\"left\">12.00</td><td align=\"left\">0.83</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Weaning practices</td><td align=\"left\">-0.38</td><td align=\"left\">-0.73</td><td align=\"left\">-2.44</td><td align=\"left\">3.26</td><td align=\"left\">0.01</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Immunization</td><td align=\"left\">4.82</td><td align=\"left\">5.14</td><td align=\"left\">-0.26</td><td align=\"left\">9.49</td><td align=\"left\">0.73</td><td align=\"left\">Confirmed</td></tr><tr><td align=\"left\">Father Education</td><td align=\"left\">3.85</td><td align=\"left\">3.66</td><td align=\"left\">0.26</td><td align=\"left\">8.24</td><td align=\"left\">0.65</td><td align=\"left\">Tentative</td></tr><tr><td align=\"left\">Mother Education</td><td align=\"left\">1.30</td><td align=\"left\">1.07</td><td align=\"left\">-1.03</td><td align=\"left\">4.18</td><td align=\"left\">0.04</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Hygiene</td><td align=\"left\">0.42</td><td align=\"left\">0.31</td><td align=\"left\">-1.27</td><td align=\"left\">2.23</td><td align=\"left\">0.00</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Under5-siblings</td><td align=\"left\">0.58</td><td align=\"left\">0.31</td><td align=\"left\">-1.32</td><td align=\"left\">2.40</td><td align=\"left\">0.02</td><td align=\"left\">Rejected</td></tr><tr><td align=\"left\">Household size</td><td align=\"left\">2.00</td><td align=\"left\">2.22</td><td align=\"left\">-1.22</td><td align=\"left\">5.00</td><td align=\"left\">0.19</td><td align=\"left\">Rejected</td></tr></tbody></table></table-wrap>" ]
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{ "acronym": [ "CI", "CMAM", "EPI", "PKR", "SD", "TB", "WHO" ], "definition": [ "Confidence interval", "Community Management of Acute Malnutrition", "Expanded Program of Immunization", "Pakistani rupee", "Standard deviation", "Tuberculosis", "World Health Organization" ] }
38
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no
2024-01-14 23:43:46
BMC Public Health. 2024 Jan 12; 24:167
oa_package/92/86/PMC10787446.tar.gz
PMC10787447
38217061
[ "<title>Introduction</title>", "<p id=\"Par7\">The Athabasca oil sands in northern Alberta, Canada, is the third largest oil reserve worldwide. In 2018, about 2.8 million barrels of oil were produced per day [##UREF##0##1##]. Oil extraction from oil sands ore produces oil sands process-affected water (OSPW) and fine fluid tailings (FFT). These waste products contain solids (sand, silt, and clay), caustic salts, residual bitumen, and solvents [##UREF##1##2##]. The waste is stored in tailings ponds so solids can settle, and the water can be re-used in extraction. Recycling OSPW conserves water but concentrates salts, heavy metals, and acid-extractable organics [##REF##28334283##3##], which are mostly naphthenic acids (NAs). NA concentrations in tailings ponds range from 40 to 120 mg L<sup>−1</sup>, but toxicity can occur in fish at concentrations as low as 2.5 mg L<sup>−1</sup> [##UREF##1##2##]. Over 55 years of mining activity, the Alberta oil sands industry amassed over 1.3 trillion L of fluid tailings as of 2020 [##UREF##2##4##], and continues to produce about 1 billion L of fresh tailings per day [##UREF##3##5##]. There currently exists no approved large-scale remediation technology for tailings, although projects are underway to test techniques such as tailings filtration, centrifugation, and oxidation [##UREF##1##2##, ##REF##28334283##3##, ##UREF##4##6##].</p>", "<p id=\"Par8\">Mined landscapes in Canada are required by law to be reclaimed to an equivalent land capacity to a natural landscape [##UREF##5##7##]. End pit lakes present a low-cost, long-term land reclamation and remediation strategy applicable on a large scale [##REF##28334283##3##, ##UREF##6##8##]. An oil sands end pit lake should sequester FFT in a decommissioned open mine pit with an overlying water cap comprised of freshwater and OSPW [##REF##28334283##3##]. Dilution of OSPW via freshwater inputs, biodegradation and tailings consolidation should improve water quality over time [##UREF##4##6##, ##UREF##6##8##], eventually allowing integration with surrounding watersheds [##UREF##6##8##]. End pit lakes are anticipated to become a regular feature of the Athabasca oil sands region, with 23 of these lakes in the planning phase [##UREF##6##8##]. However, it remains unclear whether end pit lakes will be a suitable method of tailings treatment, with major concerns including contaminant remediation, impacts on wildlife, and their safety for public use, including by Indigenous communities [##UREF##4##6##, ##UREF##6##8##]. End pit lakes for metal and coal mines are well-studied, as they have been used for over 100 years and are common around the world [##UREF##7##9##], with major challenges including acidification and metal/metalloid release [##UREF##8##10##]. In contrast, research on oil sands end pit lakes is more exploratory and mostly limited to Alberta. The major challenges are very different, and include slow sedimentation, high salinity, and hydrocarbon contamination [##UREF##4##6##, ##UREF##6##8##, ##UREF##9##11##]. Base Mine Lake (BML) is the first and currently the only full-scale demonstration oil sands end pit lake in Northern Alberta [##UREF##5##7##]. BML is located in a boreal plains ecozone [##UREF##6##8##] and exhibits a dimictic pattern typical of natural boreal lakes, with mixing occurring in the spring and fall and thermal stratification in the summer and winter [##UREF##5##7##]. Surface water turbidity increases slightly during turnover as suspended solids are mixed in the water column. The intended land use goal for BML is for it to provide habitat for typical lake plants, macroinvertebrates, and small-bodied fish, but not future public use [##UREF##5##7##]. The development of BML’s aquatic community will first require the establishment of a phytoplankton community to serve as a food source for higher trophic levels [##UREF##6##8##].</p>", "<p id=\"Par9\">Phytoplankton are a polyphyletic group of phototrophic cyanobacteria and unicellular eukarya (microalgae) that serve as a primary energy source of aquatic food webs, help drive biogeochemical cycling through carbon, nitrogen, and phosphorous fixation, and contribute dissolved oxygen and organic matter to the ecosystem [##UREF##10##12##]. The phytoplankton base of boreal lake food webs is typically comprised of low-quality nutrition sources such as cyanobacteria and chlorophytes along with higher quality sources such as diatoms, cryptophytes, dinophytes, and chrysophytes [##UREF##11##13##, ##REF##26282609##14##]. High quality phytoplankton generally contain more polyunsaturated fatty acids, which higher trophic levels such as ciliates [##UREF##12##15##, ##REF##34367571##16##], zooplankton, [##UREF##11##13##] and fish [##REF##26282609##14##] depend on. Cyanobacteria, chlorophytes, and chrysophytes typically increase in boreal lakes during summer and decline in autumn, during which time cryptophytes and diatoms increase [##UREF##11##13##, ##REF##26282609##14##]. Seasonal or eutrophic algal blooms can increase biological oxygen demand as the produced organic matter decays and consumes O<sub>2</sub> [##UREF##10##12##]. Cyanobacterial blooms can be particularly problematic for lake reclamation due to O<sub>2</sub> depletion during biomass degradation, cyanotoxin production, and the overabundance of poorly-digestible organic matter from some filamentous taxa [##UREF##6##8##, ##UREF##13##17##]. This may be a concern for EPLs such as BML because cyanobacterial blooms are common in Alberta boreal lakes [##UREF##13##17##].</p>", "<p id=\"Par10\">Phytoplankton are impacted by parameters including nutrient availability (predominantly nitrogen and phosphorus), thermal stratification, zooplankton grazing, interspecific competition, and grazing/parasitism by fungi, protozoans, and bacteria [##UREF##10##12##]. In oil sands tailings environments, phytoplankton may also be inhibited by organic and inorganic contaminants, high salinity, and turbidity [##UREF##6##8##]. For instance, phytoplankton can show sensitivity to NA concentrations &gt; 6 mg L<sup>−1</sup> [##REF##11434295##18##, ##REF##12413790##19##]. Despite this, phytoplankton communities can establish in NA-contaminated systems under high nutrient conditions and sufficient light, with primary production comparable to that of natural systems but reduced species diversity [##UREF##6##8##, ##REF##12413790##19##]. Microcosm studies have suggested that phytoplankton communities similar to non-contaminated sites can establish in systems containing oil sands tailings with a water cap [##REF##12413790##19##]. Numerous phytoplankton taxa are tolerant to high NA concentrations (&gt; 30 mg L<sup>−1</sup>), including some in the <italic>Chlorophyta</italic>, <italic>Euglenophyta</italic>, and <italic>Synechococcaceae</italic> [##UREF##14##20##]. Prior to water capping, BML was a tailings pond known as West-in Pit and had very low eukaryotic diversity, perhaps due to high toxicity (from NAs, heavy metals, and high salinity), high turbidity, and low O<sub>2</sub> content [##REF##27062087##21##]. The eukaryote community was fungi-dominated, with only very few <italic>Euglenophyta</italic>, <italic>Chrysophyceae</italic>, and <italic>Chlorophyta</italic> phytoplankton based on 18S rRNA gene analysis [##REF##27062087##21##]. In 2015, three years after water capping, 18S rRNA gene sequencing analysis revealed that only 6% of the reads belonged to exclusively phototrophic phyla, while 27% belonged to phyla containing both heterotrophs and phototrophs [##REF##31432582##22##].</p>", "<p id=\"Par11\">The phytoplankton community in BML will be crucial to its development. We used high-throughput PCR amplicon sequencing of the 23S, 18S, and 16S rRNA genes to investigate the phytoplankton community in BML over 5 years from 2016 to 2021. We hypothesized that BML’s phytoplankton community would initially resemble those in active tailings ponds but become more akin to a freshwater system over time as water quality improves in the water cap. We also quantified algae based on quantitative PCR of the 23S rRNA gene, phytoplankton cell counts, biomass, and chlorophyll <italic>a</italic> content. We predicted that the abundance of phytoplankton in BML would increase over time due to improvements in water quality and clarity.</p>" ]
[ "<title>Materials and methods</title>", "<title>Site descriptions and sampling</title>", "<p id=\"Par12\">BML (57.0109°N, 111.6219°W) is 8 km<sup>2</sup> in area, located about 45 km north of Fort McMurray, Alberta, Canada (Additional file ##SUPPL##0##1##: Fig. S1). Prior studies offer comprehensive descriptions of BML [##UREF##5##7##, ##REF##34818104##23##]. The site was first commissioned in 1978 as a mining pit called West-In Pit (WIP), then converted to a tailings pond in 1994. In 2012, FFT were added to a depth of 45–50 m and capped with 5 m of fresh water and OSPW. The capped system was renamed Base Mine Lake (BML). BML is isolated from the local watershed and the water level is maintained at 308.7 m above sea level via pump-in of freshwater from Beaver Creek Reservoir (BCR) or pump-out to the nearby extraction plant. BML receives inflow from rain, snow, and runoff, but pump-in from BCR is the major input source [##UREF##5##7##], contributing ~ 4–9% of water cap volume from 2016 to 2019, with no inflow in 2021 (see Additional file ##SUPPL##0##1##: Table S1) [##UREF##5##7##]. As of 2021, the water cap depth increased to ~ 10–13 m due to FFT settling and dewatering with a water cap volume of ~ 71 Mm<sup>3</sup>. BCR was used as a freshwater control site in our study: it does not contain any tailings or OSPW but is immediately adjacent to BML and contains some of the same freshwater.</p>", "<p id=\"Par13\">BML is dimictic, with ice-off in April to early May, spring turnover from May to mid-June, summer stratification mid-June to early September, fall turnover in September, and ice-on in mid-November. Turbidity and total suspended solids are highest during turnovers in the spring and fall and lowest in the summer, with water temperatures ranging from 0 to 24 °C depending on season and depth. From 2012 to 2016, water turbidity (50–350 Nephelometric Turbidity Units; NTU) was about ten times higher than turbidity in local freshwater bodies due to clay suspension from FFT. In an effort to sequester the clays, the chemical coagulant aluminum potassium sulfate (alum) was added to BML from September to October of 2016. Turbidity immediately decreased and has remained lower than pre-2016 values in BML every year since (ranging from 4 to 28 NTU in 2021) [##UREF##5##7##]. Surface water quality in BML has also improved gradually over time. As of 2016, dilution with freshwater has reduced metal ion concentrations in BML to within water quality guidelines, although salinity is still 10 times higher than Athabasca River water [##UREF##15##24##]. Petroleum-associated compounds including total phenolics, F2 hydrocarbons, and NAs remain elevated compared to natural sources, with average NA concentrations ranging from 27 to 30 mg L<sup>−1</sup> in 2021 [##UREF##5##7##], compared to &lt; 1 mg L<sup>−1</sup> in the Athabasca River [##UREF##1##2##].</p>", "<p id=\"Par14\">The neighboring water bodies Beaver Creek Reservoir (BCR) and Mildred Lake Settling Basin (MLSB) served as controls for an artificial freshwater ecosystem and an active tailings pond, respectively. BCR, located immediately south of BML (Additional file ##SUPPL##0##1##: Fig. S1), is 2.2 km<sup>2</sup> in size with a maximum depth of ~ 10 m and a mean depth of 2.2 m. Unlike BML, only weak thermal stratification is observed in BCR in the summer and turbidity is lower, ranging from 1 to 19 NTU. Phytoplankton, invertebrates, and fish are abundant in the reservoir. See Additional file ##SUPPL##1##2##: Table S1 for comparison of the physicochemical parameters in BML and BCR over years. MLSB is an active tailings pond ~ 10 km<sup>2</sup> in size located just north of BML. It is the oldest and largest tailings pond in the region and is characterized by an active methane cycle [##REF##28334283##3##].</p>", "<p id=\"Par15\">BML samples were taken at 1–4 week intervals during the ice-off period (May–October) and via ice coring in the winter (February–March) from three fixed sampling platforms (Additional file ##SUPPL##0##1##: Fig. S1) as described previously [##REF##34818104##23##]. The three sampling platforms were treated as replicates. BCR and MLSB samples were taken less frequently, at about 1-month intervals. BCR samples were taken from three different shoreline sampling sites and MLSB samples were taken from a single shoreline sampling site. All samples were taken from the surface (0.3–0.6 m) using Van Dorn samplers. Samples were shipped in polypropylene bottles on ice to the University of Calgary (c. 2 d shipping time) then stored at 5–8 °C upon delivery, typically for 1–2 d until processing. The hold time before sample processing likely influenced microbial communities to some extent. However, studies have shown that keeping samples on ice prior to DNA extraction is among the most effective controls for maintaining microbial community integrity [##REF##33193212##25##], and that samples kept on ice for 3 days were similar to day 0 samples in terms of their microbial community composition [##UREF##16##26##]. A major wildfire delayed sampling in 2016 until the end of June. Sampling was also interrupted in 2020 due to a pandemic shutdown.</p>", "<title>Molecular community analyses via gene amplicon sequencing</title>", "<p id=\"Par16\">Water samples (500 mL) were processed via centrifugation with DNA extracted from the pelleted material as described previously [##REF##34818104##23##]. Phytoplankton were identified using PCR amplicon sequencing with primers targeting the 23S (V5), 18S (V4), and 16S (V3-4) rRNA genes (Additional file ##SUPPL##1##2##: Table S2). The 23S rRNA priming sequences are present only in plastids and cyanobacteria [##UREF##17##27##], those for the 18S rRNA gene are universal to eukaryotes, including eukaryotic phytoplankton [##REF##20331767##28##], and those for the 16S rRNA gene are universal to bacteria, including cyanobacteria and chloroplasts [##REF##22933715##29##]. Each primer had Illumina adaptors attached to the 5’ end (Forward 5’-TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG-3’; Reverse 5’-GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA G-3’). PCR amplification conditions for each primer set are given in Additional file ##SUPPL##1##2##: Table S3. Amplicon libraries were prepared using MiSeq Reagent Kit v3 with 600 cycles (Illumina part number MS-102–3003) as described in [##REF##34818104##23##]. Each MiSeq lane had ~ 400 pooled amplicons. Feature tables from various lanes were merged for final analyses. Additional file ##SUPPL##1##2##: Table S4 lists sample metadata (i.e., source, year, season).</p>", "<p id=\"Par17\">Sequencing data were analyzed with Quantitative Insights Into Microbial Ecology 2 (QIIME2) version 2021.4 [##REF##20383131##30##]. Cutadapt software was used to trim primers and Illumina adaptor sequences from all fastq files [##UREF##18##31##]. The software package DADA2 was used to denoise, pair reads, and remove chimerae [##REF##27214047##32##], and a quality score was assessed for 10 random samples per run to adjust denoising parameters. Taxonomy was assigned to each Amplicon Sequence Variant (ASV) using the feature-classifier plugin [##REF##29291746##33##] with a naïve Bayes classifier approach. Taxonomy for the 23S rRNA gene was assigned using the MicroGreen database (μgreen-db) [##REF##31913322##34##], and taxonomy for the 16S and 18S rRNA genes were assigned through the SILVA 138 database [##REF##23193283##35##]. As described in Additional file ##SUPPL##1##2##: Tables S5-S6, the 16S and 18S rRNA gene datasets were filtered to remove non-phytoplankton sequences, and all three datasets were filtered to remove taxa unassigned at the phylum level. Additional file ##SUPPL##1##2##: Table S5 describes how reads were truncated for each primer set and taxonomy filtering parameters. Additional file ##SUPPL##1##2##: Table S6 indicates the number of features and reads for each filtration step and rRNA gene dataset. The identities of the major ASVs belonging to key phytoplankton genera were verified using the online SILVA Alignment, Classification, and Tree (ACT) service (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.arb-silva.de/aligner/\">https://www.arb-silva.de/aligner/</ext-link>) [##REF##22556368##36##] and NCBI BLAST (<ext-link ext-link-type=\"uri\" xlink:href=\"https://blast.ncbi.nlm.nih.gov/\">https://blast.ncbi.nlm.nih.gov/</ext-link>) [##REF##2231712##37##] (Additional file ##SUPPL##1##2##: Tables S7). This resulted in some manual taxonomic reassignments (See Additional file ##SUPPL##0##1##: Note 1 and Additional file ##SUPPL##1##2##: Tables S8–S10).</p>", "<title>23S-rRNA gene based quantitative PCR</title>", "<p id=\"Par18\">Quantitative PCR (qPCR) of the 23S-rRNA gene was performed as described in [##UREF##17##27##] to quantify phototrophs. qPCR was done in reactions containing 1 µL of sample gDNA, 1 µL of each forward/reverse primer (1.25 µM each), 5 µL of SYBR Green ssoAdvanced PCR Mix (Qiagen, Venlo, Netherlands), and DNAse-free water up to 10 µL (Qiagen, Venlo, Netherlands) on a Rotor-Gene 6000 thermocycler (QIAGEN, Venlo, Netherlands). Based on a search of the MicroGreen 23S rRNA gene database, the 23S rRNA gene primers used were determined as universal to phytoplankton, matching 1942 of 2326 total database sequences [##REF##31913322##34##]. Standards were constructed from a <italic>Cryptomonas</italic> 23S rRNA gene sequence, which was PCR-amplified as described above from BML water samples and then cloned into a PJET 3.0 plasmid (ThermoFisher, Waltham, MA, USA) based on the CloneJET PCR Cloning Kit protocol (Thermo Scientific). The plasmids were PCR-amplified using the 23S rRNA gene primers, then amplicons were quantified with a Qubit HS kit (Invitrogen, Carlsbad, CA, USA) and serially diluted over 7 orders of magnitude. The detection limit was ~ 100 gene copies mL<sup>−1</sup> and median amplification efficiency was 89%. Examination of qPCR melt curves suggested primer specificity.</p>", "<title>Microscopy analyses</title>", "<p id=\"Par19\">Samples for cell counts (cells L<sup>−1</sup>), biomass (mg m<sup>−3</sup>), and chlorophyll <italic>a</italic> (µg L<sup>−1</sup>) were collected using Van Dorn units. Samples were taken from the euphotic zone (0.6–0.8 m) or immediately under the ice. BML samples were taken from three platforms, but BCR samples were only taken from one of the three sampling sites. Three pseudo-replicates of two combined grabs were taken from each platform for a total of 500 mL per sample. Phytoplankton samples were preserved with approximately 15 drops of Lugol’s solution and then sent to the EcoAnalysts laboratory (Moscow, ID, USA) for taxonomic identification and enumeration. A 5–25 mL aliquot was extracted from each sample and placed into an Utermöhl counting chamber. The transect method was used to enumerate phytoplankton identified to the lowest practical taxonomic level (LPL), with at least 300 units counted per sample. Units were counted as single cells, filaments, or colonies depending on the distribution of phytoplankton. The biovolume (μm<sup>3</sup>) of each phytoplankton LPL was estimated from mean dimensions measured at 630 × magnification and related to geometric shapes [##UREF##19##38##]. Biovolume measurements were calculated once for each taxon that represented &lt; 5% relative abundance in the sample and 10 times for each that represented &gt; 5%. For taxa with great discontinuities or variations in size, at least 20 biovolume measurements were calculated per sample. Mean biovolumes were calculated for each taxon based on the quantity of individuals within each colonial taxon. Mean cell biovolume (μm<sup>3</sup>) was converted to biomass for all individual phytoplankton taxa assuming a specific gravity of 1 (i.e., 1 µm<sup>3</sup> = 1 µg). Average biovolumes and (ranges) in μm<sup>3</sup> cell<sup>−1</sup> were as follows: <italic>Euglenophyta</italic> 12,810 (77 to 257,066), <italic>Cryptophyta</italic> 12,398 (19 to 661,200), <italic>Bacillariophyta</italic> 2323 (57 to 226,195), <italic>Chlorophyta</italic> 1882 (71 to 117,718), <italic>Chrysophyceae</italic> 500 (18 to 3534), and <italic>Cyanobacteria</italic> 270 (18 to 4110). Each taxon’s total sample biomass (wet weight) was calculated using the equation: Total Biomass (µg L<sup>−1</sup>) = Average Biomass (µg cell<sup>−1</sup>) x Total Abundance (cells L<sup>−1</sup>).</p>", "<p id=\"Par20\">Chlorophyll <italic>a</italic> concentrations (µg cm<sup>−2</sup>) were measured at the University of Alberta’s Biogeochemical Analytical Service Laboratory (BASL) in Edmonton, Alberta using fluorometric analysis [##UREF##20##39##]. Detection limits for cell count, biomass, and chlorophyll <italic>a</italic> measures were, respectively, 20 cells L<sup>−1</sup>, 0.001 mg m<sup>−3</sup>, and 0.50 µg L<sup>−1</sup>.</p>", "<title>Community analyses</title>", "<title>Molecular data</title>", "<p id=\"Par21\">Heatmaps were constructed in the RStudio software using the packages <italic>gplots</italic> and <italic>vegan</italic> and the heatmap.2 function with the Bray–Curtis clustering algorithm and average linkage hierarchical clustering [##UREF##21##40##]. Alpha-diversity statistics were calculated at the ASV level in R for Chao1, observed genera, and the Shannon index using the package <italic>otuSummary</italic>. The package <italic>SRS</italic> (Scaled with Ranked Subsampling) was used to normalize samples at the ASV level [##UREF##22##41##].</p>", "<title>Molecular and microscopy data</title>", "<p id=\"Par22\">Nonmetric multidimensional scaling (NMDS) ordinations were performed in R with the package <italic>vegan</italic> [##UREF##21##40##] and taxa tables were normalized using <italic>SRS</italic> [##UREF##22##41##]. The Bray–Curtis index was used for the dissimilarity measure with 10,000 iterations. Analysis of Similarities (ANOSIM) was performed in R to test whether variation in community composition within sites was greater than across-site variation [##UREF##23##42##]. Significant associations between ASVs and site variables were tested using Indicator Species Analysis (ISA) in R with the package <italic>indicspecies</italic>, which detects whether certain taxa drive differences in community composition across sites. Optimal indicator species are defined as occurring exclusively with high frequency within a given site. Indicator ASVs were computed (p &lt; 0.05, 10,000 permutations) using the functions multipatt and IndVal.g, which accounts for unbalanced across-group sizes [##UREF##24##43##]. Species indicator P values were adjusted for multiple testing with the Benjamini–Hochberg method (p-value &lt; 0.01 unless indicated otherwise) [##UREF##25##44##].</p>", "<p id=\"Par23\">Palmer’s algal genus pollution index [##REF##27097257##45##] uses phytoplankton as bioindicators of organic pollution, and is used to evaluate the water quality of freshwater environments (e.g., [##UREF##26##46##]). This index was developed for microscopic count data, but we combined both molecular and microscopic data for more comprehensive taxonomic coverage. We calculated this index by scoring phytoplankton genera with average relative abundance of ≥ 0.50% and occurring in at least 3 samples for that given year and source for at least one dataset (calculations given in Additional file ##SUPPL##1##2##: Table S11). This index was used to gauge ecological status in BML over time and to compare BML and BCR based on genera known to be bioindicators of organic pollution, with the caveat that it has limited utility and provides only a rough estimate for comparing water quality in BML over time and between BML and BCR.</p>" ]
[ "<title>Results</title>", "<title>Phytoplankton community composition at the phylum level</title>", "<p id=\"Par24\">Community compositions based on 23S rRNA gene amplicon sequencing, microscopic cell counts, and biomass for the years 2016–2021 during the months of July to September are presented in Fig. ##FIG##0##1##, and compared with the average phytoplankton biomass community composition of Alberta boreal headwater lakes reported in [##UREF##27##47##]. Compositions are similar across the three measurements despite some obvious biases. Firstly, cell count and biomass methods only identified phytoplankton that are morphologically distinguishable and therefore did not identify certain coccoidal picophytoplankton identified in sequencing such as the chlorophyte <italic>Choricystis</italic> or the cyanobacterium <italic>Synechococcus</italic> (see Additional file ##SUPPL##0##1##: Note 2 for list of phytoplankton counted in microscopy)<italic>.</italic> This may partially explain the generally higher counts of cyanobacteria based on molecular analyses. The small cyanobacteria were less important in biomass measurements than in cell or gene counts, while euglenophytes and cryptophytes were more important due to their large cell sizes. Overall, all phytoplankton phyla except for <italic>Haptophyta</italic> occurred in similar proportions between 23S rRNA gene and cell count data, whereas biomass was more discrepant.</p>", "<p id=\"Par25\">Based on the 23S rRNA gene amplicon and cell count analyses, the phyla with the greatest relative abundances in BML were <italic>Cyanobacteria</italic> (0–73%), <italic>Chlorophyta</italic> (3.3–75%), and <italic>Cryptophyta</italic> (9.2–35%), with lower proportions of <italic>Euglenophyta</italic> (1.9–9.7%), <italic>Bacillariophyta</italic> (0.10–13.3%), and <italic>Ochrophyta</italic> (0–4.3%) (Fig. ##FIG##0##1##). The BCR community was also predominantly <italic>Cyanobacteria</italic> (61%) and <italic>Chlorophyta</italic> (14–15%) but had greater proportions of <italic>Bacillariophyta</italic> (7.5–15%) and less <italic>Cryptophyta</italic> (3.2–5.2%) than BML. Compared to natural Alberta boreal lakes, BML’s biomass estimates were similar for <italic>Cyanophyta</italic>, <italic>Cryptophyta</italic>, <italic>Bacillariophyta</italic>, and <italic>Chlorophyta</italic> (Fig. ##FIG##0##1##). <italic>Euglenophyta</italic> had much lower relative abundance in boreal lakes (&lt; 0.5%) compared to BML, while <italic>Ochrophyta</italic> and <italic>Dinoflagellata</italic> were higher in boreal lakes (15% and 11%, respectively). Haptophytes, which were not reported by the boreal lake study [##UREF##27##47##], occurred in small amounts in BCR for all years (0.13%), and appeared in BML beginning in 2017 (0.004–1.3%). Median and mean values for phyla for all samples and years are presented in Additional file ##SUPPL##1##2##: Table S12 and phyla compositions for each season are presented in Additional file ##SUPPL##0##1##: Fig. S2.</p>", "<title>Genus-level diversity</title>", "<p id=\"Par26\">Summarizing the rRNA gene sequencing data, four highly abundant phytoplankton genera (≥ 5% average relative abundance in at least 2 rRNA gene sequencing datasets) were identified in BML: <italic>Synechococcus</italic> (<italic>Cyanobacteria</italic>), <italic>Choricystis</italic> (<italic>Chlorophyta</italic>), <italic>Cryptomonas</italic> (<italic>Cryptophyta</italic>), and <italic>Euglena</italic> (<italic>Euglenophyta</italic>) (Additional file ##SUPPL##0##1##: Figs. S3-4). Additionally, <italic>Prochlorococcus</italic> (<italic>Prochlorophyta</italic>; grouped with <italic>Cyanobacteria</italic>) and <italic>Planktothrix</italic> (<italic>Cyanobacteria</italic>) had high relative abundance in BML based on the 23S rRNA gene sequencing. Genera that had high relative abundance in the natural control site BCR included <italic>Planktothrix</italic>, <italic>Synechococcus</italic>, <italic>Aulacoseira</italic> (<italic>Bacillariophyta</italic>), <italic>Cryptomonas</italic>, and <italic>Desmodesmus</italic> (<italic>Chlorophyta</italic>), while those for the tailings pond control MLSB were <italic>Prochlorothrix</italic> (<italic>Cyanobacteria</italic>), <italic>Prochlorococcus</italic>, <italic>Chlorella</italic> (<italic>Chlorophyta</italic>), and <italic>Nannochloropsis</italic> (<italic>Ochrophyta</italic>). A number of genera with lower relative abundance were also detected in each site. Based on the 18S rRNA gene sequencing analysis (which contained the most shared sample dates between sites), the overall community detected in BML was more similar to the freshwater reservoir BCR than the tailings pond MLSB (Fig. ##FIG##1##2##). For further details of the genera detected in each site, see Additional file ##SUPPL##1##2##: Table S13.</p>", "<p id=\"Par27\">Based on relative abundance data for the molecular analyses, all of the four most abundant genera in BML were persistent, occurring in ≥ 75% of all samples analysed (Additional file ##SUPPL##1##2##: Table S14A) [##REF##23864126##48##]. Genera persistent in all three sources based on at least one gene sequencing analysis included <italic>Chlorella</italic>, <italic>Choricystis</italic>, <italic>Prochlorococcus</italic>, <italic>Prochlorothrix</italic>, <italic>Synechococcus</italic>, <italic>Euglena</italic>, and <italic>Nannochloropsis</italic>, while <italic>Cryptomonas</italic> and <italic>Chlorella</italic> were persistent in both BML and BCR. BCR contained a greater percentage of persistent taxa for each analysis compared to BML (Fig. ##FIG##2##3##, Additional file ##SUPPL##1##2##: Table S14B), i.e., many taxa in BML were more transitory.</p>", "<title>Site comparisons</title>", "<p id=\"Par28\">Community composition had greater variation between sources than within sources based on ANOSIM (Additional file ##SUPPL##1##2##: Table S15), and distinct clustering by source was evident in NMDS plots using each of the ASV-level molecular data and the cell counts (Fig. ##FIG##3##4##). Therefore, BML’s phytoplankton community composition was usually distinct from both control sites over the entire study.</p>", "<p id=\"Par29\">Indicator Species Analysis (ISA) was performed on normalized datasets for molecular and cell count data (Additional file ##SUPPL##1##2##: Table S16) to identify genera and ASVs significantly indicative of a given source over the entire 5 years (stat &gt; 0.70, <italic>p</italic> &lt; 0.01). In order to normalize comparisons, this analysis used sample dates where all three sites were sampled and each sample was normalized to an equal number of sequence reads (4000, 1000, and 100 for the 23S, 18S, and 16S rRNA genes, respectively). In comparing BML to BCR using matched sample dates, the only genera indicative of BML were <italic>Oocystis</italic> (<italic>Chlorophyta</italic>) and <italic>Cryptomonas</italic> (<italic>Cryptophyta</italic>), based on cell count data and the 16S rRNA gene data, respectively. In contrast, <italic>Dolichospermum</italic> (<italic>Cyanobacteria</italic>; formerly known as <italic>Anabaena</italic>), <italic>Planktothrix</italic> (<italic>Cyanobacteria</italic>), <italic>Aulacoseira</italic> (<italic>Bacillariophyta</italic>), <italic>Desmodesmus</italic> (<italic>Chlorophyta</italic>), <italic>Monoraphidium</italic> (<italic>Chlorophyta</italic>), and <italic>Trachydiscus</italic> (<italic>Ochrophyta</italic>) were indicative of BCR based on multiple analyses. <italic>Cryptomonas</italic> was indicative of both BML and BCR based on the 18S rRNA gene. Indicator genera for MLSB were <italic>Chlorella</italic> (<italic>Chlorophyta</italic>) and <italic>Tetradesmus</italic> (<italic>Chlorophyta</italic>). See Fig. ##FIG##1##2## and Additional file ##SUPPL##0##1##: Fig. S4 for a qualitative representation of these indicator genera.</p>", "<p id=\"Par30\">Samples were also analyzed at the ASV level to determine whether different strains of the same genus or species were characteristic of each site (Additional file ##SUPPL##1##2##: Tables S17-S20). Although the same genera frequently occurred in 2 or 3 sites, these genera were usually represented by different site-specific ASVs based on ISA (Additional file ##SUPPL##1##2##: Table S17). For example, different <italic>Cyanobium</italic>/<italic>Synechococcus</italic> and <italic>Cryptomonas</italic> ASVs were found to be indicative of BML versus BCR. Similarly, different <italic>Prochlorococcus</italic> and <italic>Prochlorothrix</italic> ASVs were found to be indicative of BML versus MLSB.</p>", "<p id=\"Par31\">To illustrate this ASV-site specificity in more detail, we list the top ten most abundant ASVs that were exclusive to BML or BCR in Additional file ##SUPPL##1##2##: Table S18. ASVs were defined as exclusive if they were not detected in the other source for all samples considered. The detection limit was 1 read in a total of 4000, 1000, 100, and 10,000 normalized reads for the 23S, 18S, and 16S rRNA genes and cell count data, respectively. All of the genera <italic>Prochlorococcus</italic>, <italic>Synechococcus</italic>, and <italic>Chlorella</italic> had certain ASVs exclusive to either BML or BCR for the 23S rRNA gene. More broadly, the top ten most abundant, not necessarily exclusive, ASVs for each of <italic>Choricystis</italic>/<italic>Picochlorum</italic>, <italic>Cryptomonas</italic>, <italic>Synechococcus</italic>/<italic>Cyanobium</italic>, <italic>Euglena</italic>, <italic>Prochlorococcus</italic>, and <italic>Prochlorothrix</italic> (Additional file ##SUPPL##1##2##: Table S19) include some that were shared between BML and BCR, but others that were clearly more dominant in one site. In particular, only one of the top 10 <italic>Prochlorococcus</italic> ASVs was shared between BML and BCR for the 23S rRNA gene sequencing. The most dominant <italic>Cryptomonas</italic> ASV in BML was 8.3 times less abundant in BCR. Four shared, abundant ASVs are plotted over time (in Additional file ##SUPPL##0##1##: Fig. S5) to illustrate two different patterns observed. Those in (A-C) appear in both BML and BCR but have higher relative abundances in BML and persist even during periods when they are virtually absent in BCR, such as in 2021, when no inflow from BCR to BML occurred. This suggests that certain strains have established in BML and exhibit their own growth patterns in this site over time, without the need for continued inoculation from BCR. In contrast, Additional file ##SUPPL##0##1##: Fig. S5 (D) shows a <italic>Synechococcus</italic> ASV that is abundant in BCR but does not establish in BML, although other strains of the same species do.</p>", "<p id=\"Par32\">In summary, these data suggest that although many of the same genera and ASVs (strains) occur in 2–3 sites, there is a distinct site-specific microdiversity. Even though many more samples (and total sequences) of BML were processed, more ASVs were exclusive to BCR for gene sequencing data, indicating that the highest strain diversity was found in the freshwater site (Additional file ##SUPPL##1##2##: Table S20). The conditions in BML select for the growth of particular strains, and the community in BML does not simply reflect the community in BCR that is added via BCR pump-in water.</p>", "<title>Changes over time</title>", "<p id=\"Par33\">BML showed some weak clustering of community compositions by year based on NMDS analyses (Additional file ##SUPPL##0##1##: Fig. S6, Additional file ##SUPPL##1##2##: Table S15), but there was a lot of overlap across years, particularly for the 23S rRNA gene sequencing. Thus, long-term trends were suggested but were obscured by shorter-term variability when looking at entire communities.</p>", "<p id=\"Par34\">Therefore, indicator species analyses (ISA) were performed for BML by year to complement relative abundance data (BCR was not included in this analysis; Fig. ##FIG##4##5##, Additional file ##SUPPL##1##2##: Table S21). The community was dynamic over the 5-year study, with some genera declining and others increasing over 2–3-year periods. For example, there was a general increase in relative abundances of some genera of <italic>Chlorophyta</italic>, <italic>Cyanobacteria</italic>, <italic>Euglenophyta</italic>, <italic>Ochrophyta</italic>, and <italic>Bacillariophyta</italic> (compared to other microbes) from 2016 to 2019, but a slight decline in 2021. Conversely, dinophytes and haptophytes increased in later years (Fig. ##FIG##4##5##). A major change was the decline in <italic>Choricystis</italic> abundance in 2021, although the overall <italic>Chlorophyta</italic> fraction of the community did not decrease (Additional file ##SUPPL##0##1##: Fig. S7). ISA results for the 23S and 18S rRNA genes also showed <italic>Choricystis</italic> was an indicator for the BML community for 2016–2019, while <italic>Mychonastes</italic> was indicative of 2018–2021 (Additional file ##SUPPL##1##2##: Table S21). The 23S and 18S rRNA gene datasets each contained a single unassigned <italic>Chlorophyta</italic> ASV with a very high number of reads in BML for 2021 and low reads for previous years. Detailed analyses indicated that this represented an uncultured <italic>Oocystis</italic> (see Additional file ##SUPPL##0##1##: Note 3 for more detail).</p>", "<title>Seasonality</title>", "<p id=\"Par35\">Sequencing, cell count, and biomass data indicated similar seasonal patterns in overall community composition (Additional file ##SUPPL##0##1##: Fig. S2). However, these patterns were best illustrated by molecular analyses, which were the least time-consuming analyses and hence could be applied to more samples over time (Fig. ##FIG##5##6##). Three of the four most abundant phytoplankton genera, <italic>Cryptomonas</italic>, <italic>Choricystis</italic>, and <italic>Euglena,</italic> showed consistent seasonality over the course of the study, with abundance peaks at similar times each year. <italic>Cryptomonas</italic> generally peaked during August to September, around the time of late summer stratification and fall mixis. <italic>Synechococcus</italic> was more variable, but also usually peaked during the summer or early autumn. <italic>Choricystis</italic> peaked in June or July (the lack of a peak in 2021 could have been due to a lack of sampling) and <italic>Euglena</italic> in March to July. Based on ISA (Additional file ##SUPPL##1##2##: Table S22) and time-course data (Additional file ##SUPPL##0##1##: Figs. S7-S13), several less abundant genera also exhibited seasonal patterns, summarized in Additional file ##SUPPL##1##2##: Table S23.</p>", "<title>Alpha diversity</title>", "<p id=\"Par36\">Using only shared sample dates (i.e., times when all three sites were sampled), α-diversity in BML was intermediate between BCR and MLSB based on the 18S rRNA gene sequencing. The ASV data are shown in Fig. ##FIG##6##7##, genus level data are shown in Additional file ##SUPPL##0##1##: Fig. S14. BML was significantly less diverse than BCR for all indices based on a MANOVA with date and site as factors (Tukey’s HSD, <italic>p</italic>-value &lt; &lt; 0.01; Additional file ##SUPPL##1##2##: Table S24), and significantly more diverse than MLSB for all indices except Shannon (Tukey’s HSD, <italic>p</italic>-value &lt; 0.01; Additional file ##SUPPL##1##2##: Table S24). Hence, several measures of α-diversity in BML were intermediate to the two control sites.</p>", "<p id=\"Par37\">Similarly, in the 23S rRNA gene dataset, BML was significantly less diverse than BCR at the ASV level for observed ASVs and Faith’s index based on two-way MANOVA with date and site as factors (Additional file ##SUPPL##0##1##: Fig. S15; Tukey’s HSD, p &lt; 0.01; Additional file ##SUPPL##1##2##: Table S24). Only BML and BCR were compared in the 23S rRNA gene dataset analyses because too few MLSB samples were available.</p>", "<p id=\"Par38\">Trends over time were generally neutral for each diversity index and gene sequencing dataset, suggesting that alpha diversity was quite stable in BML over 5 years (Additional file ##SUPPL##0##1##: Figs. S15, S16, Additional file ##SUPPL##1##2##: Table S25). Slightly negative trends over time in BML were observed for diversity indices in the complete 23S rRNA gene dataset that accounted for both bacteria and eukarya (Additional file ##SUPPL##0##1##: Fig. S15; Additional file ##SUPPL##1##2##: Table S25). These likely reflected changes in cyanobacteria, as no such trends were evident in eukaryote-only datasets (18S rRNA and 23S rRNA filtered to remove bacteria). The only significantly positive temporal trends in the complete 23S rRNA gene dataset were for the Shannon and Faith indices in BCR, which were small (slopes of + 0.03 and + 0.15 per year, respectively). In the eukaryote-only datasets, the 23S rRNA gene diversity results had no significant upward or downward changes over time, and only slight positive changes were observed in the 18S rRNA gene dataset (Additional file ##SUPPL##0##1##: Fig. S16 and Additional file ##SUPPL##1##2##: Table S25). Both the weakly negative regression lines in Additional file ##SUPPL##0##1##: Fig. S15 and the weakly positive regression lines in Additional file ##SUPPL##0##1##: Fig. S16 explained very little of the overall variability (r<sup>2</sup> = 0.033–0.11), and were likely influenced by a few outliers, making any non-zero trends tentative.</p>", "<title>Palmer’s pollution index</title>", "<p id=\"Par39\">Palmer’s pollution score was calculated for BML for each separate year and for BCR as an average over all years (Table ##TAB##0##1##). BML’s pollution score ranged from low to high (11–26) over the five years but was in the high range for most years and did not change significantly over time (regression, p-value = 0.92). BCR’s pollution score was in the low to moderate range (11–17) with no significant change over time (regression, p-value = 0.91), and was significantly lower compared to BML’s pollution score (Tukey’s HSD, p-value = 0.038).</p>", "<title>Quantification of phytoplankton over time</title>", "<p id=\"Par40\">Quantitative measurements of phytoplankton generally showed higher values in the control site BCR than in BML (Fig. ##FIG##7##8##). Only the 23S rRNA gene qPCR assay showed comparable or higher populations in BML compared to BCR (Fig. ##FIG##7##8##D). Counts based on the qPCR assay were 2–4 orders of magnitude higher than microscopic counts, likely due to biases in molecular versus microscopic methods. qPCR can be biased since some organisms carry more than one copy of the 23S rRNA gene, leading to overestimation. Conversely, in the microscopic methods, many morphologically indistinct phytoplankton are overlooked, leading to underestimation. Average gene counts in MLSB were usually about one order of magnitude lower than either BML or BCR (Fig. ##FIG##7##8##D).</p>", "<p id=\"Par41\">At the <italic>p</italic> = 0.01 level, phytoplankton cell counts and biomass did not detectably change in BML over time, i.e., slopes were not significantly different from zero (Fig. ##FIG##7##8##). Of the four quantification measures, only chlorophyll <italic>a</italic> content significantly changed in BML over time, and this decline was also observed in BCR (Fig. ##FIG##7##8##C, Additional file ##SUPPL##1##2##: Table S26). Because this decline was evident in both sites, it likely reflects climate or other stochastic factors rather than any particular trend in BML. Furthermore, it is possible that this measurement is complicated by the presence of vanadium, which forms a porphyrin structure similar to that of chlorophyll <italic>a</italic> [##UREF##28##49##]. Overall, a consistent trend in total phytoplankton over the 5-year study could not be concluded.</p>" ]
[ "<title>Discussion</title>", "<title>Comparison of gene sequencing and microscopy</title>", "<p id=\"Par42\">BML is being thoroughly sampled in an adaptive management program to investigate the viability of EPLs as a reclamation strategy for oil sands mines. In this study, we examined phytoplankton community composition over multiple years using a combination of high-throughput sequencing (HTS) from three different PCR analyses (23S, 18S, and 16S rRNA genes) and microscopic cell count data, each of which have their advantages and drawbacks. For instance, many phytoplankton such as cyanobacteria and picoeukaryotes cannot be distinguished morphologically [##UREF##29##50##] without the use of additional methodologies such as flow cytometry or fluorescence microscopy, and thus some studies have observed higher phytoplankton diversity estimates with HTS than microscopy [##REF##32082274##51##, ##UREF##30##52##]. Some organisms also carry multiple copies of rRNA genes, which can introduce biases in relative abundance measures estimated via HTS [##REF##36817748##53##]. For example, the genome for one strain of <italic>Cryptomonas curvata</italic> has seven copies of the 18S rRNA gene (Joint Genome Institute Sequencing Project ID Gp0211829). HTS introduces further biases depending on the primers, DNA extraction methods, and PCR procedures, and some ASVs cannot be properly assigned a taxonomy due to the incomplete state of reference databases [##REF##32082274##51##, ##UREF##30##52##, ##UREF##31##54##]. Various works confirm that molecular and microscopy approaches are complementary and their co-application provides a more complete depiction of the whole phytoplankton community [##REF##32082274##51##]. However, few phytoplankton studies compare microscopy to HTS over multiple years (e.g., [##UREF##30##52##]), and to our knowledge, no study has used this combination of three rRNA gene analyses over multiple years, each of which also have their own benefits and disadvantages.</p>", "<p id=\"Par43\">The 16S rRNA gene can be used to identify both prokaryotic cyanobacteria and eukaryotic chloroplasts. However, heterotrophic bacteria are typically far more abundant than phytoplankton, and often only a small fraction of phytoplankton sequences are detected within a 16S rRNA gene amplicon [##UREF##31##54##]. Out of ~ 36,600 total bacterial ASV features observed in all our samples, only 2,409 were identified as belonging to phytoplankton (6.6%) (Additional file ##SUPPL##1##2##: Table S6). Sequencing of the 18S rRNA gene is commonly used to investigate general eukaryotic diversity [##REF##25851049##55##, ##REF##31913322##56##] and microalgal diversity [##REF##31913322##34##], but the primers used in our study present some constraints. Foremost, the primers do not effectively amplify for Excavates [##REF##31278828##57##], and therefore detected virtually no <italic>Euglenophyceae</italic>. Sequencing of the 18S rRNA gene is also known to estimate a greater proportion of heterotrophic flagellates compared to microscopy observations, particularly with chrysophyte clades [##UREF##32##58##]. About 5.3 million reads out of 10.5 million total raw reads were identified as heterotrophic flagellates. These were removed from the 18S dataset in an attempt to obtain exclusively microalgae (including mixotrophs; see Additional file ##SUPPL##1##2##: Table S5-6), but some heterotrophic flagellates may have remained after filtration as unclassified ochryophyte OTUs (e.g., unassigned <italic>Chrysophyceae</italic>). In contrast to the 16S and 18S rRNA genes, domain V of the 23S rRNA gene has a mostly exclusive, comprehensive coverage of photosynthetic microbial groups [##REF##31913322##34##]. However, the 23S rRNA gene is limited by the size of the sequence databases; the most comprehensive database is currently μgreen-db with just over 2,300 sequences [##REF##31913322##34##].</p>", "<p id=\"Par44\">Using multiple molecular and microscopic analyses helped us overcome some of the limitations of each analysis in identifying key phytoplankton taxa. The analyses largely agreed, lending support to our conclusions. The molecular analyses allowed some investigations not possible via traditional microscopic examinations, such as the documentation of consistent seasonal patterns, and the observation that different sites favoured different strains (ASVs) of the same genera. There appear to be common niches for phytoplankton in both the freshwater reservoir BCR and the end-pit lake BML, resulting in similar genus-level diversity, but the distinct conditions in each habitat may have selected for distinct species and strains.</p>", "<title>Phytoplankton community composition in BML</title>", "<p id=\"Par45\">Based on alpha diversity (Fig. ##FIG##6##7##) and beta diversity analyses (Figs. ##FIG##1##2##, ##FIG##3##4##, Additional file ##SUPPL##1##2##: Table S15), each of the three sites were unique. BML was intermediate to the two controls in its alpha diversity, and generally more comparable to BCR than to MLSB in its community composition. This was in-line with expectations, since BML had superior water quality compared to tailings ponds like MLSB [##REF##28334283##3##, ##REF##27062087##21##], and much better clarity after the addition of alum in 2016 [##UREF##33##59##]. Compared to BCR, BML is dimictic and had lower phosphorous content (Additional file ##SUPPL##1##2##: Table S1), factors that affect phytoplankton composition [##UREF##34##60##]. BML also contained more contaminants such as NAs and higher salinity compared to BCR, and thus more sensitive phytoplankton taxa may not have survived dispersal from BCR (discussed more below) [##REF##12413790##19##]. Compared to BCR, BML’s community composition was also less stable. As shown in Fig. ##FIG##2##3##, BML had more ephemeral and fewer persistent phytoplankton taxa over the 5-year study period.</p>", "<p id=\"Par46\">Many of the dominant phytoplankton taxa observed in BML are common in boreal lakes or similar freshwater environments. A study of 75 boreal and temperate lakes and reservoirs in Alberta found a similar community composition in natural and constructed aquatic systems, suggesting that local phytoplankton populations establish rapidly within constructed aquatic systems [##UREF##34##60##]. Dominant phyla in BML included <italic>Cyanobacteria</italic>, <italic>Cryptophyta</italic>, and <italic>Chlorophyta</italic> (Fig. ##FIG##0##1## and Additional file ##SUPPL##0##1##: Fig. S2), which are characteristic of natural boreal lakes in Canada [##UREF##27##47##, ##UREF##35##61##]. The major genera in BML included <italic>Choricystis</italic>, <italic>Synechococcus</italic>, <italic>Cryptomonas</italic>, and <italic>Euglena. Synechococcus</italic> is a typical prokaryotic picophytoplankton constituent in freshwaters [##UREF##29##50##] such as the large boreal Lake Balaton [##UREF##36##62##]. The trebouxiophyte <italic>Choricystis</italic> is ubiquitous to freshwater environments [##UREF##29##50##], and is frequently found in boreal lakes [##UREF##32##58##, ##UREF##36##62##], as are cryptophytes such as <italic>Cryptomonas</italic> [##UREF##27##47##, ##UREF##31##54##, ##UREF##32##58##]. Tropical aquatic environments, in contrast, are typically dominated by <italic>Chlorophyceae</italic>, cyanobacteria, and diatoms, with trebouxiophytes and cryptophytes typically absent or lower in abundance [##UREF##37##63##–##UREF##39##65##]. The four major genera in BML: <italic>Choricystis</italic>, <italic>Synechococcus</italic>, <italic>Cryptomonas</italic>, and <italic>Euglena,</italic> have also been detected in oil-impacted environments [##REF##27497784##66##, ##UREF##40##67##]. Some <italic>Chlorophyta</italic>, <italic>Euglenophyceae</italic>, and <italic>Synechococcales</italic> are tolerant of naphthenic acids (NAs) [##UREF##14##20##, ##REF##27497784##66##, ##REF##23031586##68##] and have been observed in oil sands tailings ponds (Additional file ##SUPPL##0##1##: Figs. S3-4) [##REF##27062087##21##]. Overall, BML’s phytoplankton community composition contains many taxa common to natural boreal lakes and petroleum-impacted environments (Fig. ##FIG##0##1##).</p>", "<p id=\"Par47\">Notably though, the groups <italic>Chrysophyceae</italic>, <italic>Bacillariophyta</italic>, and <italic>Dinophyta</italic> had lower abundances in BML than expected for a boreal lake (Fig. ##FIG##0##1##, Additional file ##SUPPL##0##1##: Figs. S11–S13). In BML’s freshwater input source, BCR, dinophytes occurred in only 2.1% of samples, possibly limiting their dispersal, but chrysophytes and diatoms are more abundant and persistent in BCR than in BML, suggesting their establishment in BML may have been restricted by water quality. Chrysophytes are known to be highly sensitive to environmental changes [##UREF##41##69##], exposure to oil contamination [##UREF##42##70##–##UREF##44##72##], and turbidity [##UREF##42##70##]. Freshwater chrysophyte diversity is highest in oligotrophic waters with low salinity (conductivity &lt; 40 µs cm<sup>−1</sup>) and acidic pH (&lt; 7.0) [##UREF##41##69##, ##UREF##45##73##]. Thus, many chrysophytes may not survive inoculation from BCR to BML, which has a similar pH but an average conductivity almost 7 times greater than BCR’s (Additional file ##SUPPL##1##2##: Table S1). Conversely, some lab studies report that chrysophytes persist in marine oil-contaminated mesocosms [##REF##32056593##74##], oil-contaminated peat bogs [##UREF##46##75##], or microcosms treated with NAs [##UREF##47##76##]. Diatoms have also been reported as sensitive to oil contamination [##UREF##46##75##, ##UREF##47##76##]. However, various pollution-tolerant diatoms commonly persist in oil-contaminated environments [##REF##31141008##77##], or those containing moderate NA concentrations (&gt; 10 mg L<sup>−1</sup>) [##REF##11434295##18##, ##REF##12413790##19##], such as <italic>Nitzschia</italic> and <italic>Navicula</italic>, which are found in BML, BCR, and MLSB. Besides being very scarce in gene sequencing data, cell count data identified dinophytes in only four BML samples, confirming that their scarcity was not due to methodological biases (Additional file ##SUPPL##0##1##: Fig. S13). Not all boreal lakes contain substantial proportions of dinophytes [##REF##29044973##78##], and they are also known to be sensitive to oil contamination [##REF##32056593##74##], so their scarcity in BML is not surprising. However, BML displayed a higher overall level of transitory, ephemeral taxa than BCR (Fig. ##FIG##2##3##), suggesting that many taxa from the BCR source water are unable to establish in BML.</p>", "<p id=\"Par48\">Phytoplankton can serve as indicators of lake trophic status [##UREF##26##46##]. Most Alberta boreal lakes are eutrophic to hypereutrophic due to high natural and anthropogenic phosphorous content. Cyanobacteria are often the dominant phytoplankton phylum, regardless of anthropogenic impact [##UREF##6##8##, ##UREF##48##79##], and are generally more abundant with increasing eutrophication, with greater amounts of <italic>Dolichospermum</italic> and <italic>Microcystis</italic> expected [##UREF##26##46##]. BML is classified as oligotrophic to mesotrophic (Additional file ##SUPPL##1##2##: Table S1) [##UREF##48##79##] and does not appear to contain a disproportionately larger cyanobacterial population compared to boreal lakes (Fig. ##FIG##0##1##). BML’s picophytoplankton community is dominated by <italic>Choricystis</italic> and <italic>Synechococcus</italic> (Fig. ##FIG##5##6##, Additional file ##SUPPL##0##1##: Figs. S7 and S9A), which are found in a wide range of trophic states [##UREF##29##50##, ##UREF##32##58##, ##UREF##36##62##, ##REF##23528076##80##] but have competitive advantages in turbid and eutrophic freshwaters. For instance, accessory pigments in <italic>Synechococcus</italic> strains confer adaptations to low-light [##UREF##29##50##]. Mixotrophs such as <italic>Cryptomonas</italic> and euglenophytes, abundant in BML (e.g., Figs. ##FIG##0##1##, ##FIG##5##6##), are also common to eutrophic waters [##UREF##26##46##, ##UREF##49##81##] and are favoured in boreal lakes with reduced light penetration [##UREF##50##82##], particularly those with lower zooplankton abundance [##UREF##51##83##].</p>", "<p id=\"Par49\">Many of the major phytoplankton members in BML have been reported as significant food web contributors in other systems. Cryptophytes such as <italic>Cryptomonas</italic> serve as a high quality nutrition source to zooplankton [##UREF##11##13##, ##UREF##12##15##], ciliates [##REF##34367571##16##], and bacteria [##REF##21873481##84##]. Picophytoplankton such as <italic>Choricystis</italic> and <italic>Synechococcus</italic> are consumed by ciliates and heterotrophic or mixotrophic nanoflagellates [##UREF##29##50##], but are low-quality nutritional sources lacking polyunsaturated fatty acids and sterols. However, they can be suitable for consumption by smaller protist grazers, by which they can undergo “trophic upgrading”. For instance, the heterotrophic nanoflagellate <italic>Paraphysomonas</italic> (highly abundant in BML based on 18S rRNA gene sequencing; data not shown) consumes these picophytoplankton and synthesizes lipids de novo, providing improved nutrition to higher trophic levels [##UREF##12##15##]. Other known grazers of <italic>Synechococcus</italic> include cryptophytes and euglenophytes [##REF##28962973##85##, ##REF##29602510##86##]. Only a handful of <italic>Synechococcus</italic> species have been reported to produce microcystins [##UREF##52##87##], with no cyanotoxin-producing strains reported in Alberta thus far [##UREF##13##17##, ##UREF##53##88##]. Filamentous cyanobacteria such as <italic>Prochlorothrix</italic> and <italic>Planktothrix</italic>, abundant in BML and BCR, respectively (Additional file ##SUPPL##0##1##: Figs. S3, S4), are known to contribute to food webs in freshwater lakes [##REF##23129401##89##, ##UREF##54##90##]. However, they can be difficult for filter-feeding zooplankton and protists to ingest [##REF##28675820##91##]; several species of <italic>Planktothrix</italic> are also known to produce cyanotoxins [##UREF##52##87##, ##UREF##53##88##]. BML is notably lower in relative abundance for diatoms, dinophytes, and photosynthetic chrysophytes (Fig. ##FIG##0##1##), which are important nutritional sources in boreal lakes [##UREF##11##13##]. Nevertheless, BML contains many of the important phytoplankton groups that are the typical bases for boreal lake food webs.</p>", "<title>Phytoplankton seasonality</title>", "<p id=\"Par50\">Seasonal changes in stratification, temperature, turbidity, light, nutrient distribution, and grazing pressure can mediate temporal changes in phytoplankton [##UREF##55##92##, ##REF##17024384##93##]. Many genera in BML experienced recurring annual patterns of growth (Additional file ##SUPPL##0##1##: Figs. S7–S13, Additional file ##SUPPL##1##2##: Table S23). <italic>Cryptomonas</italic> usually peaked in early autumn (Fig. ##FIG##5##6##, Additional file ##SUPPL##0##1##: Fig. S8), similar to observations in Norwegian and Swedish boreal lakes [##UREF##56##94##, ##UREF##57##95##]. <italic>Choricystis</italic> peaked in abundance in the spring, from May to June in BML (Fig. ##FIG##5##6##, Additional file ##SUPPL##0##1##: Fig. S7), also consistent with other studies [##UREF##58##96##, ##UREF##59##97##]. The euglenophytes <italic>Euglena</italic>, <italic>Phacus</italic>, and <italic>Lepocinclis</italic> peaked in spring from May to June, while <italic>Trachelomonas</italic> peaked in autumn (Fig. ##FIG##5##6##, Additional file ##SUPPL##0##1##: Fig. S10). Less abundant groups like diatoms and dinophytes also showed some annual patterns. Diatoms such as <italic>Asterionella</italic> and <italic>Fragilaria</italic> are known to be favoured by mixing periods [##UREF##60##98##, ##UREF##61##99##], and those in Additional file ##SUPPL##0##1##: Fig. S12 each showed at least one peak during a mixing period in BML. Consistent with our observations on BML, <italic>Asterionella</italic> and <italic>Fragilaria</italic> have been found to increase during spring in lakes, while <italic>Aulacosiera</italic> and <italic>Cyclotella</italic> are known to increase in autumn or the end of summer [##UREF##62##100##, ##UREF##63##101##]. Dinophytes in BML increased in autumn for 2018–2021 (Additional file ##SUPPL##0##1##: Fig. S13), consistent with other findings [##UREF##64##102##, ##UREF##65##103##]. Cyanobacterial blooms are generally favoured by stratification [##UREF##66##104##], as well as elevated nutrient concentrations and water temperatures [##UREF##6##8##]. They are common during the late summer or autumn months in Canadian freshwaters [##UREF##6##8##, ##UREF##13##17##, ##UREF##34##60##, ##UREF##61##99##] and other temperate regions [##UREF##67##105##], as was the case for <italic>Synechococcus</italic>, <italic>Aphanizomenon</italic>, <italic>Microcystis</italic>, and <italic>Planktothrix</italic> in BML (Fig. ##FIG##0##1##, Additional file ##SUPPL##0##1##: Fig. S9). Annual patterns in BML therefore suggest ecosystem dynamics comparable to those found in natural boreal lakes.</p>", "<title>Phytoplankton quantification</title>", "<p id=\"Par51\">It was predicted that phytoplankton populations would increase over time due to increased water clarity resulting from the 2016 alum addition [##UREF##5##7##], however, different measurements led to inconsistent conclusions. Chlorophyll <italic>a</italic> measures significantly declined in BML from 2016 to 2021. Conversely, phytoplankton cell count and biomass did not change significantly from 2016 to 2021, while 23S rRNA gene counts appeared to first increase from 2016 to 2019, and then decrease again in 2021, with no net overall linear trend. We are unable to assess whether the addition of alum in 2016 had a major immediate effect on algal growth because of a shortage of pre-2016 samples, but the algal load remained quite stable in the 5 years after clarification.</p>", "<p id=\"Par52\">Phytoplankton gene counts in BML were usually equal or higher than in BCR, but non-molecular measures suggested that phytoplankton were usually one to two orders of magnitude lower in BML than BCR (Fig. ##FIG##7##8##, Additional file ##SUPPL##1##2##: Table S26). BCR had greater nutrient content and therefore likely supported greater phytoplankton abundances. However, some measures indicated a decline in phytoplankton quantity for both sites in 2021 (Fig. ##FIG##7##8##, Additional file ##SUPPL##1##2##: Table S26). Phosphorus, nitrogen, turbidity, and total organic carbon were all lower in 2021 compared to previous years for both sites, while total hardness was about twice as high for BCR (from ~ 125 mg L<sup>−1</sup> to ~ 230 mg L<sup>−1</sup>) (Additional file ##SUPPL##1##2##: Table S1). These changes in BML and BCR in 2021 may have resulted from the pandemic shutdown of mine operations in 2020, including disruption of normal water management. During 2021, no water was pumped in to BML or BCR. More data will be needed to determine long-term trends, and whether 2021 was atypical.</p>", "<p id=\"Par53\">BML and BCR’s phytoplankton biomass and chlorophyll <italic>a</italic> content were within the ranges expected of boreal freshwater lakes. For instance, non-impacted large oligo-humic Finnish boreal lakes had total phytoplankton biomasses and chlorophyll <italic>a</italic> concentrations ranging from 120 to 980 mg m<sup>−3</sup> and 1.2–8.2 μg L<sup>−1</sup>, respectively, which match closely with ranges in BML (mean ranges were 109–11,005 mg m<sup>−3</sup> and 1.3–3.4 μg L<sup>−1</sup>; see Additional file ##SUPPL##1##2##: Table S26) [##UREF##68##106##]. BML’s chlorophyll <italic>a</italic> content was also slightly greater than that of post-logging boreal lakes in Ontario, which ranged from 0.9 to 1.2 μg L<sup>−1</sup> [##UREF##35##61##]. BCR’s biomass and chlorophyll <italic>a</italic> content were about an order of magnitude higher than BML’s (mean ranges were 1,990–1,499,159 mg m<sup>−3</sup> and 5.8–21.7 μg L<sup>−1</sup>, respectively; see Additional file ##SUPPL##1##2##: Table S26), and compared more closely to wetland-dominated Alberta boreal lakes, which had mean biomass and chlorophyll <italic>a</italic> concentrations of ~ 6,400 mg m<sup>−3</sup> and 21 μg L<sup>−1</sup>, respectively [##UREF##27##47##].</p>", "<title>Phytoplankton diversity over time</title>", "<p id=\"Par54\">The relative abundances of <italic>Cryptophyta</italic>, <italic>Chlorophyta</italic>, and <italic>Cyanobacteria</italic> did not change substantially over 5 years in BML (Figs. ##FIG##0##1##, ##FIG##5##6##, and Additional file ##SUPPL##0##1##: Figs. S7-S9). However, changes in some other taxa may indicate a changing system. Haptophytes and dinophytes increased in later years in BML (Additional file ##SUPPL##0##1##: Fig. S13), while remaining unchanged in the BCR control site. Dinophytes are natural constituents of boreal lakes (e.g., [##UREF##27##47##]), while haptophytes are predominantly marine organisms [##REF##23584973##107##], but have also been found in freshwaters in small quantities [##UREF##35##61##, ##REF##16104864##108##]. Despite the slightly saline conditions in BML, the haptophytes observed were freshwater genera belonging to <italic>Pavlovales</italic>. The increase in these taxa suggests that new species may be colonizing BML as conditions improve. In contrast, many ochrophytes and diatoms, after appearing to increase in 2018–2019, were lowest in abundance during 2021 (Additional file ##SUPPL##0##1##: Figs. S11-S12). As noted above, shutdown of pump-in to BML from BCR in 2021 may be responsible for some of these changes, although many taxa still persisted in BML (e.g., Fig. ##FIG##5##6##, Additional file ##SUPPL##0##1##: Fig. S5).</p>", "<p id=\"Par55\">New aquatic systems may become more biologically diverse over time as reclamation proceeds and new species establish [##UREF##69##109##]. BML evidently represents an intermediate state between a tailings pond and a freshwater reservoir, both in its alpha diversity and beta diversity (Fig. ##FIG##6##7##, Additional file ##SUPPL##0##1##: Figs. S14-S15). The more biodiverse freshwater reservoir BCR is a source of phytoplankton inoculation into BML, and diversity is expected to increase over time in BML relative to BCR as water quality improves. However, phytoplankton α-diversity did not consistently increase or decrease in BML over time based on different diversity metrics and gene sequencing datasets (Additional file ##SUPPL##0##1##: Figs. S14–S16 and Additional file ##SUPPL##1##2##: Table S25). Any positive trends were small, inconsistent, and explained little of the overall variation. Long-term trends may have been masked by year-to-year and seasonal variability. BML’s phytoplankton α-diversity experienced increases during autumn turnover (Additional file ##SUPPL##0##1##: Fig. S15), whereas BCR showed no clear seasonal patterns, a difference likely due to the lack of turnover periods and/or insufficient sampling of BCR. Disturbances such as the alum addition and nearby wildfires in 2016 also could have contributed to the observed variability. A study on boreal plain lakes in Alberta concluded that wildfires impacted phytoplankton communities in those lakes for 4 years after the fire [##UREF##70##110##]. More data will be necessary to conclude whether there are long-term trends in BML α-diversity.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par56\">This research establishes a baseline of phytoplankton community composition in an oil sands end pit lake based on both DNA sequencing and cell count methods. These data can be used to inform planning and management of future oil sands end pit lakes [##UREF##5##7##]. We have demonstrated the presence of phytoplankton taxa in BML comparable to those found in natural boreal lakes, with potential food web members present. BML shows distinct seasonal patterns in some phytoplankton taxa consistent with natural boreal lakes. Neither phytoplankton abundance nor alpha diversity increased notably in 5 years from 2016 to 2021, but data from future years could resolve this. BML diversity was intermediate between the freshwater and tailings controls. BML had a community composition similar to the freshwater control at higher taxonomic levels but differences were evident at the strain level, with fewer persistent strains in BML. Phytoplankton abundance and seasonality in BML were not merely a product of freshwater inflow. Instead, specific phytoplankton strains established and continued to exhibit seasonal patterns without freshwater input in 2021. Further research should continue to monitor the phytoplankton community in BML in terms of its community composition, seasonality, and diversity over time. Additional research could also clarify the roles of different phytoplankton groups in the BML food web.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Base Mine Lake (BML) is the first full-scale end pit lake for the oil sands mining industry in Canada. BML sequesters oil sands tailings under a freshwater cap and is intended to develop into a functional ecosystem that can be integrated into the local watershed. The first stage of successful reclamation requires the development of a phytoplankton community supporting a typical boreal lake food web. To assess the diversity and dynamics of the phytoplankton community in BML at this reclamation stage and to set a baseline for future monitoring, we examined the phytoplankton community in BML from 2016 through 2021 using molecular methods (targeting the 23S, 18S, and 16S rRNA genes) and microscopic methods. Nearby water bodies were used as controls for a freshwater environment and an active tailings pond.</p>", "<title>Results</title>", "<p id=\"Par2\">The phytoplankton community was made up of diverse bacteria and eukaryotes typical of a boreal lake. Microscopy and molecular data both identified a phytoplankton community comparable at the phylum level to that of natural boreal lakes, dominated by <italic>Chlorophyta</italic>, <italic>Cryptophyta</italic>, and <italic>Cyanophyta</italic>, with some <italic>Bacillariophyta</italic>, <italic>Ochrophyta</italic>, and <italic>Euglenophyta</italic>. Although many of the same genera were prominent in both BML and the control freshwater reservoir, there were differences at the species or ASV level. Total diversity in BML was also consistently lower than the control freshwater site, but consistently higher than the control tailings pond. The phytoplankton community composition in BML changed over the 5-year study period. Some taxa present in 2016–2019 (e.g., <italic>Choricystis</italic>) were no longer detected in 2021, while some dinophytes and haptophytes became detectable in small quantities starting in 2019–2021. Different quantification methods (qPCR analysis of 23S rRNA genes, and microscopic estimates of populations and total biomass) did not show a consistent directional trend in total phytoplankton over the 5-year study, nor was there any consistent increase in phytoplankton species diversity. The 5-year period was likely an insufficient time frame for detecting community trends, as phytoplankton communities are highly variable at the genus and species level.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">BML supports a phytoplankton community composition somewhat unique from control sites (active tailings and freshwater lake) and is still changing over time. However, the most abundant genera are typical of natural boreal lakes and have the potential to support a complex aquatic food web, with many of its identified major phytoplankton constituents known to be primary producers in boreal lake environments.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s40793-023-00544-3.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We would like to thank Amelia Chan, Andriy Sheremet, Elisabeth Richardson, Esther Trang, Eun-Suk Lee, Evan Haupt, Felix Nwosu, Ilona Ruhl, and Triet Tran for their assistance with sample extraction. We would especially like to thank Carla Wytrykush and Chris Beierling at Syncrude, Inc., and Michelle Betts at Hatfield Consultants for their dedicated assistance with sampling and resolving issues. Field samples were contracted by Syncrude, Inc. to Hatfield Consultants (Calgary, AB, Canada). The microscopic species identification, population counts, and biomass analyses were contracted to EcoAnalysts laboratory (Moscow, ID, USA). Water samples and microscopic datasets were kindly provided by Syncrude.</p>", "<title>Author contributions</title>", "<p>CCF and PFD were responsible for project conception, project funding, and experimental design. CCF and AVS were responsible for sample processing, rRNA gene sequencing, and qPCR. CCF, AVS, PFD, and JBD were responsible for analysing and interpreting the data. CCF and PFD wrote the paper, with comments from AVS and JBD. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Collaborative Research and Development Grant (NSERC grant CRDPJ 542973-19) in collaboration with Syncrude Canada, Ltd. CCF received support from the Alberta Graduate Excellence Scholarships (AGES) – Master’s Research, the Jim and Jean Cragg Doctoral Scholarship in Biological Sciences, and the Graeme Bell and Norma Kay Sullivan-Bell Graduate Scholarship in Biology.</p>", "<title>Availability of data and materials</title>", "<p>Amplicon sequencing data is publicly available in the SRA repository under Accession no. PRJNA1003951.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par57\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par58\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par59\">The authors declare no conflict of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Relative abundances (%) of the major phytoplankton phyla in surface waters of BML (0.3–0.6 m for 23S rRNA gene data and 0.6–0.8 m for cell count and biomass data) for each sampling year, shown in comparison to the freshwater reservoir BCR (averaged for all years) and to relative biomass estimated in Alberta boreal headwater lakes [##UREF##27##47##]. Total biomass (mg m<sup>−3</sup>) is also given as a logarithmic scale. For direct comparison of the different sites, only samples from July through September were included</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Heatmap with double hierarchical clustering analysis, depicting relative abundances of genera that comprise ≥ 1% of the total detected in the 18S rRNA gene sequencing analysis for shared sample dates between BML, BCR, and MLSB, normalized to 1000 counts using the R package <italic>SRS</italic>. Genera are colour-coded by phylum and clustered based on similarities across sites. Hierarchal cluster analyses of sites shown at the top of the heatmap include approximately unbiased alpha levels (AU) (p-values computed by multiscale bootstrap resampling) and bootstrap probability for 1000 resamplings (BP) of each node (AU/BP). AU values &gt; 95 indicate significant cluster nodes. BML and BCR consistently cluster apart from MLSB</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Taxa occurring in different proportions of surface water samples taken on shared sample dates between BML and BCR for gene sequencing data (0.3–0.6 m depth) and cell count data (0.6–0.8 m depth) over all years. Taxa for the gene sequencing data were ASVs, while those for the cell counts were species. For each set of bars, the lighter shades indicate ephemeral taxa (present in few samples), while the darker shades indicate increasingly more persistent taxa (present in most samples). BML showed more ephemeral and fewer persistent taxa than BCR. Data were normalized using scaling with ranked subsampling (SRS) [##UREF##22##41##] to 4000, 1000, 100, and 10,000 for the 23S, 18S, and 16S rRNA gene datasets and cell count data, respectively. Each bar represents the mean of three replicates ± 1 SEM. No replicates were available for BCR cell count data</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Non-metric multi-dimensional scaling ordination (NMDS) plots in BML, BCR, and MLSB surface waters based on Bray–Curtis dissimilarities of phytoplankton communities. Data were normalized using scaling with ranked subsampling (SRS) [##UREF##22##41##] to 4000, 1000, 100, and 10,000 for the 23S, 18S, and 16S rRNA gene and cell count datasets, respectively. Taxa were classified at the ASV-level for molecular data and at the species-level for cell count data. k = 2 axes for all plots. Stress scores were 0.198, 0.207, 0.142, and 0.239 for the 23S, 18S, and 16S rRNA gene and cell count datasets, respectively. Clusters with ANOSIM support are indicated by coloured circles; all samples were included in ANOSIM analysis, but circles were hand-drawn to emphasize clustering (See Additional file ##SUPPL##1##2##: Table S15). Winter samples were not included in this analysis as there was no winter sampling for BCR</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Summary of genus-level Indicator Species Analysis (ISA) results for BML surface waters over 6 years. Gaps are given by dashed lines to show that a genus was not indicative for that year (although most genera were always present at some level). UA stands for unassigned at any taxonomic level below the taxon shown. For details on the ISA statistics, see Additional file ##SUPPL##1##2##: Table S21. No sampling was conducted in 2020</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Relative abundances of the four major algal genera in BML surface waters: <bold>A</bold>\n<italic>Choricystis</italic>, <bold>B</bold>\n<italic>Cryptomonas</italic>, <bold>C</bold>\n<italic>Synechococcus</italic>, and <bold>D</bold>\n<italic>Euglena</italic>, based on 23S, 16S and/or 18S rRNA gene amplicon sequencing. Non-cyanobacteria were filtered from the 16S rRNA gene dataset and known non-photosynthetic eukaryotes were filtered from the 18S rRNA gene dataset. Also included for B) and D) are microscopic cell count data. Note that the different analyses are not fully comparable due to their respective limitations and biases (see Discussion: Gene Sequencing and Microscopy Complementarity). Data points are means of three platforms ± 1 SEM. Where error bars are not seen they are contained within the symbol. The teal bar indicates alum addition. Dashed lines indicate running averages calculated with smoothing in SigmaPlot, in which a running average is based on 10 samples. In panel B, the single extreme outlier in the microscopic count data was not used in the running average</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Alpha-diversity indices in BML, BCR, and MLSB surface waters on shared sample dates, based on 18S rRNA gene sequencing at the ASV level, normalized to 1000 counts and filtered to include only phytoplankton. The 18S rRNA gene was chosen because it had the most shared sample points. Data points in the left panels are means of three samples ± 1 SEM, except for MLSB samples, which were unreplicated. Stem-and-leaf plots (right panels) for each index indicate means, 95% confidence intervals, and ranges averaged by site over all sampling dates; points indicate outliers. Diversity indices were significantly different across sites in all cases except in BML versus MLSB for the Shannon diversity index</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>Quantification of phytoplankton for 2016–2021 based on cell counts (<bold>A</bold>), biomass (<bold>B</bold>), chlorophyll <italic>a</italic> (<bold>C</bold>), and qPCR quantification of the 23S rRNA gene (<bold>D</bold>) for surface water samples. Given are the slope (m) per year, p-values based on a t-test of slope = 0, and the r<sup>2</sup> value for the regression lines. Data points are means of three platforms ± 1 SEM for BML; points for MLSB and BCR are single values. The teal bar indicates alum addition</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Palmer’s Pollution Index results for BML and BCR surface waters (≤ 0.6 m) by year and overall</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Phytoplankton Genus</th><th align=\"left\" rowspan=\"2\">Index Value</th><th align=\"left\" colspan=\"6\">BML</th><th align=\"left\" colspan=\"6\">BCR</th></tr><tr><th align=\"left\">2016</th><th align=\"left\">2017</th><th align=\"left\">2018</th><th align=\"left\">2019</th><th align=\"left\">2021</th><th align=\"left\">Total</th><th align=\"left\">2016</th><th align=\"left\">2017</th><th align=\"left\">2018</th><th align=\"left\">2019</th><th align=\"left\">2021</th><th align=\"left\">Total</th></tr></thead><tbody><tr><td align=\"left\"><italic>Cyclotella</italic></td><td align=\"left\">1</td><td align=\"left\">–</td><td align=\"left\">18S</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">18S</td><td align=\"left\">–</td><td align=\"left\">23S, 18S, 16S</td><td align=\"left\">23S, 18S, CC</td><td align=\"left\">23S, 18S, 16S, CC</td><td align=\"left\">23S</td><td align=\"left\">23S, 18S, 16S, CC</td></tr><tr><td align=\"left\"><italic>Gomphonema</italic></td><td align=\"left\">1</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">CC</td></tr><tr><td align=\"left\"><italic>Melosira</italic></td><td align=\"left\">1</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"><italic>Navicula</italic></td><td align=\"left\">3</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">CC</td></tr><tr><td align=\"left\"><italic>Nitzschia</italic></td><td align=\"left\">3</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">18S, CC</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">18S, CC</td></tr><tr><td align=\"left\"><italic>Synedra</italic></td><td align=\"left\">2</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">CC</td></tr><tr><td align=\"left\"><italic>Ankistrodemsus</italic></td><td align=\"left\">2</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td></tr><tr><td align=\"left\"><italic>Chlamydomonas</italic></td><td align=\"left\">4</td><td align=\"left\">23S, CC</td><td align=\"left\">23S</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">23S, CC</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">CC</td></tr><tr><td align=\"left\"><italic>Chlorella</italic></td><td align=\"left\">3</td><td align=\"left\"/><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">23S, 18S</td><td align=\"left\">23S</td><td align=\"left\">23S, 18S</td><td align=\"left\">CC</td><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">23S, CC</td></tr><tr><td align=\"left\"><italic>Closterium</italic></td><td align=\"left\">1</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">CC</td></tr><tr><td align=\"left\"><italic>Micractinium</italic></td><td align=\"left\">1</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td></tr><tr><td align=\"left\"><italic>Pandorina</italic></td><td align=\"left\">1</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">–</td></tr><tr><td align=\"left\"><italic>Scenedesmus</italic></td><td align=\"left\">4</td><td align=\"left\">–</td><td align=\"left\">18S</td><td align=\"left\">CC</td><td align=\"left\">18S</td><td align=\"left\">18S, CC</td><td align=\"left\">18S, CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">18S</td><td align=\"left\">–</td><td align=\"left\">18S, CC</td></tr><tr><td align=\"left\"><italic>Stigeoclonium</italic></td><td align=\"left\">2</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"><italic>Anacystis</italic></td><td align=\"left\">1</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"><italic>Oscillatoria</italic></td><td align=\"left\">5</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">NA</td></tr><tr><td align=\"left\"><italic>Phormidum</italic></td><td align=\"left\">1</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">CC</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">–</td><td align=\"left\">NA</td><td align=\"left\">NA</td><td align=\"left\">–</td></tr><tr><td align=\"left\"><italic>Euglena</italic></td><td align=\"left\">5</td><td align=\"left\">23S, CC</td><td align=\"left\">23S, 16S, CC</td><td align=\"left\">23S, 16S, CC</td><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">23S, 16S, CC</td><td align=\"left\">–</td><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">–</td><td align=\"left\">23S</td><td align=\"left\">23S, CC</td></tr><tr><td align=\"left\"><italic>Lepocinclis</italic></td><td align=\"left\">1</td><td align=\"left\">–</td><td align=\"left\">16S</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">23S, 16S, CC</td><td align=\"left\">–</td><td align=\"left\">23S</td><td align=\"left\">23S</td><td align=\"left\">23S, CC</td><td align=\"left\">23S, CC</td><td align=\"left\">23S, CC</td></tr><tr><td align=\"left\"><italic>Phacus</italic></td><td align=\"left\">2</td><td align=\"left\">CC</td><td align=\"left\">23S, 16S, CC</td><td align=\"left\">–</td><td align=\"left\">CC</td><td align=\"left\">CC</td><td align=\"left\">23S, 16S, CC</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">23S</td><td align=\"left\">CC</td><td align=\"left\">–</td><td align=\"left\">23S, CC</td></tr><tr><td align=\"left\" rowspan=\"2\"><italic>Score</italic></td><td align=\"left\" rowspan=\"2\">44</td><td align=\"left\">11</td><td align=\"left\">26</td><td align=\"left\">21</td><td align=\"left\">22</td><td align=\"left\">16</td><td align=\"left\">28</td><td align=\"left\">11</td><td align=\"left\">17</td><td align=\"left\">16</td><td align=\"left\">14</td><td align=\"left\">13</td><td align=\"left\">30</td></tr><tr><td align=\"left\">Low</td><td align=\"left\">High</td><td align=\"left\">High</td><td align=\"left\">High</td><td align=\"left\">Moderate</td><td align=\"left\">High</td><td align=\"left\">Low</td><td align=\"left\">Moderate</td><td align=\"left\">Moderate</td><td align=\"left\">Low</td><td align=\"left\">Low</td><td align=\"left\">High</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Scores were assigned if a genus had an average relative abundance ≥ 0.50% and was present in at least 3 samples for that given year and source for at least one dataset (cell count data or 23S/18S/16S rRNA gene data). “CC” indicates cell count, “NA” indicates complete absence of the genus and “-” indicates the genus is present with &lt; 0.50% average relative abundance. “Total” indicates the score for all years combined. Scores ≥ 20 indicate clear evidence of high organic pollution, those ranging from 15–19 were moderate and were considered to have probable evidence of organic pollution, and scores &lt; 15 were low and were considered to have no evidence of organic pollution [##REF##27097257##45##]</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"40793_2023_544_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1</bold>. Notes and figures.</p></caption></media>", "<media xlink:href=\"40793_2023_544_MOESM2_ESM.xlsx\"><caption><p><bold>Additional file 2</bold>. Tables.</p></caption></media>" ]
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{ "acronym": [ "BCR", "BML", "MLSB" ], "definition": [ "Beaver Creek Reservoir", "Base Mine Lake", "Mildred Lake Settling Basin" ] }
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2024-01-14 23:43:46
Environ Microbiome. 2024 Jan 12; 19:3
oa_package/0b/fc/PMC10787447.tar.gz
PMC10787448
0
[ "<title>Background</title>", "<p id=\"Par5\">Reactive oxygen species (ROS) are a series of chemical species formed during oxygen´s cellular metabolism, which biologically participate in processes like homeostasis, defense, and signaling. However, these might become harmful to biomolecules, cells, and tissue [##REF##25744690##1##] and even promote multiple pathologies (e.g., cancer) when a loss of the cellular redox balance occurs, a process known as oxidative stress, which can be enabled by external factors such as heavy metals, smoking, alcohol consumption, and UV radiation [##UREF##0##2##, ##REF##24024158##3##]. In fact, among cancer hallmarks, high production of ROS is highlighted [##REF##25342630##4##–##REF##20370557##7##] as being linked to the initiation, promotion, and progression steps of this pathology [##REF##20840865##8##]. Therefore, many potential cancer treatment therapies have focused on ROS concentration.</p>", "<p id=\"Par6\">In 2011, Burgess introduced the term “selective oxycution,” which is defined as the selective killing of cancer cells by promoting a redox imbalance in cancer cells vs. nontumoral cells [##UREF##1##9##]. To accomplish it, four strategies have been proposed to inflict lethal damage or to trigger apoptosis in cancer cells: (1) direct exposure to ROS-generating agents (prooxidant agents); (2) inhibition of cancer cell´s antioxidant enzymes; (3) intracellular ROS production decrease (antioxidants), and (4) an appropriate combination of the three previous strategies [##REF##19269363##6##, ##UREF##2##10##–##REF##25590798##13##]. Within these strategies, several studies using natural compounds have shown selective killing in different cancer cell lines.</p>", "<p id=\"Par7\">For instance, Trachootham et al. (2006) used β-phenyl ethyl isothiocyanate (PEITC), present in cruciferous plants, to effectively disable the glutathione antioxidant system and, therefore, generate ROS accumulation selectively in ovarian cancer cells [##UREF##3##14##]. Posteriorly, Juan et al. (2008) used resveratrol, a polyphenol found in black grapes and other fruits with a high antioxidant capacity, in colorectal cancer cells, seeing that it plays a significant role in reducing cell proliferation and promoting intrinsic apoptosis mechanisms [##REF##18522405##15##]. These encourage the search for new anticancer natural compounds, especially looking into endemic plants.</p>", "<p id=\"Par8\">In Chile and Argentina, Mapuche people are characterized by a deep knowledge of nature, where they give medicinal uses to native plants, with more than 700 medicinal native Mapuche plants identified. However, little is known about their content and biological activity [##UREF##4##16##]. Among these, plants belonging to the Escallonia genus have been less explored. Particularly, Barraco (<italic>Escallonia illinita</italic> Presl.; Saxifragaceae) is a key representative of the genus, which has been well characterized and recommended by folk medicine for the treatment of hepatic, venereal, renal, and respiratory diseases and infected wounds. However, there is a lack of scientific evidence that supports such benefits. Nonetheless, some anticancer potential has been described [##UREF##5##17##–##UREF##8##20##]. Further, there are three other species from the same genus (<italic>E. rubra</italic>, <italic>E. revoluta</italic>, and <italic>E. pulverulenta</italic>), of which there is no single study or evidence of their potential uses in biomedicine. Therefore, this work uses extracts from Escallonia genus plants to evaluate their potential “selective oxycution” on cancer cell lines of the colon, breast, and prostate by measuring their antioxidant and cytotoxic capacities and their effect on redox balance.</p>" ]
[ "<title>Materials and methods</title>", "<title>Escallonia genus plant collection</title>", "<p id=\"Par9\"><italic>E. illinita, E. rubra, E. revoluta</italic>, and <italic>E. pulverulenta</italic> were collected from Laguna Verde (Latitude: -33.1; Longitude: -71.6833) and Fundo Santa Ana (Latitude: -33.2167; Longitude: -71.4) at 460 m.a.s.l. in January 2019. Employed Escallonia specimens are cataloged as common species, and their extraction and usage were performed following Chilean legislation law 20,283 “about native forest recovery and forestry foment” (Ley 20,283 “Ley sobre recuperación del bosque nativo y fomento forestal”) and Decree 28 “rules about resources destined to native forest research” (Decreto 28 “que reglamenta los recursos destinados a la investigación del bosque nativo”) of the Ministry of Agriculture of Chile. All collected plants were identified by Patricio Novoa, Forest Engineer, Botanical Expert, and Chief of the Horticulture Department, “<italic>Jardín Botánico Nacional</italic>,” Viña del Mar, Valparaíso, Chile, considering the plant’s morphological properties. Vouchers for each specimen: Ei (VALPLA 2017-11), Er (VALPLO 2017-12), Ep (VALPLO 2017-13), Ere (VALPLO 2017-14), are kept at the CIFAR, Farmacopea Chilena, Universidad de Valparaíso, Valparaíso, Chile.</p>", "<title>Extraction procedure</title>", "<p id=\"Par10\">The extraction of aerial parts from Escallonia specimens was performed by applying a non-lethal procedure. Selective pruning was done using the ANASAC PASTA PODA TPN-50 product and fungicide paint for pruning, and it involved different types of wounds on the plant. Each plant´s stem, leaves, and flowers were selected as the sections to obtain the extracts. To accomplish this, they were air-dried at room temperature and then subjected to successive extractions using different solvents of increasing polarity, like a previous report by Jara et al. (2017) [##REF##28274131##21##]. Briefly, 300 g of dried plant material was added to 500 mL of each solvent (n-hexane (H), di-chloromethane (D), ethyl acetate (A), and ethanol (E)); then, the extraction of <italic>E. illinita</italic>, <italic>E. rubra</italic>, <italic>E. revoluta</italic>, and <italic>E. pulverulenta</italic> was completed in 48 h and replicated three times. All the obtained extracts were sonicated, concentrated in a rotary evaporator at 40 °C, and stored at room temperature in darkness.</p>", "<title>Phytoconstituent compounds and antioxidant capacity analysis of extracts</title>", "<title>Total phenolic content determination</title>", "<p id=\"Par11\">The amount of total phenolic compounds in the extracts was determined using the method reported by Waterman et al. (1994) [##UREF##9##22##], with minor modifications determined by our research team [##REF##28274131##21##]. Each extracted sample (2.0 mg) was dissolved in 2.0 mL of ethanol. Then, 500 µL of the extracts were mixed with Folin-Ciocalteau reagent (2.5 mL, 0.2 N) and incubated for 5 min. Posteriorly, a 7.5% w/v Na<sub>2</sub>CO<sub>3</sub> solution (2.0 mL) was added and incubated in darkness at room temperature for 2 h. Absorbance was measured in a spectrophotometer (RayLEIGH, UV-2601, China) at 700 nm using ethanol as the blank. Absorbance values obtained were interpolated using a Gallic acid standard curve (0–200 mg*L<sup>− 1</sup>), and the total phenolic content was expressed as mM of Gallic acid equivalents (mM GAE) per g of dried extract. All the measurements were carried out in triplicate.</p>", "<title>Total flavonoid content estimation</title>", "<p id=\"Par12\">The total flavonoid content was determined using the Dowd method, as adapted by Arvouet-Grand et al. (1994) [##REF##7884635##23##]. For this, 1 mL of 2% w/v aluminum trichloride (AlCl<sub>3</sub>) in ethanol was mixed with the same volume of the extract’s solution in ethanol (1.0 mg*mL<sup>− 1</sup>). Then, the mixture was incubated for 10 min at room temperature, and absorbance was measured at 415 nm against a blank sample consisting of 1.0 mL extract solution with 1.0 mL of methanol without AlCl<sub>3</sub>. The absorbance values were interpolated using a quercetin calibration curve (0–100 mg*L-1). The total flavonoid content was expressed as mM of quercetin equivalents (mM QE) per g of dry extract. All the measurements were carried out in triplicate.</p>", "<title>Total anthraquinones content estimation</title>", "<p id=\"Par13\">This estimation was carried out using the protocol of Arvouet-Grand et al., adapted by Mellado et al. (2012) [##UREF##10##24##]. For this, a protocol like the previously exposed in Sect. 2.3.2 was followed, measuring absorbance at 486 nm. The absorbance values were interpolated using an emodin calibration curve (0–70 mg*L<sup>− 1</sup>). The total anthraquinones content was expressed as mM of emodin equivalents (mM EE) per g of dry extract. All the measurements were carried out in triplicate.</p>", "<title>Total reactive antioxidant power (TRAP) assay</title>", "<p id=\"Par14\">The method developed by Romay et al. (1996) [##REF##8731346##25##] was slightly modified for this experiment. Briefly, a 10 mM solution of 2,2′-azo-bis(2-amidino propane) (ABAP) was mixed with the same volume of 150 µM solution of 2,2′-azinobi(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) using PBS 100 mM at pH of 7.4 (TRAP solution). The mixture was incubated at 45 °C for 30 min and then cooled to room temperature. Sample solution (10 µL, 1.0 mg*mL<sup>− 1</sup> of each extract) was mixed with TRAP solution (990 µL), and the absorbance was measured after 50 s at 734 nm against the ABTS solution as the blank. The absorbance values were interpolated in a Trolox standard curve (0–120 mg*L<sup>− 1</sup>), and the TRAP values were expressed in mM Trolox equivalent antioxidant capacity (mM TEAC). All the measurements were replicated three times.</p>", "<title>Radical scavenging assays using DPPH●</title>", "<p id=\"Par15\">The DPPH assay was performed as described by Brand-Williams et al. (1995) [##UREF##11##26##] with minor modifications. The sample (100 µL, extracts at 0–10 mg*mL<sup>− 1</sup>) was mixed with a 50 µM DPPH● solution (2.9 mL) freshly prepared in ethanol. A 50 µM DPPH● solution (2.9 mL) with ethanol (0.1 mL) was used as the control. The samples and control solutions were incubated for 15 min at room temperature, and the absorbance was measured at 517 nm. The inhibition (%) was calculated employing the following equation:</p>", "<p id=\"Par16\">From the obtained Inhibition (%) values, the IC<sub>50</sub> value was determined by the dose-response equation.</p>", "<title>Hydrogen peroxide scavenging activity</title>", "<p id=\"Par17\">The ability of extracts to scavenge hydrogen peroxide can be estimated according to the method described by Ruch et al. (1989) [##REF##2470525##27##], with modifications. Hydrogen peroxide solution (40 mM) was prepared in 50 mM phosphate buffer (pH 7.4). Aliquots (0.1 mL) of different extracts were transferred into the test tubes, and their volumes were made up to 0.4 mL with phosphate buffer. After adding 0.6 mL hydrogen peroxide solution, tubes were vortexed, and after 10 min, the absorbance of the hydrogen peroxide was determined at 230 nm against a blank. The ability to scavenge hydrogen peroxide was calculated using the following equation:</p>", "<p id=\"Par18\">From the obtained Inhibition (%) values, the IC<sub>50</sub> value was determined by the dose-response equation.</p>", "<title>Ferric reducing antioxidant power (FRAP) assay</title>", "<p id=\"Par19\">With slight modifications, ferric reducing power was measured as described by Dudonné et al. (2009) [##REF##19199445##28##]. Freshly prepared TPTZ reactive (10 volumes of 300 mM acetate buffer, pH 3.6, with 1.0 volume of 10 mM TPTZ (2,4,6-tri(2-pyridyl)-s-triazine) in 40 mM hydrochloric acid, and 1.0 volume of 20 mM ferric chloride FRAP reagent (3.0 mL) was mixed with deionized water (300 µL) and the sample (100 µL, 1.0 mg*mL<sup>− 1</sup> of each extract). The mix was incubated for 30 min at 37 °C in a water bath, and the absorbance was measured at 593 nm using ethanol as the blank solution. The obtained absorbance values were interpolated in a Trolox calibrate curve (0–200 mg*L<sup>− 1</sup>), and the FRAP values were expressed in mM Trolox equivalent antioxidant capacity (mM TEAC). All the measurements were performed in triplicate.</p>", "<title>Chromatographic analysis</title>", "<p id=\"Par20\">The n-hexane (H), dichloromethane (D), ethyl acetate (A), and ethanol (E) extracts were diluted with chloroform, and analysis by gas chromatography (Hewlett Packard, Palo Alto, CA, USA) was carried out according to the method detailed elsewhere [##UREF##12##29##, ##REF##27809263##30##]. The operating conditions were as follows: on-column injection; injector temperature: 250 °C; detector temperature: 280 °C; carrier gas, He at 1.0 mL*min-1; oven temperature program: 40 °C increase to 260 °C at 4 °C *min-1, and then 260 °C for 5 min, to afford the best separation through a capillary Rtx-5MS column. Mass detector ionization employed an electron impact of 70 eV. Compounds in the chromatograms were identified by comparison of their mass spectra with those in the NIST/EPA/NIH Mass Spectral Library [##UREF##13##31##], following previous indications [##UREF##14##32##]. The retention indices were determined under the same operating conditions about a homologous n-alkanes series (C8–C36) by the equation:</p>", "<p id=\"Par21\">where n = the number of carbon atoms in the smaller n-alkane; N = the number of carbon atoms in the larger nalkane; and Tr = the retention time. Component relative concentrations were obtained by peak area normalization.</p>", "<title>Cultured cell lines</title>", "<p id=\"Par22\">The following experimental established cell lines were obtained from the American Type Culture Collection (Rockville, MD, USA): MCF-7 (human breast cancer; ATCC NO. HTB-22), HT-29 (human colon cancer; ATCC NO. HTB-38), PC-3 (human prostate cancer ATCC NO. CRL-1435) and HEK-293T (human embryonic kidney ATCC NO. CRL-3216). All cell lines were grown in a Dulbecco´s Modified Eagle Medium/Nutrient Mixture F-12 (DMEM-F12) containing 10% FCS, 100 U/mL penicillin, 100 µg*mL<sup>− 1</sup> streptomycin, and 1 mM glutamine. Cells were seeded into 96-well microliter plates at 100 µL, with 3 × 10<sup>3</sup> cells/well plating density. After a 24 h incubation at 37 °C (under a 5% humidified carbon dioxide ambient to allow cell attachment), cells were treated with different concentrations of extracts and incubated for 72 h under the same conditions. A stock solution of extracts was prepared in ethanol, and the final concentration of this solvent was kept constant at 1%. Control cultures received only 1% ethanol.</p>", "<title>In vitro cytotoxicity screening by using sulforhodamine B assay</title>", "<p id=\"Par23\">Sulforhodamine B (SRB) assay was used following the method of Skehan et al. (1990) [##REF##2359136##33##]. Cell density was determined using a microplate reader (wavelength 540 nm). Untreated cells were used as the negative control, while cells treated with doxorubicin (DOXO) were used as the positive control. In addition, all the samples were tested from 100 to 5 µg*mL<sup>− 1</sup> (concentration of extracts) using ethanol as the carrier solvent. All the measurements were replicated three times. Finally, Sigma Plot software was used to calculate the EC<sub>50</sub> value, and the selectivity index (SI) was calculated in the extracts with EC<sub>50</sub> ≤ 10 µg*mL<sup>− 1</sup>. The selectivity of each extract in each cell line was analyzed by calculating the selectivity index (SI) as EC<sub>50</sub> HEK-293T/ EC<sub>50</sub> cancer cell line. If the values of SI were equal to or greater than 2, it is said that the extract is selective [##REF##15878245##34##].</p>", "<title>Oxidative stress assays in cell lines</title>", "<p id=\"Par24\">Cells were seeded at 5 × 10<sup>5</sup> per well of 100 mm cell culture plates and incubated at 37 °C in a 5% humidified CO<sub>2</sub> ambient plus 95% air mixture per 72 h. Each cell line was treated with one of the extracts per 24 h, after which cells were washed three times with PBS 1X and detached with a 0.25% trypsin/EDTA (HyClone) solution for two minutes at 37 °C. Cells were then placed in a complete medium to inhibit the trypsin. Cells were then collected in sterile 15 mL tubes and centrifuged at 300 g for 10 min. The cell pellet was resuspended in lysis buffer (0.022 M Na<sub>2</sub>HPO<sub>4</sub>, 0.088 M NaH<sub>2</sub>PO<sub>4</sub>) diluted 1:15 in Milli Q and sonicated at 35 watts for the different oxidative stress assays. The enzymatic activity and protein oxidation were normalized by total protein (mg) [##REF##14907713##35##].</p>", "<title>Antioxidant defenses in cell lines exposed to extracts</title>", "<title>Superoxide dismutase (SOD) activity</title>", "<p id=\"Par25\">This assay was performed according to Beauchamp and Fridovich (1971) [##REF##4943714##36##], which is based on reducing cytochrome c by the superoxide radical in a xanthine/xanthine oxidase system. Briefly, 5 µL of cell lysates from different treatments was mixed with solution A, composed of 0.5 mM xanthine and 20 µM cytochrome c dissolved in a phosphate buffer (0.1 mM EDTA, 50 mM Na<sub>2</sub>HPO<sub>4</sub> and 50 mM NaH<sub>2</sub>PO<sub>4</sub>, pH 7.8) and a solution B containing xanthine oxidase and 0.1 mM EDTA (1:40). Enzymatic activity was detected at 550 nm in a spectrophotometer (RayLEIGH, UV-2601, China). The obtained absorbance values were interpolated in a SOD calibration curve (U enzyme) and normalized by protein mass (mg of protein). All the measurements were carried out in triplicate.</p>", "<title>Catalase (CAT) activity</title>", "<p id=\"Par26\">According to the methods described by Aebi (1984) [##UREF##15##37##], the activity of catalase was determined by spectrophotometrically measuring the loss of absorbance at 240 nm. of a reaction mixture consisting of 100 µL of 0.3 M H2O2 in 2.9 mL of phosphate buffer (50 mM Na2HPO4 and 50 mM NaH2PO4, pH 7.8) and 50 µL of cell lysates from different treatments. The measurement was performed for 90 s in a spectrophotometer (RayLEIGH, UV-2601, China). The obtained absorbance values were interpolated in a CAT calibration curve (U enzyme) and normalized by the protein mass (mg of protein). Each sample was analyzed in triplicate.</p>", "<title>Reduced glutathione /oxidized glutathione (GSH/GSSG) ratio assay</title>", "<p id=\"Par27\">GSH/GSS assay was performed as described in Rahman et al. (2006) [##REF##17406579##38##]. The assay is based on the reaction of GSH with DTNB (Ellman’s reagent), which produces the TNB chromophore; the latter has its maximal absorbance at 412 nm and oxidized glutathione–TNB adduct (GS–TNB). Briefly, cell lysates from different treatments were mixed with 3 mL of cold buffer (NaCl 0.15 M, Na2HPO4 0.01, NaH2PO4 0.01, pH 7.4) and centrifuged at 3000G for 15 min at 4 °C. The clear supernatant was used for the total GSH assay. The supernatant (100 µL treated with 2 µL 2-vinyl pyridine) was incubated at 37 °C with 700 µL of KPE buffer (0.1 M potassium phosphate buffer with 5 mM EDTA disodium salt, pH 7.5), 60 µL of 280 µM NADPH and 60 µL 10 mM DTNB (5,5’-dithio-bis (2-nitrobenzoic acid)) for 10 min at 30 °C to oxidize all GSH to GSSG. GSSG was then reduced by adding 60 µL GSH reductase. The rate of TNB formation was followed at 412 nm and was proportional to the sum of GSH and GSSG present. The rate was compared with a standard curve of GSH in buffer and normalized by protein mass (mg of protein). All the measurements were carried out in triplicate.</p>", "<title>Total reactive antioxidant power assay in cell lines (TRAPc)</title>", "<p id=\"Par28\">The same method that TRAP for extracts was used for cell lysate. One volume of 10 mM solution of ABAP (2,2′-azo-bis(2-amidino propane) was mixed with the same volume of 150 µM solution of ABTS (2,2′-azinobi(3-ethylbenzothiazoline-6-sulphonic acid) using PBS 100 mM at pH of 7.4 (TRAP solution). The mixture was incubated at 45 °C for 30 min and then cooled to room temperature. Cell lysate (10 µL) was mixed with the TRAP solution (990 µL), and the absorbance was measured after 50 s at 734 nm against the ABTS solution as the blank. The absorbance values were interpolated in a Trolox standard curve (0–120 mg*L<sup>− 1</sup>), and the TRAP values were expressed in mM Trolox equivalent antioxidant capacity (mM TEAC). All the measurements were replicated three times.</p>", "<title>Nrf2 and FOXO3a RT-qPCR</title>", "<p id=\"Par29\">According to the manufacturer’s recommendations, total RNA was extracted using TRIzol® RNA Isolation Reagent (Ambion, Thermo FisherScientific, Waltham, MA, USA). Template cDNA was obtained by reverse transcription of 1 µg of total RNA using iScript™ Reverse Transcription Supermix (Biorad, CA, USA). Reaction mixtures were incubated at 25° C for 5 min, 46° C for 20 min, and 95° C for 1 min.</p>", "<p id=\"Par30\">Relative quantification of gene expression levels for nuclear factor erythroid 2–related factor 2 (Nrf2) and transcription factor forkhead box O-3 a (FOXO3a) genes was carried out by real-time quantitative PCR (RT-qPCR) on CFX96 Touch™ Real-Time PCR system (Biorad, Hercules, CA, USA) using cDNA samples obtained as described before. For this purpose, SsoAdvanced Universal SYBR Green Supermix (Biorad, CA, USA) was used according to the manufacturer’s instructions. Specific primers were designed for the amplification of each gen. Nrf2-F: 5´CAACTACTCCCAGGTTGCCC-3´, Nrf2-R: 5´-AGTGACTGAAACGTAGCCGA-3´; Foxo3a-F: 5´-ACAAACGGCTCACTCTGTCC-3´, FOXO3a: 5´-GGATGGAGTTCTTCCAGCCG-3´. Gapdh-F: 5´-GAAGGTGAAGGTCGGAGTC-3´, Gapdh-R: 5´-GAAGATGGTGATGGGATTTC-3´. Comparative cycle threshold (Ct) values were obtained after the RT-PCR reaction was performed. All quantifications were normalized by the corresponding expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA that served as the normalizer gene. The relative quantification was performed using the 2-△△Ct method. RT-qPCR reactions were performed at least in triplicate.</p>", "<title>Oxidative damage and ROS in cell lines exposed to extracts</title>", "<title>Lipid peroxidation measurement</title>", "<p id=\"Par31\">Malondialdehyde (MDA), the primary marker in lipid peroxidation, was measured using the thiobarbituric acid reactive substances (TBARS) assay according to Esterbauer et al. (1982) [##REF##7159389##39##]. 1 mL of cell lysates from different treatments was treated with 30% (w/v) trichloroacetic acid (TCA) and centrifuged for 15 min at 3,000 RPM. Then, 1 mL of the supernatant was mixed with 0.67% (w/v) thiobarbituric acid (TBA). Samples were boiled for 20 min, and their absorbance spectrum was recorded at wavelengths between 400 and 600 nm using a UV–visible spectrophotometer (RayLEIGH, UV-2601, China). The concentration of the TBA-MDA adduct was determined by extrapolation from an MDA calibration curve. Each sample was analyzed in triplicate.</p>", "<title>Protein carbonyl content assay</title>", "<p id=\"Par32\">Based on the reaction of carbonyl groups generated by protein oxidation with 2-4-ditrophenylyidrazine, this assay was performed according to Levine et al. (1990) [##UREF##16##40##]. 10 µL of cell lysates from different treatments were treated with 20% (w/v) TCA on ice for 5 min and centrifuged for 15 min at 11,000 RPM. The pellet was suspended in 1 mL of 0.3% 2-4-ditrophenylyidrazine in 2 M HCl, vortexed, and left in darkness for 1 h, with periodic shaking. Then, 0.5 mL of 50% TCA was added while vortexing the sample, which was kept on ice for 5 min and centrifuged at 11,000 RPM for 5 min. The pellet was suspended in 1 mL ethanol: ethyl acetate (1:1), vortexed, and centrifuged at 11,000 RPM for 5 min. This procedure was repeated three times, and the pellet was later dried with N2 gas. After that, 2 mL of 6 M urea was added to the pellet, and the sample was incubated at 37 °C for 30 min. The reaction product was measured in a spectrophotometer (RayLEIGH, UV-2601, China) at 370 nm. The reaction product was measured at 370 nm. Each sample was analyzed in triplicate.</p>", "<title>Measurement of reactive oxygen species (ROS) production by flow cytometry</title>", "<p id=\"Par33\">Briefly, cells were treated with extracts (5, 10, and 25 µg*mL<sup>− 1</sup>) for 12 h. Untreated cells were used as the negative control, while cells treated with daunorubicin (DNR) 1 µM were used as the positive control. Intracellular ROS levels were visualized after incubation with 2’,7’-dichlorodihydro-fluorescein diacetate (DCFH<sub>2</sub>-DA) at a final concentration of 10 µM. The fluorescent dye was added for the last 30 min of the extract treatment period. After the incubation, cells were washed once in PBS, trypsinized, and centrifuged. The pellet was resuspended in PBS and examined immediately by flow cytometry [##REF##2159514##41##].</p>", "<title>Apoptosis in cell lines exposed to extracts</title>", "<title>Determination of mitochondrial potential (ΔΨmt) by flow cytometry</title>", "<p id=\"Par34\">Rhodamine 123 (Rho123), a cationic voltage-sensitive probe that reversibly accumulates in mitochondria, was used to detect changes in mitochondrial membrane potential [##REF##18079710##42##]. Cells were incubated with extracts (5, 10, and 25 µg*mL<sup>− 1</sup>) for 24 h. Untreated cells were used as the negative control, while cells treated with Carbonyl cya-nide-4-(trifluoromethoxy)phenylhydrazone (FCCP) 1 µM were used as the positive control. Subsequently, cells were stained with rhodamine 123 (1 µM) and incubated in darkness for 1 h at 37 °C. Then, the medium was removed, and cells were washed twice with PBS. Later, cells were trypsinized and collected by centrifugation (10 min at 1500G). The supernatant was discarded, and the cell pellets were resuspended in PBS and analyzed by flow cytometry using the FL1 filter. Results are expressed as a percentage of cells stained with Rho123.</p>", "<title>Determination of caspases activation by flow cytometry</title>", "<p id=\"Par35\">The activity of caspases was determined by using a fluorescent inhibitor of caspases tagged with fluorescein isothiocyanate, FITC-VAD-FMK. The CaspACE™ FITCVAD- FMK In Situ Marker was obtained from Promega. Briefly, cells were treated with extracts (5, 10, and 25 µg*mL<sup>− 1</sup>) for 48 h. Untreated cells were used as the negative control, while cells treated with daunorubicin (DNR) 1 µM were used as the positive control. Cells were incubated with CaspACE™ FITC-VAD-FMK in darkness for 20 min at room temperature. Then, the medium was removed, and cells were washed twice with PBS. Exposed cells were collected by trypsinization and centrifugation (10 min at 1500G). The supernatant was discarded, and cells were resuspended in PBS and analyzed by flow cytometry using the FL3 filter. Results are expressed as a percentage of cells stained with CaspACE™FITC-VADFMK [##REF##11980653##43##].</p>", "<title>Statistical analysis</title>", "<p id=\"Par36\">All data were reported as mean values ± standard deviation (SD). Due to non-parametric data, a Kruskal-Wallis ANOVA was used with a confidence level of 95% with STATISTICA 7.0 software.</p>" ]
[ "<title>Results</title>", "<p id=\"Par37\">The plant´s constituents extraction with increased polarity solvents (hexane (H), di-chloromethane (D), ethyl acetate (A), and ethanol (E)) resulted in 36 extracts, with 8 from <italic>E. illinita</italic> (4 from the stem and 4 from leaves), 8 from <italic>E. rubra</italic> (4 from the stem and 4 from leaves), 8 from <italic>E. revoluta</italic> (4 from the stem and 4 from leaves), and 12 from <italic>E. pulverulenta</italic> (4 from the stem, 4 from leaves and 4 from flowers).</p>", "<title>Phytochemical content and total antioxidant activity of extracts</title>", "<p id=\"Par38\">Once the extracts were obtained, the phytochemical content (i.e., total phenolic contents, flavonoids, and anthraquinone) was measured using colorimetric assays, as summarized in Table ##SUPPL##0##S1##. To highlight, total phenols and flavonoids showed significant differences in polar extracts (A, E) (<italic>p</italic> &lt; 0.05) when compared to nonpolar solvents (H, D). Further, <italic>E. pulverulenta</italic> showed the highest phenolic content in the ethanol extract from the leaves (E = 0.7015 ± 0.0203 mM GAE) and flowers (E = 0.6461 ± 0.0057 mM GAE) organs. On the other hand, <italic>E. illinita</italic> had the highest content of flavonoids in the dichloromethane extract (D = 0.6189 ± 0.0352 mM QE) and the ethylacetate extract (A = 0.7032 ± 0.0001 mM QE), both from leaves. Finally, it was determined that the highest content in total anthraquinones was found in the hexane extracts (H = 0.0597 ± 0.0006 mM EE) and in the dichloromethane extracts (D = 0.0648 ± 0.0007 mM EE) made from leaves of <italic>E. revoluta</italic>, and in the hexane extracts (H = 0.0769 ± 0.0002 mM EE) and the dichloromethane extract (D = 0.0660 ± 0.0004 mM EE) of <italic>E. rubra</italic>´s stem and leaves, respectively.</p>", "<p id=\"Par39\">The antioxidant activity of the extracts is summarized in Table ##SUPPL##0##S2##. Interestingly, for the TRAP assay, all the extracts were less active than the positive controls (Gallic acid (GA) and Butylhydroxytoluene (BHT), <italic>p</italic> &lt; 0.05). Yet, the ethanol extract from <italic>E. pulverulenta</italic>´s stem (E) shows the highest antioxidant capacity (<italic>p</italic> &lt; 0,05). Similarly, the DPPH• assay showed that all ethanolic extracts show significantly higher values than the rest of the extracts (<italic>p</italic> &lt; 0,05), especially in the ethanolic extract from the <italic>E. pulverulenta</italic>´s flower (E). However, none of the extracts had a better DPPH• scavenging capacity than reference antioxidant compounds (BHT and TROLOX®). In terms of the H<sub>2</sub>O<sub>2</sub> assay, it was found that the dichloromethane extracts from <italic>E. illinita</italic>´s stem (D) showed a significantly higher H<sub>2</sub>O<sub>2</sub> scavenger activity than the rest of the extracts (<italic>p</italic> &lt; 0,05). This extract has an improved H<sub>2</sub>O<sub>2</sub> scavenger capacity compared to the reference antioxidant compounds (BHT and TROLOX®). Finally, the FRAP assay showed that A and E extracts had better reduction antioxidant power than the other extracts (<italic>p</italic> &lt; 0.05), where the highest value was found in the ethanolic extract from <italic>E. pulverulenta</italic>´s leaves (0.00076 ± 0.00001 mM TEAC). Nonetheless, all the extracts were less active than the positive controls (GA and BHT, <italic>p</italic> &lt; 0.05). Therefore, it can be concluded that polar extracts have a higher concentration of phytoconstituents and higher total antioxidant capacity than the rest of the tested samples.</p>", "<title>In vitro cytotoxicity</title>", "<p id=\"Par40\">The cytotoxicity of the thirty-six extracts was evaluated in vitro against different cancer cell lines (HT-29, PC-3, MCF- 7, and HEK-293T), using a sulforhodamine B colorimetric assay, which was set up to obtain the EC<sub>50</sub> values of the tested extracts. Table ##TAB##0##1## shows the results of extracts with EC<sub>50</sub> values within the tested ranges.</p>", "<p id=\"Par41\">\n\n</p>", "<p id=\"Par42\">From Table ##TAB##0##1##, it is possible to identify that the EC<sub>50</sub> values ranged from 6.7 to 95.2 µg*mL<sup>− 1</sup> for the different cancer cell lines tested. Therefore, to continue with the study, the 6 extracts with the lowest EC<sub>50</sub> value (≤ 10 µg*mL<sup>− 1</sup>, highest cytotoxicity) were selected, and the selectivity index (SI) was calculated (Table ##SUPPL##0##S3##).</p>", "<p id=\"Par43\">Table ##SUPPL##0##S3## shows SI results for twenty Escallonia extracts, where only two extracts showed to act selectively against cancer cells; specifically, ethyl acetate extract from <italic>E. rubra</italic>´s stem (ErSA) was selective for prostate cancer cell line PC-3 (SI = 2.19) and hexane extract from <italic>E. pulverulenta</italic>´s stem (EpSH) was selective for colon cancer cell line HT-29 (SI = 2.31). Therefore, the research was followed, considering only these two extracts. Note that the SI values from the extracts were compared to the SI from doxorubicin (DOXO), a chemo-therapeutic used as a gold standard, which was selective for the three cancer cell lines, being their SI values for colon and breast cancer cell lines higher than any other SI from the extracts.</p>", "<title>Antioxidant defenses in cell lines exposed to extracts</title>", "<p id=\"Par44\">The two selected extracts (ErSA and EpSH) were used to analyze their impact on the oxidative stress in the cell lines employed (HEK-293T, HT-29, and PC-3). In this sense, the oxidative stress post exposition to the extracts was evaluated through the analysis of intracellular antioxidant defenses (SOD and Catalase enzymes activity, GSH/GSSG ratio, TRAP in cell, Nrf2 and FOXO3a transcription factors) and oxidative damage (lipid peroxidation, carbonyl formation, and ROS production).</p>", "<p id=\"Par45\">Related to the SOD and Catalase enzymatic activity (Figure ##SUPPL##0##S1##), the ErSA extract was selective for the PC-3 cell line showing a significant increase in SOD activity (Figure ##SUPPL##0##S1##c). On the other hand, ErSA and EpSH extracts were significantly more active for catalase on cancer cell lines than nontumor-treated cells (Figure ##SUPPL##0##S1## d, e, and f). Regarding the GSH/GSSG ratio, both extracts increased the ratio in HEK-293T, which indicates a reduction of oxidative stress (Figure ##SUPPL##0##S2##a). Further, the analysis of the antioxidant capacity in cells (TRAPc) showed that both extracts diminished TRAPc in HEK-293T, indicating a prooxidant effect (Figure ##SUPPL##0##S2##d). Also, the ErSA extract (selective for the PC-3 cell line) significantly reduced TRAPc, demonstrating a prooxidant effect (Figure ##SUPPL##0##S2##f).</p>", "<p id=\"Par46\">As enzymatic antioxidant defenses are increased, we studied the expression of transcription inducible factors, Nrf2 and FOXO3a, as regulator factors in the enzymatic response to ROS production (Fig. ##FIG##0##1##a-d). ErSA extract significantly increased the expression of both transcription factors in PC-3 cells (Fig. ##FIG##0##1##b and d), which is related to the increase in the activity of SOD and catalase in the same cell line (Figure ##SUPPL##0##S1##c and f) and reduced the expression of both factors in HEK-293T control cells. Meanwhile, EpSH extract did not affect the expression of Nrf2 and FOXO3a in HT-29 colon cancer cells and reduced the expression of both transcription factors in HEK-293T control cells (Fig. ##FIG##0##1##a and c).</p>", "<p id=\"Par47\">\n\n</p>", "<title>Oxidative damage and ROS level in cell lines exposed to extracts</title>", "<p id=\"Par48\">The oxidative damage in cell lines was evaluated by measuring lipid peroxidation and carbonyl concentration (Figure ##SUPPL##0##S3##a-f). The ErSA extract significantly increased the concentration of carbonyls in the PC-3 cell line, while no change was observed in HEK-293T control cells. On the other hand, EpSH extract showed increased carbonyl concentration and lipid peroxidation in HT-29 cells while reducing the lipid peroxidation in HEK-293T control cells.</p>", "<p id=\"Par49\">Interestingly, when the ROS levels in the cells were evaluated after exposure to the extracts, it was found that both ErSA and EpSH increased the ROS levels in PC-3 and HT-29 cells, respectively, similarly to the positive control daunorubicin (DNR, 1 µM). Further, ErSA extract generated ROS in the PC-3 cells and the control cell in a concentration-dependent manner, like the reference chemo-therapeutic used as a positive control (DNR) (Figs. ##FIG##1##2##b and ##SUPPL##0##S4##b). Nonetheless, for EpSH extract, the ROS level was significantly higher in HEK-293T than in HT-29 cells (Figs. ##FIG##1##2##a and ##SUPPL##0##S4##a).</p>", "<p id=\"Par50\">\n\n</p>", "<title>Apoptosis in cell lines exposed to the extracts</title>", "<p id=\"Par51\">It has been reported that cellular apoptosis activation could be associated with mitochondrial membrane potential and caspase activation through ROS levels [##REF##16247494##44##]. Therefore, the effect of EpSH and ErSA extracts on mitochondrial membrane potential (ΔΨmt) and caspase activation on the tested cell lines was assessed. As shown in Figs. ##FIG##1##2##c, d and ##SUPPL##0##S4##c, d, both extracts decreased the mitochondrial membrane potential in cancer cell lines (PC-3 and HT-29) in a dose-dependent manner, like the positive control. Furthermore, the ErSA extract also reduced the mitochondrial membrane potential at the highest concentration (25 µg*mL<sup>− 1</sup>) in non-tumoral HEK-293T cells, having no significant differences with PC-3 cells, suggesting a selective effect on the mitochondrial membrane potential. Related to the caspase activation, both extracts showed increased activation in the cancer cell lines, HT-29 and PC-3, indicating the apoptotic pathway activation (Figs. ##FIG##1##2##e, f, and ##SUPPL##0##S4##e,f). Both extracts showed increased caspase activity in the cancer cell lines HT-29 and PC-3, indicating the activation of the apoptotic pathway. On the one hand, ErSA extract significantly increased the caspase activity of the PC-3 cancer cell line without any other effect on nontumor HEK-293T cells. On the other, the impact of EpSH extract significantly increased the caspases activity at the highest concentration on HT-29 cells, leaving HEK-293T cells unaffected. Thus, it was observed that both extracts also promote a selective effect in terms of caspase activity. Therefore, summarizing, ErSA extract promotes an increase in ROS levels, decreasing the mitochondrial membrane potential and increasing caspase activity in PC-3 cells, showing a selective effect in caspase activation versus nontumor HEK-293T cells. Likewise, the EpSH extract increases the ROS levels, decreasing the mitochondrial membrane potential and increasing the caspase activity in HT-29 cells, where no similar effects were observed in the nontumor cell line, thus demonstrating a selective effect on HT-29 versus HEK-293T cells.</p>", "<title>Extract´s composition identification</title>", "<p id=\"Par52\">Based on the previous results, we were interested in identifying which compounds were present within the extracts and could be related to the observed data. In this way, GC-MS identification at the EpSH extract revealed the existence of six compounds, with 69.83% of the total sample amount previously reported with biological activity (Table ##SUPPL##0##S4##). The most abundant compounds within this sample correspond to alkanes, representing 40.92% of the full sample. On the other hand, ErSA extract has Lanosterol acetate triterpene as a majoritarian compound (99.9%; Table ##SUPPL##0##S5##). These triterpenes have been recently reported to possess anti-inflammatory and/ or antitumor activities [##UREF##17##45##].</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par53\">Complete extracts have been used as nutritional supplements and nutraceuticals because, generally, the effect is not generated with a single component but with a set of them, which can cause a synergic effect on specific biological targets [##REF##25214089##46##–##REF##22417416##48##]. In this context, Cho et al. (2011) previously mentioned that using sub-fractionated extracts with different solvents improves their bioactive properties by concentrating the phytoconstituents and, thus, enhancing their effects [##REF##25214089##46##]. In this way, once the solvent is evaporated, the obtained extract concentrates different phytocomponents, i.e., the hexane extraction solubilized lipophilic compounds as lipids and essential oils; the dichloromethane extraction solubilized terpenoids and sterols; the ethyl acetate extraction solubilized principally low molecular weight flavonoids as phenolic acids, flavonols, and anthocyanins; and finally, the ethanol extraction solubilized fundamentally polyphenols [##UREF##18##49##–##UREF##20##51##].</p>", "<p id=\"Par54\">Concerning those phytoconstituents presenting antioxidant capacity, there are not many studies in the Escallonia genus, but compared to the work carried out by Simirgiotis et al. (2012) [##UREF##21##52##], in our research, we got a higher concentration of phytoconstituents and an improved total antioxidant capacity. This may be due to the extraction method, the solvents, and/or the different organs used to obtain the extracts. Particularly in the extraction method, the SLE-UAE methodology (Solid liquid extraction-ultrasound-assisted extraction) used in this research has several advantageous properties: (1) selectivity in the extraction of bioactive compounds; (2) increased concentration of phytoconstituents with antioxidant capacity as polyphenols; (3) short time of extraction; (4) amelioration of extraction efficiency [##UREF##20##51##, ##REF##29692864##53##–##REF##27773280##55##]. Further, the plant´s separation by parts (organs) allows the obtention of different secondary metabolites [##UREF##10##24##].</p>", "<p id=\"Par55\">Among the 36 extracts analyzed, 20 had an EC<sub>50</sub> ≤ 10 µg*mL<sup>− 1</sup>. Manosroi et al. (2006) suggest that EC<sub>50</sub> values less than 125 µg*mL<sup>− 1</sup> might be potential candidates for developing anticancer therapeutic agents [##REF##15979235##56##]. Among these 20 extracts, only 2 were non-cytotoxic to our control nontumoral cancer cell line (HEK-293T). Further, selectivity is the essential feature of an effective anticancer drug [##UREF##23##57##], which can be obtained through the selectivity index (SI) and by comparing it against gold standard drugs (as in this work). Previous research has pointed out that a SI &gt; 2 is a promissory value [##REF##19661306##58##]. Then, considering the obtained extracts, both are good candidates for developing new drug therapies against cancer, where ErSA and EpSH show selectivity against PC-3 (prostate) and HT-29 (colon) cancer cell lines, respectively. Additionally, based on the obtained results, it is possible to establish both extracts’ oxidative stress action mechanism (selective oxycution), as shown in Fig. ##FIG##2##3##. As previously stated, ROS are implicated in various stages of cancer development [##REF##23123177##5##, ##REF##24287781##12##, ##UREF##24##59##–##REF##27277675##61##]. In this respect, cancer cells might be more sensitive to changes in redox homeostasis than normal cells due to changes in the production of ROS or the levels of antioxidant defenses, thus becoming a potential therapeutic target. Therefore, the ROS increase over basal levels can lead to a variation in the antioxidant defense efficiency and, consequently, selectively kill cancer cell lines without harming the normal cells through a phenomenon called “selective oxycution” [##REF##23123177##5##, ##UREF##1##9##, ##REF##24287781##12##, ##REF##19194462##62##].</p>", "<p id=\"Par56\">\n\n</p>", "<p id=\"Par57\">The GC-MS analysis allows us to identify the compounds within the two extracts to deepen our studies. Related to the ErSA extract, it is known that lanosterol modulates the immune response [##REF##28658622##63##], has an antiproliferative effect on daunorubicin-resistant leukemia cell line (CEM/R2) [##REF##26698156##64##], and can activate the antioxidant defenses through the Nrf2 transcription factor [##REF##28349780##65##], as the observed results for the ErSA extract in this work. On the other hand, regarding the EpSH extract, it has been previously described that eicosanes have antitumoral activity in different cancer cell lines [##REF##22619691##66##]. Also, the triacontanes present antibacterial, antidiabetic, and antitumoral activity [##UREF##25##67##, ##REF##31547263##68##]. Further, apigenin derivatives are related to antioxidant activity, promoting the Nrf2 expression and the increase in antioxidant enzymes (GSH-synthetase, catalase, and SOD) and the inhibition of ROS-producing enzymes as NOX [##REF##22864849##69##–##REF##27939619##71##]. Moreover, apigenin derivatives affect metastasis and angiogenesis in oral cancer [##REF##29434828##72##, ##REF##30875872##73##]. Additionally, ɣ-sitosterol is associated with cycle arrest and proapoptotic effect in breast and lung cancer cell lines [##REF##22440953##74##]. Finally, bisabolol derivatives have been described as antitumoral compounds, promoting ROS production and loss of mitochondrial integrity [##REF##19570051##75##] and decreasing cell proliferation and viability in pancreatic cancer cell lines [##REF##21883695##76##–##REF##28179305##78##]. This is similar to how EpSH extract affects the HT-29 cell line.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par58\">In summary, we have obtained 36 extracts with antioxidant capacity linked to their polar characteristic. Moreover, two extracts stand out with selective cytotoxicity for colon (HT-29) and prostate (PC-3) cancer cell lines. Further, both extracts showed “selective oxycution” effects, generating oxidative stress and activating regulated death pathways in cancer cell lines without affecting the control non-tumor cell line. These results indicate that ErSA and EpSH are potential candidates to develop further research against cancer; thus, future directions should be to employ more complex models, such as 3D cultures and animal models, allowing more evidence to be obtained for developing new therapeutic solutions against this pathology. Finally, our findings shed new light on the chemical and biological understanding of the ancestral native flora, a source of uncountable and unknown bioactive compounds.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Standard cancer treatments show a lack of selectivity that has led to the search for new strategies against cancer. The selective elimination of cancer cells modulating the redox environment, known as “selective oxycution”, has emerged as a viable alternative. This research focuses on characterizing the unexplored Escallonia genus plant extracts and evaluating their potential effects on cancer’s redox balance, cytotoxicity, and activation of death pathways.</p>", "<title>Methods</title>", "<p id=\"Par2\">36 plant extracts were obtained from 4 different species of the Escallonia genus (<italic>E. illinita</italic> C. Presl, <italic>E. rubra</italic> (Ruiz &amp; Pav.) Pers., <italic>E. revoluta</italic> (Ruiz &amp; Pav.) Pers., and <italic>E. pulverulenta</italic> (Ruiz &amp; Pav.) Pers.), which were posteriorly analyzed by their phytoconstituents, antioxidant capacity, and GC-MS. Further, redox balance assays (antioxidant enzymes, oxidative damage, and transcription factors) and cytotoxic effects (SRB, ∆Ψmt, and caspases actives) of those plant extracts were analyzed on four cell lines (HEK-293T, MCF-7, HT-29, and PC-3).</p>", "<title>Results</title>", "<p id=\"Par3\">36 plant extracts were obtained, and their phytoconstituents and antioxidant capacity were established. Further, only six extracts had EC<sub>50</sub> values &lt; 10 µg*mL<sup>− 1</sup>, indicating high toxicity against the tested cells. From those, two plant extracts were selective against different cancer cell lines: the hexane extract of <italic>E. pulverulenta</italic>´s stem was selective for HT-29, and the ethyl acetate extract of <italic>E. rubra</italic>´s stem was selective for PC-3. Both extracts showed unbalanced redox effects and promoted selective cell death.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">This is the first study proving “selective oxycution” induced by Chilean native plant extracts.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12906-024-04341-4.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>Conceptualization, CJG, and JV; funding acquisition, LM; investigation, CJG, CJJ, MPA, CH and CE; writing—original draft preparation, CJG, JV, MA, MP, MM; visualization, AM, IM, MA, LGGO; data curation and formal analysis, PS, PM, MA, LGGO; methodology, CJG and JV; supervision and project administration, JV and LM. All authors reviewed the manuscript.</p>", "<title>Funding</title>", "<p>This research was funded by Fondo Nacional de Desarrollo Científico y Tecnológico (1191763), Universidad de Valparaíso, for the grant CIDI (05/06).</p>", "<title>Data availability</title>", "<p>The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par61\">All methods were performed in accordance with the relevant guidelines and regulations.</p>", "<title>Consent for publication</title>", "<p id=\"Par62\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par59\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Relative expression of Nrf2 (<bold>a</bold>, <bold>b</bold>) and FOXO3a (<bold>c</bold>, <bold>d</bold>) in HEK-293T, HT-29, and PC-3 after treatment with ErSE and EpSH extracts. Cells were treated with the ErSE or EpsH extracts for 12 and 18 h (25 µg*mL<sup>− 1</sup>). Data were expressed as mean values ± standard deviation (<italic>n</italic> = 3). *# Different symbols correspond to significant differences between treatments concerning the negative control (C) per cell line (<italic>p</italic> &lt; 0,05). C = Negative Control; ErSE = ethyl acetate extract made from stems of <italic>E. rubra</italic>, selective for PC-3; EpSH = hexane extract made from stems of <italic>E. pulverulenta</italic>, selective for HT-29; C + = 5-Fluorouracil (6.5 µg*mL<sup>− 1</sup>, 50 µM)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>ROS production, loss of mitochondrial membrane potential (ΔΨmt), and caspases activity in nontumor (HEK-293T) and colon (HT-29) and prostate (PC-3) cancer cell lines after being exposed to three different concentrations (C1 = 5 µg*mL<sup>− 1</sup>, C2 = 10 µg*mL<sup>− 1</sup>, C3 = 25 µg*mL<sup>− 1</sup>) of EpSH and ErSA extracts, respectively. (<bold>a</bold>) and (<bold>b</bold>) Mean percentage of cells with ROS production. (<bold>c</bold>) and (<bold>d</bold>) Mean percentage of cells with ΔΨmt. (<bold>e</bold>) and (<bold>f</bold>) Mean percentage of cells with active caspases. For the ROS production, 1 µM daunorubicine (DRN) as a positive control (C+), for the mitochondrial membrane potential, 1 µM Carbonylcyanide-p-trifluoromethoxyphenylhydrazine (FCCP) as a positive control (C+), while 1 µM daunorubicin (DRN) was used as a positive control (C+) for caspase activation. The solvent control was 0.1% ethanol (CS) in all cases. <sup>A−E</sup> Different letters and <sup>*#+X</sup> symbols correspond to significant differences among treatments per cell line (<italic>p</italic> &lt; 0.05)</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Schematic summary of the main findings of this work. (<bold>a</bold>) ErSA selectivity for the prostate cancer (PC-3) cell line; and (<bold>b</bold>) EpSH extract selectivity for the colon cancer (HT-29) cell line. In both cases, when compared to the non-tumor cell line (HEK-293T). Symbols represent the obtained results compared to the control of each experiment; (=): no change compared with the control; Green arrow: increase compared with the control; Red arrow: decrease compared with the control; ROS: reactive oxygen species; TRAP: total reactive antioxidant power; MDA: lipoperoxidation (malondialdehyde); SOD: superoxide dismutase; CAT: catalase; GSH/GSSG: GSH/GSSG ratio; O<sub>2</sub>.-: superoxide radical; H<sub>2</sub>O<sub>2</sub>: hydrogen peroxide; H<sub>2</sub>O: wáter; ΔΨmt: mitochondrial membrane potential; Nrf2: nuclear factor erythroid 2–related factor 2; FOXO3a: transcription factor forkhead box O-3 a</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Effective mean concentration (EC<sub>50</sub>) of Escallonia extracts on nontumor (HEK-293T), breast cancer (MCF-7), colon cancer (HT-29), and prostate cancer (PC-3) cell lines</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Plant</th><th align=\"left\">Organ</th><th align=\"left\">Extract</th><th align=\"left\">MCF-7<break/>EC<sub>50</sub> (µg*mL<sup>− 1</sup>)</th><th align=\"left\">HT-29<break/>EC<sub>50</sub> (µg*mL<sup>− 1</sup>)</th><th align=\"left\">PC-3<break/>EC<sub>50</sub> (µg*mL<sup>− 1</sup>)</th><th align=\"left\">HEK-293T<break/>EC<sub>50</sub> (µg*mL<sup>− 1</sup>)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"2\">\n<italic>E. illinita</italic>\n</td><td align=\"left\" rowspan=\"2\">Stem</td><td align=\"left\">D</td><td align=\"left\">44.0401 ± 2.8211<sup>c</sup></td><td align=\"left\">24.9665 ± 3.0838<sup>c</sup></td><td align=\"left\">63.0176 ± 2.5672<sup>d</sup></td><td align=\"left\">22.7509 ± 1.5763<sup>c</sup></td></tr><tr><td align=\"left\">A</td><td align=\"left\">13.5532 ± 4.4832<sup>a</sup></td><td align=\"left\">34.6422 ± 4.7805<sup>c</sup></td><td align=\"left\">71.3293 ± 3.7622<sup>d</sup></td><td align=\"left\">18.6287 ± 4.4183<sup>b</sup></td></tr><tr><td align=\"left\" rowspan=\"5\">\n<italic>E. rubra</italic>\n</td><td align=\"left\" rowspan=\"3\">Stem</td><td align=\"left\">H</td><td align=\"left\">10.1507 ± 1.5942<sup>a</sup></td><td align=\"left\">9.3007 ± 2.9967<sup>a</sup></td><td align=\"left\">8.2581 ± 3.1385<sup>a</sup></td><td align=\"left\">13.9341 ± 1.9361<sup>a</sup></td></tr><tr><td align=\"left\">D</td><td align=\"left\">23.3823 ± 1.3818<sup>b</sup></td><td align=\"left\">19.9153 ± 5.1146<sup>b</sup></td><td align=\"left\">14.7452 ± 1.9173<sup>b</sup></td><td align=\"left\">11.6367 ± 5.1136<sup>a</sup></td></tr><tr><td align=\"left\">A</td><td align=\"left\">12.7918 ± 0.9803<sup>a</sup></td><td align=\"left\">26.375 ± 0.3326<sup>c</sup></td><td align=\"left\">6.7183 ± 2.7161<sup>a</sup></td><td align=\"left\">14.7107 ± 2.2366<sup>a</sup></td></tr><tr><td align=\"left\" rowspan=\"2\">Leaves</td><td align=\"left\">H</td><td align=\"left\">56.1876 ± 2.6042<sup>c</sup></td><td align=\"left\">15.2167 ± 1.5197<sup>d</sup></td><td align=\"left\">9.5785 ± 2.3736<sup>a</sup></td><td align=\"left\">10.2952 ± 2.2208<sup>a</sup></td></tr><tr><td align=\"left\">D</td><td align=\"left\">16.7674 ± 2.6103<sup>b</sup></td><td align=\"left\">25.0321 ± 6.5080<sup>c</sup></td><td align=\"left\">14.0886 ± 1.1765<sup>b</sup></td><td align=\"left\">11.3583 ± 2.5385<sup>a</sup></td></tr><tr><td align=\"left\" rowspan=\"3\">\n<italic>E. revoluta</italic>\n</td><td align=\"left\" rowspan=\"3\">Stem</td><td align=\"left\">H</td><td align=\"left\">39.7867 ± 3.1283<sup>c</sup></td><td align=\"left\">24.4083 ± 2.0075<sup>c</sup></td><td align=\"left\">79.3285 ± 1.2329<sup>d</sup></td><td align=\"left\">14.1480 ± 1.3285<sup>a</sup></td></tr><tr><td align=\"left\">D</td><td align=\"left\">18.3568 ± 1.8974<sup>b</sup></td><td align=\"left\">13.7411 ± 2.1074<sup>d</sup></td><td align=\"left\">14.7673 ± 4.1305<sup>b</sup></td><td align=\"left\">10.6601 ± 1.9422<sup>a</sup></td></tr><tr><td align=\"left\">A</td><td align=\"left\">22.5015 ± 4.4417<sup>b</sup></td><td align=\"left\">6.9845 ± 1.2959<sup>a</sup></td><td align=\"left\">10.7772 ± 0.6380<sup>a</sup></td><td align=\"left\">11.0185 ± 3.4961<sup>a</sup></td></tr><tr><td align=\"left\" rowspan=\"10\">\n<italic>E. pulverulenta</italic>\n</td><td align=\"left\" rowspan=\"3\">Stem</td><td align=\"left\">H</td><td align=\"left\">17.7417 ± 1.5066<sup>b</sup></td><td align=\"left\">7.5154 ± 1.9235<sup>a</sup></td><td align=\"left\">11.2879 ± 3.2494<sup>b</sup></td><td align=\"left\">17.3630 ± 8.3298<sup>b</sup></td></tr><tr><td align=\"left\">D</td><td align=\"left\">95.1946 ± 10.9158<sup>d</sup></td><td align=\"left\">24.3763 ± 2.4381<sup>c</sup></td><td align=\"left\">20.3552 ± 8.8824<sup>c</sup></td><td align=\"left\">12.0393 ± 1.7299<sup>a</sup></td></tr><tr><td align=\"left\">A</td><td align=\"left\">24.0417 ± 2.5179<sup>b</sup></td><td align=\"left\">23.9766 ± 1.0591<sup>b</sup></td><td align=\"left\">23.0374 ± 4.3020<sup>c</sup></td><td align=\"left\">11.8085 ± 1.8638<sup>a</sup></td></tr><tr><td align=\"left\" rowspan=\"3\">Leaves</td><td align=\"left\">H</td><td align=\"left\">20.3313 ± 1.6390<sup>b</sup></td><td align=\"left\">19.458 ± 2.0729<sup>b</sup></td><td align=\"left\">21.4674 ± 3.9661<sup>c</sup></td><td align=\"left\">32.1562 ± 14.5701<sup>d</sup></td></tr><tr><td align=\"left\">D</td><td align=\"left\">55.4643 ± 7.1389<sup>d</sup></td><td align=\"left\">13.6433 ± 1.9642<sup>d</sup></td><td align=\"left\">22.6237 ± 4.5147<sup>c</sup></td><td align=\"left\">13.9832 ± 0.8228<sup>a</sup></td></tr><tr><td align=\"left\">A</td><td align=\"left\">15.0914 ± 1.7535<sup>b</sup></td><td align=\"left\">22.9409 ± 9.5515<sup>b</sup></td><td align=\"left\">22.8511 ± 7.6715<sup>c</sup></td><td align=\"left\">18.0282 ± 2.5183<sup>b</sup></td></tr><tr><td align=\"left\" rowspan=\"4\">Flowers</td><td align=\"left\">H</td><td align=\"left\">15.4196 ± 2.8012<sup>a</sup></td><td align=\"left\">30.2962 ± 3.7342<sup>c</sup></td><td align=\"left\">18.5459 ± 2.5133<sup>c</sup></td><td align=\"left\">15.2301 ± 3.4980<sup>b</sup></td></tr><tr><td align=\"left\">D</td><td align=\"left\">9.3985 ± 1.8046<sup>a</sup></td><td align=\"left\">9.3284 ± 3.7723<sup>a</sup></td><td align=\"left\">8.6317 ± 2.9129<sup>a</sup></td><td align=\"left\">13.8068 ± 2.7420<sup>a</sup></td></tr><tr><td align=\"left\">A</td><td align=\"left\">19.7591 ± 4.4834<sup>b</sup></td><td align=\"left\">13.4092 ± 3.8624<sup>d</sup></td><td align=\"left\">19.5506 ± 3.8179<sup>c</sup></td><td align=\"left\">11.3231 ± 3.1435<sup>a</sup></td></tr><tr><td align=\"left\">E</td><td align=\"left\">15.9509 ± 2.2752<sup>a</sup></td><td align=\"left\">14.7024 ± 0.9387<sup>d</sup></td><td align=\"left\">20.5502 ± 4.7137<sup>c</sup></td><td align=\"left\">15.2715 ± 3.3880<sup>b</sup></td></tr></tbody></table></table-wrap>" ]
[ "<disp-formula id=\"Equ1\"><label>1</label><alternatives><tex-math id=\"M1\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{Inhibition}}\\,\\left( {\\text{\\% }} \\right)\\,{\\text{=}}\\,{\\text{100}}\\,{\\text{\\% }}\\, \\times \\,{\\text{((Acontrol}}\\, - \\,{\\text{Asample)}}\\,{\\text{/}}\\,{\\text{Acontrol)}}$$\\end{document}</tex-math></alternatives></disp-formula>", "<disp-formula id=\"Equ2\"><label>2</label><alternatives><tex-math id=\"M2\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${{\\text{H}}_{\\text{2}}}{{\\text{O}}_{\\text{2}}}\\,{\\text{Inhibition}}\\,\\left( {\\text{\\% }} \\right)\\,{\\text{=}}\\,{\\text{100}}\\,{\\text{\\% }}\\, \\times \\,{\\text{((Acontrol}}\\, - \\,{\\text{Asample)}}\\,{\\text{/}}\\,{\\text{Acontrol)}}$$\\end{document}</tex-math></alternatives></disp-formula>", "<disp-formula id=\"Equ3\"><label>3</label><alternatives><tex-math id=\"M3\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{RI}}\\,{\\text{=}}\\,{\\text{100}}\\, \\times \\,\\left( {{\\text{n}}\\,{\\text{+}}\\,{\\text{Tr}}\\,\\left( {{\\text{unknown}}} \\right)\\, - \\,{\\text{Tr}}\\,\\left( {\\text{n}} \\right)\\,{\\text{/}}\\,{\\text{Tr}}\\,\\left( {\\text{N}} \\right)\\, - \\,{\\text{Tr}}\\,\\left( {\\text{n}} \\right)} \\right)$$\\end{document}</tex-math></alternatives></disp-formula>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Data are expressed as mean values ± S.D. (<italic>n</italic> = 10)</p><p><sup>a-d</sup>Different letters correspond to significant differences among the extracts per cell line (<italic>p</italic> &lt; 0.05)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12906_2024_4341_MOESM1_ESM.docx\"><caption><p><bold>Supplementary Material 1: Supplementary Table S1.</bold> Phytoconstituents concentration per extract. <bold>Supplementary Table S2.</bold> Total antioxidant capacity per extract. <bold>Supplementary Table S3.</bold> Selectivity Index results. <bold>Supplementary Figure S1.</bold> Selected cells’ enzyme activities when exposed to selected extracts. <bold>Supplementary Figure S2.</bold> Reduced glutathione/oxidized glutathione ratio and cell total antioxidant capacity for selected cell lines when exposed to two extracts. <bold>Supplementary Figure S3.</bold> Oxidative damage measured through lipoperoxidation and carbonyl concentration for selected cell lines when exposed to two extracts. <bold>Supplementary Figure S4.</bold> Comparative histogram representing the number of events versus DCF, Rho123, and FITC-VAD-FMK fluorescence for selected cell lines when exposed to two extracts at different concentrations. <bold>Supplementary Table S4.</bold> GC-MS identification of EpSH. <bold>Supplementary Table S5.</bold> GC-MS identification of ErSE</p></caption></media>" ]
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Academic Press; 1990. pp. 464\u201378."]}, {"label": ["45."], "surname": ["Lima", "Medeiros"], "given-names": ["E", "J"], "article-title": ["Terpenoid compounds in the latex of Euphorbia Azorica from Azores"], "source": ["Biomed J Sci & Tech Res"], "year": ["2020"], "volume": ["26"], "issue": ["1"], "fpage": ["19680"], "lpage": ["2"]}, {"label": ["49."], "surname": ["Seidel", "Sarker", "Nahar"], "given-names": ["V", "SD", "L"], "article-title": ["Initial and bulk extraction of Natural products isolation"], "source": ["Natural products isolation"], "year": ["2012"], "publisher-loc": ["Totowa, NJ"], "publisher-name": ["Humana Press"], "fpage": ["27"], "lpage": ["41"]}, {"label": ["50."], "surname": ["Azmir", "Zaidul", "Rahman", "Sharif", "Mohamed", "Sahena"], "given-names": ["J", "ISM", "MM", "KM", "A", "F"], "article-title": ["Techniques for extraction of bioactive compounds from plant materials: a review"], "source": ["J Food Eng"], "year": ["2013"], "volume": ["117"], "issue": ["4"], "fpage": ["426"], "lpage": ["36"], "pub-id": ["10.1016/j.jfoodeng.2013.01.014"]}, {"label": ["51."], "surname": ["Ko\u00e7ak", "Paz\u0131r"], "given-names": ["E", "F"], "article-title": ["Effect of extraction methods on Bioactive compounds of Plant Origin"], "source": ["Turkish J Agriculture-Food Sci Technol"], "year": ["2018"], "volume": ["6"], "issue": ["6"], "fpage": ["663"], "lpage": ["75"], "pub-id": ["10.24925/turjaf.v6i6.663-675.1527"]}, {"label": ["52."], "surname": ["Simirgiotis", "Silva", "Becerra", "Schmeda-Hirschmann"], "given-names": ["MJ", "M", "J", "G"], "article-title": ["Direct characterisation of phenolic antioxidants in infusions from four Mapuche medicinal plants by liquid chromatography with diode array detection (HPLC-DAD) and electrospray ionisation tandem mass spectrometry (HPLC-ESI\u2013MS)"], "source": ["Food Chem"], "year": ["2012"], "volume": ["131"], "issue": ["1"], "fpage": ["318"], "lpage": ["27"], "pub-id": ["10.1016/j.foodchem.2011.07.118"]}, {"label": ["54."], "surname": ["Barba", "Zhu", "Koubaa", "Sant\u2019Ana", "Orlien"], "given-names": ["FJ", "Z", "M", "AS", "V"], "article-title": ["Green alternative methods for the extraction of antioxidant bioactive compounds from winery wastes and by-products: a review"], "source": ["Trends Food Sci Technol"], "year": ["2016"], "volume": ["49"], "fpage": ["96"], "lpage": ["109"], "pub-id": ["10.1016/j.tifs.2016.01.006"]}, {"label": ["57."], "mixed-citation": ["Lopez-Lazaro M. Experimental cancer pharmacology for researchers: at what concentration should my drug kill cancer cells so that it has potential for cancer therapy? Amazon Digital Services. Inc ASIN: B00MMO25NM ed. 2014."]}, {"label": ["59."], "surname": ["Liu", "Wang"], "given-names": ["J", "Z"], "article-title": ["Increased oxidative stress as a selective anticancer therapy"], "source": ["Oxidative Med Cell Longev"], "year": ["2015"], "volume": ["2015"], "fpage": ["294303"], "pub-id": ["10.1155/2015/294303"]}, {"label": ["67."], "surname": ["Xu", "Han", "Li", "Chen", "Wang", "Zhao"], "given-names": ["J", "Q-B", "S-L", "X-J", "X-N", "Z-Z"], "article-title": ["Chemistry, bioactivity and quality control of Dendrobium, a commonly used tonic herb in traditional Chinese medicine"], "source": ["Phytochem Rev"], "year": ["2013"], "volume": ["12"], "issue": ["2"], "fpage": ["341"], "lpage": ["67"], "pub-id": ["10.1007/s11101-013-9310-8"]}]
{ "acronym": [], "definition": [] }
78
CC BY
no
2024-01-14 23:43:46
BMC Complement Med Ther. 2024 Jan 13; 24:38
oa_package/c5/a1/PMC10787448.tar.gz
PMC10787449
38216987
[ "<title>Background</title>", "<p id=\"Par17\">The number of published scientific papers is constantly increasing [##UREF##0##1##, ##UREF##1##2##]. Consequently, it is becoming more challenging for end-users to distinguish between high-quality, relevant literature, and research waste which is redundant and irrelevant [##UREF##2##3##]. Furthermore, conducting redundant research is unethical and wastes human and financial resources [##REF##33115456##4##]. In the field of physiotherapy research, redundant studies are still being carried out. One example is research into the effects of exercise in patients with knee osteoarthritis. Although previous trials and a series of Cochrane reviews have shown and summarised the benefits of exercise [##UREF##3##5##–##UREF##5##7##], research on a similar topic is still ongoing [##UREF##6##8##].</p>", "<p id=\"Par18\">To counteract research waste and to conduct research in a transparent manner, the Evidence-Based Research (EBR) approach was developed [##UREF##7##9##, ##REF##32979491##10##]. It states that new research should be justified by a systematic review (SR) of the existing literature and that the results of a new study should be discussed in the context of a SR [##UREF##7##9##]. According to the EBR Network a SR is defined as “a structured and preplanned synthesis of original studies that consists of predefined research questions, inclusion criteria, search methods, selection procedures, quality assessment, data extraction, and data analysis” [##UREF##8##11##]. The EBR approach has been shown to be able to reduce research waste to some extent [##REF##32987159##12##]. However, its use in general medicine [##REF##36315526##13##–##REF##21200038##17##] or physiotherapy and rehabilitation research is questionable [##REF##28747106##18##].</p>", "<p id=\"Par19\">Among others, scientific medical journals are relevant stakeholders in implementing the EBR approach [##UREF##7##9##, ##REF##28747106##18##] as they play an important role in avoiding research waste [##REF##19525005##19##, ##UREF##9##20##]. Scientific medical journals could for instance require their authors to justify new trials through SRs. Such recommendations apply to general medicine but are also relevant to physiotherapy. Most physiotherapy research is based on randomised controlled trials (RCTs) involving patients [##REF##28747106##18##], some of whom receive unnecessary treatment if previous trials have already shown the effects of a particular intervention and there is no question of clinical equipoise.</p>", "<p id=\"Par20\">According to Ioannidis, meta-research is the study of research itself: its methods, reporting, reproducibility, evaluation and incentives [##REF##29534060##21##]. The aim of this meta-research study was to determine the extent to which physiotherapy-related scientific medical journals (PTJs) require the use of SRs for the study rationale in their author guidelines for RCTs and compare them with the author guidelines of scientific medical journals with a high impact factor in the Science Citation Index Extended (SCIE), hereafter referred to as leading journals (LJs). The comparison with LJs places the publication practices of PTJs in the current context of academic methodology, modeled on journals with potentially the highest scientific quality and relevance to their specific field. It was hypothesised that PTJs would be less likely to require the use of SRs to justify a new trial than LJs.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par21\">In this meta-research study, i.e. study on research practice, author guidelines for RCTs of PTJs and LJs were systematically reviewed. PTJs were defined as journals publishing RCTs relevant to physiotherapy. To identify PTJs, three strategies were combined.</p>", "<p id=\"Par22\">As a first strategy, the PEDro database [##UREF##10##22##], which specialises in the publication of research relevant to physiotherapy, was accessed. All clinical trials referenced and published in the last five years (between January 2016 and August 2021) were extracted and organised by the journal in which they were published using an automated Microsoft Excel (version 16.70) macro tool. Journals were then ranked by the number of publications and included if at least 22 publications, including one RCT, were referenced. The cut-off was set at 22 publications because journals were only considered relevant to physiotherapy if at least one physiotherapy-related study was published every three months. As no standard procedure on this behalf is known to the authors, this cut-off was also determined for feasibility reasons.</p>", "<p id=\"Par23\">As a second strategy, the Medline database [##UREF##11##23##] was searched via PubMed using the terms: ‘physiotherapy’ OR ‘physical therapy’ and the filters ‘humans’, ‘clinical trial’, and ‘RCT’. Studies were extracted and organised using the aforementioned Excel macro tool and journals were included using the same cut-off of 22 physiotherapy-related studies.</p>", "<p id=\"Par24\">Furthermore, another list was compiled of all journals in the rehabilitation category of the SCIE database [##UREF##12##24##], with an impact factor of at least 1.0. regardless of their number of publications in PEDro [##UREF##10##22##] or PubMed [##UREF##11##23##]. Journals in the categories ‘Sports Science’ and ‘Orthopaedics’ which are closely related to physiotherapy and rehabilitation research, were added to this list if at least 10 publications, were referenced in PEDro [##UREF##10##22##] or PubMed [##UREF##11##23##] according to the above criteria. The cut-off was set lower for these three categories as they were considered relevant to physiotherapy research but not expected to publish only studies with physiotherapy as a keyword.</p>", "<p id=\"Par25\">All included journals were combined into a final list and duplicates were removed. The final list was then compared with 25 LJs. These were defined as the 25 journals with the highest impact factor in the Journal Citation Reports (JCR) in the SCIE and therefore can be considered the most influential journals in medical science. The filter ‘Clinical Medicine’ was applied in order to exclude scientific medical journals that are concerned with basic sciences.</p>", "<p id=\"Par26\">A data extraction protocol was used in accordance with the EBR criteria to systematically search the websites of the journals. One researcher (DR) identified their publication guidelines by searching the homepage using the following search terms: ‘author guidelines’, ‘information for authors’, ‘submission guidelines’, ‘reporting guidelines’, ‘submission checklist’, ‘for authors’, and ‘about’. In the identified section, it was determined whether journals required the use of SRs to justify a new study, whether appropriate background was required, whether no background was mentioned, or whether the journal explicitly stated that no systematic review of the literature was needed. In case of uncertainty, a second researcher (RP) verified the findings.</p>", "<p id=\"Par27\">Additionally, it was assessed if journals referred to other reporting standards that require an appropriate background. These were referrals to the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network, the International Committee of Medical Journal Editors (ICMJE), the Consolidated Standards of Reporting Trials (CONSORT), or the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists [##UREF##13##25##–##REF##23295957##28##].</p>", "<p id=\"Par28\">The following terms were searched: ‘background’, ‘rationale’, ‘intro’, ‘reporting’, ‘systematic review’, ‘consort’, ‘spirit’, ‘equator’, ‘icmje’, ‘international’. The results for the two groups, PTJs, and LJs, were then compared.</p>" ]
[ "<title>Results</title>", "<p id=\"Par29\">According to the search strategy, 12,233 clinical trials which were published in 2024 journals were identified via the PEDro database and 21,197 clinical trials which were published in 1,994 journals were identified via PubMed. With the cut-off set at 22 publications, 112 journals were identified via the PEDro database, and 101 journals were identified via PubMed. According to the inclusion criteria, the search of the SCIE database resulted in 42 extracted PTJs. After removing duplicates, the final list contained 152 PTJs.</p>", "<p id=\"Par30\">Three PTJs were excluded from the analysis. One because it was not actively publishing anymore, and two because they published in languages other than German or English. Eleven of the 25 LJs were excluded as they did not publish RCTs. Therefore, after exclusion, in total, 149 PTJs were compared with 14 LJs. PTJs cover a broad range of journals, varying in impact factor (from 0.519 to 9.139) as well as in the SCIE category with most journals belonging to the category ‘Orthopedics’ (<italic>n</italic> = 18). The full list can be found in Additional file ##SUPPL##0##1##. The journal selection process is illustrated in Fig. ##FIG##0##1##.</p>", "<p id=\"Par31\">None of the PTJs required an SR for the study rationale in their author guidelines. Four of the LJs (28.57%), all associated with The Lancet group [##UREF##16##29##], required a prior SR of the literature. The journals are: 'The Lancet’, ‘Lancet Oncology’, ‘Lancet Diabetes &amp; Endocrinology’, as well as ‘Lancet Respiratory Medicine’. As shown in Table ##TAB##0##1##, an appropriate background was required in 20.13% of the PTJs and 21.43% of the LJs. These included journals within the SAGE publishing group [##UREF##17##30##] and Frontiers journals, which implemented a specific guideline known as VALID, where ‘D’ represents the requirement for grounding studies in existing literature through sufficient referencing and appropriate coverage of relevant literature [##UREF##18##31##]. The majority, 79.87% of PTJs and 50% of all LJs examined, either did not require a literature-based background or explicitly discouraged authors from using SRs to provide a rationale for the study. No specific reason was given by these journals, most of which are part of the Elsevier publishing group [##UREF##19##32##]. Most of the PTJs (74.50%) and the LJs (92.86%) refer to the reporting standards CONSORT or SPIRIT.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par32\">The primary finding of this study is that the examined PTJs and LJs rarely require the use of SRs for the justification of new trials. The majority of journals analysed refer to reporting standards such as CONSORT or SPIRIT. The CONSORT statement calls for an \"adequate background\" for the rationale of new clinical trials and also states that trials should “include a reference to a systematic review of previous similar trials or a note of the absence of such trials” [##UREF##20##33##].</p>", "<p id=\"Par33\">However, as described in the introduction, a large number of studies show that SRs are rarely used to develop study rationales [##REF##36315526##13##–##REF##21200038##17##]. In physiotherapy and rehabilitation research, this applies to only one-third of all studies reviewed [##REF##28747106##18##].</p>", "<p id=\"Par34\">Simply referring to reporting standards such as CONSORT, without explicitly requiring reference to SRs in the author guidelines, does not appear to be sufficient to encourage authors to comply and use SRs in their study justification. Clear requirements in author guidelines, such as those used by The Lancet, may be more likely to result in compliance with the methods described.</p>", "<p id=\"Par35\">The EBR Statement requires the justification of new research with a systematic review of the existing literature, placing new results in the context of the existing literature, and including the end-users’ perspective [##UREF##7##9##, ##REF##32979491##10##, ##REF##32979490##34##]. According to the EBR Statement, relevant stakeholders have different responsibilities in the research process [##UREF##7##9##]. While researchers should be able to prioritise research questions, taking into account all previous and ongoing research on the topic, and know how to find, evaluate and develop SRs, editors and journals should assess and evaluate whether the research is adequately described in the context of a SR [##UREF##7##9##]. Problems with placing current clinical research in the context of previous findings may indicate that editors and journals are not assessing the submitted papers critically enough and against the specifications of the author guidelines or their selected referrals to reporting standards like the CONSORT statement.</p>", "<p id=\"Par36\">Although several studies show that new clinical trials are not adequately referencing SRs, multiple meta-research studies show a significant increase in the total number of SRs conducted [##REF##27620683##35##–##REF##36064610##37##]. Hoffmann et al. 2021 describe a 20-fold increase in SRs from 2000 to 2019 which also plays an important role in the production of research waste. According to Ioannidis, masses of unnecessary, misleading and contradictory SRs are being published which are unable to provide an accurate assessment of the current state of research, again highlighting the importance of knowing how to critically appraise SRs [##REF##27620683##35##].</p>", "<p id=\"Par37\">This difficulty is particularly important in physiotherapy, where progress in different areas of research is uneven. While in some areas like osteoarthritis research, a series of Cochrane reviews indicate that no further research on the effects of exercise is needed [##UREF##3##5##–##UREF##6##8##], there are multiple areas where there is hardly any data or high-quality studies yet [##UREF##21##38##–##UREF##23##41##].</p>", "<p id=\"Par38\">A strength of this meta-research study is that author guidelines were systematically screened and journals were selected in a transparent manner. A limitation of this study is that only 149 PTJs were examined, so it is possible that not all journals potentially relevant to physiotherapy were captured. Also, PTJs were not included if they did not meet the cut-off of 22 publications. Thereby, journals with a low publication rate in other physiotherapy-related SCIE categories, such as ‘Rheumatology’, might not have been captured. Furthermore, the quality of the underlying publications was not determined which could induce a bias to the relevance of certain journals to physiotherapy.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par39\">Based on the findings of this study, scientific medical journals do not require their authors explicitly in their author guidelines to base a new trial on an existing SR. The majority of the analysed journals refer to the CONSORT statement which requires the use of SRs for the study justification. Only journals associated with The Lancet explicitly require the use of SRs in their author guidelines. With regard to the hypothesis of this study, it can be concluded that PTJs require the use of SRs for the study justification less than LJs. The results of this work show that PTJs rely on checklists such as the CONSORT statement instead of demanding the legitimisation of new studies through a SR of the existing literature. This potentially leaves room for unethical scientific practices and should be critically considered in future research.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Requiring authors to base their research on a systematic review of the existing literature prevents the generation of redundant scientific studies, thereby avoiding the deprivation of effective therapies for trial participants and the waste of research funds. Scientific medical journals could require this in their author guidelines. While this applies to all areas of research, it is also relevant to physiotherapy and rehabilitation research, which predominantly involve interventional trials in patients.</p>", "<title>Objective</title>", "<p id=\"Par2\">The aim of this study was to determine the extent to which the use of systematic reviews to justify a new trial is already being requested by physiotherapy-related scientific medical journals (PTJs). In addition, a comparison was made between PTJs and scientific medical journals with the highest impact factor in the Science Citation Index Extended (SCIE).</p>", "<title>Methods</title>", "<p id=\"Par3\">This meta-research study is based on a systematic examination of the author guidelines of 149 PTJs. The journals were identified and included based on the number of publications with physiotherapy as a keyword in the databases PEDro, and Medline (Pubmed). The included author guidelines were analysed for the extent to which they specified that a new trial should be justified by a systematic review of the literature. Additionally, they were compared with 14 scientific medical journals with the highest impact factor in the SCIE (LJs).</p>", "<title>Results</title>", "<p id=\"Par4\">In their author guidelines, none of the included PTJs required or recommended the use of a systematic review to justify a new trial. Among LJs, four journals (28.57%), all associated with the Lancet group, required the study justification through a systematic review of the literature.</p>", "<title>Conclusion</title>", "<p id=\"Par5\">Neither PTJs nor LJs require or recommend the use of a systematic review to justify a new trial in their author guidelines. This potentially leaves room for unethical scientific practices and should be critically considered in future research.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13643-023-02427-7.</p>", "<title>Keywords</title>", "<p>Open Access funding enabled and organized by Projekt DEAL.</p>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank Stefan Rosen for the coding of the Microsoft Excel (Version 16.70) Macro Tool.</p>", "<title>Authors’ contributions</title>", "<p>DR and RP had the idea for this work. DR, BV, and RP elaborated the methods for this study. DR analysed and interpreted the data. DR drafted the manuscript. NLR and RP were major contributors to writing the manuscript. All authors read and approved the final manuscript.</p>", "<title>Authors’ information</title>", "<p id=\"Par40\">Diane Rosen</p>", "<p id=\"Par41\">• Core staff at Evidence-Based Practice in Brandenburg - A JBI Affiliated Group at Brandenburg Medical School Theodor Fontane, Brandenburg a.d.H., Germany</p>", "<p id=\"Par42\">• Research Assistant at Alice Salomon University of Applied Sciences Berlin, Berlin, Germany</p>", "<p id=\"Par43\">• Master Student at Berlin School of Public Health, Berlin, Germany</p>", "<p id=\"Par44\">Nils L. Reiter</p>", "<p id=\"Par45\">• Research Associate at Alice Salomon University of Applied Sciences Berlin, Berlin, Germany</p>", "<p id=\"Par46\">Dr. Barbara Vogel, MPH</p>", "<p id=\"Par47\">• Senior physiotherapist, Physical Therapy, Department of Orthopedics and Sports Orthopedics, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany</p>", "<p id=\"Par48\">Dr. Robert Prill</p>", "<p id=\"Par49\">• Head of Research/Center of Orthopedics and Traumatology/Center for Joint Replacement West-Brandenburg/Center of Physiotherapy at University Hospital Brandenburg/Havel, Brandenburg a.d.H, Germany</p>", "<p id=\"Par50\">• Director of Center of Evidence Based Practice Brandenburg JBI Affiliated Group, Brandenburg Medical School Theodor Fontane, Brandenburg a.d.H., Germany</p>", "<p id=\"Par51\">• Member of the Scientific Medical Journals (SMJ) working group EVBRES Cost Action CA17117</p>", "<title>Funding</title>", "<p>Open Access funding enabled and organized by Projekt DEAL. Funded by the Brandenburg Medical School publication fund supported by the German Research Foundation and the Ministry of Science, Research and Cultural Affairs of the State of Brandenburg.</p>", "<title>Availability of data and materials</title>", "<p>The exact results of this study are shown in the supplements.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par52\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par53\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par54\">Robert Prill was a member of the EU fundet project: COST Action CA17117 EVBRES and is Director of the Center of Evidence Based Practice in Brandenburg - A JBI Affiliated Group, which both promote the EBR Approach.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow chart for the journal selection process</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Results</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Category</th><th align=\"left\" rowspan=\"2\"/><th align=\"left\">PTJs <italic>n</italic>(%)</th><th align=\"left\">LJs <italic>n</italic>(%)</th><th align=\"left\">Overall <italic>n</italic>(%)</th></tr><tr><th align=\"left\">149 (100)</th><th align=\"left\">14 (100)</th><th align=\"left\">163 (100)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"4\">SR in rationale</td><td align=\"left\">SR in rationale is required</td><td align=\"left\">0 (0)</td><td align=\"left\">4 (28.57)</td><td align=\"left\">4 (2.45)</td></tr><tr><td align=\"left\">Appropriate background needed</td><td align=\"left\">30 (20,13)</td><td align=\"left\">3 (21.43)</td><td align=\"left\">33 (20.25)</td></tr><tr><td align=\"left\">State nothing regarding background</td><td align=\"left\">103 (69,13)</td><td align=\"left\">6 (42.86)</td><td align=\"left\">109 (66.87)</td></tr><tr><td align=\"left\">Explicitly no systemic review of the literature is needed</td><td align=\"left\">16 (10,74)</td><td align=\"left\">1 (7.14)</td><td align=\"left\">17 (10.43)</td></tr><tr><td align=\"left\" rowspan=\"2\">Reporting standard</td><td align=\"left\">Refer to CONSORT or SPIRIT or both</td><td align=\"left\">111 (74,50)</td><td align=\"left\">13 (92.86)</td><td align=\"left\">124 (76.07)</td></tr><tr><td align=\"left\">Do not refer to a reporting standard</td><td align=\"left\">38 (25,5)</td><td align=\"left\">1 (7.14)</td><td align=\"left\">39 (23.93)</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Data are presented as the number of journals in the indicated category, which comply with the findings in <italic>n</italic> (%)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13643_2023_2427_Fig1_HTML\" id=\"MO1\"/>" ]
[ "<media xlink:href=\"13643_2023_2427_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1.</bold> Table with full data of results.</p></caption></media>" ]
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2024-01-14 23:43:46
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PMC10787450
0
[ "<title>Introduction</title>", "<p id=\"Par27\">Chronic total occlusion (CTO) of the coronary arteries is defined as a lesion in which a coronary artery is completely occluded for at least 3 months [##REF##16216980##1##]. One study [##REF##27561190##2##] reported that the prevalence of CTO in patients who underwent coronary angiography (CAG) to confirm the diagnosis of coronary artery disease was 20%. Percutaneous coronary intervention (PCI) in patients with CTO has a low success rate, a high risk of procedural complications, a long and costly procedure time, and unclear clinical benefits relative to patients without CTO [##REF##32417095##3##, ##REF##21518991##4##]. Previous studies have shown [##REF##23739241##5##–##REF##8213453##7##] that good coronary collateral circulation (CCC) reduces infarct size after acute myocardial infarction, decreases the risk of post-infarction complications, reduces the number of angina episodes, and decreases cardiovascular and all-cause mortality. Although the severity of coronary artery lesions is similar in different CTO patients, the severity of the disease is not identical, which may be related to the degree of CCC formation [##REF##21969521##8##]. Currently, assessment of CCC formation in patients with CTO relies on invasive CAG, noninvasive assessment methods are complex and expensive to perform, and there is a lack of simple and easy predictive assessment indexes [##REF##20855668##9##]. Therefore, there is a need to find a simple and effective biomarker to assess or predict CCC formation.</p>", "<p id=\"Par28\">Insulin resistance (IR) has been shown to be an independent risk factor for poor collateral circulation formation [##REF##19164335##10##]. Insulin resistance can be assessed by a variety of metrics, such as fasting insulin levels, normoglycemic clamp method, and homeostasis model assessment-IR (HOMA-IR) in vivo [##REF##21435930##11##–##REF##16278749##13##], however, these metrics are not routinely measured in clinical practice, especially in nondiabetic patients. The triglyceride glucose (TyG) index, calculated from the combination of fasting glucose and triglycerides, has been recognized as a novel biomarker of insulin resistance [##REF##19067533##14##]. Wu et al. [##REF##35906587##15##] confirmed that TyG index can predict the occurrence of early-onset coronary heart disease adverse cardiovascular events. Furthermore, a meta-analysis [##REF##33812373##16##] showed that TyG index is significantly associated with the risk of coronary artery disease and stroke. A high TyG index is also positively associated with carotid plaque load in individuals with prediabetes (Pre-DM) and new-onset type 2 diabetes mellitus (DM) [##REF##35310963##17##]. Meanwhile, Liu et al. [##REF##37179288##18##] found that TyG index is associated with arterial stiffness and coronary artery calcification. Based on these observations, it is hypothesized that as a novel marker for assessing insulin resistance, TyG index may be associated with CCC formation in patients with CTO. Currently, there are limited studies on the correlation between TyG index and CCC formation in patients with CTO. Gao et al. [##REF##34689767##19##] initially investigated the correlation between TyG index and collateral circulation in patients with CTO, but no studies have explored the correlation between TyG index and collateral circulation in CTO patients under different glucose metabolic states, even though TyG index is closely related to glucose metabolism. In this study, we aimed to investigate, for the first time, the correlation between TyG index and collateral circulation in CTO patients at different glucose metabolic states.</p>" ]
[ "<title>Methods</title>", "<title>Study design and population</title>", "<p id=\"Par29\">Study participants included 681 patients who were hospitalized in the Department of Cardiovascular Medicine of the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2021 and underwent coronary angiography (CAG), with at least one major epicardial coronary artery CTO lesion identified by angiographic results (Fig. ##FIG##0##1##). The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University, and written informed consent was obtained from all participants.</p>", "<p id=\"Par30\">The diagnosis of CTO lesions was based on the diagnostic criteria developed by the American Heart Association in 2011, that is, in the coronary arteries on the basis of atherosclerotic lesions due to thrombus formation, recurrent mechanization leading to complete obstruction of coronary vascular lumen and the duration of the occlusion was more than 3 month [##REF##22064601##20##].</p>", "<p id=\"Par31\">Exclusion criteria were (1) history of acute myocardial infarction within the previous 3 months, (2) PCI and/or coronary artery bypass graft treatment within the previous 3 months, (3) NYHA class III–IV or severe heart failure (left ventricular ejection fraction [LVEF] &lt; 30%), (4) severe hepatic and renal impairment (estimated glomerular filtration rate [eGFR] &lt; 30 mL/min/1.73 m<sup>2</sup>), and (5) severe infectious diseases, severe anemia, malignant tumors, etc.</p>", "<title>Data collection and definitions</title>", "<p id=\"Par32\">For cases meeting the inclusion criteria, personal information for each patient such as name, gender, age, smoking history, drinking history, etc., as well as LVEF, systolic blood pressure, and diastolic blood pressure measured in the right upper arm were collected by medical professionals at the time of admission. Venous blood specimens were collected by medical professionals early in the morning on the day after admission following fasting for at least 8 h. The blood samples were analyzed by fully automated hematology analyzers to obtain measurements for total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), fasting plasma glucose (FPG), glycosylated hemoglobin A1c (HbA1c), C-reactive protein (CRP), and creatinine (Cr). All patients underwent CAG by the radial or femoral artery route using the standard Judkins method, and the results were described and recorded by two senior interventional cardiologists.</p>", "<p id=\"Par33\">TyG index was calculated according to the following formula: TyG index = Ln [TG (mg/dL) × FPG (mg/dL)/2] [##REF##19067533##14##]. Coronary artery disease was defined as ≥ 50% luminal narrowing of at least one coronary artery (left anterior descending, left circumflex, or right coronary arteries). According to the American Diabetes Association's Standards for the Medical Management of Diabetes, DM was defined as FPG ≥ 7.0 mmol/L or HbA1c ≥ 6.5%, Pre-DM was defined as 5.6 mmol/L ≤ FPG ≤ 6.9 mmol/L or 5.7% ≤ HbA1c ≤ 6.4%, and normal glucose regulation (NGR) was defined as FPG &lt; 5.6 mmol/L or HbA1c &lt; 5.7% [##REF##24357215##21##]. The Rentrop classification was used to evaluate collateral circulation and included four grades: grade 0, no collateral vessels were filled with contrast, grade 1, collateral vessels were filled with contrast but did not perfuse the epicardial arteries, grade 2, the epicardial arteries were partially filled with contrast through the collateral vessels, and grade 3, the epicardial arteries were completely filled with contrast through the collateral vessels. In patients with multiple coronary lesions, the side branch with the highest Rentrop classification was used when there were multiple coronary side branches [##REF##3156171##22##]. According to the Rentrop grading, patients were divided into two groups: one with poor collateral circulation formation (Rentrop grade 0–1) and one with good collateral circulation formation (Rentrop grade 2–3).</p>", "<title>Statistical analysis</title>", "<p id=\"Par34\">The Kolmogorov–Smirnov test was used to assess the normality of the measurement data, which was expressed as mean ± standard deviation for normal distribution, median and interquartile spacing for non-normal distribution, and percentage for categorical variables. When grouped by the formation of collateral circulation, the t test or Mann–Whitney U test were used to compare continuous variables between the two groups, when grouped by different glucose metabolic states, analysis of variance or Kruskal–Wallis test were used to compare continuous variables between the three groups. Categorical variables were compared by χ2 test. Multicollinearity was tested in multivariable models with a variance inflation factor threshold of &lt; 5. We found multicollinearity between TG, FPG, and TyG index. Using univariate logistic regression analysis, we found that TC, HDL-C, HbA1c, and TyG index were statistically significant (<italic>P</italic> &lt; 0.05), and we included them in a multivariable logistic regression analysis to calculate odds ratios (OR) and 95% confidence intervals (CI) in order to test for a correlation between TyG index and collateral circulation in patients with CTO. Restricted cubic spline analysis was performed to reflect the dose–response relationship between TyG index and the risk of poor collateral circulation formation in different glucose metabolic states. The sensitivity and specificity of the TyG index in predicting the formation of collateral circulation were evaluated using the subjects' work characteristic curve (ROC) and area under the curve (AUC). All data were analyzed using R version 4.1.0, GraphPad Prism version 8.0.1, and SPSS for windows version 25. A P-value of &lt; 0.05 was considered statistically significant.</p>" ]
[ "<title>Results</title>", "<title>Clinical baseline data grouped according to collateral circulation</title>", "<p id=\"Par35\">Study participants were grouped based on the formation of collateral circulation, which resulted in 205 cases in the poor collateral circulation group and 476 cases in the good collateral circulation group. TyG index, FPG, HbA1c, TC, and TG were significantly higher in the poor CCC formation group compared with the good CCC group (<italic>P</italic> &lt; 0.001), whereas HDL-C showed the opposite trend, being significantly lower in the poor CCC formation group than in the good CCC group (<italic>P</italic> = 0.026). The proportion of patients with DM and Pre-DM was significantly higher in the poor CCC group compared with the good CCC group (<italic>P</italic> &lt; 0.001). In terms of age and sex ratio, there was no difference between the two groups (<italic>P</italic> &gt; 0.05) (Additional file ##SUPPL##0##1##: Table S1).</p>", "<title>Multifactorial analysis of factors related to the formation of collateral circulation</title>", "<p id=\"Par36\">Multifactorial logistic regression analysis was performed using good or poor formation of collateral circulation as the dependent variable, and each factor that was statistically significant (<italic>P</italic> &lt; 0.05) in the one-way analysis as the independent variable. The results of this analysis showed that TyG index (OR 5.104, 95% CI 3.323–7.839, <italic>P</italic> &lt; 0.001) and HbA1c (OR 1.278, 95% CI 1.120–1.458, <italic>P</italic> &lt; 0.001) were independent correlates affecting the formation of CCC (Additional file ##SUPPL##0##1##: Table S2).</p>", "<title>Baseline data of different glucose metabolism status groupings</title>", "<p id=\"Par37\">When the patients with CTO were grouped according to glucose metabolism status, there were 139 cases in the NGR group, 218 cases in the Pre-DM group, and 324 cases in the DM group. There were significant differences between the three groups in HDL-C, TG, TyG index, FPG, and HbA1c (<italic>P</italic> &lt; 0.05 for all), and the percentage of poor collateral circulation formation was significantly higher in the Pre-DM and DM groups compared with that in the NGR group (<italic>P</italic> &lt; 0.001 for all) (Table ##TAB##0##1##). HDL-C in the DM group was significantly lower than that in the NGR group (<italic>P</italic> = 0.0075), but was not significantly different from that in the Pre-DM group (<italic>P</italic> = 0.7769), and HDL-C in the Pre-DM group was not significantly different from that in the NGR group (<italic>P</italic> = 0.1674) (Additional file ##SUPPL##0##1##: Fig. S1 a). TG in the DM group was significantly higher than that in the NGR group and the Pre-DM group (both <italic>P</italic> &lt; 0.05), and TG in the Pre-DM group was not significantly different from that of the NGR group (<italic>P</italic> = 0.2345) (Additional file ##SUPPL##0##1##: Fig. S1 b).TG, TyG index, FPG, and Hb1Ac in the DM group were significantly higher than those in the NGR group and the Pre-DM group (all <italic>P</italic> &lt; 0.05), TG in the Pre-DM group was not significantly different from that in the NGR group (<italic>P</italic> = 0.2345), and TyG index, FPG, and Hb1Ac in the Pre-DM group were significantly higher than those in the NGR group (all <italic>P</italic> &lt; 0.05) (Additional file ##SUPPL##0##1##: Fig. S1b–e).</p>", "<title>Relationship between TyG index and collateral circulation in different glucose metabolic states</title>", "<p id=\"Par38\">Participants were divided into NGR group, Pre DM group, and DM group based on their glucose metabolism status, with the formation of collateral circulation as the dependent variable and statistically significant (P &lt; 0.05) factors in univariate analysis as independent variables. The multivariable logistic regression analysis was performed by substituting them into the multivariable analysis equation. In the NGR group, we found no correlation between TyG index and poor CCC formation (P &gt; 0.05). In the Pre-DM group, TyG index (OR 6.487, 95% CI 2.460–17.101, P &lt; 0.001) was found to be an independent correlate affecting CCC formation. In the DM group, TyG index (OR 6.692, 95% CI 3.648–12.157, P &lt; 0.001) and HbA1c (OR 1.371, 95% CI 1.125–1.671, P &lt; 0.001) were independent correlates affecting the formation of CCC (Table ##TAB##1##2##). The restricted cubic spline curve showed that the risk of poor collateral circulation formation in Pre-DM and DM groups was initially flat and then increased rapidly, except for the NGR group (Additional file ##SUPPL##0##1##: Fig. S2) (Table ##TAB##2##3##)</p>", "<title>Predictive value of TyG index for poor collateral circulation formation in patients with CTO</title>", "<p id=\"Par39\">We compared the AUC of TyG index with TC, TG, HDL-C and HbA1c in different glucose metabolic states. The results showed that in the NGR group, the AUC of TyG index was not significantly different from TC, TG, HDL-C and HbA1c. However, in the Pre-DM, DM, and baseline groups, we observed statistically significant differences between the AUC of the TyG index and the AUC of TC, TG, HDL-C, and HbA1c (<italic>P</italic> &lt; 0.05). These results suggest that TyG index is superior to TC, TG, HDL-C and HbA1c in predicting poor collateral circulation formation (Additional file ##SUPPL##0##1##: Table S3, Fig. S3).</p>", "<p id=\"Par40\">The ROC curve for poor coronary collateral circulation and TyG index is shown in Fig. ##FIG##1##2##. When TyG index was added to the baseline model, the optimal cutoff for predicting poor collateral circulation formation was 9.155. At this cutoff value, the sensitivity was 62.4%, the specificity was 87.4%, and the AUC was 0.799 (95% CI 0.738–0.820, <italic>P</italic> &lt; 0.001). When TyG index was added to the NGR model, the result showed that TyG index was not significant in predicting poor collateral circulation formation (<italic>P</italic> = 0.314). When TyG index was added to the Pre-DM model, the optimal cutoff for predicting poor collateral circulation formation was 9.150. At this cutoff value, the sensitivity was 47.6%, the specificity was 94.3%, and the AUC was 0.739 (95% CI 0.633–0.845, <italic>P</italic> &lt; 0.001). When TyG index was added to the DM model, the optimal cutoff value for predicting poor collateral circulation formation was 9.215. At this cutoff value, the sensitivity was 7.12%, the specificity was 81.1%, and the AUC was 0.801 (95% CI 0.751–0.851, <italic>P</italic> &lt; 0.001) (Table ##TAB##2##3##). There was no statistically significant difference in AUC of TyG index between the baseline model, Pre-DM model and DM model (<italic>P</italic> &gt; 0.05) (Additional file ##SUPPL##0##1##: Table S4).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par41\">The present study showed that TyG index was significantly associated with the risk of poor collateral circulation formation, especially in the pre-DM and DM groups. Importantly, this is the first study to reveal the correlation between TyG index and the risk of poor collateral circulation formation in different glucose metabolic states.</p>", "<p id=\"Par42\">The main advantage of the TyG index is that it is calculated from fasting glucose and triglycerides and does not require the measurement of serum insulin, thus TyG index is a simple and easy-to-use technique for evaluating insulin resistance [##REF##20484475##23##–##REF##30323862##25##]. Several studies have reported that cardiovascular events are closely related to the TyG index. Sanchez-Inigo et al. [##REF##26683265##26##] found that the TyG index can predict the occurrence of adverse cardiovascular events, and Luo et al. [##REF##31722708##27##] found that a higher TyG index is associated with an increased risk of adverse cardiovascular events after PCI for acute ST-segment elevation myocardial infarction. Guo et al. [##UREF##0##28##] suggested that the TyG index is a good indicator for the occurrence of adverse cardiovascular events in prediabetic patients. TyG index is widely used in the study of cardiovascular diseases.</p>", "<p id=\"Par43\">In this study, TyG index was found to be an independent risk factor for poor collateral circulation formation, which was consistent with the findings of Gao [##REF##34689767##19##] et al. Our ROC curve analysis showed that TyG index predicted poor collateral circulation formation with an AUC of 0.799, a sensitivity of 62.4%, and a specificity of 87.4%. This suggests that TyG index could be used as a simple, easy and inexpensive noninvasive biomarker to predict and evaluate good CCC formation in CTO patients in daily clinical practice.</p>", "<p id=\"Par44\">The effect of the TyG index on collateral circulation formation suggests that insulin resistance plays a crucial role in the formation of collateral circulation in patients with CTO. Insulin resistance causing compensatory hyperinsulinemia can impair the insulin signaling pathway in vascular endothelial cells, leading to decreased nitric oxide (NO) production and vasodilatory dysfunction, which in turn causes vascular endothelial dysfunction [##REF##21051417##29##–##REF##17525361##31##]. Hyperinsulinemia can cause impaired expression of vascular endothelial growth factor in the heart [##REF##16469952##32##]. In addition, insulin resistance can lead to disturbances in glucose metabolism and produce chronic hyperglycemia. Chronic hyperglycemia can cause an increase in free radicals through different pathways, which in turn triggers oxidative stress leading to cellular damage [##REF##25019091##33##–##REF##16824626##35##]. Furthermore, insulin resistance can cause an elevation of free fatty acids (FFA) in the blood, which can lead to mitochondrial dysfunction and an increase in reactive oxygen species production. FFA can also lead to the activation of inflammatory factors (TNF-α, IL1-β, and IL-6) and an elevation of monocyte chemotactic protein-1 (MCP-1), which can cause cellular damage and chronic inflammation [##REF##22560216##36##]. All these factors may hamper angiogenesis and arteriogenesis, thereby inhibiting the formation of collateral circulation [##UREF##1##37##].</p>", "<p id=\"Par45\">In this study, patients with CTO were also divided into NGR, Pre-DM, and DM groups according to their glucose metabolism status, and it was found that TyG index was not correlated with poor collateral circulation formation in the NGR group but was significantly correlated with the risk of poor collateral circulation formation in CTO patients in the Pre-DM group and the DM group. Furthermore, TyG index was an independent risk factor for poor collateral circulation formation in the latter two groups This suggests that the relationship between TyG index and collateral circulation formation differs for different glucose metabolic states. We hypothesize that this mechanism may be due to the fact that insulin resistance is more severe in Pre-DM, and DM patients than in those with NGR. Previous studies have shown that patients with Pre-DM have higher levels of insulin resistance compared to those with NGR [##REF##15161760##38##]. Insulin resistance is an important pathophysiologic pathway that contributes to the development of diabetes and may be present for an extended period of time before the diagnosis of diabetes is made [##REF##12231073##39##, ##REF##30067154##40##].</p>", "<p id=\"Par46\">In conclusion, this study found for the first time that TyG index was significantly associated with the risk of poor collateral circulation formation in patients with CTO, especially those with Pre-DM and DM. There are several limitations of this study that are worth considering. First, this is a single-center retrospective study with a limited sample size. Second, the results of this study were only for the Chinese population, so caution must be exercised in generalizing the results to other populations because a causal relationship could not be established. Third, the study did not differentiate between diabetic patients with well-controlled disease and diabetic patients with uncontrolled disease. Fourth, survival bias due to fatal events should not be overlooked. Fifth, there is a lack of information about glucocorticosteroids and fenofibrate drugs that may affect serum TG levels. In addition, possible survival bias due to fatal events should be recognized. Finally, insulin is not a common laboratory parameter in patients with CAD, especially in nondiabetic patients, and therefore no comparison of HOMA-IR and TyG index was performed.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">To investigate the correlation between triglyceride glucose index (TyG) and collateral circulation in patients with chronic total occlusion (CTO) of coronary arteries in different glucose metabolic states.</p>", "<title>Methods</title>", "<p id=\"Par2\">A total of 681 patients who underwent coronary angiography between January 2020 and December 2021 to determine the presence of CTO lesions in at least one major coronary artery were retrospectively included in this study. Patients were categorized into a group with poor collateral circulation formation (Rentrop grade 0–1, <italic>n</italic> = 205) and a group with good collateral circulation formation (Rentrop grade 2–3, <italic>n</italic> = 476) according to the Rentrop scale. They were also categorized according to their glucose metabolism status: normal glucose regulation (NGR) (<italic>n</italic> = 139), prediabetes mellitus (Pre-DM) (<italic>n</italic> = 218), and diabetes mellitus (DM) (<italic>n</italic> = 324). Correlation between TyG index and collateral circulation formation was analyzed by logistic regression analysis and receiver operating characteristic (ROC) curves.</p>", "<title>Results</title>", "<p id=\"Par3\">Among patients with CTO, TyG index was significantly higher in the group with poor collateral circulation formation than in the group with good collateral circulation formation. Logistic regression analysis showed that TyG index was an independent risk factor for poor collateral circulation formation (OR 5.104, 95% CI 3.323–7.839, <italic>P</italic> &lt; 0.001). The accuracy of TyG index in predicting collateral circulation formation was evaluated by the ROC curve, which had an area under the curve of 0.779 (95% CI 0.738–0.820, <italic>P</italic> &lt; 0.001). The restrictive cubic spline curves showed that the risk of poor collateral circulation formation in the Pre-DM and DM groups was initially flat and finally increased rapidly, except for the NGR group. TyG index was significantly associated with an increased risk of poor collateral circulation formation in the Pre-DM and DM groups.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">TyG index was significantly associated with the risk of poor collateral circulation formation in patients with CTO, especially those with Pre-DM and DM.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02080-3.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We sincerely thank all patients and volunteers who participated in this study, as well as the support of the Cardiology Department of the First Affiliated Hospital of Zhengzhou University.</p>", "<title>Author contributions</title>", "<p>FH and J-WZ conceived and designed the study. J-WZ performed the statistical analysis. J-WZ and RG interpreted results. J-WZ, FH, and RG drafted the report. RG, M-HN, C-XW, and YL provided critical suggestions for improving the manuscript. All authors contributed to data acquisition and to the article and approved the submitted version.</p>", "<title>Funding</title>", "<p>This work was supported by Natural Science Foundation of Henan Province (No. 182300410301), Medical Science and Technology Research Project of Henan Province (No. 2018020118), Science and Technology Plan of Henan Province (No. 182102310160), the Candidate Project of Henan Provincial Medical Science and Technology Research Funds Jointly Built by Province and Ministry (No. 2018010001), and Henan Provincial Medical Science and Technology Research Funds Jointly Built by Province and Ministry (No. SBGJ202102147).</p>", "<title>Availability of data and materials</title>", "<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par49\">The studies involving human participants were reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University. The patients/participants provided their written informed consent to participate in this study.</p>", "<title>Competing interests</title>", "<p id=\"Par50\">The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow chart of patient recruitment. <italic>CCC</italic> coronary collateral circulation, <italic>NGR</italic> normal glucose regulation, <italic>Pre-DM</italic> prediabetes mellitus, <italic>DM</italic> diabetes mellitus</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The TyG index predicts that poor coronary collateral circulation ROC curve. <italic>NGR</italic> normal glucose regulation, <italic>Pre-DM</italic> prediabetes mellitus, <italic>DM</italic> diabetes mellitus</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Clinical baseline data grouped according to different glucose metabolic status</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\">NGR</th><th align=\"left\">Pre-DM</th><th align=\"left\">DM</th><th align=\"left\" rowspan=\"2\"><italic>P</italic></th></tr><tr><th align=\"left\">(n = 139)</th><th align=\"left\">(n = 218)</th><th align=\"left\">(n = 324)</th></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"left\">59.37 ± 9.49</td><td align=\"left\">59.57 ± 9.86</td><td align=\"left\">60.06 ± 10.42</td><td char=\".\" align=\"char\">0.747</td></tr><tr><td align=\"left\">Male (n, %)</td><td align=\"left\">116 (83.5%)</td><td align=\"left\">171 (78.4%)</td><td align=\"left\">243 (75.0%)</td><td char=\".\" align=\"char\">0.129</td></tr><tr><td align=\"left\">SBP (mmHg)</td><td align=\"left\">134.06 ± 17.77</td><td align=\"left\">133.67 ± 18.88</td><td align=\"left\">133.09 ± 16.73</td><td char=\".\" align=\"char\">0.106</td></tr><tr><td align=\"left\">DBP (mmHg)</td><td align=\"left\">79.68 ± 12.52</td><td align=\"left\">78.23 ± 11.72</td><td align=\"left\">78.46 ± 10.45</td><td char=\".\" align=\"char\">0.101</td></tr><tr><td align=\"left\">Smoking history (n, %)</td><td align=\"left\">55 (39.6%)</td><td align=\"left\">55 (43.6%)</td><td align=\"left\">135 (41.7%)</td><td char=\".\" align=\"char\">0.752</td></tr><tr><td align=\"left\">Drinking history (n, %)</td><td align=\"left\">53 (23.3%)</td><td align=\"left\">63 (27.8%)</td><td align=\"left\">59 (26.0%)</td><td char=\".\" align=\"char\">0.731</td></tr><tr><td align=\"left\">History of hypertension (n, %)</td><td align=\"left\">84 (60.4%)</td><td align=\"left\">120 (55.0%)</td><td align=\"left\">198 (61.1%)</td><td char=\".\" align=\"char\">0.346</td></tr><tr><td align=\"left\" colspan=\"5\">Previous medication</td></tr><tr><td align=\"left\"> Antihypertensive drugs (n, %)</td><td align=\"left\">83 (59.7%)</td><td align=\"left\">119 (54.6%)</td><td align=\"left\">191 (59.0%)</td><td char=\".\" align=\"char\">0.521</td></tr><tr><td align=\"left\"> Lipid-lowering drugs (n, %)</td><td align=\"left\">133 (95.7%)</td><td align=\"left\">205 (94.0%)</td><td align=\"left\">310 (95.7%)</td><td char=\".\" align=\"char\">0.648</td></tr><tr><td align=\"left\"> Antiplatelet drugs (n, %)</td><td align=\"left\">129 (92.8%)</td><td align=\"left\">201 (92.2%)</td><td align=\"left\">300 (92.6%)</td><td char=\".\" align=\"char\">0.975</td></tr><tr><td align=\"left\"> Antidiabetic drugs (n, %)</td><td align=\"left\">9 (6.5%)</td><td align=\"left\">27 (12.4%)</td><td align=\"left\">166 (51.2%)</td><td char=\".\" align=\"char\">&lt; 0.001*</td></tr><tr><td align=\"left\" colspan=\"5\">Laboratory examination</td></tr><tr><td align=\"left\"> cTnI (ng/mL)</td><td align=\"left\">0.010 (0.010–0.020)</td><td align=\"left\">0.010 0.010–0.020)</td><td align=\"left\">0.010 (0.010–0.020)</td><td char=\".\" align=\"char\">0.425</td></tr><tr><td align=\"left\"> BNP (pg/mL)</td><td align=\"left\">131.79 ± 61.11</td><td align=\"left\">128.03 ± 56.08</td><td align=\"left\">130.85 ± 59.81</td><td char=\".\" align=\"char\">0.821</td></tr><tr><td align=\"left\"> Cr (μmol/L)</td><td align=\"left\">70.16 ± 12.83</td><td align=\"left\">70.23 ± 13.68</td><td align=\"left\">68.47 ± 14.53</td><td char=\".\" align=\"char\">0.592</td></tr><tr><td align=\"left\"> eGFR (mL/min/1.73 m<sup>2</sup>)</td><td align=\"left\">92.03 ± 12.19</td><td align=\"left\">93.28 ± 12.67</td><td align=\"left\">68.47 ± 14.53</td><td char=\".\" align=\"char\">0.470</td></tr><tr><td align=\"left\"> CRP (mg/L)</td><td align=\"left\">1.26 (0.74–1.83)</td><td align=\"left\">1.34(0.77–1.90)</td><td align=\"left\">1.32 (0.78–1.83)</td><td char=\".\" align=\"char\">0.668</td></tr><tr><td align=\"left\"> TC (mg/dL)</td><td align=\"left\">3.36 (2.88–3.91)</td><td align=\"left\">3.58(3.00–4.29)</td><td align=\"left\">3.54 (3.09–4.22)</td><td char=\".\" align=\"char\">0.083</td></tr><tr><td align=\"left\"> TG (mg/dL)</td><td align=\"left\">1.22 (0.90–1.75)</td><td align=\"left\">1.38(1.03–1.81)</td><td align=\"left\">1.56 (1.10–2.11)</td><td char=\".\" align=\"char\">&lt; 0.001*</td></tr><tr><td align=\"left\"> HDL-C (mg/dL)</td><td align=\"left\">0.96 (0.82–1.15)</td><td align=\"left\">0.91 (0.79–1.05)</td><td align=\"left\">0.90 (0.78–1.04)</td><td char=\".\" align=\"char\">0.010*</td></tr><tr><td align=\"left\"> LDL-C (mg/dL)</td><td align=\"left\">1.97 (1.57–2.42)</td><td align=\"left\">2.07 (1.65–2.64)</td><td align=\"left\">2.10 (1.66–2.61)</td><td char=\".\" align=\"char\">0.118</td></tr><tr><td align=\"left\"> FPG (mmol/L)</td><td align=\"left\">4.60 (4.25–5.05)</td><td align=\"left\">5.01 (4.57–5.46)</td><td align=\"left\">7.20 (6.01–9.05)</td><td char=\".\" align=\"char\">&lt; 0.001*</td></tr><tr><td align=\"left\"> HbA1c (%)</td><td align=\"left\">5.40 (5.30–5.50)</td><td align=\"left\">6.00 (5.80–6.20)</td><td align=\"left\">7.60 (6.90–9.00)</td><td char=\".\" align=\"char\">&lt; 0.001*</td></tr><tr><td align=\"left\"> LVEF (%)</td><td align=\"left\">61.00 (57.50–64.00)</td><td align=\"left\">61.00 (52.00–63.00)</td><td align=\"left\">61.00 (52.00–64.00)</td><td char=\".\" align=\"char\">0.312</td></tr><tr><td align=\"left\"> TyG index</td><td align=\"left\">8.43 (8.06–8.81)</td><td align=\"left\">8.63 (8.37–8.89)</td><td align=\"left\">9.11 (8.70–9.52)</td><td char=\".\" align=\"char\">&lt; 0.001*</td></tr><tr><td align=\"left\" colspan=\"5\">Number of vascular stenosis</td></tr><tr><td align=\"left\"> 1</td><td align=\"left\">17 (12.2%)</td><td align=\"left\">21 (9.6%)</td><td align=\"left\">24 (7.4%)</td><td char=\".\" align=\"char\">0.580</td></tr><tr><td align=\"left\"> 2</td><td align=\"left\">33 (23.7%)</td><td align=\"left\">52 (23.9%)</td><td align=\"left\">81 (25%)</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\"> 3</td><td align=\"left\">89 (64.1%)</td><td align=\"left\">145 (66.5%)</td><td align=\"left\">219 (67.6%)</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\" colspan=\"5\">CTO related artery</td></tr><tr><td align=\"left\"> LAD</td><td align=\"left\">64 (38.1%)</td><td align=\"left\">95 (34.3%)</td><td align=\"left\">138 (34.5%)</td><td char=\".\" align=\"char\">0.784</td></tr><tr><td align=\"left\"> LCX</td><td align=\"left\">36 (21.4%)</td><td align=\"left\">69 (24.9%)</td><td align=\"left\">105 (26.3%)</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\"> RCA</td><td align=\"left\">68 (40.5%)</td><td align=\"left\">113 (40.8%)</td><td align=\"left\">157 (39.3%)</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\" colspan=\"5\">Rentrop collateral grading</td></tr><tr><td align=\"left\"> 0</td><td align=\"left\">5 (3.6%)</td><td align=\"left\">11 (5.0%)</td><td align=\"left\">38 (11.7%)</td><td char=\".\" align=\"char\">&lt; 0.001*</td></tr><tr><td align=\"left\"> 1</td><td align=\"left\">19 (13.7%)</td><td align=\"left\">31 (14.2%)</td><td align=\"left\">101 (31.2%)</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\"> 2</td><td align=\"left\">47 (33.8%)</td><td align=\"left\">86 (39.4%)</td><td align=\"left\">121 (37.3%)</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\"> 3</td><td align=\"left\">68 (48.9%)</td><td align=\"left\">90 (41.3%)</td><td align=\"left\">64 (19.8%)</td><td char=\".\" align=\"char\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Correlations between TyG index and poor Coronary Collateral Circulation in different glucose metabolism states</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"3\">Univariate analysis</th><th align=\"left\" colspan=\"3\">Multivariate analysis</th></tr><tr><th align=\"left\">OR (95% CI)</th><th align=\"left\">β</th><th align=\"left\"><italic>P</italic></th><th align=\"left\">OR (95% CI)</th><th align=\"left\">β</th><th align=\"left\"><italic>P</italic></th></tr></thead><tbody><tr><td align=\"left\">NGR</td><td align=\"left\">TyG index</td><td char=\"(\" align=\"char\">1.733 (0.770–3.900)</td><td char=\".\" align=\"char\">0.55</td><td char=\".\" align=\"char\">0.184</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\" rowspan=\"3\">Pre-DM</td><td align=\"left\">TC</td><td char=\"(\" align=\"char\">1.414 (1.020–1.959)</td><td char=\".\" align=\"char\">0.346</td><td char=\".\" align=\"char\">0.038</td><td char=\"(\" align=\"char\">1.160 (0.783–1.717)</td><td char=\".\" align=\"char\">0.148</td><td char=\".\" align=\"char\">0.459</td></tr><tr><td align=\"left\">HDL-C</td><td char=\"(\" align=\"char\">0.120 (0.019–0.774)</td><td char=\".\" align=\"char\">− 2.120</td><td char=\".\" align=\"char\">0.026</td><td char=\"(\" align=\"char\">0.363 (0.042–3.104)</td><td char=\".\" align=\"char\">− 1.014</td><td char=\".\" align=\"char\">0.354</td></tr><tr><td align=\"left\">TyG index</td><td char=\"(\" align=\"char\">8.224 (3.459–19.557)</td><td char=\".\" align=\"char\">2.107</td><td char=\".\" align=\"char\">&lt; 0.001</td><td char=\"(\" align=\"char\">6.487 (2.460–17.101)</td><td char=\".\" align=\"char\">1.870</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr><tr><td align=\"left\" rowspan=\"4\">DM</td><td align=\"left\">TC</td><td char=\"(\" align=\"char\">1.605 (1.230–2.094)</td><td char=\".\" align=\"char\">0.473</td><td char=\".\" align=\"char\">&lt; 0.001</td><td char=\"(\" align=\"char\">1.138 (0.815–1.588)</td><td char=\".\" align=\"char\">0.129</td><td char=\".\" align=\"char\">0.448</td></tr><tr><td align=\"left\">HDL-C</td><td char=\"(\" align=\"char\">0.285 (0.090–0.902)</td><td char=\".\" align=\"char\">− 1.257</td><td char=\".\" align=\"char\">0.033</td><td char=\"(\" align=\"char\">0.791 (0.181–3.453)</td><td char=\".\" align=\"char\">− 0.235</td><td char=\".\" align=\"char\">0.791</td></tr><tr><td align=\"left\">HbA1c</td><td char=\"(\" align=\"char\">1.716 (1.437–2.048)</td><td char=\".\" align=\"char\">0.540</td><td char=\".\" align=\"char\">&lt; 0.001</td><td char=\"(\" align=\"char\">1.371 (1.125–1.671)</td><td char=\".\" align=\"char\">0.315</td><td char=\".\" align=\"char\">0.002</td></tr><tr><td align=\"left\">TyG index</td><td char=\"(\" align=\"char\">9.283 (5.341–16.136)</td><td char=\".\" align=\"char\">2.228</td><td char=\".\" align=\"char\">&lt; 0.001</td><td char=\"(\" align=\"char\">6.692 (3.648–12.157)</td><td char=\".\" align=\"char\">1.901</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>The predictive value of TyG index for poor coronary collateral circulation</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Variable</th><th align=\"left\">AUC</th><th align=\"left\">95% CI</th><th align=\"left\">Cutoff point</th><th align=\"left\">Sensitivity</th><th align=\"left\">Specificity</th><th align=\"left\"><italic>P</italic></th></tr></thead><tbody><tr><td align=\"left\">Total</td><td align=\"left\">TyG index</td><td char=\".\" align=\"char\">0.799</td><td align=\"left\">0.738–0.820</td><td char=\".\" align=\"char\">9.155</td><td char=\".\" align=\"char\">0.624</td><td char=\".\" align=\"char\">0.874</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr><tr><td align=\"left\">NGR</td><td align=\"left\">TyG index</td><td char=\".\" align=\"char\">0.565</td><td align=\"left\">0.441–0.690</td><td char=\".\" align=\"char\">7.955</td><td char=\".\" align=\"char\">0.985</td><td char=\".\" align=\"char\">0.199</td><td char=\".\" align=\"char\">0.314</td></tr><tr><td align=\"left\">Pre-DM</td><td align=\"left\">TyG index</td><td char=\".\" align=\"char\">0.739</td><td align=\"left\">0.633–0.845</td><td char=\".\" align=\"char\">9.150</td><td char=\".\" align=\"char\">0.476</td><td char=\".\" align=\"char\">0.943</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr><tr><td align=\"left\">DM</td><td align=\"left\">TyG index</td><td char=\".\" align=\"char\">0.801</td><td align=\"left\">0.751–0.851</td><td char=\".\" align=\"char\">9.215</td><td char=\".\" align=\"char\">0.712</td><td char=\".\" align=\"char\">0.811</td><td char=\".\" align=\"char\">&lt; 0.001</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>SBP</italic> systolic blood pressure, <italic>DBP</italic> diastolic blood pressure, <italic>cTnI</italic> cardiac troponin I, <italic>NT-pro BNP</italic> N-terminal B-type natriuretic peptide, <italic>Cr</italic> creatinine, <italic>eGFR</italic> estimated glomerular filtration rate, <italic>CRP</italic> C-reactive protein, <italic>TC</italic> total cholesterol, <italic>TG</italic> triglyceride, <italic>HDL-C</italic> high-density lipoprotein cholesterol, <italic>LDL-C</italic> low-density lipoprotein cholesterol, <italic>FPG</italic> fasting plasma glucose, <italic>HbA1c</italic> glycated hemoglobin, <italic>LVEF</italic> left ventricular ejection fraction, <italic>TyG</italic> triglyceride glucose, <italic>NGR</italic> normal glucose regulation, <italic>Pre-DM</italic> prediabetes mellitus, <italic>DM</italic> diabetes mellitus, <italic>LAD</italic> left anterior descending artery, <italic>LCX</italic> left circumflex coronary artery, <italic>RCA</italic> right coronary artery</p><p>*Statistically significant difference between two groups</p></table-wrap-foot>", "<table-wrap-foot><p><italic>OR</italic> odds ratios, <italic>CI</italic> confidence interval, <italic>NGR</italic> normal glucose regulation, <italic>Pre-DM</italic> prediabetes mellitus, <italic>DM</italic> diabetes mellitus, <italic>TC</italic> total cholesterol, <italic>HDL-C</italic> high-density lipoprotein cholesterol, <italic>HbA1c</italic> glycosylated hemoglobin A1c, <italic>TyG</italic> triglyceride glucose</p><p><italic>Pre-DM</italic> TC was adjusted for HDL-C, <italic>TyG index</italic> TyG index was adjusted for TC, HDL-C HDL-C was adjusted for TC, TyG index, <italic>DM</italic> TC was adjusted for HDL-C, HbA1c, TyG index HDL-C was adjusted for TC, HbA1c, TyG index HbA1c was adjusted for TC, HDL-C, TyG index was adjusted for TC, HDL-C, HbA1c</p></table-wrap-foot>", "<table-wrap-foot><p><italic>AUC</italic> area under the curve, <italic>CI</italic> confidence interval, <italic>NGR</italic> normal glucose regulation, <italic>Pre-DM</italic> prediabetes mellitus, <italic>DM</italic> diabetes mellitus</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2080_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12933_2023_2080_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"12933_2023_2080_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Table S1.</bold> Clinical baseline information according to the grouping of collateral circulation. <bold>Table S2.</bold> Poor collateral circulation formation in relation to various risk factors. <bold>Table S3.</bold> Comparison of TyG index and other factors AUC in different glucose metabolic states. <bold>Table S4.</bold> Comparison of AUC of TyG index in different glucose metabolic states. <bold>Figure S1.</bold> Biochemical indexes in different glucose metabolic states. <bold>a</bold> HDL-C, <bold>b</bold> TG, <bold>c</bold> TyG index, <bold>d</bold> FPG, <bold>e</bold> HbA1c. <bold>Figure S2.</bold> TyG index and poor CCC restricted cubic spline curves in different glucose metabolic states. <bold>a</bold> Normal glucose regulation, <bold>b</bold> prediabetes mellitus, <bold>c</bold> diabetes mellitus. <bold>Figure S3.</bold> TyG index and other factors predicted poor collateral circulation formation in different glucose metabolic states.</p></caption></media>" ]
[{"label": ["28."], "surname": ["Guo", "Feng", "Zhang", "Zhai", "Yang", "Liu", "Liu", "Shi", "Zhou"], "given-names": ["Q", "X", "B", "G", "J", "Y", "Y", "D", "Y"], "article-title": ["Influence of the triglyceride-glucose index on adverse cardiovascular and cerebrovascular events in prediabetic patients with acute coronary syndrome"], "source": ["Front Endocrinol"], "year": ["2022"], "volume": ["13"], "fpage": ["843072"], "pub-id": ["10.3389/fendo.2022.843072"]}, {"label": ["37."], "surname": ["Seiler"], "given-names": ["CJE"], "article-title": ["The human coronary collateral circulation"], "source": ["Eur J Clin Investig"], "year": ["2010"], "pub-id": ["10.1111/j.1365-2362.2010.02282.x"]}]
{ "acronym": [ "SBP", "DBP", "cTnI", "NT-pro BNP", "Cr", "eGFR", "CRP", "TC", "TG", "HDL-C", "LDL-C", "FPG", "HbA1c", "LVEF", "TyG", "NGR", "Pre-DM", "DM", "LAD", "LCX", "RCA", "*" ], "definition": [ "Systolic blood pressure", "Diastolic blood pressure", "Cardiac troponin I", "N-terminal B-type natriuretic peptide", "Creatinine", "Estimated glomerular filtration rate", "C-reactive protein", "Total cholesterol", "Triglyceride", "High-density lipoprotein cholesterol", "Low-density lipoprotein cholesterol", "Fasting plasma glucose", "Glycated hemoglobin", "Left ventricular ejection fraction", "Triglyceride glucose", "Normal glucose regulation", "Prediabetes mellitus", "Diabetes mellitus", "Left anterior descending artery", "Left circumflex coronary artery", "Right coronary artery", "Statistically significant difference between two groups" ] }
40
CC BY
no
2024-01-14 23:43:46
Cardiovasc Diabetol. 2024 Jan 13; 23:26
oa_package/97/01/PMC10787450.tar.gz
PMC10787451
38216926
[ "<title>Background</title>", "<p id=\"Par10\">The mitochondrial fatty acid oxidation disorder, medium-chain acyl-CoA dehydrogenase (MCAD) deficiency, is one of the most common inherited metabolic diseases, with an estimated birth prevalence as high as 1 in 12,000 in Canada [##UREF##0##1##, ##REF##21083904##2##]. The MCAD enzyme is involved in the breakdown of medium-chain fatty acids, [##REF##11409868##3##] which is required for sustaining euglycemia after the depletion of glycogen stores, for example, during high energy activities, when fasting, or when unwell with fever or vomiting [##UREF##1##4##, ##REF##28516128##5##]. Deficiency of this enzyme markedly increases the risk of life-threatening manifestations during such periods of catabolic stress, including metabolic decompensations characterized by hypoketotic hypoglycemia, lethargy, and/or seizures [##REF##20532824##6##, ##REF##8120710##7##]. Treatment typically involves the avoidance of prolonged fasting, medical monitoring during periods of illness, and the provision of rapidly available carbohydrates [##REF##33372121##8##]. Longer-term preventive interventions, such as carnitine supplementation, are used in some children with MCAD deficiency, although evidence regarding their benefits and harms is lacking [##UREF##2##9##–##REF##23426616##11##]. Newborn screening has transformed outcomes for children with MCAD Deficiency by allowing early diagnosis and presymptomatic treatment to prevent mortality (1, 2, 30, 31). Newborn screening panels in Canada vary from province to province; most provinces began screening for MCAD deficiency in the early 2000s (range 2001–2012).</p>", "<p id=\"Par11\">To improve care and long-term outcomes for children with MCAD deficiency, rigorous approaches to evaluation of treatments are needed, informed by reliable, sustainable, and longitudinal measurement of clinically meaningful and patient-centred outcomes [##REF##21630065##12##, ##REF##25856667##13##]. A core outcome set (COS) is a small group of priority outcomes agreed upon by stakeholders interested in a specific health condition with the goal of encouraging the standardized measurement and reporting of endpoints measured during clinical trials for that condition [##REF##26792080##14##, ##REF##24962012##15##]. The development and implementation of COSs can support the synthesis of evidence and the comparison of findings across clinical trials where appropriate. These outcomes can also be collected as part of a high-quality disease registry to establish robust observational data over time and to facilitate registry-based randomized trials, where a trial is implemented in a registry platform that incorporates rigorous outcome measurement [##REF##30081484##16##]. There is a particular need for multi-centre and international collaboration in rare disease settings, given the small number of patients in any single centre. A COS can facilitate such collaboration in rare disease research as part of the harmonization of data on long-term outcomes and treatment effectiveness in small populations, thereby increasing the robustness of data pooling and thus improving the quality of evidence.</p>", "<p id=\"Par12\">We recently developed a COS for children with MCAD deficiency as part of the Core Outcome Measures in Effectiveness Trials (COMET) initiative (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.comet-initiative.org\">www.comet-initiative.org</ext-link>), [##REF##28681707##17##] relying on: (i) a systematic review of prior studies of MCAD deficiency to derive a potential list of relevant outcomes; [##REF##31937333##18##] and (ii) a multi-stakeholder consensus approach (Delphi survey and workshop) involving patients and families, clinicians, and policymakers [##REF##34266901##19##]. The final COS comprised eight core outcomes for children up to age 12 years diagnosed with MCAD deficiency, four of which could be ascertained from a child’s metabolic chart and therefore were identified as being of primary interest for the present study: emergency department use, fasting times, metabolic decompensation, and death [##REF##34266901##19##]. Some outcomes, notably emergency department use, may alternatively be measured using population-wide healthcare administrative data, as demonstrated in a previous Ontario-based study from our group [##REF##30902101##20##]. However, these administrative records often lack the detailed clinical information needed to reliably measure outcomes such as fasting and episodes of metabolic decompensation.</p>", "<p id=\"Par13\">To facilitate prospective collection of these clinical outcomes and thereby support observational registries and clinical trials for children with MCAD deficiency, there is a need to establish the feasibility and sustainability of measuring these outcomes in routine clinical settings, and for outcomes other than death, the opportunity for ascertainment on a long-term and regular basis [##REF##27618914##21##]. To assess the quality of existing metabolic chart core outcomes data and their future suitability for prospective measurement during metabolic clinic visits, we used existing cohort data to investigate the frequency of clinic visits and quality of metabolic chart data for selected outcomes.</p>" ]
[ "<title>Materials and methods</title>", "<title>Data source and eligibility</title>", "<p id=\"Par14\">The Canadian Inherited Metabolic Diseases Research Network (CIMDRN) established a consent-based cohort of nearly 800 children across Canada diagnosed with one of 31 Inherited Metabolic Diseases (IMD), including MCAD deficiency, [##REF##32276663##22##] and included collection of clinical data from the metabolic charts for enrolled children, from birth up to a maximum of 11 years of age. The cohort was developed as a platform to support research that broadly seeks to understand health care and outcomes in this pediatric population.</p>", "<p id=\"Par15\">Children were eligible for the CIMDRN cohort if they were born between January 1, 2006 and December 31, 2015, and received care for a confirmed diagnosis of MCAD deficiency at one of the 13 participating treatment centres between birth and March 31, 2017. Research staff at participating centres retrospectively abstracted data from electronic and/or paper charts depending on the type of metabolic chart in use at the participating centre at the time of each visit. At baseline, abstracted data pertained to participant and family characteristics, medical history, source of ascertainment, and diagnostic tests completed. For each visit to the metabolic clinic after diagnosis, the results of follow-up tests, disease-specific outcomes, treatment, and acute and chronic diagnoses were abstracted. Data fields were selected to support anticipated research questions related to health care and outcomes and to capture information likely to be present in existing metabolic charts. All data were entered as open- and closed-ended responses in a series of study-specific, web-based data collection forms developed with extensive input from metabolic clinicians across Canada who were members of CIMDRN. The data collection forms were submitted to and stored on a central study database in Research Electronic Data Capture (REDCap), [##UREF##3##23##, ##REF##31078660##24##] a secure, web-based software platform hosted at the Children’s Hospital of Eastern Ontario Research Institute; these forms can be obtained by contacting the corresponding author). In addition to the careful design of intuitive data collection tools and regular communication with treatment centre research staff, in order to maintain data quality, the data were subject to a detailed verification process by staff at the CIMDRN central office, including a review of each participant’s full dataset and periodic monitoring of summary measures [##REF##32276663##22##]. A unique, study-specific patient identifier was assigned to each participant in lieu of names and other identifying information to uphold patient confidentiality. Ethics approval for the protocol outlining cohort enrollment, clinical data collection, and analysis was granted by the Children’s Hospital of Eastern Ontario Research Ethics Board, the Ottawa Health Science Network Research Ethics Board, and the research ethics board at each participating centre.</p>", "<p id=\"Par16\">For the present study, we conducted an analysis of these previously abstracted metabolic chart data from enrolled children with MCAD deficiency. Children were excluded if they had no recorded clinic visits after initial enrollment, for example, due to complete absence of data entry or death prior to their initial clinic visit. Children were followed until the study end date of March 31, 2017 unless they were deceased or discharged from a participating metabolic centre during the study period (e.g., due to relocation to a centre not participating in the cohort study). Children who moved to a participating centre from a non-participating centre during the study period were followed from the date of their first recorded clinic visit with the participating centre.</p>", "<p id=\"Par17\">For each participant, data were abstracted from charts and entered into REDCap chronologically, starting from birth or the youngest age of a first recorded clinic visit at a participating centre. If data entry for a participant ended before March 31, 2017 and we were unable to confirm a death or discharge from the clinic, we used all available data for that participant in the analysis. An exception was when calculating visit frequencies (rates per child per year) that involved summing follow-up time; for these analyses, we considered children with incomplete data to be lost to follow-up at the end of the oldest age group to which they were known to be followed for the complete period.</p>", "<title>Analysis</title>", "<p id=\"Par18\">We described the demographic characteristics (e.g., year of birth, sex, consenting treatment centre) and baseline clinical characteristics (e.g., ascertainment method and neonatal complications) using frequencies and percentages. We calculated confidence intervals for incidence rates using the exact Poisson distribution or the normal approximation to the Poisson distribution as appropriate. Confidence intervals for means were expressed using the standard normal distribution. All cell counts representing fewer than five children were suppressed as “ &lt; 5” to reduce the risk of identifying participants, in accordance with research ethics requirements. SAS software® version 9.4 (SAS Institute Inc., Cary, North Carolina, USA) was used for all statistical analyses.</p>", "<p id=\"Par19\">Data collection intervals among participants varied, depending on each child’s schedule of visits to the metabolic clinic. We considered the frequency of visits as an indicator of the frequency of opportunity for outcome measurement. To determine the potential future feasibility of collecting core outcomes prospectively by relying on existing clinical encounters, we reported the frequency of visits to the metabolic clinic and telehealth encounters over time, expressed as rates per child per year, calculated as the total number of visits divided by total person-time of follow-up. Visit rates are presented by child age using 6-month intervals in the first year of life and 2-year intervals thereafter. They exclude visits occurring prior to two months of age in order to focus on visits occurring after a complete diagnosis is typically established, and when core outcome measurement may be most relevant. We explored variation in the frequency of clinic visits among participating centres treating five or more children by presenting results separately for each centre.</p>", "<p id=\"Par20\">To evaluate the quality of data for each of the outcomes of interest, we explored the four core outcomes of interest and their components, guided by Kahn et al.’s framework [##REF##27713905##25##] covering three data quality concepts: completeness, conformance, and plausibility. To address completeness, we examined the extent to which individual components of a particular outcome were captured in abstracted data. To address conformance, we measured the extent to which data were entered in the proposed format and whether there existed variation in how outcomes were measured, abstracted, or recorded across sites. To address plausibility, we examined whether aggregate measures reflected a reasonable measurement or health trajectory over time for a child with MCAD deficiency, expressed as rates or summary measures of core outcomes across age groups as appropriate. For one of the core outcomes of interest, metabolic decompensation, there exists no widely accepted clinical definition. Thus, to ascertain whether metabolic chart-abstracted data may be used to measure this outcome for children with MCAD deficiency, we first identified acute clinical manifestations commonly associated with metabolic decompensation (e.g., hypoglycemia, seizures). Next, two pediatric metabolic physicians (PC, MTG) made independent inferences about whether each event identified by abstracted data constituted a true metabolic decompensation, judging each event as a yes (decompensation) or no (not a decompensation). The physicians relied solely on the abstracted data items to make this judgement. We measured agreement between the two raters using Cohen’s kappa coefficient.</p>" ]
[ "<title>Results</title>", "<title>Sample characteristics</title>", "<p id=\"Par21\">There were 132 children with a confirmed diagnosis of MCAD deficiency enrolled in the CIMDRN cohort. Eight children were excluded from further analyses since they were either deceased within the neonatal period, lost-to-follow-up prior to their first clinic visit, or data abstraction from their metabolic chart had not been initiated at the time of analysis. Children were distributed across the eligible years of birth, with the highest proportion born in 2014–2015 (Table ##TAB##0##1##). Slightly fewer than half (44%) of children were female. The proportions of children recruited from different metabolic centres generally reflected the population catchment associated with those centres. Children were enrolled from metabolic centres located in seven provinces across Canada. Ascertainment was almost exclusively achieved through newborn screening, occasionally in combination with other methods such as family history/cascade testing or symptomatic presentation. Amongst the 104 infants for whom the presence or absence of neonatal complications were available, hypoglycemia (isolated or with other neonatal complications) was reported in 13%, and is notable as a complication possibly associated with MCAD deficiency. An additional 18% of infants did not have documented neonatal hypoglycemia but were noted to have other neonatal complications. These included requirement for intravenous fluids (7%), respiratory distress (7%), need for antibiotics (7%), and jaundice (6%). The median follow-up time was 5.2 years (Interquartile Range [IQR] = 3.0–8.4 years) among participating children, with 113 children (91%) followed from birth until the end of the data collection period. Eleven children had less than complete follow-up during the study period due to late enrollment (e.g., moving from a non-participating centre) or were lost to follow-up prior to the completion of the study (e.g., discharge, incomplete data entry).\n</p>", "<title>Visits to the metabolic clinic</title>", "<p id=\"Par22\">Overall, there were 202 recorded visits to the metabolic clinic during the pre-defined diagnostic period (the first two months after birth, as almost all cases were ascertained through newborn screening). This represented an average of 1.7 visits (95% confidence interval, 1.5–1.9 visits) per child during which they underwent biochemical and molecular genetic testing to establish a diagnosis of MCAD deficiency.</p>", "<p id=\"Par23\">There was a total of 945 follow-up visits to the metabolic clinic among eligible children at 2 months of age and older. The frequency of visits to the metabolic clinic over time was highest from 2–6 months of age (2.8 visits per child per year), with a gradual, but sustained decline thereafter (2.1 visits per child per year from 6–12 months, 1.5 visits per child per year from 1–3 years, 1.2 visits per child per year from 3–5 years, and 1.0 visits per child per year at 5 years of age and older) (Fig. ##FIG##0##1##). Among centres treating five or more children with MCAD deficiency, the centre-specific trends in visit rates by child age were mostly consistent with the overall trend (see Additional file ##SUPPL##0##1##). There was, however, considerable variation in the magnitude of the rates, likely due to random variation, but possibly reflecting differences in clinic- and clinician-specific management practices.</p>", "<title>Data quality: emergency department visits</title>", "<p id=\"Par24\">Emergency department visits were measured at each metabolic clinic visit, based on the number of trips to the emergency department that had occurred since the most recent previous clinic visit and the reasons prompting those visits. This information was generated from records in the child’s metabolic chart, either derived from clinician report based on the interaction with the family during the clinic visit or from emergency department records embedded in the metabolic chart.</p>", "<title>Completeness</title>", "<p id=\"Par25\">The number of times that the child had visited the emergency department since their last clinic visit was recorded for approximately 95% of metabolic clinic visits (Table ##TAB##1##2##) but this varied widely among centres and among individual participants (data not shown). Among 389 recorded emergency department visits for the 124 participants, 94 visits (24%) were missing the exact calendar date of the visit and five visits (1%) were missing the reason for which the child had received emergency care (the latter included unintelligible entries).\n</p>", "<title>Conformance</title>", "<p id=\"Par26\">The majority of emergency department visits were recorded using validated date fields with accompanying text fields for the reason prompting the visit. However, among the 94 visits without an exact date, 22 emergency department visits had a partial time period entered in a separate open-ended comment (e.g., the month or season within a particular year). For 59 visits (63% of all visits with missing information for calendar date), it was possible to infer at least the approximate age of the child at the time of the visit since it occurred temporally between two clinic visits at known ages.</p>", "<title>Plausibility</title>", "<p id=\"Par27\">There were no duplicates for data values identifying unique emergency department visits and all emergency department visits were reported as occurring after the participant’s date of birth. Approximately 25 children had no recorded emergency visits during their follow-up over an average period of 4.6 years. Based on a previous study in a sample of children with MCAD deficiency in Ontario, Canada, [##REF##30902101##20##] approximately 920 emergency department visits were expected in the present study cohort. However, among 124 eligible participants, there were only 389 emergency department visits recorded, representing 42% of expected visits.</p>", "<p id=\"Par28\">Rates of visits to the emergency department (Fig. ##FIG##1##2##) were lower than expected within all age groups based on comparison to the previously published Ontario study [##REF##30902101##20##]. For example, on average, children with MCAD deficiency in the Ontario study visited the emergency department at a rate of 1.5 visits per child per year within the first 6 months of age and 2.5 visits per child per year between 6 months and 1 year of age. For children in the present study cohort, however, these rates were 0.67 and 0.77 metabolic chart-recorded emergency department visits per child per year on average during the same time periods, respectively. The general trend across age groups was similar across the two studies, and both documented the highest observed frequency of emergency department use as occurring between 6 and 12 months of age. The most common reasons for seeking emergency care were similar between our cohort and the previous Ontario study as well: nausea/vomiting (131 visits), upper respiratory tract infections with or without cough (86 visits), and fever (66 visits). Conversely, the frequency of inpatient hospitalizations over time aligned more closely with the published health care administrative data (see Additional file ##SUPPL##0##1##), [##REF##30902101##20##] with 68% (190/280) of expected hospital admissions captured in chart-abstracted data.</p>", "<title>Data quality: fasting</title>", "<p id=\"Par29\">Fasting refers to a prescribed maximum period without food or drink as tolerated when well (under usual circumstances) or during intercurrent illness (to prevent acute manifestations of MCAD deficiency). An increased fasting tolerance may be reflective of, or change in response to, improved clinical status of the patient with respect to MCAD deficiency [##REF##16788829##26##].</p>", "<title>Completeness</title>", "<p id=\"Par30\">Eighty-one children (65%) were prescribed an initial treatment pertaining to fasting avoidance with 67 prescriptions outlining specific details regarding the maximum number of hours recommended without feeding when well. Beyond the initial treatment, four centres (treating 18 children) did not record prescribed maximum fasting times and an additional eight children from other centres were missing fasting values at every metabolic clinic visit. There was an update to the prescribed diet (e.g., energy, fat, carbohydrates) and composition (e.g., supplements) during approximately 52% of the metabolic clinic visits. It was unknown whether any update occurred during 24 (2%) of the metabolic clinic visits. For the metabolic clinic visits during which there was an update to the overall diet, the prescribed fasting time was recorded approximately 74% of the time; thus fasting time was recorded during 39% of all metabolic clinic visits (Table ##TAB##1##2##). When fasting time was not recorded, it may have been missing, unknown, or unchanged from the previous visit.</p>", "<title>Conformance</title>", "<p id=\"Par31\">When an acceptable fasting range was provided instead of a specific amount of time (e.g., a prescribed maximum fasting range of 8 to 10 h), we considered the median value of the range to define the fasting time. Some children were prescribed different fasting times for daytime versus overnight; thus, we defined the child’s fasting time as the larger value (maximum amount of time). If a child’s fasting time was defined based on the presence of an additional source of carbohydrates (e.g., fasting with or without cornstarch), we defined the fasting time as the value without extraneous intervention (the lower value) since this represented the amount of time tolerated in normal physiological states.</p>", "<title>Plausibility</title>", "<p id=\"Par32\">For a number of children, there were no updates to the prescribed diet for long periods of time. As a result, if a lack of update in a metabolic chart were to be considered equivalent to an unchanged prescribed maximum tolerated fasting time (i.e., if we were to carry forward the last explicitly recorded fasting time), the recommended duration of fasting would appear much lower than expected at older ages.</p>", "<p id=\"Par33\">When considering only explicitly recorded values, the median prescribed fasting time when well was 3.5 h (IQR = 3.3–4.0 h) for children under 6 months of age, 6.0 h (IQR = 5.0–8.0 h) for those aged 6 months up to 12 months, 10.0 h (IQR = 8.5–12.0 h) for those aged 1 year up to 2 years, and 12.0 h (IQR = 10.0–12.0 h) for those aged 2 years and older (Table ##TAB##2##3##). These lengths of time were in approximate agreement with published recommendations for maximum fasting times for children with MCAD deficiency, [##REF##16788829##26##] with a lower median time identified from 6–12 months of age, corresponding to the age period with the highest rate of emergency department use in this cohort. There was no evidence to suggest that the frequency of fasting prescriptions changed over calendar time within age categories (data not shown).\n</p>", "<title>Data quality: metabolic decompensation</title>", "<p id=\"Par34\">The core outcome set defined metabolic decompensation as an acute episode characterized by one or both of the following cardinal features: 1) hypoglycemia and 2) encephalopathy (e.g., lethargy, seizure). Additional supportive evidence based on the results of biochemical tests could include at least one documented abnormal level of substances in the blood indicative of an altered physiological state (e.g., depleted blood glucose, elevated liver aminotransferases) [##REF##34266901##19##].</p>", "<title>Completeness</title>", "<p id=\"Par35\">The components required to ascertain a decompensation were routinely available within the medical chart (e.g., the results of biochemical tests, reasons for seeking emergency care, acute manifestations). However, identifying an event required clinical judgement influenced by a variety of factors and circumstances, which rendered its derivation complicated. Temporal association of laboratory findings or biomarkers with diagnoses or symptoms was not always possible based on inconsistency in recording of exact dates. In addition to the lack of completeness in reporting of emergency department visits and hospital admissions, the ability to identify metabolic decompensations from abstracted data was limited when no monitoring tests were recorded during these visits and admissions, and when the reasons prompting care were non-specific (Table ##TAB##1##2##). To this end, there existed large variation among treatment centres in the level of detail abstracted and/or available in the metabolic chart.</p>", "<title>Conformance</title>", "<p id=\"Par36\">Research staff extracting data for the cohort study rarely used the data collection forms to specify a metabolic decompensation as a direct disease-specific outcome even when it was otherwise apparent that an episode had occurred based on other reported clinical measures. Thus, we relied on associated complications noted in the data extracted from the metabolic chart based on the language used by the health care team to describe a metabolic decompensation. Furthermore, acute manifestations indicative of a metabolic decompensation were not always associated with a specific date; thus, multiple manifestations occurring over a short period of time could not reliably be considered as mutually exclusive events. On a case-by-case basis and to avoid duplicating events, we considered multiple data items possibly contributing to a metabolic decompensation to be related to a single episode if they were reported within the same general time period (e.g., during a single hospital admission) and could not be reliably separated.</p>", "<title>Plausibility</title>", "<p id=\"Par37\">We identified 99 unique events among eligible participants comprised of individual clinical indicators (e.g., reasons for emergency department visits and hospital admission, acute/chronic diagnoses and manifestations, and biochemical measurements) potentially contributing to a single metabolic decompensation. This included one of or any combination of the following: i) direct reference to metabolic decompensation (reported during 13 events); ii) laboratory-confirmed blood (&lt; 3.5 mmol/L) or clinician-reported hypoglycemia (reported during 34 events); or iii) emergency department visits, hospital admissions, or findings reported outside of routine metabolic clinic visits for indications of preventative IV glucose use and/or monitoring for hypoglycemia (reported during 32 events), elevated aspartate and alanine aminotransferases (reported during 18 events), lethargy (reported during 14 events), seizures (reported during nine events), or direct reference to possible encephalopathy (reported during two events).</p>", "<p id=\"Par38\">Two raters (PC, MTG) independently assessed abstracted data items for the 99 potential events. Thirty-five events were resolved as episodes of metabolic decompensation by both raters. An additional 20 events were identified as metabolic decompensations by one of two raters only; 19 of these were classified as episodes of decompensation by rater 1 and not by rater 2. The remaining events were not considered decompensations by either rater. Inter-rater agreement yielded a Cohen’s kappa statistic of 0.61 (95% confidence interval, 0.45–0.76), indicating moderate to substantial agreement [##UREF##4##27##]. The lack of very high interrater disagreement was explained by differing interpretation of the requirement for hypoglycemia. Unless there was documented hypoglycemia warranting intervention, raters agreed that isolated reports of intravenous glucose administration (or possible evidence thereof, such as elevated blood glucose levels during hospital admissions) were likely to be precautionary measures taken to avoid fatty acid oxidation and insufficient to confirm a metabolic decompensation. However, we also recognized the difficulty in excluding a metabolic decompensation event when there was no available chart-abstracted glucose level prior to intravenous administration of glucose. In all cases agreed upon by both raters, there was a direct report of a metabolic decompensation and/or evidence for hypoglycemia, therefore we considered these to be “definite” metabolic decompensation events. In 19 of the 20 remaining cases, a glucose level prior to intravenous administration was unavailable, and we considered these “possible” metabolic decompensation events (Table ##TAB##3##4##).\n</p>", "<p id=\"Par39\">Prior to 12 months of age, on average, there were approximately 13–18 episodes of metabolic decompensation per 100 children per year depending on the number of raters who endorsed that one had occurred (Table ##TAB##3##4##). Among children 12 months of age or older, on average, there were approximately 3 to 6 episodes of metabolic decompensation per 100 children per year. Overall, the median age of metabolic decompensation was approximately 12 to 15 months among episodes that could be ascribed an exact age (i.e., with exact dates available) [##REF##11263545##28##, ##REF##12456920##29##]. Metabolic decompensations are most common between 6 and 18 months of age [##REF##19655016##30##]. Similar to our results, in a previous study, among a sample of 114 children with MCAD deficiency who had previously experienced an acute crisis, the median age at first manifestation was approximately 18 months [##REF##16737882##31##].</p>", "<title>Data quality: death</title>", "<p id=\"Par40\">Since children in this cohort were almost exclusively ascertained by newborn screening, as expected from early identification and initiation of treatment, [##UREF##0##1##] the core outcome of death was fortunately rare (n &lt; 5), occurring only in few neonates exhibiting highly adverse clinical features prior to diagnosis. Therefore, the data quality related to this outcome could not be evaluated. We note that children who died in the early neonatal period without a confirmed diagnosis of MCAD deficiency prior to death (i.e., those who died prior to a positive newborn screening result and subsequent referral) would not have been eligible to participate in the CIMDRN cohort study and thus would not have been identified as part of the present research; the cohort study enrolled only those children who had a confirmed MCAD deficiency diagnosis and received care at a participating clinic and thus we were only able to identify mortality occurring during the study period.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par41\">This study sought to evaluate the quality of existing metabolic chart data and its future suitability for measuring select core outcomes from a COS for MCAD deficiency: emergency department use, fasting time, metabolic decompensation, and death. We found a decreasing rate of follow-up visits to the metabolic clinic by age, consistent with evidence suggesting that the highest risk periods for developing complications occur in younger age groups [##REF##16737882##31##]. Based on the frequency of follow-up visits to the metabolic clinic, an opportunity exists to measure these clinical core outcomes in the metabolic clinic setting at least once per year regardless of patient age. Although other COS studies have defined specific time points for measurement of core outcomes according to disease-specific milestones and timelines, [##REF##27223626##32##] there is no published benchmark for the frequency of collection of core outcomes in children. For MCAD deficiency, the minimum frequency of visits required to capture meaningful change in an outcome may depend on the outcome itself, its measurement scale’s responsiveness to change, and, in studies evaluating management strategies, the specific treatment being evaluated as it relates to the expected length of time until a change in outcome can be expected. Therefore, alternative strategies to collect clinical core outcomes from children who visit the metabolic clinic less frequently may be required; improvements to the provision of virtual ambulatory health care and to shared electronic health records during the SARS-COv2 pandemic may present opportunities for such alternatives.</p>", "<p id=\"Par42\">We believe that rates of emergency department visits were likely to have been underestimated when relying on metabolic chart data alone, but otherwise followed anticipated trends by age. We found the highest rate of emergency department visits between 6 and 12 months of age, which is consistent with previous literature and corresponds with the highest risk period for experiencing metabolic decompensations [##REF##16617240##33##]. It is well known that the accuracy of medical records data depend on the type of data collected; demographic, outcome, and discharge information collected as part of standardized sections of the chart have been found to have the highest accuracy [##REF##16085195##34##]. Data quality may be further maximized when relying on outcomes, such as emergency department visits, that rely in large part on a binary response, such as the presence or absence of a health event. However, <italic>post-hoc</italic> follow-up investigation with research staff at each participating centre suggested that information captured within the metabolic chart pertaining to emergency department visits often corresponded to visits that had occurred at same health care institution’s emergency department. Emergency department visits occurring at other centres, such as at local community hospitals, may not have been captured unless the information had been parent-reported, forwarded by the emergency care team, or otherwise requested by the metabolic team. There was an improved comparability of rates of inpatient hospitalizations with gold standard measures relative to rates of emergency department visits [##REF##30902101##20##]. This suggests that emergency department visits warranting more critical and longer-term care may be more rigorously documented in the metabolic chart. Collectively then, when relying on metabolic chart data, we hypothesize that whether an emergency department visit that occurs is captured depends on the nature and severity of the visit and its relevance to a child’s disease as well as whether the visit occurred at the same institution (which in turn seems likely to vary according to both disease severity and geographic proximity of the child’s residence to the hospital with which the outpatient metabolic clinic is associated). The fact that emergency visits occurring at community hospitals may be missed from metabolic charts and that these visits may be distinct in nature from those that are captured suggests a need for additional pro-active measures to systematically capture emergency care. Strategies may include supplementing metabolic chart data with patient- or parent-reported forms and linkable comprehensive health care administrative data.</p>", "<p id=\"Par43\">Measuring prescribed maximum fasting times from metabolic chart data that had been documented for clinical rather than research purposes was problematic. Although similar to emergency department visits in that the quality of reporting of this outcome relied on the presence or absence of a fasting prescription recorded in the metabolic chart, [##REF##16085195##34##] it is possible that updates were often the product of informal discussions between a clinician and a patient or their family member/caregiver that are not documented. We found that some centres provided families/caregivers with a clinic-specific protocol describing standard recommended fasting times according to age periods. In such cases, only exceptions to this algorithm may have been recorded in the metabolic chart. Consequently, recommended fasting times were updated highly infrequently in patients’ charts, particularly at certain centres. Therefore, consistent reporting of fasting times for prospective research will require the use of clinic report forms completed at each metabolic clinic visit that appropriately capture prescribed diets and recommended fasting times.</p>", "<p id=\"Par44\">In this study, the agreement among metabolic physicians was considered moderate to substantial in terms of characterizing abstracted data items as episodes of metabolic decompensation. The nature of the disagreements in classification between the two observers suggested that each had a differential threshold for an event to be considered a metabolic decompensation. For example, hypoglycemia was a common clinical characteristic among events identified as decompensations by both raters, but invariably reflects a late symptom of metabolic decompensation [##REF##16617240##33##]. A factor rendering it difficult to measure occurrence of metabolic decompensations consistently is that emergency care for MCAD deficiency is often focused on mitigating risk and thus it can be difficult to distinguish a “near miss” (i.e., decompensation avoided due to an intervention) from a full blown decompensation. It was also difficult to temporally associate clinical manifestations contributing to a single event based on metabolic chart data. Certain features occurring alone may not always constitute a true decompensation and may require clinical expertise and judgement (e.g., based on the age of child, the perceived severity of disease, temporal association with other indicators, “susceptibility” from prior events, and other comorbidities). In general, diagnostic information has been found to have lower accuracy compared to other data, which can introduce systematic errors in the absence of standardized definitions and non-adherence to those definitions [##REF##16085195##34##]. Thus, this outcome requires a clear operational definition meaningful to a large number of clinicians treating children with MCAD deficiency. The refinement and application of practice guidelines to include the diagnosis of metabolic decompensation events and for acute management of patients with MCAD Deficiency could also both benefit patient care and also the usability of chart abstracted data for research and quality improvement.</p>", "<p id=\"Par45\">Metabolic centres with both paper-based charts and electronic health records participated in the initial cohort study, with some having referenced both formats of the chart concurrently and others having transitioned to their electronic system during the latter period of the clinic visit eligibility. It was not possible to formally examine whether the quality of metabolic chart data differed based on the format of the chart. Anecdotally, however, we anticipate that differences between centres in the quality of data and reporting are not dependent on the format of the chart due to the inconsistent way that clinical data are currently captured even in electronic forms. Standardization of clinical forms and field definitions (whether paper or electronic) across clinics to the extent possible will likely be required.</p>", "<p id=\"Par46\">The data quality issues we identified currently limit our ability to leverage real-world clinical data for children with MCAD deficiency in research and quality assurance initiatives to inform and improve care. These findings indicate a need for investment in platforms and infrastructure to support high quality routine outcome monitoring in clinical settings to produce usable data that can be synthesized and compared across care centres. Such platforms will facilitate evidence generation to ultimately improve care and outcomes for children with MCAD deficiency, for example through high-quality prospective multi-centre registries that can provide long-term natural history data and support pragmatic trials.</p>", "<title>Limitations</title>", "<p id=\"Par47\">We capitalized on the availability of existing cohort data abstracted from metabolic charts to evaluate reporting of core outcomes for pediatric MCAD deficiency. However, because the CIMDRN cohort study was not specifically designed to collect our core outcome set, it is possible that we underestimated the extent to which the information required to document core outcomes was present in patients’ metabolic charts compared with the variables that we could extract from the database. Specifically, a health event or variable that was indicative of a particular outcome may be inadequate or unavailable in the longitudinal database simply because the definitions and measurement criteria for that outcome were selected a posteriori relative to the cohort data collection. A further limitation to our study is the current scarcity of data available for older children. Included data on older age groups were populated mainly by children with longer follow-up and born in earlier years by nature of the data collection period relative to the years of birth included in this study. Finally, clinicians relied solely on abstracted data items to evaluate the incidence of metabolic decompensations and did not have access to the child’s medical history, which may have influenced their clinical judgement and their ability to correctly identify decompensation episodes.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par48\">Opportunities to record core outcomes at the metabolic clinic occur at least annually for children with MCAD deficiency. Methods to comprehensively capture emergency care received at outside institutions are needed. To reduce substantial heterogeneous recording of core outcome across treatment centres, improved reporting standards are required for consistent documentation of recommended fasting times and a consensus definition for metabolic decompensations needs to be developed and implemented.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Generating rigorous evidence to inform care for rare diseases requires reliable, sustainable, and longitudinal measurement of priority outcomes. Having developed a core outcome set for pediatric medium-chain acyl-CoA dehydrogenase (MCAD) deficiency, we aimed to assess the feasibility of prospective measurement of these core outcomes during routine metabolic clinic visits.</p>", "<title>Methods</title>", "<p id=\"Par2\">We used existing cohort data abstracted from charts of 124 children diagnosed with MCAD deficiency who participated in a Canadian study which collected data from birth to a maximum of 11 years of age to investigate the frequency of clinic visits and quality of metabolic chart data for selected outcomes. We recorded all opportunities to collect outcomes from the medical chart as a function of visit rate to the metabolic clinic, by treatment centre and by child age. We applied a data quality framework to evaluate data based on completeness, conformance, and plausibility for four core MCAD outcomes: emergency department use, fasting time, metabolic decompensation, and death.</p>", "<title>Results</title>", "<p id=\"Par3\">The frequency of metabolic clinic visits decreased with increasing age, from a rate of 2.8 visits per child per year (95% confidence interval, 2.3–3.3) among infants 2 to 6 months, to 1.0 visit per child per year (95% confidence interval, 0.9–1.2) among those ≥ 5 years of age. Rates of emergency department visits followed anticipated trends by child age. Supplemental findings suggested that some emergency visits occur outside of the metabolic care treatment centre but are not captured. Recommended fasting times were updated relatively infrequently in patients’ metabolic charts. Episodes of metabolic decompensation were identifiable but required an operational definition based on acute manifestations most commonly recorded in the metabolic chart. Deaths occurred rarely in these patients and quality of mortality data was not evaluated.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Opportunities to record core outcomes at the metabolic clinic occur at least annually for children with MCAD deficiency. Methods to comprehensively capture emergency care received at outside institutions are needed. To reduce substantial heterogeneous recording of core outcome across treatment centres, improved documentation standards are required for recording of recommended fasting times and a consensus definition for metabolic decompensations needs to be developed and implemented.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12887-023-04393-4.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We extend a sincere thank you to the research staff and students at all of the participating centres who helped administer the CIMDRN cohort study.</p>", "<title>Authors’ contributions</title>", "<p>RI participated in the conception and design of the study, analysis and interpretation of data, and drafting the article. PC participated in the conception, design and supervision of the study, acquisition and interpretation of the data, and critical revisions to the article. MT and BKP participated in the conception, design and supervision of the study, interpretation of the data, and critical revisions to the article. MTG, JBK, VA, CBG, DB, AKJC, SD, SG, CRG, SJG, MIF, NK, MK, EL, ML, JM, BM, SMA, AM, JJM, LN, AP, MP, CP, SR, RS, AS, KS, NS, RS, SSI, KT, YT, LT, CVK, AV, JW, and ACY participated in the design of the study, acquisition and interpretation of data, and critical revisions to the article. MP and KT participated in the analysis and interpretation of the data and critical revisions to the article. DC, KW, NJB, JL, MO, and BJW participated in the design of the study, interpretation of the data, and critical revisions to the article. All authors read and approved the final version of the manuscript.</p>", "<title>Funding</title>", "<p>This study was supported by a Canadian Institutes of Health Research (CIHR) Emerging Team Grant, TR3-119195.</p>", "<title>Availability of data and materials</title>", "<p>The datasets generated and/or analysed during the present study are not publicly available in order to protect the privacy of the study participants. Other materials used for this study (e.g., data collection tools, data dictionary, detailed data privacy/protection procedures, etc.) are available from the corresponding author (Pranesh Chakraborty, Children’s Hospital of Eastern Ontario, [email protected], 1 (613) 737–7600 extension 3437) upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par49\">The study was performed in accordance with relevant guidelines and regulations—Declaration of Helsinki, Good Clinical Practice, and the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS2). Ethics approval was obtained for the protocol of the original cohort study upon which this study was established, namely from the Children’s Hospital of Eastern Ontario Research Ethics Board (#13/23E), from the Ottawa Health Science Network Research Ethics Board (#20140436-01H), and from each participating metabolic centre. Written informed consent was obtained from legal guardians for participants (all under the age of 18 years). Additionally, assent was obtained from participants if applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par50\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par51\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Follow-up visits per child per year to the metabolic clinic, by age at the visit. Error bars represent 95% confidence intervals using the normal approximation to the Poisson distribution. One child may contribute to multiple age groups due to longitudinal follow-up</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Emergency department visits per child per year, by age at the visit. Error bars represent 95% confidence intervals using the normal approximation to the Poisson distribution. One child may contribute to multiple age groups due to longitudinal follow-up</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Participant characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Characteristic</th><th align=\"left\">Frequency (%)</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\"><bold>Year of birth</bold> (<italic>n</italic> = 124)</td></tr><tr><td align=\"left\"> 2006–2007</td><td align=\"left\">20 (16%)</td></tr><tr><td align=\"left\"> 2008–2009</td><td align=\"left\">27 (22%)</td></tr><tr><td align=\"left\"> 2010–2011</td><td align=\"left\">18 (15%)</td></tr><tr><td align=\"left\"> 2012–2013</td><td align=\"left\">28 (23%)</td></tr><tr><td align=\"left\"> 2014–2015</td><td align=\"left\">31 (25%)</td></tr><tr><td align=\"left\"><bold>Sex (female)</bold> (<italic>n</italic> = 124)</td><td align=\"left\">54 (44%)</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Consenting treatment centre</bold> (<italic>n</italic> = 124)</td></tr><tr><td align=\"left\"> Centre A</td><td align=\"left\">30 (24%)</td></tr><tr><td align=\"left\"> Centre B</td><td align=\"left\">29 (23%)</td></tr><tr><td align=\"left\"> Centre C</td><td align=\"left\">15 (12%)</td></tr><tr><td align=\"left\"> Centre D</td><td align=\"left\">10 (8%)</td></tr><tr><td align=\"left\"> Centre E</td><td align=\"left\">10 (8%)</td></tr><tr><td align=\"left\"> Centre F</td><td align=\"left\">8 (7%)</td></tr><tr><td align=\"left\"> Centre G</td><td align=\"left\">5 (4%)</td></tr><tr><td align=\"left\"> Centre H</td><td align=\"left\">5 (4%)</td></tr><tr><td align=\"left\">Other participating centres<sup>a</sup></td><td align=\"left\">12 (10%)</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Ascertainment</bold> (<italic>n</italic> = 124)<sup>b</sup></td></tr><tr><td align=\"left\"> Newborn screening method only</td><td align=\"left\">107 (86%)</td></tr><tr><td align=\"left\"> Newborn screening and other method(s)</td><td align=\"left\">13–16</td></tr><tr><td align=\"left\"> Other method(s) only</td><td align=\"left\"> &lt; 5</td></tr><tr><td align=\"left\"><bold>Neonatal complications (yes)</bold> (<italic>n</italic> = 104)</td><td align=\"left\">32 (31%)</td></tr><tr><td align=\"left\"> Hypoglycemia</td><td align=\"left\">13 (13%)</td></tr><tr><td align=\"left\"> Other complications without documented hypoglycemia (e.g. respiratory distress, antibiotics, IV fluids, and/or jaundice)</td><td align=\"left\">19 (18%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Highlighted findings for core outcomes according to each data quality concept</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">Emergency department use</td><td align=\"left\"><p>Completeness: Presence or absence and number of emergency department visits since the last clinic visit was reported at 95% of clinic visits</p><p>Conformance: Exact dates of emergency department visits were not always reported, but the age at the visit could often be inferred if it occurred between two clinic visits at known ages</p><p>Plausibility: Although exhibiting similar trends by age, observed rates are underestimated when compared to a previously published study in Ontario using health care administrative data. Only 42% of expected visits were recorded in the chart</p></td></tr><tr><td align=\"left\">Fasting times</td><td align=\"left\"><p>Completeness: Recommended fasting times were updated during approximately 39% of visits. Clinic-specific fasting protocols were provided by some centres, leading to a lack of patient-specific reporting in the chart</p><p>Conformance: Fasting prescriptions were frequently reported as a range of time, based on the presence/absence of other interventions, or based on specific times of day</p><p>Plausibility: Median fasting times that were explicitly recorded in this sample followed published recommendations by age</p></td></tr><tr><td align=\"left\">Metabolic decompensation</td><td align=\"left\"><p>Completeness: Results of monitoring tests that were expected to be ordered were frequently missing and variation was noted in the level of detail recorded or abstracted</p><p>Conformance: Episodes were ascertained mainly based on their associated manifestations and rarely directly reported</p><p>Plausibility: Median age at decompensation roughly followed known ages during which children with MCAD deficiency commonly exhibit symptoms</p></td></tr><tr><td align=\"left\">Death</td><td align=\"left\">Fortunately, death occurred extremely rarely in this cohort. Therefore, data quality for this outcome was not able to be evaluated</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Prescribed fasting times in the CIMDRN cohort and in published recommendations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"><bold>Age Group</bold></th><th align=\"left\"><bold>Number of patients with at least one recorded prescribed fasting time</bold><sup>a</sup></th><th align=\"left\"><bold>Prescribed fasting time in the CIMDRN cohort</bold><break/>Median (IQR)</th><th align=\"left\"><bold>Published fasting times recommendations</bold> [##REF##16788829##26##]</th></tr></thead><tbody><tr><td align=\"left\"> &lt; 6 months</td><td align=\"left\">99</td><td align=\"left\">3.5 h (3.3–4.0)</td><td align=\"left\">N/A</td></tr><tr><td align=\"left\">6 to &lt; 12 months</td><td align=\"left\">67</td><td align=\"left\">6.0 h (5.0–8.0)</td><td align=\"left\">8.0 h</td></tr><tr><td align=\"left\">1 to &lt; 2 years</td><td align=\"left\">59</td><td align=\"left\">10.0 h (8.5–12.0)</td><td align=\"left\">10.0 h</td></tr><tr><td align=\"left\"> ≥ 2 years</td><td align=\"left\">55</td><td align=\"left\">12.0 h (10.0–12.0)</td><td align=\"left\">12.0 h</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Age based rates of metabolic decompensation, estimated by one or two raters identifying a decompensation</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"><bold>Age Group</bold></th><th align=\"left\"><bold>Number of potential events considered</bold></th><th align=\"left\"><bold>No. events labelled as metabolic decompensations</bold></th><th align=\"left\"><bold>Rate per 100 children per year (95% CI)</bold><sup>a</sup></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"4\"><bold>Overall</bold></td></tr><tr><td align=\"left\"> Definite</td><td align=\"left\">99</td><td align=\"left\">35</td><td align=\"left\">5.0 (3.6–6.9)</td></tr><tr><td align=\"left\"> Definite + Possible</td><td align=\"left\"/><td align=\"left\">55</td><td align=\"left\">7.9 (6.0–10.2)</td></tr><tr><td align=\"left\" colspan=\"4\"><bold> &lt; 12 months</bold></td></tr><tr><td align=\"left\"> Definite</td><td align=\"left\"/><td align=\"left\">16</td><td align=\"left\">13.0 (7.8–21.0)</td></tr><tr><td align=\"left\"> Definite + Possible</td><td align=\"left\">38</td><td align=\"left\">22</td><td align=\"left\">18.0 (11.7–27.1)</td></tr><tr><td align=\"left\" colspan=\"4\"><bold> ≥ 12 months</bold></td></tr><tr><td align=\"left\"> Definite</td><td align=\"left\"/><td align=\"left\">19</td><td align=\"left\">3.3 (2.1–5.1)</td></tr><tr><td align=\"left\"> Definite + Possible</td><td align=\"left\">61</td><td align=\"left\">33</td><td align=\"left\">5.7 (4.0–8.0)</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup> “Other participating centres” are those who enrolled fewer than five participants; the total number of participants from these centres is presented in the table</p><p><sup>b</sup>Based on CIMDRN’s privacy policy, cells representing less than five children are suppressed as “ &lt; 5” and a range is provided in the preceding cell to ensure the small cell size is not calculable</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>Median values were calculated for children with more than one fasting prescription reported within a single age group, and only for those prescriptions with exact values provided (for example, excluding prescriptions stating only “avoidance of fasting” or “frequent feedings”)</p></table-wrap-foot>", "<table-wrap-foot><p>a) A single child may contribute to both age groups due to longitudinal follow-up</p><p>b) “Definite” = Chart-documented hypoglycemia or explicit documentation of metabolic decompensation, “Possible” = cases without chart-documented hypoglycemia prior to intravenous glucose administration</p><p><sup>a</sup>95% confidence intervals calculated using the exact Poisson distribution</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12887_2023_4393_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12887_2023_4393_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"12887_2023_4393_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Supplemental Figure 1.</bold> Rates of follow-up visits to the metabolic clinic stratified by treatment centre (A-H). <bold>Supplemental Figure 2.</bold> Rates of inpatient hospitalizations according to the age at the visit.</p></caption></media>" ]
[{"label": ["1."], "surname": ["Horvath", "Davidson", "Stockler-Ipsiroglu", "Lillquist", "Waters", "Olpin"], "given-names": ["GA", "AGF", "SG", "YP", "PJ", "S"], "article-title": ["Newborn screening for MCAD deficiency: Experience of the first three years in British Columbia, Canada"], "source": ["Can J Public Heal"], "year": ["2008"], "volume": ["99"], "issue": ["4"], "fpage": ["276"], "lpage": ["280"], "pub-id": ["10.1007/BF03403754"]}, {"label": ["4."], "mixed-citation": ["Merritt JL 2nd, Chang IJ. Medium-Chain Acyl-Coenzyme A Dehydrogenase Deficiency. In: Adam MP, Feldman J, Mirzaa GM, et al., editors. GeneReviews\u00ae [Internet]. Seattle (WA): University of\u00a0Washington, Seattle; 1993-2023.\u00a02000. Available from: "], "ext-link": ["https://www.ncbi.nlm.nih.gov/books/NBK1424/"]}, {"label": ["9."], "surname": ["Batten", "Chronopoulou", "Pierre"], "given-names": ["W", "E", "G"], "article-title": ["P37 A single paediatric centre experience of l-carnitine supplementation in medium-chain acyl-coa dehydrogenase deficiency (mcadd)"], "source": ["Arch Dis Child"], "year": ["2018"], "volume": ["103"], "fpage": ["e2"], "pub-id": ["10.1136/archdischild-2017-314585.46"]}, {"label": ["23."], "surname": ["Harris", "Taylor", "Thielke", "Payne", "Gonzalez", "Conde"], "given-names": ["PA", "R", "R", "J", "N", "JG"], "article-title": ["Research electronic data capture (REDCap) \u2013 A metadata-driven methodology and workflow process for providing translational research informatics support"], "source": ["J Biomed Inf."], "year": ["2009"], "volume": ["42"], "issue": ["2"], "fpage": ["377"], "lpage": ["81"], "pub-id": ["10.1016/j.jbi.2008.08.010"]}, {"label": ["27."], "surname": ["McHugh"], "given-names": ["ML"], "article-title": ["Interrater reliability: The kappa statistic"], "source": ["Biochem Medica"], "year": ["2012"], "volume": ["22"], "issue": ["3"], "fpage": ["276"], "lpage": ["282"], "pub-id": ["10.11613/BM.2012.031"]}]
{ "acronym": [ "COMET", "CIMDRN", "IMD", "MCAD", "REDCap" ], "definition": [ "Core Outcome Measures in Effectiveness Trials", "Canadian Inherited Metabolic Diseases Research Network", "Inherited metabolic diseases", "Medium-chain acyl-CoA dehydrogenase", "Research Electronic Data Capture" ] }
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CC BY
no
2024-01-14 23:43:46
BMC Pediatr. 2024 Jan 13; 24:37
oa_package/66/10/PMC10787451.tar.gz
PMC10787452
0
[ "<title>Introduction</title>", "<p id=\"Par4\">Wastewater surveillance became an important public health tool during the COVID-19 pandemic. Wastewater surveillance programs identified outbreaks within communities and individual buildings and it is increasingly being used to detect variants of concern [##REF##35306079##1##–##REF##36773920##11##]. The goal of wastewater surveillance is to provide data to public health agencies so that they may make informed decisions regarding mitigation strategies such as physical distancing, masking, business closures, and distribution of resources such as prophylactic vaccines.</p>", "<p id=\"Par5\">The State of Michigan Department of Health and Human Services (MDHHS) initiated a wastewater surveillance program in 2021. The program included partnerships between academic laboratories and regional public health departments that spanned large and small metropolitan areas and rural areas in both the lower and upper peninsulas. Central Michigan University (CMU) formed a partnership with the Central Michigan District Health Department (CMDHD). This partnership provided an opportunity to look at the dynamics of SARS-CoV-2 at a public university and in the surrounding small metropolitan and rural communities [##REF##37353028##12##]. We identified ten on-campus sewer sites and nine off-campus wastewater treatment plants (WWTPs) to sample on a weekly basis. The population sizes serviced by these WWTPs ranged from as large as 35,397 to as small as 851.</p>", "<p id=\"Par6\">Sampling began in July 2021, which was at least seven months after emergence of the Alpha variant (B.1.1.7). The Alpha variant first appeared in North America in late November 2020 and became the predominant SARS-CoV-2 variant by the end of March 2021. The Alpha variant diverged into multiple lineages, including B.1.1.7-derivatives like Q.3. The Q.3 lineage is present in 5,422 clinical sequences worldwide that were uploaded to the NCBI database, and a positive sample was first collected on 7-11-20 (The dates used to describe samples are formatted using the American system (MM-DD-YY)). The Q.3 lineage was detected in clinical samples from Michigan 16 times between 2-18-21 and 7-9-21.</p>", "<p id=\"Par7\">It became clear that our smallest WWTP (estimated population served: 851) consistently produced higher concentrations of SARS-CoV-2 genome copies. Samples taken from this site from 2021 to 2023 were sequenced and many contained sequences that corresponded to an Alpha variant lineage. These sequences also accumulated novel mutations over time, including previously described mutations found only in cryptic lineages derived from wastewater and not in circulating clinical samples [##REF##35115523##13##, ##REF##36240259##14##]. In this manuscript, a cryptic mutation is a mutation previously identified in cryptic lineages, which were previously identified in wastewater but not clinical samples. It’s important to highlight that many of the mutations previously identified in cryptic lineages have since been identified in clinical samples. We hypothesize that an individual was chronically infected with an Alpha variant lineage for 20–28 months. During this time, the virus adapted by accumulating novel mutations, which included previously described cryptic mutations [##REF##35115523##13##, ##REF##36240259##14##]. Importantly, we found that the earliest sample corresponded to Alpha variant lineage Q.3, which closely aligned with clinical sequences reported in summer and fall 2021; however, the sequence diverged over time and accumulated novel mutations.</p>", "<p id=\"Par8\">These data reveal that wastewater surveillance in small metropolitan and rural communities provide an opportunity to identify novel isolates and reconstruct genes due to lower contamination with unrelated sequences. These data also suggest that humans and other animals can chronically shed SARS-CoV-2 over many months, which is associated with accumulation of adaptive mutations. Mutations associated with chronic infection may be useful to identify individuals who are chronically infected and to drive selection of appropriate therapeutics.</p>" ]
[ "<title>Materials and methods</title>", "<title>Selection of sample sites</title>", "<p id=\"Par9\">Central Michigan University (CMU) is a public research university in the City of Mt. Pleasant, Isabella County, Michigan, with an average population during the 2021–2022 academic year of 13,684 students and staff. Ten sample sites were selected on campus that collected wastewater downstream from most campus buildings, including residential halls, apartments, and academic/administrative buildings. The waste stream at these sites includes a mixture of wastewater from CMU and upstream residential areas in the City of Mt. Pleasant. Nine off-campus sites throughout the jurisdictions of the Central Michigan District Health Department (CMDHD) and Mid-Michigan District Health Department (MMDHD) were selected [##REF##37353028##12##], which included the City of Mt. Pleasant, Union Township, City of Alma, City of Clare, City of Evart, three Houghton Lake townships, and Village of Marion wastewater treatment plants (WWTPs). These locations represent various land uses and population densities including urban, rural, and suburban areas, providing a large footprint of SARS CoV-2 virus shedding in Central Michigan.</p>", "<title>Wastewater collection</title>", "<p id=\"Par10\">Since July 2021, wastewater samples (500–1000 mL) were collected once each week on either Monday or Tuesday from ten sanitary sewer sites and nine WWTP influent streams (after grit removal). Sanitary sewer grab samples consisted of wastewater flowing from university dormitories and buildings and the surrounding community. Influent to WWTPs were collected as grab samples or 24-hour composite samples [##REF##37353028##12##]. Samples were held at 4 °C no more than 48 h before analysis.</p>", "<title>Virus concentration and RNA extraction</title>", "<p id=\"Par11\">The protocol described by Flood et al. 2021 and adopted by the Michigan wastewater surveillance network was used to concentrate virus from samples and extract viral RNA [##REF##37353028##12##, ##REF##34296387##15##]. Briefly, 100 mL wastewater or water as a negative control was mixed with 8% (w/v) molecular biology grade PEG 8000 (Promega Corporation, Madison WI) and 0.2 M NaCl (w/v). The sample was mixed slowly on a magnetic stirrer at 4 °C for 2–16 h. Following overnight incubation, samples were centrifuged at 4,700×g for 45 min at 4 °C. The supernatant was then removed, and the pellet was resuspended in the remaining liquid, which ranged from 1 to 3 mL. All sample concentrates were aliquoted and stored at -80 °C until further processing. Viral RNA was extracted from concentrated wastewater using the Qiagen QIAmp Viral RNA Minikit according to the manufacturer’s protocol with previously published modifications (Qiagen, Germany) [##REF##34296387##15##]. In this study, a total of 200 µl of concentrate was used for RNA extraction resulting in a final elution volume of 80 µl. Extracted RNA was stored at -80 °C until analysis. A wastewater negative extraction control was included. To derive recovery efficiencies for each sample site, samples were inoculated with 10<sup>6</sup> gene copies (GC)/mL Phi6 bacteriophage (Phi6) prior to the addition of PEG and NaCl. Wastewater samples were mixed, and a 1 mL sample was reserved and stored at -80 °C. RNA was extracted as stated above.</p>", "<title>Detection and quantification of SARS-CoV-2</title>", "<p id=\"Par12\">A one-step RT-ddPCR approach was used to determine the copy number/20 µL of SARS-CoV-2, and data were converted to copy number/100 mL wastewater for N1 and N2 targets using the method published by Flood et al., 2001 [##REF##34296387##15##]. All the primers and probes used in this study were published previously [##REF##37353028##12##]. Droplet digital PCR was performed using Bio-Rad’s 1-Step RT-ddPCR Advanced kit with a QX200 ddPCR system (Bio-Rad, CA, USA). Each reaction contained a final concentration of 1 × Supermix (Bio-Rad, CA, USA), 20 U µL<sup>−1</sup> reverse transcriptase (RT) (Bio-Rad, CA, USA), 15 mM DTT, 900 nmol l<sup>−1</sup> of each primer, 250 nmol l<sup>−1</sup> of each probe, 1 µL of molecular grade RNAse-free water, and 5.5 µL of template RNA for a final reaction volume of 22 µL [##REF##37353028##12##, ##REF##34296387##15##–##REF##29096303##17##]. RT was omitted for DNA targets. Droplet generation was performed by microfluidic mixing of 20 µL of each reaction mixture with 70 µL of droplet generation oil in a droplet generator (Bio-Rad, CA, USA) resulting in a final volume of 40 µL of reaction mixture-oil emulsions containing up to 20,000 droplets with a minimum droplet count of &gt; 9000. The resulting droplets were then transferred to a 96-well PCR plate that was heat-sealed with foil and placed into a C1000 96-deep-well thermocycler (Bio-Rad, CA, USA) for PCR amplification using the following parameters: 25 °C for 3 min, 50 °C for 1 h, 95 °C for 10 min, followed by 40 cycles of 95 °C for 30 s and 60 °C for 1 min with ramp rate of 2 °C/s 1 followed by a final cycle of 98 °C for 10 min. Following PCR thermocycling, each 96-well plate was transferred to a QX200 Droplet Reader (Bio-Rad, CA, USA) for the concentration determination through the detection of positive droplets containing each gene target by spectrophotometric detection of the fluorescent probe signal. All analyses were run in triplicate for each marker. To derive recovery efficiencies for each sample site, Phi6-spiked pre- and post-PEG concentration RNA samples were used to quantify Phi6 copy number using the previously published primers and probes [##REF##37353028##12##]. The degree of PCR inhibition was also quantified in each sample by spiking 10 µL of 10<sup>5</sup> GC/ml Phi6 in a sample’s Buffer AVL, including positive controls that lacked wastewater.</p>", "<title>Data analysis</title>", "<p id=\"Par13\">All SARS-CoV-2 gene data were converted from GC per 20 µL reaction to GC per 100 mL wastewater sample before analysis [##REF##37353028##12##, ##REF##34296387##15##]. Non-detects (ND) were assigned their individual sample’s limit of detection for the purposes of data reporting, although any weekly on-campus or off-campus samples whose values matched the theoretical limit of detection were removed prior to statistical analysis. The limit of detection was calculated for each individual sample based on both the molecular assays’ theoretical detection limits (i.e., 3 positive droplets for RT-ddPCR; the lowest standard curve concentration for RT-qPCR) and the concentration factor of each processing method examined. All wastewater data were reported to MDHHS and uploaded to the Michigan COVID-19 Sentinel Wastewater Epidemiological Evaluation Project (SWEEP) dashboard (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.michigan.gov/coronavirus/stats/wastewater-surveillance/dashboard/sentinel-wastewater-epidemiology-evaluation-project-sweep\">https://www.michigan.gov/coronavirus/stats/wastewater-surveillance/dashboard/sentinel-wastewater-epidemiology-evaluation-project-sweep</ext-link>).</p>", "<title>Sequencing</title>", "<p id=\"Par14\">RNA was shipped to GT Molecular (Fort Collins, CO) on dry ice. Library preparation was done using GT Molecular’s proprietary method, which utilized ARTIC 4.1 primers for SARS-CoV-2 amplicon generation (<ext-link ext-link-type=\"uri\" xlink:href=\"https://artic.network/ncov-2019\">https://artic.network/ncov-2019</ext-link>). Amplicons were pooled and sequenced on a Miseq using 2 × 150 bp reads. FASTQ files were analyzed using GT Molecular’s bioinformatics pipeline, and variant-calling was performed using a modified and proprietary version of Freyja [##REF##35798029##18##]. FASTQ files for each sample listed in Table ##TAB##0##1## are available in the NCBI SRA database (Submission ID: SUB13897431; BioProject ID: PRJNA1027333).</p>", "<title>Spike reconstruction and identification of novel mutations</title>", "<p id=\"Par15\">FASTQ files from 11-9-21, 9-12-22, 4-24-23, and 5-1-23 contained reads that spanned the entire Spike protein, they lacked contamination with other variants of concern based on variant calling, and they had high relative abundance of the Alpha variant lineage B.1.1.7 derivative. This allowed for reconstruction of a consensus Spike gene for each of the above wastewater samples. Specifically, we uploaded FASTA-formatted .txt files into Galaxy (<ext-link ext-link-type=\"uri\" xlink:href=\"https://usegalaxy.org/\">https://usegalaxy.org/</ext-link>) that represented the SARS-CoV-2 reference Spike gene. We then uploaded each of the paired-end FASTQ files for each wastewater sample. The Bowtie2 program was used to map reads against each reference sequence, creating individual .bam files per sample. The default setting was used for analysis. The Convert Bam program was then used to convert .bam files to FASTA multiple sequence alignments. Multiple sequence alignment files were uploaded to MEGA (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.megasoftware.net/\">https://www.megasoftware.net/</ext-link>) and converted to amino acid sequence The consensus amino acid sequence from each of these samples was manually reconstructed and then aligned with the SARS-CoV-2 Spike reference sequence and a consensus Alpha variant lineage Q.3 sequence derived from 16 clinical samples collected in Michigan from 2-18-21 to 7-9-21. The Q.3 lineage was chosen because the earliest wastewater sample that tested positive for SARS-CoV-2 Alpha variant (i.e., 10-26-21) was Alpha variant lineage Q.3 based on the GT Molecular variant calling pipeline. Mutations that were present in wastewater samples but not in the SARS-CoV-2 Spike reference sequence or clinical sample were characterized as novel mutations. FastQC was used to quantify the total number of reads in each FASTQ file, the total number of reads that aligned to the reference Spike, the read length, and the number of poor-quality sequences (Supplementary Table ##SUPPL##0##1##).</p>", "<title>Novel and cryptic mutation hotspot analyses</title>", "<p id=\"Par16\">We identified novel mutations as described above. Previous literature also identified cryptic sequence hotspots in SARS-CoV-2 Spike [##REF##35115523##13##, ##REF##36240259##14##]. We tracked the percent prevalence of novel and cryptic mutations in wastewater samples that were positive for the Alpha variant lineage. Specifically, we uploaded FASTA-formatted .txt files into Galaxy (<ext-link ext-link-type=\"uri\" xlink:href=\"https://usegalaxy.org/\">https://usegalaxy.org/</ext-link>) that represented the SARS-CoV-2 reference Spike. We then uploaded each of the paired-end FASTQ files for each wastewater sample. The Bowtie2 program was used to map reads against the reference sequence. The default setting was used for analysis. The Convert Bam program was then used to convert .bam files to FASTA multiple sequence alignments. Multiple sequence alignment files were uploaded to MEGA (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.megasoftware.net/\">https://www.megasoftware.net/</ext-link>) and converted to amino acid sequence for open-reading frame analysis. Novel and cryptic mutations were identified manually, and the column of reads were copied and pasted into Excel. The column was selected, and the Analyze Data tool was selected to calculate the percent prevalence of the novel and cryptic mutations. This was repeated for each novel and cryptic mutations across all samples positive for Alpha variant lineage and the percent prevalence data was represented as heatmaps. Novel mutations present in the 2021, 2022, and 2023 consensus Spike proteins were mapped onto the furin cleaved spike protein of SARS-CoV-2 with one RBD erect using UCSF Chimera [##REF##32647346##19##]. This atomic structure was selected because it had the greatest resolution of each amino acids across the Spike protein and allowed mapping of most novel mutations.</p>" ]
[ "<title>Results</title>", "<title>Chronic shedding of an Alpha variant lineage at a rural WWTP</title>", "<p id=\"Par17\">Wastewater samples were collected between July 2021 and June 2023 from ten on-campus sanitary sewer sites and nine WWTP influent streams. SARS-CoV-2 genome copies per 100 mL wastewater were determined each week and reported to MDHHS. One site was notable for higher peaks of virus shedding, which culminated in a peak that was 4 logs higher than the mean for all sites, although high peaks of activity were observed since 9-21-21 (Fig. ##FIG##0##1##). In order to identify the SARS-CoV-2 variant responsible for this activity, RNA extracted from stored wastewater concentrates was shipped to GT Molecular and their NGS and variant calling pipeline was used. RNA from the site of interest and neighboring sites were analyzed as a control. The site of interest contained high relative abundance of Delta variant lineage AY.25.1 at the first time point tested (i.e., 9-21-21) (Fig. ##FIG##0##1##; Table ##TAB##0##1##). This corresponded to the beginning of the Delta variant wave in Central Michigan [##REF##37353028##12##]. The site of interest began shedding the Alpha variant lineage during the next two time points tested (i.e., 10-26-21 and 11-9-21) (Fig. ##FIG##0##1##; Table ##TAB##0##1##). This was preceded by sequencing data from clinical samples, which revealed 16 Alpha variant lineage Q.3 isolates collected from 2-18-21 to 7-9-21 (Table ##TAB##1##2##). The site of interest had high relative abundance of Omicron variant lineages during the next two time points tested (i.e., 3-14-22 and 4-25-22) (Fig. ##FIG##0##1##; Table ##TAB##0##1##). This corresponded to the end of the first Omicron wave in Central Michigan [##REF##37353028##12##]. The Alpha variant lineage became the dominant isolate in all remaining wastewater samples from the site of interest in all 2022 and 2023 samples tested, with relative abundance ranging from 47.1 to 98.0%. The Alpha variant lineage was also detected in the closest neighboring WWTP on 4-10-23, which corresponded to a large peak in virus shedding at that site (Fig. ##FIG##0##1##; Table ##TAB##0##1##). Other sites contained Omicron variant lineages BG.5, XBB.1.5, XBB.1.5.23, XBB.1.28, XBB.1.5.1, XBB.1.5.17, XBB.1.5.49, and Delta variant lineage DT.2 at varying relative abundance (Table ##TAB##0##1##).</p>", "<title>Accumulation of novel mutations in the RBD and NTD</title>", "<p id=\"Par18\">We reasoned that chronic shedding of SARS-CoV-2 would lead to accumulation of novel or cryptic mutations that do not align with sequences identified in most clinical and wastewater samples. Alignment of reconstructed consensus genes with the SARS-CoV-2 Spike reference gene and a consensus Alpha variant lineage clinical sequence revealed that the Spike proteins harbored 9 novel mutations in 2021, 25 novel mutations in 2022, and 38 novel mutations in 2023 (Supplemental Fig. ##SUPPL##1##1##). We expanded this analysis by quantifying the percent prevalence of each of the 38 novel mutations identified in the 2023 samples across all wastewater samples that were positive for the Alpha variant lineage. A heatmap showed that these mutations accumulated within the population over time, while also retaining diversity at each position (Fig. ##FIG##1##2##). This analysis was also performed using previously published cryptic mutations [##REF##35115523##13##, ##REF##36240259##14##].</p>", "<p id=\"Par19\">The majority of the novel mutations accumulated in the receptor binding domain (RBD) and N-terminal domain (NTD) of the surface (a.k.a., spike) glycoprotein (Fig. ##FIG##2##3##A–F). The following mutations were identified in the RBD: A372T, R403K, K444R, V445A, G446D, Y449N, L452Q, Y453F, N460K, S477N, E484V, Q493K, Q498L, G504D, and Y505H. The following mutations were identified in the NTD: T19K, H49Y, W64R, H66Q, I68Del, T76I, V143Del, Y144Del, K147T, S151I, G181E, N196S, Y248S, and G257D. Additional mutations were identified toward the C-terminus: D571G, I587V, V772A, L828F, T941S, V1176F, K1191N, and Q1201K. Many of these mutations were not mapped onto the Spike protein due to a lack of resolution toward the C-terminus (Supplementary Fig. ##SUPPL##1##1##).</p>", "<p id=\"Par20\">The closest neighboring WWTP also contained the Alpha variant lineage (Table ##TAB##0##1##). Alignment of the reconstructed Spike gene from CE 4-10-23 revealed shared mutations with reconstructed Spike genes from 11-9-21, 9-12-22, and 5-1-23, and four unique mutations: L24S, H245Y, V445A, and Y1155F (Supplementary Fig. ##SUPPL##2##2##). The mutations shared with the reconstructed Spike proteins from 11-9-21, 9-22-22, and 5-1-23 suggested that CE 4-10-23 shared a common ancestor with more recent isolates.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par21\">Central Michigan University participated in a statewide SARS-CoV-2 wastewater surveillance network starting July 2021. Two major waves of SARS-CoV-2 passed through the central Michigan region during the 2021/2022 academic year, which were characterized by the emergence of Delta and Omicron variants [##REF##37353028##12##]. Delta and Omicron variants were preceded by the Alpha variant B.1.1.7. The SARS-CoV-2 Alpha variant B.1.1.7 wave passed through central Michigan during winter/spring 2021. Distinct Alpha variant subpopulations were also present at that time including Q.3 and Q.4 lineages.</p>", "<p id=\"Par22\">Retrospective analysis of wastewater data revealed that one rural site produced consistently higher concentrations of SARS-CoV-2 copy numbers since September 2021. NGS sequencing revealed that this site began shedding an Alpha variant lineage by October 2021 and that this continued to at least May 2023. Clinical sequence data revealed that Alpha variant lineage Q.3/Q.4 was present in Michigan between February to July 2021. This preceded the start of wastewater surveillance in central Michigan and our first detection of the Alpha variant lineage in wastewater by 3–8 months. It is unclear how many individuals were originally infected with this lineage at the site of interest, and it is unclear how many individuals continued to shed the virus into the sewer shed. However, due to the small population served at this rural WWTP, our November 2021 Alpha variant lineage Spike gene reconstruction likely represents a chronic infection that lasted for 3–8 months. At this stage of the chronic infection, the Alpha variant lineage already accumulated 9 novel mutations in the Spike gene.</p>", "<p id=\"Par23\">Most of the mutations reside in the Spike RBD and NTD. These domains are critical for host receptor binding and contain key epitopes leveraged by the adaptive immune system to control and prevent repeat infection. A striking mutation that developed in 2023 was R403K. This converted the RGD receptor binding motif to KGD, which is present in SARS-CoV-1 – a historically more lethal yet less transmissible virus [##REF##32283163##20##–##REF##36669646##22##]. This is particularly interesting since R403 is highly conserved in SARS-CoV-2 Spike and only 294 of ~ 3.4 million sequences recorded on GSAID contained a conservative change of R403K [##REF##34824253##23##]. Many other mutations have also been previously characterized. For instance, engineering the A372T mutation into SARS-CoV-2 reduced binding to ACE2 and enhanced replication in human lung cells [##REF##34289344##24##]. K444R, V445A, G446D, Y449N, L452Q, N460K, S477N, and E484V (and cryptic mutation E484A) have been associated with resistance to antibody-mediated neutralization, and N460K was previously observed during a persistent infection in an immunocompromised patient [##REF##36240259##14##, ##REF##36519597##25##–##REF##34234131##33##]. E848V also reduced ACE2 binding [##REF##34234131##33##]. L452Q had higher binding to soluble ACE2 [##REF##34968415##31##]. Y453F increased binding to mink ACE2 [##REF##34748603##34##]. Q493K increased binding to mouse ACE2 and developed in an immunocompromised patient undergoing convalescent plasma treatment [##REF##33993052##35##–##REF##34431691##37##]. Q498L was predicted to lower stability of Spike and ACE2 interaction but no studies are available to confirm this prediction [##REF##35772213##38##]. G504D is associated with immune evasion; however, the G504D substitution is rarely observed in SARS-CoV-2 strains, with a mutant rate below 0.002% [##REF##34481543##29##, ##REF##36168054##39##]. Y505H was in all lineages of the Omicron variant suggesting that it enhanced immune evasion and receptor binding [##REF##36097349##40##].</p>", "<p id=\"Par24\">In the NTD, H49Y impacts Spike structure and influences binding of several antiviral compounds and increased resistance to vaccine sera [##REF##36519597##25##, ##REF##33633229##41##]. T76I increases infectivity in the Lambda variant, although it is suggested that it behaves as a compensatory mutation [##REF##34968415##31##]. T76I also effects antibody binding and immune escape [##REF##35474215##42##]. V143Del is present in Omicron variants suggesting that it enhanced immune evasion and receptor binding [##REF##35016194##43##]. Y144Del may play a role in ACE2 receptor binding or neutralizing antibody escape and deletions in this region were identified in immunocompromised patients [##REF##34431691##37##, ##REF##34125658##44##, ##REF##35958144##45##]. T19K, W64R, H66Q, I68Del, K147T, S151I, G181E, N196S, Y248S, and G257D substitutions have not been characterized. Toward the C-terminus, L828F is a highly prevalent cryptic mutation, which has an unknown origin, although likely due to shedding from chronically infected humans or animals [##REF##35115523##13##, ##REF##36240259##14##]. D571G, I587V, V772A, T941S, V1176F, K1191N, and Q1201K substitutions have not been characterized.</p>", "<p id=\"Par25\">Collectively, the mutations that have accumulated in the Spike gene are likely a response to the host’s innate and adaptive immune systems, and perhaps due to long-term persistence in an immunosuppressed patient and adaptation to any prophylactic or targeted drugs used to clear the infection [##REF##34431691##37##, ##REF##35958144##45##–##REF##37341553##47##]. The presence of previously identified cryptic mutations suggest that these mutations may predict a chronic infection. The goal of this work is not to identify the person(s) responsible for chronically shedding this virus. However, we would like to highlight the potential of wastewater surveillance and possibly fecal testing for identification of long COVID. This would be particularly useful if convergent mutations emerge during a chronic infection that are predictive of this condition. The spectrum of mutations might guide appropriate selection of antivirals and antibody-based therapies. Additional mutations outside of the Spike gene were also present in these samples but not analyzed for this manuscript. It is likely that mutations outside of the Spike gene are also important to facilitate chronic infection.</p>", "<p id=\"Par26\">In summary, these data support that an individual can be chronically infected with SARS-CoV-2 over many months and possibly a few years. During this time, SARS-CoV-2 can accumulate many mutations in the Spike gene, which concentrate in the RBD and NTD. Further research is needed to determine if these mutations are predictive of chronic infection and if they can be used as a biomarker in individuals with Long COVID and leveraged to tailor selection or development of pharmaceutical therapies. Additionally, this study shows that small WWTPs can enhance the resolution of rare biological events and allow for total reconstruction of viral genes and their corresponding proteins.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Central Michigan University (CMU) participated in a state-wide SARS-CoV-2 wastewater monitoring program since 2021. Wastewater samples were collected from on-campus sites and nine off-campus wastewater treatment plants servicing small metropolitan and rural communities. SARS-CoV-2 genome copies were quantified using droplet digital PCR and results were reported to the health department.</p>", "<title>Results</title>", "<p id=\"Par2\">One rural, off-campus site consistently produced higher concentrations of SARS-CoV-2 genome copies. Samples from this site were sequenced and contained predominately a derivative of Alpha variant lineage B.1.1.7, detected from fall 2021 through summer 2023. Mutational analysis of reconstructed genes revealed divergence from the Alpha variant lineage sequence over time, including numerous mutations  in the Spike RBD and NTD.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">We discuss the possibility that a chronic SARS-CoV-2 infection accumulated adaptive mutations that promoted long-term infection. This study reveals that small wastewater treatment plants can enhance resolution of rare events and facilitate reconstruction of viral genomes due to the relative lack of contaminating sequences.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12864-024-09977-7.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>", "<p>\n</p>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank MDHHS and MiNET for supporting wastewater collection, processing, and data analysis. We also thank the WWTP staff who provided samples every week during a pandemic. We thank CMU undergraduate assistants Justus Holben, Gabrielle Reau, Jessica Broach, Hamzah Khan, Jayde-Ann Taylor, Ashley Bergmooser, Kaitlyn Perry, Emily Rosema, and Alexis Bruce for their support. This is contribution number 197 of the Central Michigan University Institute for Great Lakes Research.</p>", "<title>Authors’ contributions</title>", "<p>MJC wrote the manuscript and directed the wastewater monitoring activities, HY and LAR analyzed FASTQ data and developed the heatmap, ASW and JDA performed all wastewater monitoring activities including submission of samples for NGS, MRW supported data analysis and submission to the health department and manuscript revision, RLU served as a liaison between wastewater treatment plants and student research assistants, and EWA assisted in data analysis and manuscript revision. MPN and RJL reanalyzed data and revised the manuscript during the peer review process.</p>", "<title>Funding</title>", "<p>Michigan Department of Health and Human Services (MDHHS).</p>", "<title>Availability of data and materials</title>", "<p>FASTQ files for each sample listed in Table ##TAB##0##1## are available in the NCBI SRA database (Submission ID: SUB13897431; BioProject ID: PRJNA1027333).</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par27\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par28\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par29\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>SARS-CoV-2 genome copies (GC)/100 mL wastewater detected at each weekly sample site from July 2021 to June 2023. Two letter site codes and dates are shown that correspond to sequenced samples and the variant that was identified in the highest relative abundance is indicated in parentheses. The colors and shapes associated with each sample are located in the graphical legend</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Heatmap showing the percent prevalence of novel and previously identified cryptic mutations (*) in each wastewater sample that was positive for the Alpha variant lineage [##REF##35115523##13##, ##REF##36240259##14##]. Empty cells represent mutations that had fewer than 3 reads</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Novel mutations present in the (<bold>A</bold>, <bold>D</bold>) 2021, (<bold>B</bold>, <bold>E</bold>) 2022, and (<bold>C</bold>, <bold>F</bold>) 2023 consensus Spike proteins were mapped onto the furin cleaved spike protein of SARS-CoV-2 with one RBD erect represented as red Corey-Pauling_Koltun (CPK) spheres using UCSF Chimera [##REF##32647346##19##]</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>GT molecular variant calling</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Location code</th><th align=\"left\">Sample date</th><th align=\"left\">VOC (%)<sup>a</sup></th><th align=\"left\">Lineage(s) (%)<sup>b</sup></th></tr></thead><tbody><tr><td align=\"left\">VM</td><td align=\"left\">9-21-21</td><td align=\"left\">Delta (98.4)</td><td align=\"left\">AY.25.1 (84.8)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">10-26-21</td><td align=\"left\">Alpha (94.2)</td><td align=\"left\">Q.3 (94.2)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">11-9-21</td><td align=\"left\">Alpha (94.9)</td><td align=\"left\">Q.4 (94.7)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">3-14-22</td><td align=\"left\">Omicron (93.8)</td><td align=\"left\">XBB.2.3.11 (74.3)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">4-25-22</td><td align=\"left\">Omicron (95.1)</td><td align=\"left\"><p>XBB.1.5.81 (17.7)</p><p>XBB.1.16.1 (17.5)</p><p>XBB.1.5.10 (15.0)</p><p>EG.5 (7.7)</p><p>XBB.1.5.72 (7.4)</p><p>GJ.1.2 (5.9)</p><p>FD.1.1 (5.1)</p></td></tr><tr><td align=\"left\">VM</td><td align=\"left\">9-12-22</td><td align=\"left\">Alpha (97.3)</td><td align=\"left\">Q.4 (96.9)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">3-13-23</td><td align=\"left\">Alpha (98.0)</td><td align=\"left\">Q.4 (65.5)</td></tr><tr><td align=\"left\" rowspan=\"3\">VM</td><td align=\"left\" rowspan=\"3\">3-27-23</td><td align=\"left\">Omicron (27.1)</td><td align=\"left\">Q.4 (47.1)</td></tr><tr><td align=\"left\" rowspan=\"2\">Alpha (47.1)</td><td align=\"left\">B.1.1.28 (16.2)</td></tr><tr><td align=\"left\">XBB.1.5.49 (7.9)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">4-24-23</td><td align=\"left\">Alpha (97.9)</td><td align=\"left\">Q.4 (89.7)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">5-1-23</td><td align=\"left\">Alpha (97.4)</td><td align=\"left\">Q.4 (97.1)</td></tr><tr><td align=\"left\">VM</td><td align=\"left\">5-15-23</td><td align=\"left\">Alpha (96.6)</td><td align=\"left\">Q.4 (93.8)</td></tr><tr><td align=\"left\" rowspan=\"2\">C6</td><td align=\"left\" rowspan=\"2\">1-2-22</td><td align=\"left\">Omicron (89.9)</td><td align=\"left\">BA.1.1 (82.5)</td></tr><tr><td align=\"left\">Delta (7.6)</td><td align=\"left\">B.1.617.2 (7.3)</td></tr><tr><td align=\"left\">CA</td><td align=\"left\">6-6-22</td><td align=\"left\">Omicron (99.8)</td><td align=\"left\">BG.5 (99.8)</td></tr><tr><td align=\"left\">MP</td><td align=\"left\">2-20-23</td><td align=\"left\">Omicron (98.4)</td><td align=\"left\">XBB.1.5 (45.1)</td></tr><tr><td align=\"left\" rowspan=\"4\">CL</td><td align=\"left\" rowspan=\"4\">2-28-23</td><td align=\"left\" rowspan=\"4\">Omicron (99.1)</td><td align=\"left\">DT.2 (49.9)</td></tr><tr><td align=\"left\">BQ.1.1 (16.1)</td></tr><tr><td align=\"left\">BQ.1.1.37 (16.1)</td></tr><tr><td align=\"left\">BQ.1.1.52 (16.1)</td></tr><tr><td align=\"left\" rowspan=\"5\">UT</td><td align=\"left\" rowspan=\"5\">4-3-23</td><td align=\"left\">Omicron (86.5)</td><td align=\"left\">XBB.1.5 (19.6)</td></tr><tr><td align=\"left\" rowspan=\"4\">Delta (7.4)</td><td align=\"left\">XBB.1.5.23 (15.9)</td></tr><tr><td align=\"left\">XBB.1.28 (15.6)</td></tr><tr><td align=\"left\">XBB.1.5.1 (8.2)</td></tr><tr><td align=\"left\">XBB.1.5.17 (7.5)</td></tr><tr><td align=\"left\">CE</td><td align=\"left\">4-10-23</td><td align=\"left\">Alpha (89.0)</td><td align=\"left\">Q.4 (88.8)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>SARS-CoV-2 Alpha variant Q.3/Q.4 clinical sequence from Michigan</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Accession</th><th align=\"left\">Organism</th><th align=\"left\">Pangolin</th><th align=\"left\">Geo location</th><th align=\"left\">Host</th><th align=\"left\">Isolation source</th><th align=\"left\">Collection date</th></tr></thead><tbody><tr><td align=\"left\">OL892482</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">swab</td><td align=\"left\">2/18/2021</td></tr><tr><td align=\"left\">MZ158978</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">3/29/2021</td></tr><tr><td align=\"left\">MW991267</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">3/31/2021</td></tr><tr><td align=\"left\">MZ025257</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">4/4/2021</td></tr><tr><td align=\"left\">OL812274</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">swab</td><td align=\"left\">4/8/2021</td></tr><tr><td align=\"left\">MZ071109</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">oronasopharynx</td><td align=\"left\">4/12/2021</td></tr><tr><td align=\"left\">MZ131434</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">oronasopharynx</td><td align=\"left\">4/16/2021</td></tr><tr><td align=\"left\">OL803302</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">swab</td><td align=\"left\">4/23/2021</td></tr><tr><td align=\"left\">MZ416155</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">oronasopharynx</td><td align=\"left\">5/12/2021</td></tr><tr><td align=\"left\">MZ353922</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">oronasopharynx</td><td align=\"left\">5/20/2021</td></tr><tr><td align=\"left\">OK296641</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">5/24/2021</td></tr><tr><td align=\"left\">OK233076</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">oronasopharynx</td><td align=\"left\">5/25/2021</td></tr><tr><td align=\"left\">OK292910</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">6/12/2021</td></tr><tr><td align=\"left\">OK187847</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">6/18/2021</td></tr><tr><td align=\"left\">MZ780743</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">6/18/2021</td></tr><tr><td align=\"left\">MZ728995</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.3</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">7/9/2021</td></tr><tr><td align=\"left\">MZ025226</td><td align=\"left\">SARS-CoV-2</td><td align=\"left\">Q.4</td><td align=\"left\">USA: Michigan</td><td align=\"left\">Homo sapiens</td><td align=\"left\">unknown</td><td align=\"left\">4/3/2021</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup>Relative abundance of variants of concern (VOC) as a percentage</p><p><sup>b</sup>Relative abundance of VOC lineages as a percentage</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12864_2024_9977_Fig1_HTML\" id=\"d32e740\"/>", "<graphic xlink:href=\"12864_2024_9977_Fig2_HTML\" id=\"d32e1056\"/>", "<graphic xlink:href=\"12864_2024_9977_Fig3_HTML\" id=\"d32e1094\"/>" ]
[ "<media xlink:href=\"12864_2024_9977_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Supplemental Table 1.</bold> MEGA and FastQC analyses of wastewater samples positive for an Alpha variant lineage.</p></caption></media>", "<media xlink:href=\"12864_2024_9977_MOESM2_ESM.docx\"><caption><p><bold>Additional file 2: Supplemental Figure 1.</bold> Clustal Omega alignment of reconstructed 2021, 2022, and 2023 Spike proteins with reference and consensus Alpha variant Q.3 clinical sequence Spike proteins.</p></caption></media>", "<media xlink:href=\"12864_2024_9977_MOESM3_ESM.docx\"><caption><p><bold>Additional file 3: Supplemental Figure 2.</bold> Clustal Omega alignment of reconstructed 2021, 2022, and 2023 Spike proteins with reconstructed Spike protein from CE 4-10-23. Mutations unique to CE-4-10-23 are highlighted in grey.</p></caption></media>" ]
[{"label": ["5."], "mixed-citation": ["Jarvie M, Reed M, Southwell M, Wright B, Nguyen D, Ngoc T. Thi. RT-ddPCR Wastewater monitoring of COVID-19 across the Eastern upper Peninsula of Michigan. SSRN. 2022."]}]
{ "acronym": [], "definition": [] }
47
CC BY
no
2024-01-14 23:43:46
BMC Genomics. 2024 Jan 13; 25:59
oa_package/f8/0d/PMC10787452.tar.gz
PMC10787453
0
[ "<title>Introduction</title>", "<p id=\"Par6\">During the COVID-19 pandemic the Dutch national government took measures to prevent and reduce the number of COVID-19 infections. These included social measures (e.g., distancing, visitor restrictions), hygiene measures and a test, trace and isolate strategy for those who showed COVID-19 symptoms. These measures have had a large impact on society. Many studies already examined the effects of such measures on well-being. For example, feelings of loneliness were higher during stricter measures related to social contacts [##UREF##0##1##–##REF##37408335##3##]. Some studies showed marked fluctuations in mental health during different periods of the pandemic; i.e., a decline in mental health after stringency of measures increased and an improvement after measures relaxed [##UREF##2##4##–##UREF##6##8##]. People indicated this was partly because of missing friends and family due to the restrictions on social contacts.</p>", "<p id=\"Par7\">One of the preventive measures that impacted social life during the pandemic was the visitor restriction policy (hereafter referred to as VRP); i.e., governmental advice to limit the number of household visitors per day (see Fig. ##FIG##0##1## and Appendix ##SUPPL##0##1## for the VRP per period). Compared to other measures, VRP might be considered as a measure with great impact on daily life, as it hinders social contact which is important for well-being. Complying with social distancing measures, like VRP, requires a large effort, therefore, it is defined as a high-cost measure [##REF##34345009##9##]. Several international studies reported on the adherence to these measures [##REF##34710125##10##–##REF##34521650##13##]. Mobility data showed that lockdown policies and vaccination impacted household visitation patterns. During the first lockdown a strong reduction in household visitations was observed. After relaxation of the VRP visitations increased again. Interestingly, during following lockdowns with reinforced VRP, there was a less strong decline in household visitation (i.e., lower adherence to the rules), which might be explained by multi-lockdown fatigue and inconsistent policy over time [##UREF##7##11##]. Other studies stated that compliance with social restriction rules (e.g., avoiding gatherings and going out, physical distancing) requires major behavior changes [##UREF##7##11##, ##UREF##8##14##].</p>", "<p id=\"Par8\">Altogether, many studies have been conducted over the past two years regarding the general impact of COVID-19 measures on well-being. However, there is a lack of qualitative studies on individuals’ responses to changing COVID-19 measures over time and their well-being, specifically regarding VRP. Since VRP might be an impactful measure, it is relevant to examine further. The current study therefore aimed to examine how people experienced the VRP during different phases of the pandemic and how it affected their well-being. Qualitative studies provide insight into the underlying reasons and considerations people might have to cope with and comply with VRP and its impact on well-being. We examined how people cope with the VRP over a longer period and how it affects their well-being, by following a cohort of 15 interviewees for 21 months during the COVID-19 pandemic (May 2020 (start of the Corona Behavior Unit)-December 2021 (end of funding)) in 12 interview rounds.</p>" ]
[ "<title>Methods</title>", "<title>Study design and recruitment</title>", "<p id=\"Par9\">This study used an empirical and iterative research design. We conducted a research in an pandemic. Given the crisis situation and the rapidity of implementing the measures we had to be flexible and act on the situation with the information and capacity that was available.</p>", "<p id=\"Par10\">For the first interview round (May 1st, 2020) 34 individuals were selected from participants of the COVID-19 questionnaire ‘research on behavioral measures and well-being’ [##UREF##9##16##] of the RIVM (National Institute for Public Health and the Environment), GGD GHOR Nederland (Association of Regional Public Health Services and Regional Medical Emergency Preparedness and Planning offices in the Netherlands)and 25 GGD’s (Municipal Health Service) [##UREF##1##2##]. In the first round of the questionnaire, ‘research on behavioral measures and well-being’, participants were asked if they were willing to participate in further in-depth research. Among the participants who agreed, we selected a sample of 36 participants, based on the capacity of the team of researchers. Of the 36 participants we eventually interviewed 34 participants. Two participants could not be reached. This selection was based on the participants’ age, education, urban or rural living environment, health situation and current living situation, of which a random sample was invited to participate in the interviews. These background factors were selection because the research thought those factors that could explain adherence and non-adherence to the measures taken by the government. During the first interview round, interviewees were asked if they were willing to participate in an interview cohort. They all agreed. For the cohort, we attempted to create an optimal distribution of age, gender, education, place of living (geographical distribution in the Netherlands and distribution of rural and urban areas), well-being and compliance with COVID-19 measures (Table ##TAB##0##1##). Therefore, 17 out of 34 participants were selected to participate in the cohort. Although the original number of interviewees was higher, due to the aims of this research and capacity of the research team, we focused only on the cohort interviewees (<italic>n</italic> = 17), since our goal was to examine the effects of changing the VRP over time on the behavior of the participants and how they coped with the changes. This study was conducted following the RIVM guidelines and regulations. In line with the Central Committee on Research Involving Human Subjects (see <ext-link ext-link-type=\"uri\" xlink:href=\"https://english.ccmo.nl/\">https://english.ccmo.nl/</ext-link>), the questionnaire study does not meet the requirement of the Law for Research Involving Human Subjects (WMO) and was exempted from formal ethical review. Informed consent was obtained from all interviewees included in the study. All interviews were recorded with the consent of the interviewee and participants gave consent for publishing their anonymized answers.\n</p>", "<p id=\"Par11\">Two interviewees dropped out during the interview period. One dropped out because of workload, the other did not give a reason. Therefore 15 interviewees were included in this study, who were interviewed at 12 time points.</p>", "<title>Data collection</title>", "<p id=\"Par12\">Data was collected between 1 May 2020 and 1 December 2021. The intervals between the 12 interviews varied. At the start of the pandemic many measures were implemented by the government. During certain periods, communication from the government about COVID-19 and the frequency of changing the measurements decreased. The frequency of interviewing changes accordingly. During the 21-month research period there were phases of strengthening and relaxation of measures (see Fig. ##FIG##0##1## and Appendix ##SUPPL##0##1##). As mentioned before, we used an iterative design, because we had to be flexible due to the crisis situation that was unpredictable. So we could keep up with developments in the Netherlands and deepen the relevant results of the previously mentioned quantitative questionnaire.</p>", "<p id=\"Par13\">Every round a team of eight researchers conducted semi-structured telephone interviews over a five-day period. Interviews were recorded with the consent of the interviewee. Interviewers and interviewees were paired. Therefore, the interviewer was aware of the story of the interviewee and a relation based on trust was built between them.</p>", "<p id=\"Par14\">In total 176 interviews were conducted. Four interviews were missed by interviewees, because of health problems, vacation or a lack of time due to a heavy workload. Interviews were transcribed verbatim. Anonymized data can be requested by the first author upon reasonable request.</p>", "<title>Instruments</title>", "<p id=\"Par15\">Every round an interview guide was developed that was adapted and updated to the COVID-19 related situation at that time, to deepen the outcome of relevant results of the cohort questionnaire, to containing the most urgent and relevant themes for policy in the Netherlands. Before starting the interviews, the interview-guide was discussed with the interviewers. Since individuals were followed over time, we were able to monitor developments in well-being, reported behavior and thoughts regarding COVID-19 measures. Additionally, questions were asked about plans interviewees made for meeting their social contacts (e.g., for Christmas, birthdays), and their experiences, actual behavior and motivation afterwards. Interpretations of some interviewees’ responses about their compliance and well-being were verified by the interviewers during later interviews.</p>", "<title>Well-being</title>", "<p id=\"Par16\">Every interview round interviewees were asked about their general well-being: i.e., how they were doing and whether there has been a change in their situation since the previous interview regarding their health, well-being, life, employment status and relationship(s). In different interview rounds questions were asked about well-being in relation to the measures at that time, the interviewees’ individual situation and the general situation of the pandemic.</p>", "<title>Visitor restriction policy</title>", "<p id=\"Par17\">Questions about the VRP were specifically asked in round 2, 3, 6, 8, 9, 11 and 12. The VRP was only included in the interview guide if there was a change in the VRP rule. Interviewees were asked how they dealt with the VRP (excluding school, hospital, nursing home and all other assisted living medical facilities) and under what conditions they visited or received visitors at home. In other rounds, some interviewees mentioned the (impact of) VRP without specifically being asked about it.</p>", "<p id=\"Par18\">Examples of questions about the VRP:<list list-type=\"bullet\"><list-item><p id=\"Par19\">Round 8: What measures are you thinking of in relation to the holidays?</p></list-item><list-item><p id=\"Par20\">Round 9: How does the lockdown affects you (regarding social distancing and the VRP of 2 people)?</p><p id=\"Par21\">Round 12: You may now invite a maximum of 4 visitors to your home. This number has been adjusted several times in the corona pandemic:<list list-type=\"bullet\"><list-item><p id=\"Par22\">How do you handle this measure in practice? -Is this different from what you did before?</p></list-item><list-item><p id=\"Par23\">What is it like for you to move back along with the constantly changing number of people you may receive in your home?</p></list-item></list></p></list-item><list-item><p id=\"Par24\">Round 12: Do you have any activities or events planned in the next few weeks where you expect the visitor measure to fray? If so, how will you handle them?</p></list-item></list></p>", "<title>Analysis</title>", "<p id=\"Par25\">Interviews from round 1 to 9 were coded in MAXQDA by five research-assistants from the Radboud University under supervision of PS, JE and FA. They used a codebook developed by PS, JE and FA, based on the Health Belief Model, the COVID-19 measures, social dilemma theory and themes mentioned by the interviewees like well-being [##UREF##9##16##]. A conceptual framework about the VRP was not available at that time, as most studies found in literature date from the period after the interviews had started. During the encoding process the research-assistants discussed their findings with PS, JE and FA and coded each other’s interviews four times for interrater reliability.</p>", "<p id=\"Par26\">The research-assistants were only available to code the transcripts of round 1 to 9. Because of lack of capacity round 10 to 12 were coded by focusing specifically on VRP (by researchers FA and AG). Next, all relevant codes in MAXQDA related to VRP and well-being were selected. Two researchers simultaneously checked if the selected fragments were indeed relevant and related to well-being, compliance and thoughts in relation to VRP.</p>", "<p id=\"Par27\">The analysis was conducted using a thematic framework to structure high number of coded segments [##UREF##10##17##]. This framework showed several factors related to compliance and well-being, which will be described in the results. Both inductive and deductive methods were used. During analysis new themes were added to the framework. Both the storylines of each interviewee and the different phases of the pandemic were analyzed.</p>" ]
[ "<title>Results</title>", "<p id=\"Par28\">When looking at the impact of the changing VRP on compliance and well-being of interviewees we observed that people dealt with it in very different ways as the impact on self-reported well-being also differed between interviewees. Some strictly adhered to the measure while others sometimes deviated from it, and some suffered mentally while others did not experience any problems. Results showed that the way in which interviewees dealt with VRP could be classified into four different categories. These four categories are based on a combination of interviewees’ reported level of impact on well-being (low to high) and level of compliance (low to high) (see Fig. ##FIG##1##2##).</p>", "<p id=\"Par29\">These four categories were labeled as ‘Resilient-Followers’, ‘Resilient-Rulebreakers’, ‘Suffering-Followers’ and ‘Suffering-Rulebreakers’. ‘Resilient’ and ‘Suffering’ refer to the degree of impact of the VRP on well-being, ‘Followers’ and ‘Rulebreakers’ refer to the level of compliance to the VRP restrictions. It should be noted that these categories are not fixed, but gradual. Also the interviewees could deviate from the classified category in some rounds. Two researchers (FA and AG) independently assigned each interviewee to one of the categories, based on the initial interview, which showed full agreement. Additionally, the assigned category was verified with each interviewee in the last interview. All interviewees could relate to/agreed to their assigned category. For each category, we examined how interviewees dealt with the VRP during the pandemic. We analyzed factors that played a role in (non)compliance and looked at the impact on well-being. Different factors played a role in the four different categories (see Table ##TAB##1##2##), which are discussed in detail following the timeline of the pandemic below.\n</p>", "<title>Spring 2020 (May–June 2020) – increased stringency of VRP (three visitors) (<italic>N</italic> = 15)</title>", "<p id=\"Par30\">For all categories different motivations for (non)compliance were observed. For Resilient-Followers, risk perception played a major role in compliance. Interviewees complied with the measure because they were afraid of a COVID-19 infection and/or belonged to a high-risk group (because of health problems or higher age). Even though they missed their contacts, they considered being careful not to get COVID-19 as more important.</p>", "<p id=\"Par32\">When it comes to compliance, several Resilient-Followers had a clear goal in mind: their own protection. In addition, interviewees mentioned that you 'just have to follow the government rules’. A few interviewees indicated that their social circle is small, so their existing social structures were not disrupted by VRP and, therefore, compliance required little to no adjustments. The well-being of Resilient-Followers was not (or hardly) affected by the measure, even though interviewees did miss having social contact. Acceptance of the situation seemed to play a role; Resilient-Followers seemed able to be resigned to the situation.</p>", "<p id=\"Par34\">Resilient-Rulebreakers did not always comply with the measure. However, they believed they could reduce the risk by carefully making a risk assessment of the people they meet (e.g., only people with low-risk behavior). The measure had little impact on their well-being, partly because they did not strictly comply with the measure, but also because the measure provided social rest, despite missing social contacts.</p>", "<p id=\"Par36\">Suffering-Followers did comply with the measure, but it had a substantial impact on well-being from the beginning of the pandemic.</p>", "<p id=\"Par38\">Several Suffering-Followers indicated they have many social contacts and were used to meeting in groups. Their social structures were disrupted by the measure and the adjustment they had to make was considerable. For example, one of the interviewees met with a large group of friends online, but digital contact compromised the quality of the contact:</p>", "<p id=\"Par40\">Despite the impact the measure had on well-being (such as feeling sad, depressed or anxious), Suffering-Followers still managed to stay compliant. They had several motives to comply, for example risk perception, wanting to follow government rules and working in healthcare.</p>", "<p id=\"Par42\">For Suffering-Rulebreakers the measure also had a great impact on well-being, but unlike Suffering-Followers, Suffering-Rulebreakers did not always comply with the measure, for various reasons. First, they tried to find a balance between compliance and well-being.</p>", "<p id=\"Par44\">Second, interviewees considered it safe or ‘okay’ to invite more people if they were able to keep a distance and no one showed symptoms.</p>", "<p id=\"Par46\">Third, interviewees indicated that the rule did not fit someone’s social structure.</p>", "<p id=\"Par48\">Fourth, several Suffering-Rulebreakers indicated that, like Suffering-Followers, they had many social contacts and were used to meeting in groups. The VRP had such a large impact on their existing social structures and, therefore, their well-being, that Suffering-Rulebreakers deviated from the measure to meet their social needs. The analysis showed that interviewees felt better as a result.</p>", "<p id=\"Par50\">Fifth, Suffering-Rulebreakers trusted family and friends would not have the virus.</p>", "<p id=\"Par52\">Lastly, the people in the social environment of Suffering-Rulebreakers usually did not comply to the VRP, which allowed people to deviate from the measure together.</p>", "<p id=\"Par53\">It should be noted that Rulebreakers in this cohort did try to comply with the measure at least a little. A high-risk perception was a reason to not completely disregard the measure. For example, interviewees worked in healthcare or had vulnerable people in their social environment. Instead of following the measure as prescribed, interviewees made their own well-considered risk assessment and interpreted the measure in their own way, to safeguard their well-being or because a rule did not make sense to them. In that way, they could justify their non-compliance, as for them, it felt like the right or logical thing to do.</p>", "<title>Summer 2020 (June – September 2020) <italic>– </italic>relaxation of VRP (no restrictions) (<italic>N</italic> = 15)</title>", "<p id=\"Par54\">When the measure was relaxed, especially the Suffering groups experienced mental relief. They immediately felt better and frequently met with friends again.</p>", "<p id=\"Par56\">Although Resilient-Followers did not feel negative towards relaxation of the measure, they remained cautious about seeing others. Some interviewees remained stricter than the measure prescribed.</p>", "<p id=\"Par58\">This also applied to a few Suffering-Followers, who remained cautious because of their work.</p>", "<title>Fall/ winter (October 2020-January 2021) – increased stringency of VRP (from max. six to three, two, one visitor) (October – November 2020 <italic>N</italic> = 15 and January 2021 <italic>N</italic> = 13)</title>", "<p id=\"Par60\">When the VRP was reinforced as infection rates rose, Resilient-Followers complied with the measure again without difficulty. They accepted the new situation and adapted easily. Appointments that no longer fit the current measure were cancelled. For some interviewees compliance was easy, because they had a small social circle.</p>", "<p id=\"Par62\">For Resilient-Rulebreakers, reinforcement of the measure did not have much impact on well-being either. Regarding compliance they indicated they were particularly selective about the people they chose to meet. However, the Suffering groups, who were frequently making appointments with groups of friends when there were no restrictions, faced severe challenges when the number of visitors was limited again. As the measure lasted longer and the number of visitors was limited further, it became increasingly difficult. For example, one of the younger Suffering-Followers indicated:</p>", "<p id=\"Par64\">These interviewees especially struggled with the rule because the maximum number of visitors did not match the number of friends they usually met. Suffering-Followers complied with the rule: they met others in smaller groups or sought creative solutions such as meeting online. Suffering-Rulebreakers, however, deviated from the rule when it disrupted their usual social structure. For several interviewees it did not feel right to exclude people who belonged to the same group. One Suffering-Rulebreaker said:</p>", "<p id=\"Par66\">He chose to deviate from the rule because not seeing his group of friends had more impact on him than getting COVID-19.</p>", "<p id=\"Par68\">Another interviewee mentioned that she chose ‘customization’ of the measure and weighed the risk:</p>", "<title>Christmas and birthdays</title>", "<p id=\"Par70\">During Christmas 2020, the VRP was relaxed and allowed three visitors (instead of two). The measure had a great impact on interviewees’ usual traditions and the setting in which one normally celebrated Christmas. In practice, interviewees dealt with the measure differently. Followers, for example, adjusted their Christmas celebrations to the maximum number of visitors that was allowed, celebrated it in small groups spread over several days or celebrated it online.</p>", "<p id=\"Par72\">Resilient-Rulebreakers indicated they did not strictly adhere to the allowed number of visitors. They reasoned that the spreading of visitors had the same risk as seeing each other at the same time. In terms of risk, three people were considered the same as three households.</p>", "<p id=\"Par74\">One Suffering-Rulebreaker indicated she would not strictly adhere to the number if it would mean excluding family members:</p>", "<p id=\"Par76\">Several interviewees thought about which household it would be best to celebrate Christmas; the largest house would facilitate distancing, which would justify a few more visitors.</p>", "<p id=\"Par77\">Most Resilient-Followers looked at the restrictions with Christmas level-headed; Resilient-Rulebreakers had mixed feelings, but also experienced social rest; the Suffering groups thought about Christmas as ‘not so much fun’, ‘unhappy’, ‘tough’, ‘disappointing’ and ‘very unfortunate’. Several interviewees noted that you must make something of it yourself. Some also found it quieter and less running around.</p>", "<p id=\"Par78\">Regarding birthdays, interviewees also dealt with the VRP in various ways. Some interviewees cancelled their birthdays, others had a 'split birthday', which meant the birthday was celebrated in time blocks. For example, one Suffering-Follower described:</p>", "<title>Mental breaking-point: one visitor</title>", "<p id=\"Par80\">A mental breaking-point for the Suffering groups was the moment when the VRP allowed only one visitor (20 January 2021–28 April 2021). Suffering-Followers continued to comply with the measure (because of risk perception, following the government rule and working in healthcare), but the mental price they had to pay was increasing. For example, one of the interviewees experienced deep disappointment and sadness when she had to adjust the plans she made for the umpteenth time:</p>", "<p id=\"Par82\">Another interviewee mentioned the uncertainty of whether scheduled appointments could continue, caused psychological pressure:</p>", "<p id=\"Par84\">Whereas with a maximum of two or three visitors it was still possible to have some social contacts, with only one visitor allowed, the limit seemed to have been reached among interviewees. For example, one interviewee said:</p>", "<p id=\"Par86\">Despite the large impact on well-being, Suffering-Followers continued to comply with the measure. Suffering-Rulebreakers, on the other hand, deviated more and more from the measure for the sake of their well-being; by deviating and making the rule 'fit', they felt better.</p>", "<p id=\"Par87\">For many interviewees, in all groups, the VRP of one did not make sense anymore and was ‘practically inconvenient’. In many cases visitors come in pairs, for example if you want to invite a couple, your parents, your sister and her partner etc. Interviewees asked themselves why they were only allowed to invite one visitor and not one household, as according to them the risk of getting infected with COVID-19 would be the same. In practice, for Rulebreakers this resulted in relaxing the measure to allow one household instead of one person.</p>", "<p id=\"Par89\">Resilient-Followers looked at the measure level-headed, but found it practically inconvenient (e.g., if they wanted to invite a couple), but this did not lead to rule-breaking. One interviewee explained:</p>", "<title>Spring/summer (April-August 2021) – relaxation of VRP (max. two visitors, no restrictions) (<italic>N</italic> = 14)</title>", "<p id=\"Par91\">For the Suffering groups, relaxation of the VRP from one to two visitors immediately led to improved well-being. Also, among Resilient-Followers people were happy with this small relaxation of the measure, but they were also levelheaded about it.</p>", "<p id=\"Par93\">In the summer of 2021, there was a period without VRP. Interviewees in all categories took advantage of the relaxation, except for two Resilient-Followers for whom, due to a small social circle, it didn’t change much. Some of the Suffering groups met with large friend groups again. It was remarkable that several Followers indicated they did meet more friends, but they still received limited visitors at home. Risk perception due to, for example, vulnerable health or work played a role in this.</p>", "<p id=\"Par95\">For several interviewees, being vaccinated – which might be a new ‘factor’ in making considerations in spring/summer 2021 – was not a reason to stop being cautious. Particularly within Resilient-Followers, interviewees took someone's vaccination status into account when meeting; some preferred to meet only with people who have been vaccinated.</p>", "<p id=\"Par97\">This is also the case for Resilient-Rulebreakers, who assessed the risk of the situation and people they met.</p>", "<title>Fall (November 2021) – increased stringency of VRP (max. four visitors) (<italic>N</italic> = 15)</title>", "<p id=\"Par99\">After a summer with no VRP, the measure was introduced again in the fall of 2021, stating a maximum of four visitors. Resilient-Followers again had no difficulty in complying with the measure and it did not affect their well-being. They accepted the situation and again complied because of risk perception. Additionally, interviewees rarely met with more than four people, which made compliance easier. This also applied to Resilient-Rulebreakers. The pandemic changed formerly busy social schedules, which were now preferably quieter.</p>", "<p id=\"Par101\">Interviewees indicated that if the restriction changes to less than four visitors, there was a chance they would no longer comply to the measure, as they did earlier. Almost all Suffering-Followers complied with the measure again. Some had no problems with it, because they rarely invited more than four people at a time.</p>", "<p id=\"Par103\">For others, the measure did affect well-being, but this was not a reason for non-compliance because of risk perception, a wish to follow the government rules and working in healthcare. For a few Suffering-Followers their ‘compliance limit’ was reached when the measure was reintroduced. Although they managed to comply throughout the pandemic despite the significant effect on well-being, now the measure was no longer followed. The interviewees did not completely disregard the measure, but they made different considerations than before. One interviewee mentioned that he invited just a little more people than the rule prescribed, because he and the people around him have been vaccinated and did a self-test beforehand.</p>", "<p id=\"Par105\">The other Suffering-Follower interviewee indicated she struggled so much with having this measure implemented for the umpteenth time, that the VRP no longer determined her decisions. She looked at what number of visitors felt right.</p>", "<p id=\"Par107\">Suffering-Rulebreakers indicated they experienced little inconvenience when the measure was introduced again. For them, it did not change much, mostly because they did not strictly comply with the measure anyway. Some of them still complied with the measure 'a little'. For example, one interviewee indicated that he applied for a maximum of ten visitors, because that did not feel like a major restriction and because it allowed him to see his group of friends. He considered social contact as more important than compliance, because it was necessary for his mental well-being.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par109\">The goal of this descriptive qualitative study was to examine the impact of the visitor restriction policy on compliance and well-being by following a cohort of 15 interviewees during the COVID-19 pandemic. The VRP appeared to be a measure with substantial impact on well-being for some and showed fluctuating compliance, in which feasibility and frequent changes in the VRP played a role.</p>", "<p id=\"Par110\">When looking at well-being (Suffering/Resilient) and compliance (Followers/Rulebreakers), four different categories of people could be identified, who coped with the VRP in different ways and for different reasons. Both Following groups complied mainly because of risk perception and cue to action from the government, which seem to correspond with predictors of behavior from the Health Belief Model: perceived severity, susceptibility and cue to action [##UREF##11##18##]. The main difference between Resilient-Followers and Suffering-Followers was that the Resilient group accepted the situation and was not much affected in their well-being, while the Suffering group experienced a negative impact. Rulebreakers, on the other hand, did not always comply with the VRP. Both Rulebreaking groups made their own risk assessment, deviated when the measure was not considered logical to them and if the rule did not fit into their social structures. The main difference between Suffering-Rulebreakers and Resilient-Rulebreakers was that Suffering-Rulebreakers mainly deviated from the measure because they tried to find a balance between compliance and their well-being, while Resilient-Rulebreakers did not experience an impact on well-being.</p>", "<p id=\"Par111\">A main finding of this study is that for most interviewees, especially among the Suffering groups, the VRP was perceived as an impactful measure, since it disrupted social structures. This is in line with previously mentioned studies, stating that social distancing rules require large behavior changes and are experienced as a high-cost measure [##REF##34345009##9##, ##UREF##8##14##]. To miss out on important family meetings, support and closeness from friends and family had a negative effect on well-being. Suffering-Rulebreakers felt not seeing friends had a larger impact than getting infected would having); rule-breaking gave mental relief. Maintaining mental health and well-being as a reason for non-adherence is also found in literature [##UREF##12##19##]. Additionally, for some, non-adherence seems caused by the need to take control over their lives [##REF##34710125##10##]. As seen among Suffering-Rulebreakers, they deviate to take control over their social needs and to keep themselves mentally healthy.</p>", "<p id=\"Par112\">Another finding is that well-being seemed closely related to the number of visitors that was allowed, which showed a clear breaking point for all interviewees, including the most compliant ones. One visitor per day made it difficult to maintain existing social structures and felt not logical for most interviewees. Interviewees indicated that well-being improved when more visitors were allowed; four visitors was considered practically feasible, since most interviewees were used to inviting a maximum of four visitors, also before the COVID-19 pandemic. When less visitors were allowed, most interviewees showed a decrease in compliance and/or well-being, except for Resilient-Followers, for whom the number of visitors hardly affected well-being and compliance.</p>", "<p id=\"Par113\">It also appeared that the frequent changes in the VRP negatively impacted well-being, future perspective and resilience of the Suffering groups. They were constantly challenged to change their plans when the VRP changed. While Suffering-Followers remained compliant, this was a reason for Suffering-Rulebreakers to deviate from the rule. This is in line with another study that found when policy decisions were experienced as too changeable, adherence might be affected [##REF##34710125##10##]. This is, according to Williams et al. (2021) also the case for inconsistent and confusing rules, which we also found as a reason for non-compliance in both Rulebreaking groups. Only Resilient-Followers easily adjusted to the fluctuating pattern of the VRP, where acceptation of the situation seemed to play a role.</p>", "<p id=\"Par114\">We took then background factors, age, gender, educational level, urban or rural living environment, health situation and current living situation of the participants into account when selecting the participants. However, we couldn’t see clear differences in our data when looking at background factors. Due to the small sample, examining the impact of demographic factors is difficult.</p>", "<p id=\"Par115\">Although research [##UREF##7##11##] showed that youngsters did not always adhere to the rules, possibly because of their lower risk perception, in our study we see that the youngsters adhered to the rules. They had responsible jobs, or didn’t want to be the reason their grandparents got infected. Therefore, our data does not support this general observation. The youngsters in our research met more people then allowed because of their social structures. And when they met more people then allowed, the risks were calculated. The small sample could also be the reason we couldn’t conclude that being young and therefore belonging to a low risk-group was a reason for non-adherence to the VRP. Lastly, the four categories were quite stable during the various phases of the pandemic, meaning overall, interviewees continued to behave in a similar way, for similar reasons. Only a few interviewees ‘switched’ to another category (i.e., Suffering-Followers to Suffering-Rulebreakers) in the autumn of 2021 (the last period of stricter VRP). For some interviewees well-being was a decisive factor in the decision to stop complying. The long duration of the pandemic and repeated introduction of the VRP made that they could no longer cope. For some, vaccination played a role. It made them feel safe, which resulted in a lower risk perception and, therefore, different considerations regarding compliance. Also in other groups we observed new factors over time like vaccination (e.g., only inviting people who have been vaccinated or feeling more safe) and self-tests that influenced behavior. However, for some, vaccination was no reason to be less careful.</p>", "<title>Implications</title>", "<p id=\"Par116\">Firstly, this study showed that the stringency of the VRP has a clear limit when it comes to well-being and compliance. During the winter of 2020–2021, when the VRP allowed one visitor, many interviewees showed a mental breaking-point. The restriction of one visitor had a great impact on well-being and showed consequences for compliance and support for the policy. For example, many interviewees mentioned that the policy was not logical anymore. They considered one visitor as risky as multiple visitors, when they are part of the same household. Thus, when it is difficult to understand why a certain VRP is implemented, support might be lower, possibly resulting in lower compliance. During future pandemics, it is therefore important to explain why certain choices are made. Additionally, policymakers should keep in mind that the VRP should be practically feasible to prevent non-compliance. For example, many interviewees often invited two people at the same time (e.g., a couple), which made one visitor very impractical. Results showed that a VRP that allowed four visitors was practically feasible, making compliance easier, with a smaller impact on well-being. These findings may help policymakers to weigh up the impact and the feasibility of a VRP next to epidemiological factors.</p>", "<p id=\"Par117\">Secondly, when considering a VRP during a pandemic, it should be noted that people apply several strategies for having social contact to maintain well-being, that might undermine its goal to reduce infections. For example, celebrating Christmas and birthdays in small groups on multiple days or in time blocks on the same day, choosing the largest house (to keep enough distance), taking self-tests and meeting only with people who are vaccinated.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par118\">This study has notable strengths. First, this study had a longitudinal design, following a cohort of 15 interviewees from May 2020 until December 2021. Therefore, the results provide an in-depth view of compliance with the VRP and well-being during the different phases of pandemic. Second, every interviewee was interviewed by the same interviewer. The interviewer was aware of the story of the interviewee and a relationship of trust was build. Lastly, during the interviews, the researchers’ interpretation of the interviewees’ behavior was reflected upon to check whether the interpretation of the data was correct. Also, the assigned category was verified in the last interview round by asking the interviewee if they recognized themselves in the description.</p>", "<p id=\"Par119\">However, this study also has some limitations. Interviewees were selected from respondents of the large quantitative cohort study of the RIVM, GGD GHOR and 25 GGD’s, which was not representative of the Dutch population. The interviewees were mostly highly educated people with no migration background, who were generally compliant (e.g., rulebreakers deviated from the rule only when it was necessary to regain well-being and made deliberate risk assessments). As the sample of interviewees was not representative, other relevant experiences could be missed in this research.</p>", "<p id=\"Par120\">The interviewees were interviewed about different measures taken by the government, besides the VRP. When analyzing the interviews in relation to VRP we observed a relation between the compliance with the VRP and other measures (e.g., 1,5 m distancing rule, closing of places where people usually meet). This association was beyond the scope of the current study. However, future studies might consider the dependence between different measures.</p>", "<p id=\"Par121\">Lastly, the measures taken to prevent the spread of COVID-19 started at March 2020 in the Netherlands. It took time to set up the study and the data collection started on May 1st 2020.Therefore we miss the information about the very beginning of the pandemic and the start of the restrictions. However, we assume that starting after several weeks after the official start of the pandemic didn’t affect our analysis much. Funding ended in December 2021, therefore the interviews stopped while the restrictions were still applied.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par122\">With this longitudinal qualitative study, we aimed to observe the impact of the VRP on compliance and well-being by following a cohort of 15 interviewees during 12 interview rounds over a period of 21 months during the COVID-19 pandemic (May 2020-December 2021). The VRP appeared to be a measure with substantial impact on well-being for some and showed fluctuating compliance, in which feasibility and frequent changes in the VRP played a role. This study showed that four categories can be identified when observing the impact of the VRP on well-being and compliance. Some follow the VRP, while others deviate, and some experience a lower well-being, while others are resilient. Well-being seemed related to the number of visitors that was allowed: four visitors was feasible, while one visitor resulted in a negative breaking-point in resilience, which had an impact on compliance even among the most compliant. Taken together, this study provides valuable insights into the implications of and compliance to a VRP during different phases of the COVID-19 pandemic, which may contribute to policymaking during future pandemics.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">In this qualitative study we observed in-depth the impact of the visiting restriction policy (VRP, i.e. number of visitors allowed at home) on well-being and compliance during the COVID-19 pandemic to regulate infection rates.</p>", "<title>Methods</title>", "<p id=\"Par2\">A cohort of 15 interviewees was followed throughout the COVID-19 pandemic in the Netherlands in 12 interview rounds (May 2020-December 2021). Every round semi-structured telephone interviews were conducted by a team of 8 researchers. In total 176 interviews were conducted.</p>", "<title>Results</title>", "<p id=\"Par3\">This study showed that four categories can be identified when observing the impact of the VRP on well-being and compliance. For Resilient-Followers reasons for compliance were risk perception, following government rules, and for some having a small social circle. Because they accepted the situation, well-being was hardly affected. Resilient-Rulebreakers made their own risk assessment of people they met. Their well-being was hardly affected, because they experienced social rest and interpreted the measure in their own way. Suffering-Followers complied, because of risk perception, following government rules, and working in healthcare. However, the VRP had substantial impact on well-being, because social structures were disrupted. Suffering-Rulebreakers gave their own interpretation to the VRP, trying to find a balance between compliance and well-being. We observed that the categories were quite stable over time.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The VRP appeared to be a measure with substantial impact on well-being for some, mostly because social structures were disrupted. The measure showed fluctuating compliance, in which feasibility and frequent changes in the VRP played a role. Well-being seemed related to the number of visitors that was allowed; a restriction of four visitors was feasible, while one visitor resulted in a negative breaking-point in resilience, which had an impact on compliance, even among the most compliant. Taken together, this study provides valuable insights into the implications of and compliance to a VRP during different phases of the COVID-19 pandemic, which may contribute to policymaking during future pandemics.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12889-024-17665-0.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We gratefully acknowledge our interviewees for their loyal participation in 12 interview rounds during the COVID-19 pandemic. Also, we acknowledge our colleagues from the RIVM Corona Behavioural Unit: Sam Krouwel, Michelle Zonneveld, Frank den Hertog, Mirjam Busch, Lise Albers, Guus Luijben, Christiaan Oostdijk and Jasmijn Bijning for conducting the interviews, Wijnand van den Boom for plotting the VRP with the COVID-19 stringency index and Nina van der Vliet for the literature search on the VRP. Lastly, we also acknowledge Eveline de Boer, Sharley Vullers, Bo Polman, Lisanne Vergouwen and Elsa Kannekens and Serena Daalmans from the Radboud University for coding transcripts.</p>", "<title>Authors’ contributions</title>", "<p>The authors FA, AG, JE, PS and GK contributed to the study conception and design. Material preparation, data collection and analysis were performed by FA, AG, JE and PS. The first draft of the manuscript was written by FA and AG. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>The first three months of the study were funded by ZonMw (Care Research Netherlands and Medical Sciences) and NWO (Dutch Research Council) (grant number 10150062010009). After that the study was funded by the Ministry of Health, Welfare and Sport of the Netherlands. The funder played no role in the design of the study or the interpretation of the data.</p>", "<title>Availability of data and materials</title>", "<p>The datasets (recordings and transcripts) generated and/or analyzed during the current study are not publicly available due to privacy reasons, but are available from the first author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par123\">In line with the Central Committee on Research Involving Human Subjects (see <ext-link ext-link-type=\"uri\" xlink:href=\"https://english.ccmo.nl/\">https://english.ccmo.nl/</ext-link>), the questionnaire study does not meet the requirement of the Law for Research Involving Human Subjects (WMO) and was exempted from formal ethical review.</p>", "<p id=\"Par124\">Informed consent was obtained from all interviewees included in the study. All interviews were recorded with the consent of the interviewee. We gave the participants the right to stop the interview whenever they want and without the obligation to give a reason. Every round we mentioned the participants this right to withdraw from the interview(series).</p>", "<title>Consent for publication</title>", "<p id=\"Par125\">N/a. Participants gave consent for publishing their anonymized answers.</p>", "<title>Competing interests</title>", "<p id=\"Par126\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Visitor restriction policy per interview round plotted with COVID-19 stringency index. The COVID-19 Stringency index is calculated as a mean score of the stringency level of a government’s response to control COVID-19 infections on any given day, ranging from 0 (no measures) to 100 (strictest measures) [##REF##33686204##15##]. The dark grey areas imply the period of restriction and the light grey areas imply the periods of relaxation of the COVID-19 restrictions</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Graphic representation of four different categories in well-being and compliance related to VRP</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Background information interview cohort (<italic>n</italic> = 15) (information based on information from all interview rounds)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"><italic>Interviewee nr</italic></th><th align=\"left\"><italic>Year of birth</italic></th><th align=\"left\"><italic>Educational level</italic></th><th align=\"left\"><italic>Gender</italic></th><th align=\"left\"><italic>Migration background</italic></th><th align=\"left\"><italic>Living in rural or urban area</italic></th><th align=\"left\"><italic>State of employment during interview series</italic></th><th align=\"left\"><italic>Self-reported vulnerable health</italic></th><th align=\"left\"><italic>Household composition</italic></th><th align=\"left\"><italic>Vaccinated with at least one COVID-19 vaccine</italic><sup>a</sup></th></tr></thead><tbody><tr><td align=\"left\"><italic>1</italic></td><td align=\"left\">1959</td><td align=\"left\">low</td><td align=\"left\">male</td><td align=\"left\">no</td><td align=\"left\">rural</td><td align=\"left\">unemployed/disabled</td><td align=\"left\">yes</td><td align=\"left\">lives with partner and two children</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>2</italic></td><td align=\"left\">1948</td><td align=\"left\">high</td><td align=\"left\">male</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">retired</td><td align=\"left\">no</td><td align=\"left\">lives with partner</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>3</italic></td><td align=\"left\">1955</td><td align=\"left\">middle</td><td align=\"left\">male</td><td align=\"left\">yes</td><td align=\"left\">urban</td><td align=\"left\">employed, worked on location at an airport</td><td align=\"left\">yes</td><td align=\"left\">lives alone</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>4</italic></td><td align=\"left\">1954</td><td align=\"left\">high</td><td align=\"left\">female</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">employed on location in healthcare</td><td align=\"left\">no</td><td align=\"left\">lives alone</td><td align=\"left\">no</td></tr><tr><td align=\"left\"><italic>5</italic></td><td align=\"left\">1982</td><td align=\"left\">middle</td><td align=\"left\">female</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">unemployed</td><td align=\"left\">no</td><td align=\"left\">lives with parents</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>6</italic></td><td align=\"left\">1995</td><td align=\"left\">high</td><td align=\"left\">female</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">student: after studying she worked as a policy advisor</td><td align=\"left\">no</td><td align=\"left\">lives with partner</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>7</italic></td><td align=\"left\">1989</td><td align=\"left\">high</td><td align=\"left\">female</td><td align=\"left\">no</td><td align=\"left\">suburban</td><td align=\"left\">employed on location in healthcare</td><td align=\"left\">no</td><td align=\"left\">lives with partner and two children</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>8</italic></td><td align=\"left\">2002</td><td align=\"left\">low</td><td align=\"left\">male</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">scholar: as a side-job works on location in a shop</td><td align=\"left\">no</td><td align=\"left\">lives with parents</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>9</italic></td><td align=\"left\">1978</td><td align=\"left\">high</td><td align=\"left\">female</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">employed; works from home as teacher later as communication advisor</td><td align=\"left\">no</td><td align=\"left\">lives with partner</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>10</italic></td><td align=\"left\">1954</td><td align=\"left\">middle</td><td align=\"left\">male</td><td align=\"left\">no</td><td align=\"left\">urban</td><td align=\"left\">retired</td><td align=\"left\">yes</td><td align=\"left\">lives with partner</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>11</italic></td><td align=\"left\">1955</td><td align=\"left\">high</td><td align=\"left\">female</td><td align=\"left\">no</td><td align=\"left\">rural</td><td align=\"left\">unemployed</td><td align=\"left\">yes</td><td align=\"left\">lives alone</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>12</italic></td><td align=\"left\">1998</td><td align=\"left\">low</td><td align=\"left\">female</td><td align=\"left\">No</td><td align=\"left\">urban</td><td align=\"left\">student/ employed, worked on location in healthcare and teacher at school</td><td align=\"left\">no</td><td align=\"left\">lives alone</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>13</italic></td><td align=\"left\">1995</td><td align=\"left\">high</td><td align=\"left\">male</td><td align=\"left\">No</td><td align=\"left\">urban</td><td align=\"left\">Employed works on location in healthcare</td><td align=\"left\">no</td><td align=\"left\">lives with partner</td><td align=\"left\">yes</td></tr><tr><td align=\"left\"><italic>14</italic></td><td align=\"left\">1995</td><td align=\"left\">high</td><td align=\"left\">female</td><td align=\"left\">No</td><td align=\"left\">rural</td><td align=\"left\">student/employed, works on location in social youth care</td><td align=\"left\">no</td><td align=\"left\">lives alone</td><td align=\"left\">no</td></tr><tr><td align=\"left\"><italic>15</italic></td><td align=\"left\">1969</td><td align=\"left\">middle</td><td align=\"left\">male</td><td align=\"left\">No</td><td align=\"left\">urban</td><td align=\"left\">employed, works on location in healthcare</td><td align=\"left\">no</td><td align=\"left\">lives with partner and three children</td><td align=\"left\">yes</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Factors in compliance and well-being per category (information based on data from all interview rounds)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"><bold>Factors for compliance</bold></th><th align=\"left\"><bold>Factors for non-compliance</bold></th><th align=\"left\"><bold>Factors for well-being</bold></th></tr></thead><tbody><tr><td align=\"left\"><bold>Resilient-Followers</bold></td><td align=\"left\"><p>-risk perception</p><p>-cue to action (government rules)</p><p>-small social circle</p></td><td align=\"left\">-</td><td align=\"left\"><p>-acceptance of situation</p><p>-levelheaded</p></td></tr><tr><td align=\"left\"><bold>Resilient-Rulebreakers</bold></td><td align=\"left\">-</td><td align=\"left\"><p>-make own risk assessment</p><p>-do what feels logical</p></td><td align=\"left\"><p>-social rest</p><p>-levelheaded</p></td></tr><tr><td align=\"left\"><bold>Suffering-Followers</bold></td><td align=\"left\"><p>-risk perception</p><p>-cue to action (government rules)</p><p>-working in healthcare</p></td><td align=\"left\">-</td><td align=\"left\"><p>-large social network (disruption social structures</p><p>-feeling sad, depressed or anxious</p></td></tr><tr><td align=\"left\"><bold>Suffering-Rulebreakers</bold></td><td align=\"left\">-</td><td align=\"left\"><p>-balancing between compliance and well-being</p><p>-own risk assessment</p><p>-do what feels logical</p><p>-large social network (disruption social structures)</p><p>-not willing to exclude someone</p><p>-trust family/friends to not have the virus</p><p>-social environment</p></td><td align=\"left\">-feeling sad, depressed or anxious</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[ "<disp-quote><p id=\"Par31\"><italic>\"On one hand you miss it, but you're also alert. If you're having face-to-face contact, it can also be risky, someone could infect you. So, it gives me mixed feelings. You miss it, but on the other hand, you know it's not beneficial either.\" – interviewee 5, female, 38 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par33\"><italic>\"I do miss it, shaking hands and a hug, and other things too but yeah, it's just the way it is.\" – interviewee 5, female, 38 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par35\"><italic>\"I've sort of got used to it, but I do miss it a lot. But I don't think I'd want to go back to the old situation either, because I notice that I also really enjoy the weekends with the children and the peace and quiet.\" – interviewee 7, female, 30 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par37\"><italic>\"The crisis doesn’t affect me, just the measures that are established. It feels like running into a wall, I feel anxious, because of sitting inside and the restrictions. It's not pleasant. If you're used to having lots of social contacts, eating out a lot, going to the gym, having an active life which is no longer possible, that doesn't really make you happy.\" – interviewee 10, male, 65 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par39\"><italic>\"When we normally meet with my group of friends, which is quite large, about fifteen friends, you easily talk in smaller groups and to different people from time to time. But online you can't really do that when you're all in a chatroom, because then you're all together the whole time, so that’s harder. I have the idea that the quality of conversations is much lower because you don't have the opportunity to have a real conversation. I do notice more and more that I miss that contact in person.\" – interviewee 6 female, 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par41\"><italic>\"We keep the social contacts at a low level, because we work in healthcare. We feel that we have a different responsibility to people, it would be different if we had worked for a regular organization.\" – interviewee 15, male, 50 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par43\"><italic>\"The measures, of course, are always tough. Because you must find balance between trying to comply as much as possible and on the other hand keeping yourself happy enough, so to speak\". – interviewee 8, male, 17 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par45\"><italic>\"With friends I sometimes find it difficult. You tend to color outside the lines. So, I think that when the measure is four people maximum, and you invite five people and the fifth one can keep distance and has no symptoms, it is okay. Of course, you must pay attention to the maximum numbers, but if everyone is just healthy, what does one person more matter? Of course, you shouldn't invite ten or twenty more, but one more is not the end of the world.\" – female, interviewee 12, 23 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par47\"><italic>\"To me, it doesn't feel right to exclude friends because you're only allowed to invite three people, even though they belong to the group.\" – interviewee 14, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par49\"><italic>\"Because I feel relaxed when being with friends and family. You could say ‘see your contacts digitally’, but for me that doesn't have the same value as face-to-face contact. So that's my excuse to see more people than allowed.\" – interviewee 14, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par51\"><italic>\"It was an afternoon that we wanted to play cards with friends, and actually we were with more people than the measure prescribed. But we knew our friends were also no risk seekers and compliant, so we discussed it with them.\" – interviewee 9, female 41 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par55\"><italic>\"It's going fine. The measures have been relaxed, so because of that my mood has brightened up a bit too. The measures had a great impact on social life, but now we have more social contacts, so relaxation of the measures has a positive effect.\" – interviewee 10, male 65 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par57\"><italic>\"There are some family gatherings that I don't go to, because I read on the internet, and also on teletext, that most infections happen during family gatherings. So, I try to avoid that.\" – interviewee 5, female 38 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par59\"><italic>\"I'll be very honest, if I didn't work in healthcare, I wouldn't be so concerned about the risk of infecting someone else in my work and wouldn't be so aware of the consequences. Now I feel responsibility towards other people because I’m a nurse. I don't want to risk infecting others. I've seen what COVID-19 does to you in hospital, how people get sick from it, die from it. So, I feel a very big responsibility to at least make sure I can't become one of the sources of infection.\" – interviewee 15, male 50 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par61\"><italic>\"We don't make a big deal about that. It's just the way it is. I always assume it's temporary, that's in the back of your mind, so we should be able to do so.\" – interviewee 3, male 64 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par63\"><italic>\"When I think about how much I'm at home compared to earlier, the difference is more than 50%. Before COVID-19, I was really doing much, visiting people and eating together. Every time you're really limited in what you can do. I think that's the whole thing, every time new measures are taken, you must change your plans again. And every time it just sucks a little bit more.\" – interviewee 6, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par65\"><italic>\"Of course, it feels kind of bad if you have a group of eight friends, like me, and not invite that last person. So, you’re allowed to invite six, but when I'm the seventh one, and another friend the eighth one, we may not come, so that’s really kind of bad.” – interviewee 8, male 17 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par67\"><italic>\"I think sometimes something, in this case a measure, has more impact than it should have. That would have had a bigger impact on me than getting COVID-19. The chance of getting seriously ill is small, I mean, still it could kill me. But you know, I could also die from riding my bike, which is also a risk I take daily. So, choosing to see my friends is just another risk I take daily. And for me, the risk of getting infected is worth it.\" – interviewee 8, male 17 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par69\"><italic>\"I try to adhere to everything, but I also look at it as a kind of customization. If I think that five people in my house is also fine, we can keep enough distance and it does not give an extra risk, then I choose to do it, while it is not actually allowed.\" – interviewee 14, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par71\"><italic>\"My uncle and aunt are going to make a Christmas dinner, so everyone picks up their meal and we're going to eat together behind the laptop. So, everybody eats Christmas dinner in their own house with their own household, behind the laptop. This is how our family can still celebrate Christmas together.\" – interviewee 6, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par73\"><italic>\"My parents say, if we see one couple one day, and see the other couple the other day, the risk of getting COVID-19 is the same when meeting all together at the same time. Of course, you’re allowed to invite three people at Christmas. I wonder if that's three people, or if you can also interpret that as three households. After all, if we visit my parents as children, you might as well bring your partner, which doesn't really matter anymore if you live together.” – interviewee 7, female 30 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par75\"><italic>“You can invite a maximum of three people, but when there's four of us, then I'm not going to say at Christmas, 'hey sister-in-law, you can't come because you're the fourth person.' Then I would invite her of course. But meeting with the whole family like we normally do, we wouldn’t do that. It would probably be in smaller groups.” – interviewee 14, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par79\"><italic>\"We had planned my son’s birthday before the new measures came in. We just canceled it and we now have split it up into three days with three guests maximum each day.\" – interviewee 15, male 50 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par81\"><italic>\"The new restrictions make me feel a little less happy. And then I say it mildly. At the last press conference, when the minister announced the maximum number is reduced from two to one, I was really sad. Mainly because each time there are more restrictions. First there were six people, then three, then two, and now one. Every time I think about how I should deal with it, and how I can ensure I can still see friends or have social contacts within the measures. Every time I've just succeeded in planning things within the measures, the whole situation changes again, and new measures come into force. And then I must start all over again, inventing and planning things. It's always a lot of disappointment. When seeing the press conference, I had to cry very hard. Just because I thought, I can't keep going anymore.” – interviewee 6, female 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par83\"><italic>\"I think that, more than anything else, that brings psychological pressure. Every time a press conference is coming up, you are nervous that appointments that you’ve made earlier must be cancelled. When the number was reduced from two to one visitor, you had to cancel appointments again, which were not possible anymore.\" – interviewee 13, male 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par85\"><italic>\"We had quite a few contacts that we always visited as a couple. That's just all quite complicated to get that sorted out. I find that very difficult, I feel like there’s nothing fun possible anymore. In the previous situation, in which the number was three or two, it was often possible to see each other within the measures, and you still had a nice evening or afternoon, that you could see each other from a distance. But at that time at least it felt like I still had some social contact.\" – interviewee 13, male 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par88\"><italic>\"It could happen though that the two of us are somewhere, so like yesterday I was with my girlfriend at another friend's house. Yeah, that's not actually allowed. On the other hand, I think if I have COVID-19, my girlfriend probably has it too.\" – interviewee 8, male 17 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par90\"><italic>\"Both family and friends understand why we do it, so we don't evaluate it in terms of terrible and annoying, because that's not helpful. It doesn't make any sense to catastrophize it. You only make yourself unhappy with that. Of course, it was difficult to invite a limited number of people, but the people I know are rational and it didn't cause any problems. It's difficult to invite just one person when you invite a married couple. Then it’s hard to say, ‘you are allowed, and you are not’, so there are some people we haven't invited at this point that we normally would have invited.” – interviewee 2, male, 71 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par92\"><italic>\"Relaxation, especially when you can invite two people again, is nice. But it's not the main thing for me, because life doesn't stop when there are restrictions.\" – interviewee 2, male 71 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par94\"><italic>\"In two weeks, our middle one will have his birthday, and then we will just have another birthday party with time blocks to not exceed the number of people. We set the number at eight for this birthday, that's the maximum. I keep in mind a maximum number of people. Besides, we haven't started seeing people more often because the rule has been relaxed more.\" – interviewee 15, male 50 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par96\"><italic>\"If people let us know that they don't want to be vaccinated for whatever reason, then I don't make an appointment with those people. So yeah, that's too bad, but it’s not going to happen. I'm not taking any risks. Not for my own health, but also not for the people around me.\" – interviewee 10, male 65 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par98\"><italic>\"We do make different considerations now. Either people have had a COVID-19 infection or people have been vaccinated, and then the risk feels lower to me. But four unvaccinated, COVID-19-naive people together, we wouldn't do that. So, we think about our choices and the consequences they could have. When we invite people, we think about who has which serology, who is vaccinated, who might have COVID-19.\" – interviewee 7, female 30 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par100\"><italic>\"I don't notice it that much I guess, because I don't invite more than four people that often. That has changed since the pandemic and especially because you really speak to each other better and you have more in-depth conversations than just ‘how are you’. So, I think it's also genuinely more sociable and enjoyable.\" – interviewee 7, female, 30 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par102\"><italic>\"No problem, it's rare that we receive more than two guests. In this household it doesn't happen that often, so it doesn’t make any difference for us.\" – interviewee 10, male, 65 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par104\"><italic>\"In terms of group size, I was much stricter when no one had been vaccinated yet, or when only I had been vaccinated. You notice by being vaccinated you are more flexible. But I am strict about self-testing. If we consider inviting more people, then I really want everyone to do a self-test beforehand, just to protect each other.\" – interviewee 13, male, 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par106\"><italic>\"I do think the most regrettable thing is that visitation is restricted again. I also notice friends don’t comply with it, even family members who were very strict at first. Today is my sister's birthday, which she celebrates with my parents for dinner. We agreed with the family that it would be okay if there are ten of us, if nobody has any symptoms and if we do a self-test beforehand. I notice that more and more people, like my friends, and even my strict family, look at how the measure can be circumvented. So now it's more about, at least around me, what people are comfortable with and not necessarily what the measure prescribes. Of course, what feels comfortable can be influenced by the measures, speaking for myself, but I notice it's not leading anymore.\" – interviewee 14, female, 25 years old</italic></p></disp-quote>", "<disp-quote><p id=\"Par108\"><italic>\"I’m quite willing to invite fewer people, but whether it's four or eight... But I wouldn't have more than ten people at home. I want to adhere to it a little, but I don't feel like complying with all the rules very strictly now. Because I'm done with it and I think that the value of being able to have certain forms of social contact, that's worth more than the risk of getting COVID-19 from that.\" – interviewee 8, male, 17 years old</italic></p></disp-quote>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup>The vaccination campaign started at 8 January 2021. We asked the vaccination status in the interview round 9 (11–14 January 2021) and in interview round 14 (24–31 August 2021)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Fatima Arrahmani and Annerike Gorter shared first authorship and contributed to the manuscript equally.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12889_2024_17665_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12889_2024_17665_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"12889_2024_17665_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Appendix 1. </bold>Overview of interview rounds and VRP per interview round.</p></caption></media>" ]
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{ "acronym": [ "VRP" ], "definition": [ "Visitor Restriction Policy. The Visitor Restriction Policy is one of the preventive measures that impacted social life during the pandemic, i. e. governmental advice to limit the number of visitors allowed at home per day" ] }
19
CC BY
no
2024-01-14 23:43:46
BMC Public Health. 2024 Jan 13; 24:175
oa_package/70/b5/PMC10787453.tar.gz
PMC10787454
0
[ "<title>Introduction</title>", "<p id=\"Par14\">The incidence rate of cervical spondylosis increases steadily along with changes in lifestyle and population aging. Its main etiology is cervical disk herniation or foraminal stenosis, which causes radiating pain and numbness in neck, shoulder, and upper extremity. They can lead to long-term disability, pain, and financial burden, and contribute to poor quality of life [##REF##2267608##1##, ##REF##24994052##2##].</p>", "<p id=\"Par15\">Since the sagittal balance was reported to be significantly related to patients’ health-related quality of life (HRQOL), the importance of sagittal alignment and sagittal balance has been gradually recognized [##REF##31481082##3##]. Cervical sagittal imbalance is one of the main reasons for cervical disk degeneration and associated disorders [##REF##32962694##4##–##REF##26315953##6##]. Cervical sagittal balance-related parameters, including C0-2 angle (C0-2), C2–C7 cervical lordosis (CL), C2 slope (C2S), T1 slope (T1S), and T1S minus CL (T1S-CL) [##REF##32101155##7##], are being used to evaluate the severity and treatment outcomes of the disease [##REF##33153470##8##]. Odontoid incidence (OI) is one of the most important anatomic parameters in terms of cervical sagittal balance and equals the sum of the positional parameters odontoid tilt (OT) and C2S (OI = OT + C2S) [##REF##35793937##9##]. OI strongly correlates with CL through C2S, thus largely determining the different cervical types and consequent mechanisms of cervical spine degeneration [##REF##35793937##9##]. The analysis of OI is essential to understand the impact of cervical sagittal alignment and to make an surgical strategy for cervical deformity correction. OT indicates the spatial orientation of the odontoid process, which may vary depending on the balance of cranial and horizontal gaze, and could aid in two-dimensional analyzes of cervical alignment and balance [##REF##26571180##10##].</p>", "<p id=\"Par16\">Different imaging modalities such as standing X-ray radiography [##REF##26571180##10##] and supine magnetic resonance imaging (MRI) [##REF##23962996##11##] are commonly used to assess cervical spine alignment. However, body posture and the role of the head in cervical load-bearing may have an impact on the spine, leading to different results [##REF##33881642##12##–##REF##24776700##14##]. Standing X-ray provides gravity balance information; however, in patients with a short neck or high sternum, the endplates of the lower cervical and upper thoracic vertebrae may not be clear, thus affecting the measurement of cervical sagittal parameters [##REF##28456677##15##]. Supine MRI can provide anatomical structure information of soft tissues with high spatial resolution [##REF##32015409##16##]; however, it cannot reflect the natural upright state of the spine, since cervical balance is obtained in an upright posture. Therefore, to provide a more comprehensive and reliable reference for the prevention, diagnosis and treatment of cervical spine diseases, further studies investigating correlations and differences between cervical spine parameters measured by different imaging methods are needed. In this study, we assessed whether there was a difference between cervical sagittal parameters measured by standing X-ray and those by supine MRI and validated whether OI is a constant anatomic parameter. We explored correlations between cervical sagittal parameters and determined the formula for predicting cervical sagittal parameters.</p>" ]
[ "<title>Materials and methods</title>", "<title>Case selection</title>", "<p id=\"Par17\">Ethical approval was obtained from the Ethics Committee of our hospital. Adults aged between 18 and 40 aged without spinal symptoms were included in this study. All participants were selected from those population undergoing annual routine health checkups at the Center of Health Management, affiliated with The First Affiliated Hospital of Guangxi Medical University from January 1, 2011 to October 31, 2022.</p>", "<title>Patient selection criteria</title>", "<p id=\"Par18\">The following screening criteria were used for ensuring the health status of study participants and excluding factors that might interfere with results in order to improve the accuracy and reliability of the study.</p>", "<p id=\"Par19\">All participants had to provide available clinical data, including standardized lateral cervical spine radiographs and MRI images to meet the inclusion criteria. Exclusion criteria included a history of cervical spine trauma, infection, tumor, deformity, history of cervical spine surgery, or history of other spinal trauma and disease to avoid measurement bias and disease progression. Additionally, individuals with diagnosed diseases, degenerative changes (.g.,, decreased disk height or osteophyte formation), a history of treatment related to the cervical spine, a history of spinal surgery, or overall sagittal alignment abnormalities were excluded.</p>", "<title>Acquisition conditions</title>", "<p id=\"Par20\">The radiographic protocol was standardized. For each subject, cervical spine lateral radiographs were obtained with a 10 × 12-inch cassette at a 72-inch (182 cm) distance with the radiographic tube centered at the C4–C5 disk space with no magnification. Subjects were instructed to stand in a comfortable position and keep their eyes forward with their arms extended on their chests. The MRI images were obtained using a 1.5-T system (Signa; GE Medical Systems). Subjects were placed in the scanner chamber in a supine position.The cervical cord was imaged in neutral position with a standard MR receive coil (HD Head Neck and Spine Array) dedicated to spinal imaging. The T2-weighted MR images were acquired with a field of view (FOV) of 260 mm and a matrix size of 512 × 512 pixels. Later, MRI data was measured on T2-weighted MR images. The interval between X-ray and MRI examinations was not more than 2 months in each case to avoid the implications of disease progression for the results.</p>", "<title>Data collection and measurement</title>", "<p id=\"Par21\">Data was collected by one of investigators in the research team, who would not be involved in final data analysis. The assessment was performed by two senior spine surgeons (with 12 and 6 years' clinical experience, respectively). They performed the following measurements of cervical sagittal parameters on X-ray and MRI images using the Surgimap software (Nemaris, Inc., New York, NY, USA): OI, OT, C2S, C0-2 angle, C2-7 angle, T1S and T1S-CL. OI was defined as the angle between the line perpendicular to the C2 endplate (C2EP) at its midpoint and the line connecting this point to the center of the odontoid process. OT was defined as the angle created by a line running from the C2EP midpoint to the center of the odontoid process and the vertical axis. C2S was defined as the angle between the C2EP and a horizontal line. The C0-2 angle, an angle between the C2EP and the McRae line was measured. The C2-7 angle was measured as the angle between C2 and C7 lower endplates. T1S was defined as an angle formed between the T1 upper endplate and the horizontal plane (Figs. ##FIG##0##1##, ##FIG##1##2##). Two assessors completed the measurements independently and averaged them for the final results.</p>", "<title>Statistical analyzes</title>", "<p id=\"Par22\">All data in this study was analyzed by using SPSS (version 26), R (version 4.2.2) and RStudio (version 1.1.463). Inter-observer agreement for each parameter was assessed by the intraclass correlation coefficient (ICC) [##REF##18839484##17##], whose values are expressed as 95% confidence intervals (CI). The ICC takes values ranging from 0 to 1, with a larger value indicating a better agreement. According to the recommendations of Fleiss [##UREF##0##18##] and Landis [##REF##843571##19##], ICC values between 0.00 and 0.40 indicate poor agreement, between 0.40 and 0.74 indicate good agreement, and between 0.75 and 1.00 indicate excellent agreement.</p>", "<p id=\"Par23\">In this study, all parameters are presented as mean ± standard deviation. If the parameters conformed to normal distributions, the paired t-test would be carried out to analyze the differences between X-ray and MRI. For correlation analysis between two imaging studies, the Pearson correlation test was used, which was expressed as <italic>r</italic> coefficient. The <italic>r</italic> coefficients ranging from − 1.0 to − 0.5 or 0.5 to 1.0 suggest strong correlation, − 0.5 to − 0.3 or 0.3 to 0.5 indicate moderate correlation, − 0.3 to − 0.1 or 0.1 to 0.3 represent weak correlation, and − 0.1 to 0.1 imply no correlation or very weak correlation. A P value &lt; 0.05 was considered to be statistically significant.</p>" ]
[ "<title>Results</title>", "<p id=\"Par24\">A total of 96 individuals who participated in health checkups were screened in this study, from whom, 54 were excluded based on the exclusion criteria. The study population consisted of 42 participants [15 (35.7%) males and 27 (64.3%) females] with a mean age of 29.1 ± 5.97 (18–39 years old). The study involved the measurement of seven sagittal parameters and a total of 588 measurements were obtained. Two evaluators performed separately the measurements for the radiographic and MRI studies.</p>", "<title>Inter-observer agreement</title>", "<p id=\"Par25\">By the credibility of analyzes, the inter-observer agreement of all cervical spine parameters on X-ray and MRI was as follows: X-ray: 0.552 (OI), 0.855 (OT), 0.907 (C2S), 0.942 (C0-2), 0.965 (C2-7), 0.952 (T1S), 0.897 (T1S-CL); MRI: 0.723 (OI), 0.819 (OT), 0.958 (C2S), 0.985 (C0-2), 0.963 (C2-7), 0.948 (T1S), 0.924 (T1S-CL). Except for the inter-observer agreement of 0.552 and 0.723 for OI on X-ray and MRI, respectively, both of which were in good agreement, the remaining parameters showed excellent agreement. This indicates that the overall inter-observer agreement was great and the results were statistically significant (P &lt; 0.001) (Table ##TAB##0##1##).</p>", "<title>Cervical sagittal parameters</title>", "<p id=\"Par26\">The mean cervical sagittal parameters on X-ray were 15.38° ± 2.32° (OI), 12.51° ± 6.18° (OT), 2.8° ± 6.36° (C2S), 24.6° ± 9.47° (C0-2), 20.76° ± 9.73° (C2-7), 31.71° ± 8.4° (T1S), 10.95° ± 8.21° (T1S-CL). The mean cervical sagittal parameters on MRI were 16.68° ± 4.33° (OI), 5.44° ± 6.51° (OT), 11.4° ± 6.83° (C2S), 15.03° ± 6.26° (C0-2), 12.24° ± 10° (C2-7), 28.37° ± 7.21° (T1S), 16.13° ± 8.17° (T1S-CL). After X-ray and MRI paired t-test, the results were: − 1.29° ± 4.38° (OI), 7.07° ± 7.39° (OT), − 8.6° ± 7.03° (C2S), 9.57° ± 9.68° (C0-2), 8.52° ± 9.59° (C2-7), 3.34° ± 7.42° (T1S), − 5.19° ± 7.95° (T1S-CL). The results showed that there was no significant difference of OI in X-ray and MRI (<italic>p</italic> &gt; 0.05), and OT, C0-2, C2-7, and T1S were significantly greater on X-ray than on MRI (<italic>p</italic> &lt; 0.05), while C2S and T1S-CL were significantly smaller on X-ray than on MRI (<italic>p</italic> &lt; 0.05) (Table ##TAB##1##2##).</p>", "<title>X-ray and MRI parameter correlation</title>", "<p id=\"Par27\">After Pearson's analysis, the same cervical sagittal parameters on X-ray and MRI were found to be significantly correlated (<italic>p</italic> &lt; 0.05), including C2-7 (<italic>r</italic> = 0.528), T1S (<italic>r</italic> = 0.557), T1S-CL (<italic>r</italic> = 0.529), C2S (<italic>r</italic> = 0.433), and OT (<italic>r</italic> = 0.322). Whereas, C0-2 and OI did not have a significant correlation between X-ray and MRI (<italic>p</italic> &gt; 0.05).</p>", "<title>Parameter correlations</title>", "<p id=\"Par28\">After Pearson's analysis, the correlations between X-ray cervical spine parameters were as follows: OT was significantly correlated with C2S (<italic>r</italic> = − 0.93), C2-7 (<italic>r</italic> = 0.71), and T1S-CL (<italic>r</italic> = − 0.69), but not with OI, C0-2, and T1S. C2S was significantly correlated with C0-2 (<italic>r</italic> = 0.32), C2-7 (<italic>r</italic> = -0.69), and T1S-CL (<italic>r</italic> = 0.78). There was no significant correlation between OI and the other parameters. C2-7 was significantly correlated with C2S (<italic>r</italic> = − 0.69), OT (<italic>r</italic> = 0.71) and T1S-CL (<italic>r</italic> = − 0.57). T1S was significantly correlated with C2-7 (<italic>r</italic> = 0.6) and T1S-CL (<italic>r</italic> = 0.31). T1S-CL was significantly correlated with C2S (<italic>r</italic> = 0.78), C2-7 (<italic>r</italic> = − 0.57), OT (<italic>r</italic> = − 0.69) and T1S (<italic>r</italic> = 0.31) (Fig. ##FIG##2##3##).</p>", "<p id=\"Par29\">For the MRI data, we derived the following correlation results: The OT was significantly correlated with C2S (<italic>r</italic> = − 0.76), C2-7 (<italic>r</italic> = 0.56), T1S (<italic>r</italic> = 0.36), and T1S-CL (<italic>r</italic> = − 0.37), but not with OI and C0-2. C2S was significantly correlated with C0-2 (<italic>r</italic> = 0.51), C2-7 (<italic>r</italic> = − 0.74), OI (<italic>r</italic> = 0.38), OT (<italic>r</italic> = − 0.76), and T1S-CL (<italic>r</italic> = 0.69), but not with T1S. OI was significantly correlated with C2S (<italic>r</italic> = 0.38), C0-2 (<italic>r</italic> = 0.47), and T1S-CL (<italic>r</italic> = 0.49), but not with OT, C2-7, and T1S. C2-7 was significantly correlated with C2S (<italic>r</italic> = − 0.74), OT (<italic>r</italic> = 0.56), C0-2 (<italic>r</italic> = − 0.37), T1S (<italic>r</italic> = 0.59), and T1S-CL (<italic>r</italic> = − 0.7), but not with OI. T1S was significantly correlated with C2-7 (<italic>r</italic> = 0.59) and OT (<italic>r</italic> = 0.36). T1S-CL was significantly correlated with C0-2 (<italic>r</italic> = 0.41), OI (<italic>r</italic> = 0.49), C2S (<italic>r</italic> = 0.78), C2-7 (<italic>r</italic> = − 0.7) and OT (<italic>r</italic> = − 0.37), but not with T1S (Fig. ##FIG##2##3##).</p>", "<title>Validation of formula efficacy</title>", "<p id=\"Par30\">This study validated the efficacy of the formula CL = 0.36 × 0I − 0.67 × 0T − 0.69 × T1S model on X-ray and MRI. The results showed a significant correlation between predictive value and observed value on X-ray and MRI. Specifically, the correlation coefficient (<italic>r</italic>) on X-ray was -0.862 with an R2 value of 0.744; on MRI, the correlation coefficient (<italic>r</italic>) was -0.783 with an R2 value of 0.614 (Fig. ##FIG##3##4##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par31\">In this study, the sagittal plane parameters of the cervical spine measured by X-ray and MRI showed good overall inter-observer agreement. They were also similarly accurate and reliable for determining the OI. This confirms that OI is independent and stable under the influence of external factors, which is consistent with the results of a previous study [##REF##35793937##9##, ##REF##30762740##20##, ##REF##28180991##21##]. To maintain an overall sagittal balance of the cervical spine, an increase in the angles of C0-2 and T1S-CL is required. The results of this study showed that C2S on the X-ray was positively correlated with C0-2 and T1S-CL, while it was negatively correlated with C2-7. Furthermore, OT, C2-7, and T1S obtained from X-ray measurements had greater angles compared to those obtained from MRI, while C2S and T1S-CL had smaller angles. This difference may be due to the pressure exerted on the vertebrae by the weight of the skull during X-ray in the standing position, whereas the reaction force of the bed has an effect on the vertebrae during MRI in the supine position. This is consistent with the results of a previous study [##REF##34919463##22##], which found that skull contact with the table and applying a reaction force on the neck that projected posteriorly resulted in a decrease in the angle of rotation of the first thoracic vertebra, which resulted in a smaller T1S observed on MRI.</p>", "<p id=\"Par32\">Unlike Lee’s study [##REF##35793937##9##], the correlation between the OI and the C2S, C0-2, and T1S-CL is pronounced on MRI images in our study. There are several possible explanations for this diskrepancy, which include the differences in the sagittal configuration of cervical spine between Chinese and Koreans, and the differences between MRI and EOS techniques. OI may be affected by the complex anatomy of the odontoid and the difficulty in stabilizing the odontoid tip since it rotates on its own between the anterior arch of the atlas and the transverse ligament of the atlas measurement [##REF##28054384##23##, ##REF##15723251##24##]. We found no significant correlation between C0-2 and OI, agrees exceptionally well with what Ames et al. have concluded in their study that smaller correlation coefficients for this parameter in close proximity to the head [##REF##24113358##25##]. According to the research findings of Lee and his colleagues, other factors may contribute more to the overall alignment of the cervical spine, resulting in a moderate correlation coefficient, compared to the parameter of the odontoid process closest to the head [##REF##35793937##9##]. This phenomenon may result from measurement error, anatomical differences, distinctions between imaging methods, or other unknown factors.</p>", "<p id=\"Par33\">Previous studies have demonstrated that if the CL is not sufficient to match the patient's given T1S, the second cervical vertebra will tilt forward to increase the C2S [##REF##31513111##26##]. This suggests that OT decreases when the C2S angle increases, which is identical with the findings of Lee et al. [##REF##35793937##9##]. These phenomena may reflect the structural interrelationships and physiological characteristics in the sagittal plane of the cervical spine. On MRI, OT was significantly correlated with C2S, C2-7, T1S, and T1S-CL, suggesting that OT may reveal the structural and positional relationships of the overall cervical spine. Specifically, a reduced OT angle may result in a forward tilt of C2S and C2-7 and a backward tilt of T1S and T1S-CL, thereby affecting the position and structure of the overall cervical spine. This study confirmed and validated the formula proposed by Lee et al. [##REF##35793937##9##], for predicting the normative CL of a given patient: CL = 0.36 × OI − 0.67 × OT − 0.69 × T1S. The formula predicts CL with a high predictive accuracy in X-ray and MRI applications. Not only does this formula possibly provide a threshold for cervical deformity, but it also implies a goal for surgical correction to reconstruct the predicted physiological cervical alignment.</p>", "<p id=\"Par34\">This study has several limitations. First, it was a retrospective study with minor variations in the location of subjects on radiographic images, which may lead to selection bias. Second, the sample size was small and only healthy subjects were included, which may not be fully representative of the entire population. To reduce heterogeneity among participants, we only included the healthy subjects who exhibited no signs of degenerative disk changes. Some normal individuals with degenerative changes (disk height loss or osteophytes) were excluded in this study, which may also create a selection bias. Third, in our study, the accuracy of OI measurements on X-ray images might be limited because of a less clear depiction of the odontoid process on X-ray images than that on MRI images.This phenomenon may lead to a slight underestimation of ICC on X-ray in our study. Fourth, we could not further analyze some factors (gender, age, and disk height loss) that influence cervical sagittal balance. These potential confounders may exert an impact on the correlation between OI and cervical sagittal parameters, and consequently, may weaken the validity of the results. Thus the results need to be interpreted with caution.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par35\">In summary, OI was verified as a constant anatomic parameter, demonstrating the necessity of a combined assessment of cervical sagittal balance by employing standing X-ray and supine MRI. The formula CL = 0.36 × OI − 0.67 × OT − 0.69 × T1S can be used to predict CL in cervical sagittal parameters. This study has great significance in clinical applications, especially for medical imaging specialists who need to be aware of the differences of measurements between standing X-ray and supine MRI when evaluating cervical sagittal balance.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">To assess whether there is a difference between measurements of odontoid incidence (OI) and other cervical sagittal parameters by X-ray radiography and those by supine magnetic resonance imaging (MRI).</p>", "<title>Methods</title>", "<p id=\"Par2\">Standing X-ray and supine MRI images of 42 healthy subjects were retrospectively analyzed. Surgimap software was employed to measure cervical sagittal parameters including OI, odontoid tilt (OT), C2 slope (C2S), C0-2 angle, C2-7 angle, T1 slope (T1S) and T1S-cervical lordosis (CL). Paired samples t-test was applied to determine the difference between parameters measured by standing X-ray and those by supine MRI. In addition, the statistical correlation between the parameters were compared. The prediction of CL was performed and validated using the formula CL = 0.36 × OI − 0.67 × OT − 0.69 × T1S.</p>", "<title>Results</title>", "<p id=\"Par3\">Significant correlations and differences were found between cervical sagittal parameters determined by X-ray and those by MRI. OI was verified to be a constant anatomic parameter and the formula CL = 0.36 × OI − 0.67 × OT − 0.69 × T1S can be used to predict CL in cervical sagittal parameters.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">OI is verified as a constant anatomic parameter, demonstrating the necessity of a combined assessment of cervical sagittal balance by using standing X-ray and supine MRI. The formula CL = 0.36 × OI − 0.67 × OT − 0.69 × T1S can be applied to predict CL in cervical sagittal parameters.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>None.</p>", "<title>Author contribution</title>", "<p>Conceptualization: JH; Data curation: HLA; Formal analysis: HLA, QHY; Methodology: HLA, XHY; Project administration: JH, CWY; Visualization: HLA; Writing—original draft: HLA; Writing—review and editing: JH.</p>", "<title>Funding</title>", "<p>The author(s) disklosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Natural Science Foundation of China (81860406), Guangxi Natural Science Foundation (2018GXNSFAA281127) and Youth Science Foundation of Guangxi Medical University (GXMUYSF201329). No benefit in any form has been seen or will be received from a commercial party related directly or indirectly to the subject of this manuscript.</p>", "<title>Availability of data and materials</title>", "<p>The data used and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par36\">The study has been approved by the Medical Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (2023-E008-01).</p>", "<title>Competing interests</title>", "<p id=\"Par37\">The authors have no conflicts of interest to declare in relation to this article.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Measurement of odontoid process parameters and cervical spine parameters on DR images. <bold>A</bold>: Measurement of OI, OT and cervical spine parameters on DR images of a healthy 35-year-old male; <bold>B</bold>: High-resolution views of OI and OT on DR images of a healthy 35-year-old male.DR, digital radiography; OI, odontoid incidence; OT, odontoid tilt</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Measurement of odontoid process parameters and cervical spine parameters on MRI images. <bold>A</bold>: Measurement of OI, OT and cervical spine parameters on MRI images of a healthy 35-year-old male; <bold>B</bold>: High-resolution views of OI and OT on MRI images of a healthy 35-year-old male.MRI, magnetic resonance imaging; <italic>OI</italic>, odontoid incidence; <italic>OT</italic>, odontoid tilt</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Heat map of correlations. <bold>A</bold>: Pearson correlation analysis between OI, OT and cervical parameters on cervical DR images; <bold>B</bold>: Pearson correlation analysis between OI, OT and cervical parameters on cervical MRI images. <italic>OI</italic> odontoid incidence; <italic>OT</italic> odontoid tilt; <italic>DR</italic> digital radiography; <italic>MRI</italic> magnetic resonance imaging</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Validation of CL prediction formula efficacy. <bold>A</bold>: Validation of CL prediction formula efficacy on DR images; <bold>B</bold>: Validation of CL prediction formula efficacy on MRI images. R2 represents the coefficient of determination. <italic>CL</italic> cervical lordosis; <italic>DR</italic> digital radiography; <italic>MRI</italic> magnetic resonance imaging</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Inter-observer reliability and pairwise difference of each parameter between observers</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\" colspan=\"2\">Observer</th><th align=\"left\" colspan=\"2\">Inter-observer reliability</th></tr><tr><th align=\"left\"/><th align=\"left\">A<sup>a</sup></th><th align=\"left\">B<sup>a</sup></th><th align=\"left\"/><th align=\"left\"/></tr><tr><th align=\"left\">Parameters</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Mean (SD)</th><th align=\"left\">ICC</th><th align=\"left\"><italic>p</italic></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"5\"><italic>DR</italic></td></tr><tr><td align=\"left\">OI (°)</td><td align=\"left\">15.37 (2.35)</td><td align=\"left\">15.4 (3.18)</td><td align=\"left\">0.552</td><td align=\"left\">0.007</td></tr><tr><td align=\"left\">OT (°)</td><td align=\"left\">13.98 (6.27)</td><td align=\"left\">11.03 (6.68)</td><td align=\"left\">0.855</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C2S (°)</td><td align=\"left\">1.24 (6.27)</td><td align=\"left\">4.37 (6.68)</td><td align=\"left\">0.907</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C0-2 (°)</td><td align=\"left\">22.87 (9.72)</td><td align=\"left\">26.34 (9.47)</td><td align=\"left\">0.942</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C2-7 (°)</td><td align=\"left\">21.45 (9.94)</td><td align=\"left\">20.07 (9.81)</td><td align=\"left\">0.965</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">T1S (°)</td><td align=\"left\">31 (8.13)</td><td align=\"left\">32.41 (9.00)</td><td align=\"left\">0.952</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">T1S-CL (°)</td><td align=\"left\">9.55 (7.92)</td><td align=\"left\">12.35 (9.10)</td><td align=\"left\">0.897</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"5\"><italic>MRI</italic></td></tr><tr><td align=\"left\">OI (°)</td><td align=\"left\">15.9 (4.87)</td><td align=\"left\">17.45 (4.86)</td><td align=\"left\">0.723</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">OT (°)</td><td align=\"left\">5.10 (7.01)</td><td align=\"left\">5.78 (7.14)</td><td align=\"left\">0.819</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C2S (°)</td><td align=\"left\">11.04 (7.02)</td><td align=\"left\">11.76 (6.90)</td><td align=\"left\">0.958</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C0-2 (°)</td><td align=\"left\">15.27 (6.28)</td><td align=\"left\">14.8 (6.32)</td><td align=\"left\">0.985</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C2-7 (°)</td><td align=\"left\">12.66 (10.28)</td><td align=\"left\">11.81 (10.07)</td><td align=\"left\">0.963</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">T1S (°)</td><td align=\"left\">28.85 (7.13)</td><td align=\"left\">27.89 (7.62)</td><td align=\"left\">0.948</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">T1S-CL (°)</td><td align=\"left\">16.19 (8.85)</td><td align=\"left\">16.08 (8.09)</td><td align=\"left\">0.924</td><td align=\"left\"> &lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Pairwise differences of cervical sagittal parameters between DR and MRI</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">DR</th><th align=\"left\">MRI</th><th align=\"left\">Pairwise Difference</th><th align=\"left\"/></tr><tr><th align=\"left\">Parameter</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Mean (SD)</th><th align=\"left\"><italic>p</italic> value</th></tr></thead><tbody><tr><td align=\"left\">OI (°)</td><td align=\"left\">15.38 (2.32)</td><td align=\"left\">16.68 (4.33)</td><td align=\"left\"> − 1.29 (4.38)</td><td align=\"left\">0.063</td></tr><tr><td align=\"left\">OT (°)</td><td align=\"left\">12.51 (6.18)</td><td align=\"left\">5.44 (6.51)</td><td align=\"left\">7.07 (7.39)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C2S (°)</td><td align=\"left\">2.80 (6.36)</td><td align=\"left\">11.40 (6.83)</td><td align=\"left\"> − 8.60 (7.03)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C0-2 (°)</td><td align=\"left\">24.60 (9.47)</td><td align=\"left\">15.03 (6.26)</td><td align=\"left\">9.57 (9.68)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">C2-7 (°)</td><td align=\"left\">20.76 (9.73)</td><td align=\"left\">12.24 (10)</td><td align=\"left\">8.52 (9.59)</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\">T1S (°)</td><td align=\"left\">31.71 (8.40)</td><td align=\"left\">28.37 (7.21)</td><td align=\"left\">3.34 (7.42)</td><td align=\"left\">0.006</td></tr><tr><td align=\"left\">T1S-CL (°)</td><td align=\"left\">10.95 (8.21)</td><td align=\"left\">16.13 (8.17)</td><td align=\"left\"> − 5.19 (7.95)</td><td align=\"left\"> &lt; 0.001</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><sup>a</sup><italic>A</italic>, <italic>B</italic> represent the two observers who participated in the study</p><p><italic>DR</italic> digital radiography; <italic>MRI</italic> magnetic resonance imaging; <italic>OI</italic> odontoid incidence; <italic>OT</italic> odontoid tilt; <italic>C2S</italic> C2 slope; <italic>TIS</italic> T1 slope; <italic>CL</italic> cervical lordosis</p></table-wrap-foot>", "<table-wrap-foot><p><italic>DR</italic> digital radiography; <italic>MRI</italic> magnetic resonance imaging; <italic>OI</italic> odontoid incidence; <italic>OT</italic> odontoid tilt; <italic>C2S</italic> C2 slope; <italic>TIS</italic> T1 slope; <italic>CL</italic> cervical lordosis</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13018_2024_4542_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13018_2024_4542_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"13018_2024_4542_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"13018_2024_4542_Fig4_HTML\" id=\"MO4\"/>" ]
[]
[{"label": ["18."], "surname": ["Fleiss"], "given-names": ["JL"], "source": ["Design and analysis of clinical experiments"], "year": ["2011"], "publisher-name": ["Wiley"]}]
{ "acronym": [ "MRI", "OI", "OT", "C2S", "T1S", "CL", "ICC", "CI", "HRQOL" ], "definition": [ "Magnetic resonance imaging", "Odontoid incidence", "Odontoid tilt", "C2 slope", "T1 slope", "Cervical lordosis", "Intraclass correlation coefficient", "Confidence intervals", "Health-related quality of life" ] }
26
CC BY
no
2024-01-14 23:43:46
J Orthop Surg Res. 2024 Jan 13; 19:63
oa_package/ab/de/PMC10787454.tar.gz
PMC10787455
0
[ "<title>Background</title>", "<p id=\"Par5\">Dietary patterns are ever-changing towards higher consumption of added sugars, unhealthy fats, salt, and refined carbohydrates in various low- and middle-income countries (LMICs), including sub-Saharan Africa (SSA) [##UREF##0##1##]. Unhealthy food consumption (UFC) that begins early in life is associated with a higher risk of nutrient inadequacy, becoming overweight or obese, and related chronic diseases later in life [##REF##31309223##2##]. Consumption of candies, chocolate, chips, French fries, cakes, and cookies displaces more nutritious foods and limits the consumption of crucial vitamins and minerals [##UREF##1##3##]. Repeated intake of unhealthy foods, including sweet beverages, enhances the need for the sweet taste, resulting in consumption of and a preference for sweet-tasting foods thereafter [##REF##31309223##2##]. High consumption of unhealthy foods and beverages is also associated with poor diet quality among children [##REF##37404859##4##].</p>", "<p id=\"Par6\">Appropriate feeding in early childhood plays a central role in acceptable growth and development [##UREF##2##5##]. In the first 1000 days of life (from pregnancy to two years of age), nutritional status determines the body’s metabolic model, which often impacts the risk of juvenile and adult obesity and other diseases and lasts for a lifetime [##REF##29194402##6##]. The nutritional factors in this time period include the nutritional status of the mother during pregnancy, breastfeeding, formula feeding, and appropriate complementary feeding [##REF##27563917##7##]. The intake of solid or semi-solid foods increases at 6 months, whereas breastfeeding and formula feeding are progressively reduced [##REF##33630931##8##].</p>", "<p id=\"Par7\">The consumption of unhealthy foods are associated with higher risk of acquiring non-communicable diseases including type 2 diabetes, hypertension, hypercholesterolemia, and obesity [##REF##22224718##9##]. Worldwide, around 43 million children aged 0–59 months are overweight or obese, and nearly 81% of them are living in LMICs [##REF##20861173##10##]. Infant and young children’s feeding practices, rapid weight gain, the child’s diet, and a sedentary lifestyle are contributing factors to the development of infant and childhood obesity [##REF##22332105##11##, ##REF##18606933##12##]. Childhood overweight and obesity is attributed to the fifth leading global risk for mortality, accounting for 44% of the diabetes burden, 23% of the ischemic heart disease, and 7-41% of certain cancers [##UREF##3##13##]. Literature indicated an increasing burden of childhood overweight or obesity in SSA, with a pooled prevalence of 5.1%, and a higher prevalence was reported in the South African region (8.8%) [##REF##34980043##14##, ##REF##31908777##15##]. Unhealthy diets were also determinants of overweight or obesity among children and adolescents [##REF##31938033##16##].</p>", "<p id=\"Par8\">Healthy eating and consumption of important nutrients helps to achieve and maintain a healthy body weight and reduce the risk of developing high blood pressure, heart disease, type 2 diabetes, cancer, osteoporosis, iron deficiency, and dental caries [##UREF##4##17##]. Healthy eating behaviors are also associated with improved cognitive function [##REF##19930787##18##]. Different guidelines indicated the need to avoid or limit unhealthy foods when feeding infant and young children [##REF##28922262##19##]. However, research from the SSA regarding UFC remains limited, with no studies quantifying the pooled prevalence of UFC among young children in the region. To our knowledge, there is no study conducted in SSA to determine the pooled prevalence and associated factors of UFC among children aged 6 to 23 months using the most recent WHO and UNICEF guidelines for assessing infant and young child feeding practices published in 2021. Therefore, this study is intended to assess the pooled prevalence and determinants of unhealthy food consumption among children aged 6 to 23 months in sub-Saharan African countries using the recent demographic and health survey.</p>" ]
[ "<title>Methods and materials</title>", "<title>Data sources, study design, and sampling</title>", "<p id=\"Par9\">A cross-sectional pooled data using recent DHS from five sub-Saharan African countries, which were conducted between 2015/16 and 2022 was employed. Demographic and health surveys from five sub-Saharan African countries including Kenya (2022), Malawi (2015/16), Tanzania (2022), Uganda (2016), and South Africa (2016) were used. The data were appended to figure out the pooled prevalence of UFC and its determinants among children aged 6–23 months in sub-Saharan African countries. Different datasets, including those for children, males, women, births, and households are included in the survey for each country. For this study, the kid’s record (KR file) was used. The DHS is a nationwide survey mostly collected every five years across LMICs. It makes cross-country comparison possible as it uses standard procedures for sampling, questionnaires, data collection, cleaning, coding, and analysis [##REF##23148108##20##].</p>", "<p id=\"Par10\">The DHS employs a stratified two-stage sampling technique [##UREF##5##21##]. The first stage involves the development of a sampling frame, consisting of a list of primary sampling units (PSUs) or enumeration areas (EAs), which covers the entire country and is usually developed from the latest available national census. The second stage is the systematic sampling of households listed in each cluster or EA. In the current study, a total weighted sample of 16,226 children aged 6 to 23 months were (Table ##TAB##0##1##). Further information on the survey sampling strategies is available in the DHS guideline [##UREF##6##22##].</p>", "<p id=\"Par11\">\n\n</p>", "<title>Variables of the study</title>", "<title>Outcome variable</title>", "<p id=\"Par12\">The dependent variable of this study was unhealthy food consumption (“1”: consumed unhealthy food, “0”: didn’t consume unhealthy food). Unhealthy food consumption is defined as the consumption of selected sentinel foods (chocolates, sweets, candies, pastries, etc.) during the previous day [##UREF##0##1##]. If any amount of food from any of the sentinel categories has been consumed, children are counted as “consumed unhealthy food,” otherwise they are counted as “not consumed unhealthy food.”</p>", "<title>Independent variables</title>", "<p id=\"Par13\">Both individual and community-level variables were considered. Individual-level variables: maternal age (15–24 years, 25–34 years, 35–49 years), maternal education (no education, primary, secondary or higher), current marital status of the mother (married, unmarried), maternal occupation (not working, working), media exposure (yes, no), wealth index (poor, middle, rich), place of delivery (home, health facility), attended 4 + ANC visits (yes, no), PNC checkup (yes, no), age of the child (6–8 months, 9–11 months, 12–17 months, 18–23 months), and sex of the child (male, female). Community-level variables: place of residence (urban, rural), community poverty level (low, high), community literacy (low, high), and community level media exposure (low, high) (Fig. ##FIG##0##1##).</p>", "<p id=\"Par14\">\n\n</p>", "<title>Description of independent variables</title>", "<title>Media exposure</title>", "<p id=\"Par15\">Created by combining whether a respondent reads newspapers/magazines, listens to the radio, and watch television and coded as “yes” if the mother was exposed to at least one of these media and “no” otherwise.</p>", "<title>Community level media exposure</title>", "<p id=\"Par16\">The proportion of women who had exposed to at least one media; television, radio, or newspaper and categorized based on national median value as low (communities with ≤ 50% of women exposed) and high (communities with &gt; 50% of women exposed) community-level media exposure.</p>", "<title>Community literacy</title>", "<p id=\"Par17\">The proportion of women with a minimum of primary level of education derived from data on respondents’ level of education. Then, it was categorized using national median value to values: low (communities with ≤ 50% of women have at least primary education) and high (communities with &gt; 50% of women have at least primary education) community literacy.</p>", "<title>Community poverty level</title>", "<p id=\"Par18\">Aggregated variable from household wealth status (proportion of women from poor and rich wealth status) and it was recoded as low and high community poverty level likewise.</p>", "<title>Data processing and analysis</title>", "<p id=\"Par19\">Data extracted from the recent DHS data sets were cleaned, recorded, and analyzed using STATA/SE version 14.0 statistical software. Sample weight was employed to manage sampling errors and non-responses. Continuous variables were categorized, and categorical variables were further re-categorized. Descriptive analysis was carried out to present the data in frequencies and percentages. Both the individual and community-level variables were presented using descriptive statistics. The DHS data’s variables were organized in clusters; 16,226 children are nested within households, and households were nested within 1692 clusters. The assumptions of independent observations and equal variance across clusters were broken to employ the traditional logistic regression model. This is an indication that using a sophisticated model to take into account between-cluster factors is necessary. As a result, multilevel mixed-effects logistic regression was used to determine the factors associated with UFC. Multilevel mixed effect logistic regression follows four models: the null model (outcome variable only), mode I (only individual-level variables), model II (only community-level variables), and model III (both individual and community-level variables). The model without independent variables (the null model) was used to check the variability of UFC across the cluster. The association of individual-level variables with the outcome variable (Model I) and the association of community-level variables with the outcome variable (Model II) were assessed. In the final model (Model III), the association of both individual and community-level variables was fitted simultaneously with the outcome variable (UFC).</p>", "<p id=\"Par20\">The magnitude of the clustering effect and the degree to which community-level factors explain the unexplained variance of the null model were quantified by checking the intra-class correlation coefficient (ICC) and proportional change in variance (PCV). A model with the lowest deviance was selected as the best-fitted model. Finally, variables with a p-value less than 0.05 and an adjusted odds ratio (AOR) with a 95% confidence interval (CI) were described as statistically significant variables associated with the consumption of unhealthy foods. The presence of multi-collinearity between covariates was checked by using a variance inflation factor (VIF) falling within acceptable limits of 1–10, indicating the absence of significant collinearity across independent variables. Missing and “don’t know” data on foods and liquids given is treated as not given in numerator and included in denominator.</p>", "<title>Random effects</title>", "<p id=\"Par21\">Random effects or measures of variation of the outcome variable were estimated using the median odds ratio (MOR), ICC, and PCV. ICC and PCV were used to measure the variation between clusters. Taking clusters as a random variable, the ICC reveals the variation of UFC between clusters and is computed as ICC = VC/(VC + 3.29)×100%. The MOR is the median value of the odds ratio between the area of the highest risk and the area of the lowest risk for UFC when two clusters are randomly selected, using clusters as a random variable; MOR = 𝑒 0.95√VC. In addition, the PCV demonstrates the variation in the prevalence of UFC explained by factors and computed as PCV= (Vnull-VC)/Vnull×100%; where Vnull = variance of the null model and VC = cluster level variance [##UREF##7##23##]. The association between the likelihood of unhealthy food consumption and individual and community-level independent variables was estimated by the fixed effects.</p>" ]
[ "<title>Results</title>", "<title>Individual- and community-level characteristics of study subjects</title>", "<p id=\"Par22\">A total of 16,226 children aged 6 to 23 months were included in this study. The mean age of mothers was 27.64 ± 0.05 years, and 43.61% of them fall in the age range of 25–34 years. More than half (53.39%) of the mothers completed primary education, and 81.84% of them are currently married. Regarding occupation, 64.10% of mothers had work, and nearly two-thirds (66.13%) of them had media exposure. More than one-third (33.93%) of the mothers in SSA had rich socioeconomic status. The majority (84.13%) of mothers in SSA countries were delivered at health facilities, and only 31.93% of them had PNC checkups. More than half (61.48%) of mothers attended 4 + ANC visits during their pregnancy. The mean age of children was 14.28 ± 0.04 months, and 33.16% of them fall in the age range of 12–17 months. More than half (50.95%) of children aged 6–23 months were male. More than three-fourths (76.16%) of the study subjects were from rural areas, and 54.36% of them had low community-level media exposure. More than half (50.44%) of mothers of children aged 6–23 months had low community-level poverty, and 60.48% of them had high community-level literacy (Table ##TAB##1##2##).</p>", "<p id=\"Par23\">\n\n</p>", "<title>Pooled prevalence of unhealthy food consumption</title>", "<p id=\"Par24\">In the present study, 13.41% (95% CI: 12.89–13.94%) of children aged 6–23 months consumed unhealthy foods during the day preceding the survey (Fig. ##FIG##1##2##). The result showed that consumption of unhealthy foods increases with increasing household wealth status, with the proportion of children who consumed unhealthy foods being lowest among children from poor household families (10.12%) and highest among rich household families (18.07%) (Fig. ##FIG##2##3##). The consumption of unhealthy foods was high in South Africa (35.13%), followed by Malawi (14.25%), and low in Tanzania (6.80%) (Fig. ##FIG##3##4##).</p>", "<p id=\"Par25\">\n\n</p>", "<p id=\"Par26\">\n\n</p>", "<p id=\"Par27\">\n\n</p>", "<title>Measures of variation and model fitness</title>", "<p id=\"Par28\">A null model was used to determine whether the data supported the decision to assess randomness at the community level. Findings from the null model showed that there were significant differences in UFC between communities, with a variance of 0.2362062 and a P value of 0.000. The variance within clusters contributed 93.30% of the variation in UFC, while the variance across clusters was responsible for 6.70% of the variation. In the null model, the odds of UFC differed between higher- and lower-risk clusters by a factor of 1.52 times. The intra-class correlation value for Model I indicated that 5.70% of the variation in UFC accounts for the disparities between communities. Then, with the null model, we used community-level variables to generate Model II. According to the ICC value from Model II, cluster variations were the basis for 5.53% of the differences in UFC. In the final model (model III), which attributed approximately 5.61% of the variation in the likelihood of UFC to both individual and community-level variables, the likelihood of UFC varied by 1.49 times across low and high UFC (Table ##TAB##2##3##).</p>", "<p id=\"Par29\">\n\n</p>", "<title>Individual and community-level factors associated with unhealthy food consumption</title>", "<p id=\"Par30\">In the final fitted model of multivariable multilevel logistic regression, maternal educational level, marital status of the mother, exposure to media, wealth index, place of delivery, PNC checkup, the current age of the child, and community level media exposure were factors significantly associated with consumption of unhealthy foods among children aged 6–23 months. Mothers of children who completed secondary or higher education were 63% and 44% times less likely to give unhealthy foods to their child than those who had no education and completed primary education, respectively [AOR = 0.37; 95% CI (0.30, 0.46)] and [AOR = 0.56; 95% CI (0.50, 0.62)]. The odds of UFC were 1.19 times higher among unmarried women compared with their counterparts [AOR = 1.19; 95% CI (1.05, 1.34)]. Those mothers who had media exposure were 36% less likely to give their child unhealthy foods compared with mothers who hadn’t [AOR = 0.64; 95% CI (0.56, 0.72)].</p>", "<p id=\"Par31\">Household wealth status was another determinant of UFC, in which children from wealthier households were 1.20 times more likely to consume unhealthy foods compared with those from poor economic status [AOR = 1.20; 95% CI (1.05, 1.37)]. Mothers who delivered at a health facility were 26% less likely to feed their child unhealthy foods compared with those who delivered at home [AOR = 0.74; 95% CI (0.62, 0.87)]. Children of mothers who had PNC checkups were 44% less likely to consume unhealthy foods compared with their counterparts [AOR = 0.66; 95% CI (0.60, 0.73)]. This study also revealed high consumption of unhealthy foods as the child gets older. The odds of UFC were 3.88, 2.80, and 2.00 times higher among children aged 18–23, 12–17, and 9–11 months compared with those aged 6–8 months [AOR = 3.88; 95% CI (3.25, 4.63)], [AOR = 2.80; 95% CI (2.34, 3.34)], and [AOR = 2.00; 95% CI (1.64, 2.45)]. Finally, children from a community with low media exposure were 1.18 times more likely to consume unhealthy foods compared with their counterparts [AOR = 1.18; 95% CI (1.04, 1.34)] (Table ##TAB##3##4##).</p>", "<p id=\"Par32\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par33\">In the current study, the pooled prevalence of UFC among children aged 6–23 months in SSA countries was 13.41% (95% CI: 12.89–13.94%). This finding was lower than studies conducted in Ethiopia (63.7%) [##REF##37231455##24##] and Brazil (43.1%) [##REF##29890116##25##]. This discrepancy might be attributed to differences in sample size, study period, study area, and socio-economic status of the study subjects. The previous studies were conducted in a single area using a small sample size, whereas the current study uses pooled data from five countries and a larger sample size. The difference might also be due to differences in the determination of the outcome variable. The current study uses the 2021 WHO guideline indicators for infant and child feeding practices to get UFC. The study conducted in Brazil was conducted in 2019 before the declaration of this guideline.</p>", "<p id=\"Par34\">Maternal educational status, marital status of the mother, exposure to media, wealth index, place of delivery, PNC checkup, the current age of the child, and community-level media exposure were determinants of UFC. Highly educated mothers were less likely to feed their children unhealthy foods. This finding was in agreement with studies conducted in Ethiopia [##REF##37231455##24##], Brazil [##REF##29890116##25##–##REF##24405527##27##], and Mexico [##REF##31454895##28##]. This might be due to the fact that mothers with a low educational level are more likely to have poor understandings about the significance of consuming healthy foods like fresh fruits and vegetables [##UREF##9##29##]. Mothers with a high educational level are also more often limited their children’s consumption of unhealthy foods such as sweets, soft drinks, and chips [##REF##9783876##30##]. This can also be explained by the association between low maternal education and low purchasing capacity, as well as a lack of access to health-related information, which could possibly lead to the choice of unhealthy foods for children [##REF##23988496##31##]. Thus, children of mothers with low education are better suited to be targeted for interventions aimed at reinforcing the attainment of healthy eating habits and reducing adverse health effects.</p>", "<p id=\"Par35\">Similarly, the odds of UFC were 1.19 times higher among unmarried women compared with their counterparts. This might be due to the lower average nutritional status of never-married, widowed, and divorced women [##UREF##10##32##]. This can also be explained by the fact that married mothers living with their husbands are more knowledgeable about healthy foods for children, and husbands may contribute money to buy different foods. Mothers are better encouraged to stay in relationships to get the most basic support from their partner. Mothers who had media exposure were less likely to give their children unhealthy foods compared with mothers who hadn’t. Likewise, children from a community with low media exposure were 1.18 times more likely to consume unhealthy foods compared with their counterparts. This finding was supported by a study conducted in Indonesia [##REF##28802300##33##]. This might be due to the effectiveness of mass media in disseminating healthy feeding messages, as large audiences across boundaries can be potentially reached [##UREF##11##34##]. Mother’s knowledge, attitudes, beliefs, and behaviors towards healthy eating habits can be shaped through routine exposure to mass media [##UREF##12##35##]. Mass media campaigns for health promotion and disease prevention, including healthy eating habits among children, are essential to reducing unhealthy food consumption.</p>", "<p id=\"Par36\">Children from wealthier households were 1.20 times more likely to consume unhealthy foods compared with those from poor wealth status. A similar finding was reported by a study conducted in West Africa [##REF##31717487##36##]. This might be attributed to the fact that the richest families may have the income to buy unhealthy foods like sweets and chocolates. Children from wealthier households may also consume candies, chocolate, chips, French fries, cakes, and cookies more than those from poor families, as they rely on other cheap foods. Children of mothers who delivered at a health facility and had a PNC checkup were less likely to consume unhealthy foods. This might be due to the fact that mothers who deliver at health facilities can get advice from health professionals about healthy feeding habits. The counseling provided to mothers during post-natal checkups could also contribute to decreased consumption of unhealthy foods. Finally, high consumption of unhealthy foods was reported as the child got older. The odds of UFC were four, three, and two times higher among children aged 18–23, 12–17, and 9–11 months compared with those aged 6–8 months. This finding was consistent with studies conducted in African and Asian urban contexts [##REF##29032629##37##], Nepal [##REF##31225707##38##], and West Africa [##REF##31717487##36##]. Our finding was contradicted by a study conducted in Ethiopia [##REF##37231455##24##]. This might be due to the fact that as the child gets older, they become more vulnerable to the effects of different situations they encounter, enabling food selections that are not healthy. Another possible reason could be child preference and a strong claim for sweet and inconvenient foods as they get older.</p>", "<title>Strengths and limitations of the study</title>", "<p id=\"Par37\">The use of a nationally representative, large sample size across three countries in SSA to determine the pooled prevalence of UFC and identify its individual and community-level factors among children aged 6 to 23 months is the main strength of this study. The other strength of the present study is the use of advanced statistical models that consider individual and community-level factors. The current study also has some limitations. First, as we only included five countries in the SSA, the findings may not be generalizable to all SSA countries. Secondly, the causal relationship between the outcome variable and independent variables could not be established due to the cross-sectional nature of the study design. Finally, there might be a possibility of recall bias as the DHS survey depends on respondents’ self-reporting.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par38\">Nearly one out of seven children aged 6 to 23 months consumed unhealthy foods. Maternal educational level, marital status of the mother, exposure to media, wealth index, place of delivery, PNC checkup, and the current age of the child were factors significantly associated with unhealthy food consumption. Therefore, improving women’s education, disseminating nutrition-related information through the media, providing more attention to poor and unmarried women, and strengthening health facility delivery and postnatal care services are recommended to reduce the consumption of unhealthy foods by infants and young children.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Unhealthy food consumption that begins early in life is associated with a higher risk of nutrient inadequacy and related chronic diseases later in life. Healthy eating and consumption of important nutrients help to maintain a healthy body weight and reduce the risk of developing chronic conditions. Research from sub-Saharan Africa regarding consumption of unhealthy foods remains limited, with no studies quantifying the pooled prevalence among young children. Therefore, this study is intended to assess the pooled prevalence and determinants of unhealthy food consumption among children aged 6 to 23 months.</p>", "<title>Methods</title>", "<p id=\"Par2\">Data from the most recent demographic and health surveys of five countries in sub-Saharan Africa conducted between 2015 and 2022 were used. A total weighted sample of 16,226 children aged 6 to 23 months was included in the study. Data extracted from DHS data sets were cleaned, recorded, and analyzed using STATA/SE version 14.0 statistical software. Multilevel mixed-effects logistic regression was used to determine the factors associated with the dependent variable. Intra-class correlation coefficient, likelihood ratio test, median odds ratio, and deviance (-2LLR) values were used for model comparison and fitness. Finally, variables with a p-value &lt; 0.05 and an adjusted odds ratio with a 95% confidence interval were declared statistically significant.</p>", "<title>Results</title>", "<p id=\"Par3\">The pooled prevalence of unhealthy food consumption among children aged 6 to 23 months was 13.41% (95% CI: 12.89-13.94%). Higher consumption of unhealthy foods was reported among mothers with low education [adjusted odds ratio (AOR) = 0.37; 95% confidence interval (CI) (0.30, 0.46)], unmarried women [AOR = 1.19; 95% CI (1.05, 1.34)], who had no media exposure [AOR = 0.64; 95% CI (0.56, 0.72)], delivered at home [AOR = 0.74; 95% CI (0.62, 0.87)], who hadn’t had a PNC checkup [AOR = 0.66; 95% CI (0.60, 0.73)], wealthier households [AOR = 1.20; 95% CI (1.05, 1.37)], older children (aged ≥ 9 months) [AOR = 3.88; 95% CI (3.25, 4.63)], and low community level media exposure [AOR = 1.18; 95% CI (1.04, 1.34)].</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Nearly one out of seven children aged 6 to 23 months consumed unhealthy foods. Maternal educational level, marital status of the mother, exposure to media, wealth index, place of delivery, PNC checkup, and the current age of the child were factors significantly associated with unhealthy food consumption. Therefore, improving women’s education, disseminating nutrition-related information through the media, providing more attention to poor and unmarried women, and strengthening health facility delivery and postnatal care services are recommended.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We are grateful to the DHS program for letting us use the relevant DHS data in this study.</p>", "<title>Author contributions</title>", "<p>Conceptualization, data curation, formal analysis, and investigation were done by E.G.M, A.F.Z, and B.T. Methodology and software were done by E.G.M, M.A.T, B.S.W, and T.T.T. Supervision, validation, visualization, and writing the original draft were done by E.G.M, A.F.Z, B.S.W, M.A.T, and T.T.T. Writing, reviewing, and editing were done by E.G.M and B.T. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.</p>", "<title>Funding</title>", "<p>Not applicable.</p>", "<title>Data availability</title>", "<p>The data from the five SSA countries is publicly available online at (<ext-link ext-link-type=\"uri\" xlink:href=\"https://dhsprogram.com/data/available-datasets.cfm\">https://dhsprogram.com/data/available-datasets.cfm</ext-link>).</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to participate</title>", "<p id=\"Par40\">Permission was granted to download and use the data from <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.dhsprogram.com/data/dataset_admin/login_main.cfm\">https://www.dhsprogram.com/data/dataset_admin/login_main.cfm</ext-link> before conducting the study. Ethical clearance was obtained from the Institution Review Board of the DHS Program, ICF International. The procedures for DHS public-use data sets were approved by the Institution Review Board. Identifiers for respondents, households, or sample communities were not allowed in any way, and the names of individuals or household addresses were not included in the data files. The number for each EA in the data file does not have labels to show their names or locations. There were no patients or members of the public involved since this study used a publicly available data set.</p>", "<title>Consent for publication</title>", "<p id=\"Par41\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par39\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Conceptual framework for factors associated with unhealthy food consumption among children aged 6 to 23 months in SSA</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Unhealthy food consumption among children aged 6 to 23 months in sub-Saharan African countries, DHS 2015/16 to 2022 (<italic>n</italic> = 16,226)</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Unhealthy food consumption by household wealth status among children aged 6 to 23 months in sub-Saharan African countries, DHS 2015/16 to 2022 (<italic>n</italic> = 16,226)</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Unhealthy food consumption by country among children aged 6 to 23 months in sub-Saharan African countries, DHS 2015/16 to 2022 (<italic>n</italic> = 16,226)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Sample size for unhealthy food consumption and its determinants among children aged 6 to 23 months in sub-Saharan African countries</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Country</th><th align=\"left\">Year of survey</th><th align=\"left\">Weighted sample (n)</th><th align=\"left\">Weighted sample (%)</th></tr></thead><tbody><tr><td align=\"left\">Kenya</td><td align=\"left\">2022</td><td align=\"left\">2,944</td><td align=\"left\">18.14</td></tr><tr><td align=\"left\">Malawi</td><td align=\"left\">2015/16</td><td align=\"left\">4,843</td><td align=\"left\">29.85</td></tr><tr><td align=\"left\">Tanzania</td><td align=\"left\">2022</td><td align=\"left\">3,189</td><td align=\"left\">19.65</td></tr><tr><td align=\"left\">Uganda</td><td align=\"left\">2016</td><td align=\"left\">4,359</td><td align=\"left\">26.86</td></tr><tr><td align=\"left\">South Africa</td><td align=\"left\">2016</td><td align=\"left\">891</td><td align=\"left\">5.50</td></tr><tr><td align=\"left\" colspan=\"2\">\n<bold>Total sample size</bold>\n</td><td align=\"left\">16,226</td><td align=\"left\">100</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Individual-and community-level characteristics of study subjects, pooled data from five SSA countries (<italic>n</italic> = 16,226)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Category</th><th align=\"left\">Frequency (n)</th><th align=\"left\">Percentage (%)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Maternal age</td><td align=\"left\">15–24 years</td><td align=\"left\">6,260</td><td align=\"left\">38.58</td></tr><tr><td align=\"left\">25–34 years</td><td align=\"left\">7,076</td><td align=\"left\">43.61</td></tr><tr><td align=\"left\">35–49 years</td><td align=\"left\">2,890</td><td align=\"left\">17.81</td></tr><tr><td align=\"left\" rowspan=\"3\">Maternal educational level</td><td align=\"left\">No formal education</td><td align=\"left\">2,364</td><td align=\"left\">14.57</td></tr><tr><td align=\"left\">Primary</td><td align=\"left\">8,663</td><td align=\"left\">53.39</td></tr><tr><td align=\"left\">Secondary and above</td><td align=\"left\">5,199</td><td align=\"left\">32.04</td></tr><tr><td align=\"left\" rowspan=\"2\">Current marital status of the mother</td><td align=\"left\">Married</td><td align=\"left\">13,280</td><td align=\"left\">81.84</td></tr><tr><td align=\"left\">Unmarried</td><td align=\"left\">2,946</td><td align=\"left\">18.16</td></tr><tr><td align=\"left\" rowspan=\"2\">Maternal occupation</td><td align=\"left\">Not working</td><td align=\"left\">5,822</td><td align=\"left\">35.90</td></tr><tr><td align=\"left\">Working</td><td align=\"left\">10,399</td><td align=\"left\">64.10</td></tr><tr><td align=\"left\" rowspan=\"2\">Exposure to media</td><td align=\"left\">Yes</td><td align=\"left\">10,731</td><td align=\"left\">66.13</td></tr><tr><td align=\"left\">No</td><td align=\"left\">5,495</td><td align=\"left\">33.87</td></tr><tr><td align=\"left\" rowspan=\"3\">Wealth index</td><td align=\"left\">Poor</td><td align=\"left\">7,620</td><td align=\"left\">46.96</td></tr><tr><td align=\"left\">Middle</td><td align=\"left\">3,100</td><td align=\"left\">19.11</td></tr><tr><td align=\"left\">Rich</td><td align=\"left\">5,506</td><td align=\"left\">33.93</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of delivery</td><td align=\"left\">Home</td><td align=\"left\">2,575</td><td align=\"left\">15.87</td></tr><tr><td align=\"left\">Health facility</td><td align=\"left\">13,651</td><td align=\"left\">84.13</td></tr><tr><td align=\"left\" rowspan=\"2\">Attended 4 + ANC visits</td><td align=\"left\">Yes</td><td align=\"left\">9,976</td><td align=\"left\">61.48</td></tr><tr><td align=\"left\">No</td><td align=\"left\">6,250</td><td align=\"left\">38.52</td></tr><tr><td align=\"left\" rowspan=\"2\">PNC checkup</td><td align=\"left\">Yes</td><td align=\"left\">4,993</td><td align=\"left\">31.93</td></tr><tr><td align=\"left\">No</td><td align=\"left\">10,643</td><td align=\"left\">68.07</td></tr><tr><td align=\"left\" rowspan=\"4\">Age of child</td><td align=\"left\">6–8 months</td><td align=\"left\">2,809</td><td align=\"left\">17.32</td></tr><tr><td align=\"left\">9–11 months</td><td align=\"left\">2,832</td><td align=\"left\">17.45</td></tr><tr><td align=\"left\">12–17 months</td><td align=\"left\">5,381</td><td align=\"left\">33.16</td></tr><tr><td align=\"left\">18–23 months</td><td align=\"left\">5,204</td><td align=\"left\">32.07</td></tr><tr><td align=\"left\" rowspan=\"2\">Sex of child</td><td align=\"left\">Male</td><td align=\"left\">8,267</td><td align=\"left\">50.95</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">7,959</td><td align=\"left\">49.05</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of residence</td><td align=\"left\">Rural</td><td align=\"left\">12,357</td><td align=\"left\">76.16</td></tr><tr><td align=\"left\">Urban</td><td align=\"left\">3,869</td><td align=\"left\">23.84</td></tr><tr><td align=\"left\" rowspan=\"2\">Community media exposure</td><td align=\"left\">Low</td><td align=\"left\">8,821</td><td align=\"left\">54.36</td></tr><tr><td align=\"left\">High</td><td align=\"left\">7,405</td><td align=\"left\">45.64</td></tr><tr><td align=\"left\" rowspan=\"2\">Community poverty</td><td align=\"left\">Low</td><td align=\"left\">8,184</td><td align=\"left\">50.44</td></tr><tr><td align=\"left\">High</td><td align=\"left\">8,042</td><td align=\"left\">49.56</td></tr><tr><td align=\"left\" rowspan=\"2\">Community literacy</td><td align=\"left\">Low</td><td align=\"left\">6,413</td><td align=\"left\">39.52</td></tr><tr><td align=\"left\">High</td><td align=\"left\">9,813</td><td align=\"left\">60.48</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Model comparison and random effect analysis for unhealthy food consumption among children aged 6–23 months in Sub-Saharan African countries</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Parameter</th><th align=\"left\">Null model</th><th align=\"left\">Model I</th><th align=\"left\">Model II</th><th align=\"left\">Model III</th></tr></thead><tbody><tr><td align=\"left\">Variance</td><td align=\"left\">0.2362062</td><td align=\"left\">0.199689</td><td align=\"left\">0.1924122</td><td align=\"left\">0.1955166</td></tr><tr><td align=\"left\">ICC</td><td align=\"left\">6.70%</td><td align=\"left\">5.70%</td><td align=\"left\">5.53%</td><td align=\"left\">5.61%</td></tr><tr><td align=\"left\">MOR</td><td align=\"left\">1.58</td><td align=\"left\">1.52</td><td align=\"left\">1.51</td><td align=\"left\">1.49</td></tr><tr><td align=\"left\">PCV</td><td align=\"left\">Reference</td><td align=\"left\">15.46%</td><td align=\"left\">18.54%</td><td align=\"left\">17.23%</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Model fitness</bold>\n</td></tr><tr><td align=\"left\">LLR</td><td align=\"left\">-6360.511</td><td align=\"left\">-5790.518</td><td align=\"left\">-6301.657</td><td align=\"left\">-5786.415</td></tr><tr><td align=\"left\">Deviance</td><td align=\"left\">12,721.022</td><td align=\"left\">11,581.036</td><td align=\"left\">12,603.314</td><td align=\"left\">11,572.830</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Multivariable multilevel logistic regression analysis of individual and community-level factors associated with UFC among children aged 6–23 months in SSA countries</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Category</th><th align=\"left\">Model I<break/>AOR (95% CI)</th><th align=\"left\">Model II<break/>AOR (95% CI)</th><th align=\"left\">Model III<break/>AOR (95% CI)</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"3\">Maternal age</td><td align=\"left\">15–24 years</td><td align=\"left\">1.12 (0.97, 1.29)</td><td align=\"left\"/><td align=\"left\">1.12 (0.97, 1.30)</td></tr><tr><td align=\"left\">25–34 years</td><td align=\"left\">1.01 (0.87, 1.15)</td><td align=\"left\"/><td align=\"left\">1.01 (0.87, 1.16)</td></tr><tr><td align=\"left\">35–49 years</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"3\">Maternal educational level</td><td align=\"left\">No formal education</td><td align=\"left\">0.36 (0.29, 0.45)*</td><td align=\"left\"/><td align=\"left\">0.37 (0.30, 0.46)*</td></tr><tr><td align=\"left\">Primary</td><td align=\"left\">0.56 (0.50, 0.62)*</td><td align=\"left\"/><td align=\"left\">0.56 (0.50, 0.62)*</td></tr><tr><td align=\"left\">Secondary and above</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Marital status of the mother</td><td align=\"left\">Married</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\">Unmarried</td><td align=\"left\">1.19 (1.06, 1.34)*</td><td align=\"left\"/><td align=\"left\">1.19 (1.05, 1.34)*</td></tr><tr><td align=\"left\" rowspan=\"2\">Maternal occupation</td><td align=\"left\">Not working</td><td align=\"left\">0.91 (0.82, 1.01)</td><td align=\"left\"/><td align=\"left\">0.90 (0.81, 1.01)</td></tr><tr><td align=\"left\">Working</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Exposure to media</td><td align=\"left\">Yes</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\">No</td><td align=\"left\">0.65 (0.58, 0.74)*</td><td align=\"left\"/><td align=\"left\">0.64 (0.56, 0.72)*</td></tr><tr><td align=\"left\" rowspan=\"3\">Wealth index</td><td align=\"left\">Poor</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\">Middle</td><td align=\"left\">1.11 (0.96, 1.27)</td><td align=\"left\"/><td align=\"left\">1.09 (0.94, 1.25)</td></tr><tr><td align=\"left\">Rich</td><td align=\"left\">1.25 (1.11, 1.41)*</td><td align=\"left\"/><td align=\"left\">1.20 (1.05, 1.37)*</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of delivery</td><td align=\"left\">Home</td><td align=\"left\">0.73 (0.62, 0.86)*</td><td align=\"left\"/><td align=\"left\">0.74 (0.62, 0.87)*</td></tr><tr><td align=\"left\">Health facility</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Attended 4 + ANC visits</td><td align=\"left\">Yes</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\">No</td><td align=\"left\">0.92 (0.83, 1.02)</td><td align=\"left\"/><td align=\"left\">0.92 (0.83, 1.02)</td></tr><tr><td align=\"left\" rowspan=\"2\">PNC checkup</td><td align=\"left\">Yes</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\">No</td><td align=\"left\">0.66 (0.60, 0.73)*</td><td align=\"left\"/><td align=\"left\">0.66 (0.60, 0.73)*</td></tr><tr><td align=\"left\" rowspan=\"4\">Age of child</td><td align=\"left\">6–8 months</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\">9–11 months</td><td align=\"left\">2.01 (1.64, 2.45)*</td><td align=\"left\"/><td align=\"left\">2.00 (1.64, 2.45)*</td></tr><tr><td align=\"left\">12–17 months</td><td align=\"left\">2.80 (2.34, 3.35)*</td><td align=\"left\"/><td align=\"left\">2.80 (2.34, 3.34)*</td></tr><tr><td align=\"left\">18–23 months</td><td align=\"left\">3.88 (3.25, 4.63)*</td><td align=\"left\"/><td align=\"left\">3.88 (3.25, 4.63)*</td></tr><tr><td align=\"left\" rowspan=\"2\">Sex of child</td><td align=\"left\">Male</td><td align=\"left\">0.93 (0.84, 1.02)</td><td align=\"left\"/><td align=\"left\">0.93 (0.84, 1.02)</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">1</td><td align=\"left\"/><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Place of residence</td><td align=\"left\">Rural</td><td align=\"left\"/><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">Urban</td><td align=\"left\"/><td align=\"left\">1.56 (1.40, 1.74)*</td><td align=\"left\">1.07 (0.94, 1.21)</td></tr><tr><td align=\"left\" rowspan=\"2\">Community media exposure</td><td align=\"left\">Low</td><td align=\"left\"/><td align=\"left\">1.01 (0.90, 1.15)</td><td align=\"left\">1.18 (1.04, 1.34)*</td></tr><tr><td align=\"left\">High</td><td align=\"left\"/><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\" rowspan=\"2\">Community poverty</td><td align=\"left\">Low</td><td align=\"left\"/><td align=\"left\">1</td><td align=\"left\">1</td></tr><tr><td align=\"left\">High</td><td align=\"left\"/><td align=\"left\">0.86 (0.76, 0.97)*</td><td align=\"left\">0.92 (0.81, 1.05)</td></tr><tr><td align=\"left\" rowspan=\"2\">Community literacy</td><td align=\"left\">Low</td><td align=\"left\"/><td align=\"left\">0.79 (0.69, 0.89)*</td><td align=\"left\">0.93 (0.81, 1.06)</td></tr><tr><td align=\"left\">High</td><td align=\"left\"/><td align=\"left\">1</td><td align=\"left\">1</td></tr></tbody></table></table-wrap>" ]
[]
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[ "<table-wrap-foot><p>ICC: Intra cluster correlation, LLR: log-likelihood ratio, MOR: median odds ratio, PCV: Proportional change in variance</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[]
[{"label": ["1."], "mixed-citation": ["WHO. Indicators for assessing infant and young child feeding practices: definitions and measurement methods. 2021."]}, {"label": ["3."], "mixed-citation": ["Ireland H. Feeding your baby: introducing family foods. Health Service Executive; 2018."]}, {"label": ["5."], "mixed-citation": ["WHO. Essential nutrition actions: improving maternal, newborn, infant and young child health and nutrition. 2013."]}, {"label": ["13."], "mixed-citation": ["WHO. Global health risks: mortality and burden of disease attributable to selected major risks. World Health Organization; 2009."]}, {"label": ["17."], "mixed-citation": ["McGuire S. Scientific report of the 2015 dietary guidelines advisory committee. Washington, DC: US Departments of Agriculture and Health and Human Services, 2015. Advances in nutrition. 2016;7(1):202-4."]}, {"label": ["21."], "mixed-citation": ["Aliaga A. In: Ruilin R, editor. Cluster optimal sample size for demographic and health surveys. 7th International Conference on Teaching Statistics\u2013ICOTS; 2006."]}, {"label": ["22."], "surname": ["Croft", "Marshall", "Allen", "Arnold", "Assaf", "Balian"], "given-names": ["T", "AM", "CK", "F", "S", "S"], "source": ["Guide to DHS statistics: DHS-7 (version 2)"], "year": ["2020"], "publisher-loc": ["Rockville, MD"], "publisher-name": ["ICF"]}, {"label": ["23."], "surname": ["Sommet", "Morselli"], "given-names": ["N", "D"], "article-title": ["Keep calm and learn multilevel logistic modeling: a simplified three-step procedure using Stata, R, mplus, and SPSS"], "source": ["Int Rev Social Psychol"], "year": ["2017"], "volume": ["30"], "fpage": ["203"], "lpage": ["18"], "pub-id": ["10.5334/irsp.90"]}, {"label": ["26."], "surname": ["Saldan", "Mello"], "given-names": ["PC", "DF"], "article-title": ["Variables associated with the consumption of unhealthy foods by children aged from 6 to 23 months in a city in the countryside of Paran\u00e1 State, Brazil"], "source": ["DEMETRA Alimenta\u00e7\u00e3o Nutri\u00e7\u00e3o &amp; Sa\u00fade"], "year": ["2019"], "volume": ["14"], "fpage": ["e43705"], "pub-id": ["10.12957/demetra.2019.43705"]}, {"label": ["29."], "mixed-citation": ["Campbell K, Crawford D, Jackson M, Cashel K, Worsley T, Gibbons K et al. Family food environments of 5\u20136 year-old-children: does socioeconomic status make a difference? 2002."]}, {"label": ["32."], "surname": ["Djuikom", "van de Walle"], "given-names": ["MA", "D"], "article-title": ["Marital status and women\u2019s nutrition in Africa"], "source": ["World Dev"], "year": ["2022"], "volume": ["158"], "fpage": ["106005"], "pub-id": ["10.1016/j.worlddev.2022.106005"]}, {"label": ["34."], "surname": ["Wakefield", "Loken", "Hornik"], "given-names": ["MA", "B", "RC"], "article-title": ["Use of mass media campaigns to change health behaviour"], "source": ["The Lancet"], "year": ["2010"], "volume": ["376"], "issue": ["9748"], "fpage": ["1261"], "lpage": ["71"], "pub-id": ["10.1016/S0140-6736(10)60809-4"]}, {"label": ["35."], "mixed-citation": ["Viswanath K, Ramanadhan S, Kontos EZ. Mass media. Macrosocial determinants of population health. 2007:275\u2009\u2013\u200994."]}]
{ "acronym": [ "ANC", "AOR", "CI", "DHS", "ICC", "IYC", "LMICs", "MOR", "PCV", "PNC", "SSA", "UFC", "VIF", "WHO" ], "definition": [ "Antenatal Care", "Adjusted Odds Ratio", "Confidence Interval", "Demographic and Health Survey", "Intra-class Correlation Coefficient", "Infants and Young Children", "low- and middle-income countries", "Median Odds Ratio", "Proportional Change in Deviance", "Postnatal Care", "sub-Saharan Africa", "Unhealthy Food Consumption", "Variance Inflation Factor", "World Health Organization" ] }
38
CC BY
no
2024-01-14 23:43:46
BMC Pediatr. 2024 Jan 13; 24:40
oa_package/4d/f5/PMC10787455.tar.gz
PMC10787456
0
[ "<title>Background</title>", "<p id=\"Par19\">Loneliness refers to a negative subjective feeling state of being alone, separate or apart from others, and has been conceptualized as an imbalance or discrepancy between desired social contacts and actual social contacts [##UREF##0##1##]. This discrepancy leads to the negative experience of feeling lonely and/or the distress of feeling socially isolated even when surrounded by family, friends, or other people. This definition underlines that feeling lonely does not necessarily mean being alone nor does being alone necessarily mean feeling lonely. Indeed, one can feel lonely in the crowd [##UREF##1##2##, ##UREF##2##3##].</p>", "<p id=\"Par20\">Three dimensions of loneliness have been described: social, emotional, and existential loneliness [##UREF##2##3##]. Social loneliness refers to the perceived absence of quality friendships or family connections, i.e., connections within one’s relational space. The term emotional loneliness refers to the perceived absence of someone significant, a person on whom one can rely for emotional support during crises, who provides mutual help, and who affirms one’s value as a person [##UREF##1##2##]. Existential loneliness differs from social and emotional loneliness. While social and emotional loneliness are associated with a lack of meaningful social relationships and social companionship, existential loneliness is the result of a broader separation related to the nature of existence and, to the lack of meaning in life. Accordingly, an individual may be in the desired company of others but experience existential loneliness [##UREF##3##4##].</p>", "<p id=\"Par21\">Understanding of the negative effects of loneliness on health and wellbeing has raised awareness at the societal and public health level. In the long–term, loneliness can lead to or aggravate chronic diseases such as cardiovascular disease, diabetes type 2, cerebrovascular disease, as well as anxiety, depression, cognitive and mental deterioration, disability and increase mortality [##UREF##3##4##–##REF##10892794##7##].</p>", "<p id=\"Par22\">Several studies have shown that social support interventions and regular small group meetings in which members actively participate are among the most effective interventions for alleviating loneliness [##REF##37295285##8##–##REF##32054474##10##]. Specifically, the intervention strategy “Circle of Friends”, a group-based approach of peer support and empowerment developed and led by the Finnish Association for the Welfare of Older Adults, has been shown to be effective to improve well-being and health of lonely older people [##UREF##6##11##–##UREF##8##14##].</p>", "<p id=\"Par23\">Experiences and contact with nature can facilitate dynamic processes of social or interpersonal interaction [##REF##21596466##15##, ##UREF##9##16##] as well as improve aspects of physical and mental health [##REF##31713144##17##]. Various green space designs and nature experiences can deliver diverse benefits with respect to wellbeing. For example, higher levels of species diversity in parks have been shown to improve mental wellbeing [##REF##33556912##18##]; different sensory experiences such as sounds, smells and tactile sensations have a variety of pathways to wellbeing [##UREF##10##19##] and the participant experience can also affect wellbeing in multiple ways, from adventure-based activities to seated relaxation [##REF##28763021##20##]. When combining contact with nature with regular small group meetings, social processes are reinforced by shared learning, relatedness, and social participation [##REF##36608945##21##, ##UREF##11##22##]. Accordingly, the social connection experienced by spending time outdoors with others is increasingly being studied to reduce stress, promote cognitive development and to alleviate loneliness [##REF##31713144##17##, ##REF##34057994##23##–##UREF##13##26##].</p>", "<p id=\"Par24\">Social prescribing is a referral system to connect people with diverse needs with assets in their communities [##REF##31713144##17##, ##UREF##14##27##]. This emerging socially oriented practice fosters and maintains social connections and, consequently, reduces the risk of social isolation and loneliness and promotes health and well-being. It has also been shown to reduce the number of primary care visits and the use of other health services [##REF##19223606##12##, ##UREF##15##28##–##UREF##16##30##]. In the frame of social prescribing, nature-based social interventions offer a novel socio-environmental innovation to improve wellbeing by linking people in need to local natural resources [##UREF##13##26##, ##REF##27265562##29##, ##UREF##17##31##].</p>", "<p id=\"Par25\">The European Commission funded project entitled “Reimagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces (RECETAS)” was launched in March 2021 [##UREF##12##25##]. The premise of the project is that social prescribing in natural spaces can serve to alleviate loneliness by engaging people in socially organized activities that are connected to the natural environment in which they live and carry out their daily activities [##UREF##12##25##, ##UREF##18##32##]. Interventions that reach and engage diverse populations vulnerable to loneliness and who may face barriers to accessing and enjoying public space and outdoor activities in groups will be developed and tested. Importantly, the intervention tested in RECETAS will link nature-based solutions and green infrastructure with professionals working in local health and social care systems. This will strengthen the evidence for causal relationships between experiences in nature, loneliness alleviation, and increase in health-related quality of life.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par26\">The study protocol has been developed based on the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines [##REF##23295957##33##].</p>", "<p id=\"Par27\">The aim of the three related studies presented in this paper is to evaluate whether the nature-based social intervention “Friends in Nature” (FIN) is more effective improving health-related quality of life and reducing loneliness among people suffering from loneliness than recommending nature-based activities in addition to usual care. Moreover, these studies are also aimed at characterizing the context, including the natural environment in which the sessions take place, understanding the implementation process and the mechanisms linking the intervention and its components to wellbeing benefits, as well as exploring the perceived effects.</p>", "<title>Study design</title>", "<p id=\"Par28\">Three related randomized controlled trials will be implemented under the umbrella of the RECETAS project: the RECETAS-BCN Trial in Barcelona (Spain), the RECETAS-PRG Trial in Prague (Czech Republic) and the RECETAS-HLSNK trial in Helsinki (Finland).</p>", "<p id=\"Par29\">These three trials are designed following a common protocol, share the objectives and approach, and apply the same intervention framework. Notwithstanding, they test the hypothesis in different populations and cultural contexts, and, therefore, the RECETAS intervention and assessments are adapted to the local context and target populations. Accordingly, the trials will be conducted and analyzed separately as independent studies but, in addition, results may also be combined. A qualitative study is nested in each trial and further explained in the process evaluation.</p>", "<p id=\"Par30\">An initial feasibility study was conducted with the objectives of assessing the practicability of recruiting participants, the ability to carry out the study procedures, the implementation of the intervention, and the evaluation of the measurement tools. The feasibility study uses qualitative and quantitative methods and was conducted between March and December 2022.</p>", "<title>Participants</title>", "<title>Recruitment</title>", "<p id=\"Par31\">The recruitment pathways differ across the trials to reach their specific target population.</p>", "<p id=\"Par32\">The RECETAS-BCN trial will be conducted in Barcelona province and the recruitment process will involve the engagement of and commitment from local organizations. We will use a neighborhood-based participatory approach [##UREF##19##34##]. Participants will be recruited from primary health and social care settings, third-sector organizations, community groups, and volunteer organizations who will identify potential participants.</p>", "<p id=\"Par33\">The RECETAS-PRG trial will be conducted in the city of Prague, and it will be focused on older persons living at home who will be reached via different information channels: leaflets distributed to GPs and care providers, contact with senior’s organizations, and information in media (radio, newspapers).</p>", "<p id=\"Par34\">The RECETAS-HLSNK trial will be conducted in Helsinki and metropolitan area and the participants will be recruited directly from 25 assisted living facilities by interviewing all residents who are cognitively able and willing to answer a screening questionnaire.</p>", "<title>Eligibility criteria</title>", "<p id=\"Par35\">A common eligibility criterion of the three trials is suffering from loneliness according to a screening question tailored to the cultural context as following: “Do you suffer from loneliness?” in Barcelona and Helsinki and “Do you feel lonely?” in Prague. Participants would screen positive when answering ‘sometimes’ or ‘often, or always’ but not if they say, ‘never or hardly ever’ [##REF##19223606##12##].</p>", "<p id=\"Par36\">In the three trials, those having a serious illness with a prognosis of less than 6 months will be excluded. In Barcelona and Prague, participants will be excluded if they have: any disability (i.e., mental, cognitive, somatic, or sensorial), cognitive decline or any mental health disorders in case it prevents them from participating in the group dynamics and activities in nature or it might interfere with the social interactions.</p>", "<p id=\"Par37\">The RECETAS-BCN trial will focus on adults (18+) from socio-economically deprived areas. Specific eligibility criteria in Barcelona are being 18 years or older; being able to give informed consent in Spanish or Catalan; being able to participate in group dynamics and communicate in one of the local languages, to have capacity to walk independently and to be willing to undergo study measurements. Groups will include participants from the same local area.</p>", "<p id=\"Par38\">The RECETAS-PRG trial will include community-dwelling older adults. Specific eligibility criteria in Prague requires the participant to be over 60 years old, living in the community, understanding the informed consent in Czech and to be willing to undergo study measurement.</p>", "<p id=\"Par39\">The RECETAS-HLSNK trial will include older adults living in assisted living facilities. Residents identified by staff will be approached to respond to a screening questionnaire by an interview. The questionnaire includes questions about loneliness, wishes for nature-based experiences and willingness to participate in group-based intervention. Specific eligibility criteria in Helsinki require the participant to be at least 55 years old, to live permanently in assisted living facility, participate in the study voluntarily, to have the Mini-mental State Examination (MMSE) at least 15 points (i.e., not being moderately-severely cognitively impaired), to be able to move with or without assisting devices and to have sufficient sight, hearing, and communication skills to participate in group activities.</p>", "<p id=\"Par40\">In the three trials, if an individual meets the eligibility requirements, the study personnel will explain the intervention and the randomization procedures, data collection requirements as well as the risks and benefits of participating in the trial. Trial information will be offered in local languages and informed consent from participants will be collected before the baseline assessment.</p>", "<title>Sample size</title>", "<p id=\"Par41\">The sample size has been calculated to detect a clinically significant difference of 0.015 - 0.04 in the primary outcome HRQOL-15D [##REF##11491191##35##] between the intervention and control arms. The calculation is based on a typical standard deviation in this type of population 0.11, type I error 5% and power 80%. The sample assumes a 25% loss to follow-up. The sample size calculation assumes that participants in each study site will be analyzed independently. The sample size was evaluated using simulation-based sample size calculation. The resulting sample size is 316 participants per city (158 per randomization arm). The group-based intervention requires 5-12 persons per group, with means building approximately 13-30 groups in each city to reach the 158 participants allocated to the intervention arm.</p>", "<title>Randomization</title>", "<p id=\"Par42\">Each trial will conduct a centralized randomization procedure. Computer-generated random allocation sequences will be generated for each trial, using blocks of varying sizes. The allocation sequence is generated by a researcher who is not involved in the data collection process. A different researcher enrolls participants and assigns them to the corresponding arm. In addition, the allocation to the study conditions is securely stored. Cohabiting couples will be randomized to the same study group, to avoid contamination. Concealed allocation of participants to intervention or control arm will be conducted after baseline assessment, being participants informed of their group allocation at this timepoint.</p>", "<p id=\"Par43\">As a strategy to reduce attrition, study staff will discuss study expectations with participants prior to randomization and will ask eligible participants whether they will be able to commit to the study protocol. Individuals who do not feel that they can maintain this commitment will be excluded from the study, while those positive about their commitment to the study protocol will be enrolled. Likewise, as a strategy to increase the retention in the study after randomization, study personnel will maintain contact with intervention and control participants through assessment time points and interim check-ins to minimize dropout and loss to follow-up.</p>", "<title>Blinding</title>", "<p id=\"Par44\">The study will conduct blinded outcome assessments. The professionals informing participants of their allocation and those delivering the interventions will be different from outcome assessors. Baseline questionnaires and measures will be conducted at T0 before random allocation to ensure blinding. When conducting the rest of assessments, outcome assessors will ask participants not to disclose their allocation during their interactions. However, due to the nature of the intervention, it might be difficult to avoid participants providing information that could help assessors to know their assigned arm. Therefore, in Barcelona, to assess the success of this strategy, outcome assessors will report after each assessment whether participants revealed their allocation, or if they could guess it.</p>", "<p id=\"Par45\">The delivery of the intervention cannot be blinded due to its nature and participants are aware of being part of the intervention or the control arm. Data analysts will be blinded to participant allocations.</p>", "<title>Intervention arm: “Friends in nature” (FIN)</title>", "<p id=\"Par46\">FIN is described based on The Template for Intervention Description and Replication (TIDR) guidelines [##UREF##20##36##].</p>", "<p id=\"Par47\">FIN is an adaptation from the Circle of Friends® methodology customized to the specific target population in each trial and with a focus on nature-based activities. This complex intervention has two main components that are expected to complement and make synergies with each other: 1) peer support group and empowerment process including specific group dynamics and elements that were adapted according to the Circle Of Friends® methodology (individual interview, empowerment letter, diaries and training) [##UREF##8##14##] and 2) the nature-based activities chosen by participants from a menu based on their preferences. Figure ##FIG##0##1## provides a schematic explanation of the intervention model. Trained facilitators are key persons in the intervention, their training is described in section 2.3.1.</p>", "<p id=\"Par48\">The intervention requires 5-12 persons per group. Two trained facilitators are assigned to each group to support the group dynamics by fostering empowerment and, at the end of the group process, independence from the facilitator. Two facilitators enable the study team to observe the group more thoroughly, give feedback to each other, and make better use of group dynamics, as well as increasing safety.</p>", "<title>Co-created menu</title>", "<p id=\"Par49\">This menu describes the nature-based activities and resources in the intervention area and can help participants to increase their knowledge of these opportunities nearby and provide tips for maximizing their use. The menu includes activities promoted by the municipality or grassroots organizations which can accommodate the group of participants, open and freely accessible nature areas, or new activities specifically organized for the RECETAS group (e.g., urban sketching).</p>", "<p id=\"Par50\">To develop the menu, local stakeholders were engaged in a social network analysis in the earlier stages of the RECETAS project. The co-creation process enabled the development of this menu, which is tailored to the local resources. The co-creation process conducted for the RECETAS-BCN trial is explained in a separate paper [##UREF##19##34##].</p>", "<title>Individual interview</title>", "<p id=\"Par51\">During week 1, participants assigned to the intervention arm will undergo an individual interview by the pair of trained facilitators. The aim of the interview is to identify individual’s expectations, nature-based interests, and achievement goals regarding social connections and loneliness alleviation and to create an environment that allows participants to experience they are being heard and seen. This discussion is an important first step in connecting and building trust with the facilitators, prepares the individual for the group process and enhances the opportunities to influence one’s own life situation. Additionally, this individual consultation allows the participants to develop personalized plans to strengthen social connections and improve wellbeing, and to articulate their feelings about being in nature and the kinds of activities they enjoy, are willing to try, and/or concerns about being outdoors or part of a group. Finally, the interview also helps the facilitator learn about the life of the participant and plan the start of the group process.</p>", "<title>Empowerment letter</title>", "<p id=\"Par52\">After the interview, facilitators write a personally tailored Empowerment Letter for each participant which is delivered before the first day of the session. This letter supports the participant’s empowerment and highlights the person’s strengths and topics that are important to them in their everyday life as they emerged in the interview. The letter is also aimed at encouraging them to take part in the first group session, to start with enthusiasm and to commit to continuing.</p>", "<title>Group-based sessions: empowerment, social connectiveness and connection to nature</title>", "<p id=\"Par53\">The 5-12 participants allocated to intervention group are invited to join nine group-based sessions once a week with a duration of at least 2 hours after the individual interview. On one hand, as proposed by Circle of Friends® methodology, group sessions are aimed at building supportive relationships, developing new social ties, and learning about ways in which they can alleviate loneliness. On the other hand, as added in the RECETAS project, groups also aim to increase the understanding of the power and meaning of nature on one’s wellbeing, enhancing active agency of the participants in their living surroundings and increasing time spent outdoors with nature. The social and the natural component of the intervention are expected to act synergistically with each other reinforcing their effects.</p>", "<p id=\"Par54\">The social component of the intervention is organized around several key activities. Group dynamics include learning to know each other (for example, through a personal object), or establishing ground rules for a positive group environment. Discussions and activities include both loneliness, and how to alleviate it, and nature as a source of wellbeing, as well as dynamics to foster group cohesion around cultural aspects such as food, music, dance, and so forth. These activities might be carried out both indoors and outdoors, but priority is given to activities outdoors in natural environments, weather permitting. To enhance the nature component, the menu is introduced during the first group session and used to show available nature-based activities. Moreover, the group will share their level of experience in nature, and their respective interests, hobbies, and preferences, so that the group together can choose and plan the activities that they want to explore, based on the menu and their own ideas. Activities in nature can be classified as: engaging with nature (e.g., gardening, planting, bird watching, forest bathing), being in nature (e.g., walking) and social activities done in natural surroundings (e.g., discussion about loneliness, picnic, music). Through the group process, participants will increase their social and peer support and emotional wellbeing as they participate in socially supported nature-based activities. As the intervention progresses, facilitators gradually step back, and the group plans how to continue group meetings and maintain connections after intervention ends.</p>", "<title>Learning diaries</title>", "<p id=\"Par55\">Learning diaries are written together by the two trained facilitators to capture group processes through written observation after each session describing the main aims for the specific session, the development of the session and the aims for the next session. Reporting participant experiences promotes reflective learning and helps evaluate the goals of the group meetings with the co-facilitator.</p>", "<title>Training and mentoring facilitators</title>", "<p id=\"Par56\">The training of facilitators is central to the RECETAS interventions. There, facilitators will learn about loneliness, the elements of the original Circle of Friends® group model [##UREF##21##37##], how to plan a group, how to conduct the interview and write the empowerment letter, and how to facilitate the group processes and dynamics of FIN. The training also provides content on how to include nature-based activities within the group dynamics, why and how contact with nature helps improve mental and physical health, and social connectedness and might alleviate loneliness. The training combines theoretical sessions with reflections, dynamics, and feedback. Based on these experiences and feedback received by trainer and peers, facilitators can form their own integrated knowledge based on theory, personal experience, and active reflection.</p>", "<p id=\"Par57\">The facilitator training program will be adapted from the Circle of Friends® methodology in each city for the corresponding trial [##UREF##21##37##]. Initially, the team from Finland from the Finnish Association for the Welfare of Older Adults will conduct a series of webinars to train the trainers in Barcelona and Prague. Those trainers will facilitate the pilot intervention while being monitored and mentored by the Finnish team to finalize their training. These facilitators will then become the new local trainers in charge of educating and mentoring new local facilitators conducting the intervention groups during the trial.</p>", "<p id=\"Par58\">Mentoring is also an important part of the training process and consists of reading the empowerment letters and the weekly learning diaries and providing periodic feedback to facilitators. Accordingly, the mentor fosters a process of reflection, evaluation, and feedback and, thus, promotes growth in the group facilitators roles. The training process also includes observations by trainers at selected moments in the intervention to observe group processes. These observations are shared with the group facilitators and discussed to ensure the group process continues in line with the scope of the intervention [##UREF##21##37##].</p>", "<title>Control arm</title>", "<p id=\"Par59\">In Barcelona and Prague participants of the control arm receive a brief intervention consisting of signposting, i.e., a professional provides them individually information and choices to participate in local nature-based activities available in the co-created menu. The menu is printed and delivered to control participants as a resource sheet or leaflet and explained to the participants during an interview. In addition, these participants will further receive standard care, including social prescribing from primary health care and social care if available.</p>", "<p id=\"Par60\">In Helsinki, as participants are dependent on the staff, both residents (participants) and relatives receive information about the trial and the favorable effects of nature in a common meeting but otherwise receive usual care.</p>", "<title>Outcomes</title>", "<p id=\"Par61\">Outcomes will be assessed at baseline (T0), month 3 (T1, end of the intervention), month 6 (T2, 3 months post the intervention) and month 12 (T3, 9 months post the intervention). All researchers in charge of conducting the assessments will undergo a training session. These elements are described in Fig. ##FIG##1##2##, in accordance with the SPIRIT 2013 trial guidelines.</p>", "<p id=\"Par62\">At baseline, socio-demographic information regarding age, gender, educational level, living arrangement and working situation will be collected.</p>", "<p id=\"Par63\">Primary outcomes of the three trials include: health-related quality of life measured with the HRQOL-15 D questionnaire [##REF##11491191##35##] and overall loneliness assessed by The De Jong Gierveld 11-item loneliness scale, which also measures separately social and emotional loneliness [##UREF##22##38##].</p>", "<p id=\"Par64\">Secondary outcomes will vary according to the study and population and will measure changes in psychosocial health (e.g., subjective well-being, quality of life, utilities, capabilities, mood, perceived stress, quality of sleep, anxiety, and depressive symptoms, and cognitive aspects); environmental and health behaviors (e.g., physical activity, time spent outdoors, and use of nature-based activities); intrapersonal processes (e.g., knowledge, attitudes, and beliefs related to the alleviation of loneliness; awareness and use of nature-based activities); interpersonal processes (e.g., peer support, relatedness and social ties, social involvement); use of health and social resources (use of health and social services and medication) and their corresponding costs as well as the costs of the intervention itself; and function, disability and health outcomes. For an overview of primary and secondary outcomes specified in each city, outcome measures, instruments, and assessment time points, see Fig. ##FIG##2##3##.</p>", "<p id=\"Par65\">Intermediate factors or mediators of the impact will be measured with standardized scales during the intervention. These indicators include empowerment by increasing self-efficacy and active agency; increasing confidence, relatedness, and enjoyment; and increasing sense of belonging (Fig. ##FIG##2##3##). Moreover, a health economic questionnaire has been developed to assess the amount of health and social services used (including medical consultations, in-patient hospital services, medication, or community care contacts).</p>", "<p id=\"Par66\">To evaluate nature exposure prompts it is needed to assess their experiences in nature both during the session and the time spent in nature the last week through a short questionnaire. Nature exposure received by participants during the intervention period is assessed as the activities in nature conducted during the sessions. Specifically, we will characterize three components of the nature experience that have previously been linked to mental wellbeing. First, the actual and perceived biodiversity of the green or blue space will be recorded. Actual species diversity will be characterized as the number of species present and their functional characteristics, for example, the species richness and abundance of street trees in a park. Data will be derived from remote sensing and existing surveys of the environment in which the intervention takes place. Perceived biodiversity will be recorded through participant feedback [##REF##33556912##18##, ##UREF##10##19##]. Second, exposure to nature will be recorded as a measure of the time and/or proximity to nature during the intervention. Third, the type of experience will be measured as either incidental (e.g., observing nature on a walk), or experiential (e.g., planting trees). The evaluation takes place after each session of the intervention group, either by filling out a paper- or digital form, as preferred by participants. In this moment, participants are asked to report also the activities conducted last week outside the sessions. Participants of the intervention arm in the three trials with difficulties in reading or writing will be assisted in filling respective questionnaires about the sessions in nature.</p>", "<p id=\"Par67\">Baseline confounders, such as age, gender, or education, will be measured at the beginning of the trials (T0). For measuring time-dependent confounders as discussed with experts in social science, epidemiology, and causal inference, a short questionnaire on mental and physical wellbeing, self-confidence and the influence of the weather will be collected during the intervention.</p>", "<p id=\"Par68\">In Barcelona and Prague, control group participants will complete a diary with the weekly time spent in nature. Furthermore, in the RECETAS-HLSNK trial, the days and time spent outdoors outside the group will be retrieved from the nurses’ records of the assisted living facilities for each study participant of both arms.</p>", "<title>Process evaluation</title>", "<p id=\"Par69\">Nature-based social interventions are complex and require a process evaluation to understand how implementation, causal mechanisms, and context shape outcomes. Therefore, the three trials comprise a process evaluation designed following the Medical Research Council guidance [##UREF##23##39##] to assess specifically fidelity and reach of the implementation, the contextual aspects of each intervention site, mechanisms of impact, and perceived effects.</p>", "<p id=\"Par70\">As part of the trial protocol, a quality control protocol will be designed to monitor intervention reach. Specifically, the intervention reach will capture the percentage eligible to the study who choose to enroll, participants who drop out of the intervention and why, and those who complete assessments at each time point. This part of the study will provide important information for future real-life implementation.</p>", "<p id=\"Par71\">Methodologically, mixed research methods, i.e., a combination of qualitative and quantitative procedures, are applied. As quantitative procedures, attendance registries will be used to assess the adherence of each participant to the group-based sessions and fidelity checklists will be applied to measure the degree of implementation of the intervention as planned. Dose delivered (i.e., fidelity) and received (i.e., adherence) will shed light on whether participants attend the intervention, how often they attend, and the activities in which they participate. In addition, standardized scales will capture those variables considered a priori as intermediate factors or mediators of the impact on the outcome variables as commented before. Reported adverse events and other unintended effects of the interventions such as falls and other accidents during the activities and interpersonal conflicts will be recorded in the learning diary, analyzed, and reported.</p>", "<p id=\"Par72\">Qualitative methods will be used to describe participants’ experience of loneliness, explore the processes undergone such as the dynamics in the groups, and elucidate the experiences of the intervention, whether and how they are maintained, and the mechanisms underlying the effects. Likewise, at group level, the dynamics will be analyzed as a key element to understanding the process of each group and how participants use the elements of the FIN intervention.</p>", "<p id=\"Par73\">Several qualitative techniques will be used, and triangulation techniques will provide us complementary views from various angles. Specifically, semi-structured interviews with study participants and professionals, when appropriate, will be conducted, as well as researcher’s participant observations of several group sessions. In addition, we will include facilitators diaries of each group session describing the group processes, as material for the qualitative study. Participants for the qualitative interviews will be selected to reach an heterogenous sample according to the main characteristics affecting process and effects (e.g., age, gender, cultural background, and socio-economic background).</p>", "<p id=\"Par74\">The analysis will be inductive, and the qualitative and quantitative findings will help to refine the theory of the intervention to finally support the interpretation of the results on the effectiveness of the intervention.</p>", "<title>Ethics and dissemination</title>", "<p id=\"Par75\">The study design was approved by the corresponding Ethics and Research Committee of each intervention site: The clinical trial of Barcelona received the approval of the Research Ethics Committee (REC) from UVic-UCC (Code: 214/2022), and the Research Ethics Committee of the Primary Health Care Research Institute of Catalonia Jordi Gol (Code CEIm: 22/170-P). The clinical trial of Helsinki obtained the approval of the Helsinki University Hospital Ethics Committee. They also received approval from Social Services and Health Care of the City of Helsinki. Finally, the protocol in Prague was approved by the Ethics Committee of the Faculty of Humanities, Charles University. Participation is voluntary and all participants (and their closest proxy when appropriate) will be asked to sign informed consent before the start of the study.</p>", "<p id=\"Par76\">Ethical aspects of the studies and arising concerns are carefully followed and discussed during the team meetings. Specifically, RECETAS has defined a steering committee lead by the coordination center (ISGlobal) with representants of all partners who meet monthly for continuous update and decision making of each WorkPackage (WP), including the trials. Moreover, a specific WP is in charge of the ethics requirements with an independent Ethics Advisor. Last, an External Advisory Board periodically oversees the progress of the project and supports decision making on relevant issues.</p>", "<p id=\"Par77\">Regarding the dissemination plan, a publication committee with rotating members has been established to supervise scientific dissemination. The results of the studies will be published in open access regardless of the outcome. Researchers will communicate trials results to participants, professionals involved and stakeholders once data is analyzed after finishing all the studies. Moreover, RECETAS uses social media (Twitter, web page, Instagram, and LinkedIn) to support communication of the results to the general public.</p>", "<title>Data and statistical analysis</title>", "<title>Analysis plan</title>", "<p id=\"Par78\">All randomized participants will be included in analyses under an intention-to-treat (ITT) approach, where all participants will be analyzed in the group they were originally allocated to if they have at least two measurement time points available, regardless of protocol violations. We will compute statistical comparisons between the groups using t-tests, Mann Whitney U tests, or Chi-Square tests when appropriate. Repeated measures will be analyzed using mixed models, with appropriate distribution and link functions, and an unstructured correlation structure, with treatment groups, time, and their interactions as fixed factors. Incidence rates of health and social services will be estimated and compared between the groups using the Poisson type regression models. A Cox Proportional Hazard model will be used to test whether allocation to intervention or control arm has efficacy on mortality. The normality of the variables will be tested graphically and by using Shapiro-Wilk W tests. All analyses will be adjusted for relevant covariates and effect modifiers (e.g., age, gender, comorbidities). In cases where assumptions are not met (e.g., non-normality) for continuous variables, a bootstrap-type method or Monte Carlo <italic>p</italic>-values (small number of observations) for categorical variables will be used. In addition to the ITT analysis, a causal inference-based per-protocol analysis will be performed to assess the effect of compliance on the outcomes of loneliness and quality of life using a structural nested model with g-estimation [##REF##28976864##40##, ##REF##32223524##41##]. Furthermore, cost-effectiveness analyses along the trials (based on loneliness outcome), cost-utility analyses along the trials and cost-capability analyses along the trials will be performed. Several secondary and subgroup analyses will be performed (e.g., for stage of dementia, type of loneliness, etc.) to identify effect modification.</p>", "<title>Data management and monitoring</title>", "<p id=\"Par79\">A specific WP called “Evaluate Nature-Based Social Prescribing through Intervention Studies”, led by UVic-UCC, coordinates the three trials and, among its tasks, data management and data monitoring are the responsibility of ISGlobal. The RECETAS Data Management Plan has established guidelines to inform how each partner involved in the three trials has to proceed with managing the data. Each participant will have a code and the respective answers associated with that code. All the information will be collected at Redcap (Research Electronic Data Capture), a secure, web-based software designed to support data capture for research studies for the creation and management of online databases and surveys ensuring anonymization [##REF##18929686##42##, ##REF##31078660##43##]. The assessor has restricted the information to ensure participant assignments are blinded.</p>" ]
[]
[ "<title>Discussion</title>", "<p id=\"Par80\">The three RECETAS trials will provide evidence on the effectiveness of a nature-based social intervention tailored to a diversity of vulnerable populations suffering from loneliness (adults from socio-economic disadvantaged urban areas, older people living in assisted living and community-dwelling older adults) in three different cities (Barcelona, Helsinki, and Prague). Thus, the target populations will comprise a diversity of age groups, languages, socio-economic levels, in different cultural contexts with varying climates, natural resources and community assets within Europe.</p>", "<p id=\"Par81\">In the recruitment process, identifying people suffering from loneliness might be challenging, due to the complexity of this phenomenon. First, loneliness is a subjective feeling that might be difficult to recognize for oneself and to communicate to others. Moreover, it is a dynamic feeling that changes over time [##REF##36322145##44##]. Second, there is stigma and taboo around it and lonely individuals might deny suffering from it. Last, it can also be erroneously identified by professionals referring participants who live alone or have limited socials contacts but do not feel lonely.</p>", "<p id=\"Par82\">Signposting of nature-based activities has been chosen as comparison next to control arm. This low level of social prescribing is based on a brief intervention and works best for people who are confident and skilled enough to find their own way to services [##UREF##14##27##]. However, we aim to find meaningful differences when compared to the group-based intervention, especially when considering the profile of participants and their condition of suffering from loneliness.</p>", "<p id=\"Par83\">The three-related but independent trials have been designed following a common protocol, sharing the objectives and approach, and applying the same intervention framework. Notwithstanding, the RECETAS intervention and assessments are adapted to the local context and target populations. However, the shared assessments such as the primary outcomes (15D and De Jong Gierveld Loneliness scale) [##REF##11491191##35##, ##UREF##22##38##] might work better for one or the other population. For instance, the low levels of functional disability expected in the younger population targeted in Barcelona might suggest 15D having a ceiling effect, while they might be sensitive to change with the population of Prague and Helsinki. On the other hand, the process evaluation and the qualitative study nested in each trial will support understanding the specificities and common pathways and mechanisms across the three sites.</p>", "<p id=\"Par84\">It is important to consider the difficulty of maintaining the blinding of outcome evaluations. Although we ask participants not to disclose it, it is very difficult to prevent participants from revealing the group to which they have been assigned or giving any clue, when answering questionnaires about friendships, daily activities, etc. Another challenge is the loss of participants along the study from recruitment to the 12-month assessment, since we target vulnerable population including frail and disabled older population and younger population with socio-economic burden. A further limitation is the restricted time horizon of the trials. To estimate long-term effectiveness and cost effectiveness, a decision-analytic model will be developed.</p>", "<p id=\"Par85\">Interventions on loneliness trying to show effectiveness face several challenges and the FIN is not free of them [##UREF##24##45##]. With the FIN intervention, we work at group level (meso level) aiming to impact individual’s wellbeing at micro level. However, it does not impact the social determinants of health at macro level such as the living situation and the socio-economic constraints, which are also main drivers of loneliness. FIN offers a range of opportunities to increase social connectedness in quantity and quality and promote participation in nature-based activities and resources in a safe environment of peer support. Accordingly, different profiles of persons with social or emotional loneliness might find their own pathway among these elements to alleviate their suffering. Nevertheless, FIN is not meant to address all forms of loneliness and social needs, but it is a solution that could benefit especially those who like groups and nature.</p>", "<p id=\"Par86\">Results will potentially lead to validation of the effectiveness of Nature-Based Social Prescription in supporting populations at risk of loneliness via engagement in socially oriented opportunities in safe, inclusive, and accessible green and blue outdoor urban spaces [##UREF##12##25##]. Accordingly, RECETAS meets the growing need for programs addressing loneliness and quality of life by harnessing the beneficial impact of nature on enhancing social connections. The three trials will provide evidence on pathways or mechanisms on how nature (type and dose) influences quality of life.</p>", "<p id=\"Par87\">If successful, the three RECETAS trials will provide an evidence-based approach for using social prescribing to address loneliness. FIN represents a low-cost, creative means to strengthening social networks, reducing stress, and facilitating social connectedness among participants and providers. We believe that investments in FIN, as a nature-based social intervention, will lead to improved urban health and well-being by promoting aesthetic experiences, increasing active citizenship, strengthening neighborhood ties, and fostering social connections across different social and economic groups. This will harness the social processes that are fundamental to sustainable behavior change and that will improve both mental and physical health, as well as the policies needed to maintain and enhance the benefits beyond the scope of the RECETAS project.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">The negative effects of loneliness on population health and wellbeing requires interventions that transcend the medical system and leverage social, cultural, and public health system resources. Group-based social interventions are a potential method to alleviate loneliness. Moreover, nature, as part of our social and health infrastructure, may be an important part of the solutions that are needed to address loneliness. The RECETAS European project H2020 (Re-imagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces) is an international research project aiming to develop and test the effectiveness of nature-based social interventions to reduce loneliness and increase health-related quality of life.</p>", "<title>Methods</title>", "<p id=\"Par2\">This article describes the three related randomized controlled trials (RCTs) that will be implemented: the RECETAS-BCN Trial in Barcelona (Spain) is targeting people 18+ from low socio-economic urban areas; the RECETAS-PRG Trial in Prague (Czech Republic) is addressing community-dwelling older adults over 60 years of age, and the RECETAS-HLSNK trial is reaching older people in assisted living facilities. Each trial will recruit 316 adults suffering from loneliness at least sometimes and randomize them to nature-based social interventions called “Friends in Nature” or to the control group. “Friends in Nature” uses modifications of the “Circle of Friends” methodology based on group processes of peer support and empowerment but including activities in nature. Participants will be assessed at baseline, at post-intervention (3 months), and at 6- and 12-month follow-up after baseline. Primary outcomes are the health-related quality-of-life according to 15D measure and The De Jong Gierveld 11-item loneliness scale. Secondary outcomes are health and psychosocial variables tailored to the specific target population. Nature exposure will be collected throughout the intervention period. Process evaluation will explore context, implementation, and mechanism of impact. Additionally, health economic evaluations will be performed.</p>", "<title>Discussion</title>", "<p id=\"Par3\">The three RECETAS trials will explore the effectiveness of nature-based social interventions among lonely people from various ages, social, economic, and cultural backgrounds. RECETAS meets the growing need of solid evidence for programs addressing loneliness by harnessing the beneficial impact of nature on enhancing wellbeing and social connections.</p>", "<title>Trial registration</title>", "<p id=\"Par4\">Barcelona (Spain) trial: ClinicalTrials.gov, ID: NCT05488496. Registered 29 July 2022.</p>", "<p id=\"Par5\">Prague (Czech Republic) trial: ClinicalTrials.gov, ID: NCT05522140. Registered August 25, 2022.</p>", "<p id=\"Par6\">Helsinki (Finland) trial: ClinicalTrials.gov, ID: NCT05507684. Registered August 12, 2022.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12889-023-17547-x.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>On behalf of the entire RECETAS consortium we thank each partner for their contributions to the development of this project, the scores of stakeholders who contributed to our co-creation processes in Barcelona, Helsinki, and Prague, and the numerous staff members who supported these efforts.</p>", "<title>Authors’ contributions</title>", "<p>LCP and JSL drafted this manuscript based on the grant proposal conceived and written by JSL, LCP, ACC, AJ, VD, AB, LR, AK, MMA, LBB, SBA, MRF, CC, US, UR, SP, IH, KHP. All the authors made contributions to the methods section of the manuscript and reviewed the entire manuscript. Specifically, LCP, ACC, JSL, KHP, AJ and ALS constructed the conceptual model; LCP and JSL drafted the discussion, and all authors contributed to the Introduction and the Conclusion sections. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This work is supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 945095. This work is also supported by the Spanish Ministry of Science, Innovation and Universities through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S), and by the Generalitat de Catalunya through the CERCA Program. Helsinki University Hospital VTR Funding has been received for the trial. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The authors and their contributions to the manuscript are independent from the funder.</p>", "<title>Availability of data and materials</title>", "<p>The RECETAS Data Management Plan has established guidelines to inform which data will be open, available upon request, and restricted to project personnel. All open research data in RECETAS will be deposited in a certified repository (e.g., ZENODO) and open access will be established to identify users for access and use of this data. Other resources and tools developed in the project will be made available via the project website (www.recetasproject.eu) or upon request. Data sharing is not applicable to this article as no datasets have been generated thus far.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par88\">The study protocols have been reviewed and approved in the three cities. The clinical trial of Barcelona received the approval of Research Ethics Committee (REC) at UVic-UCC with the registration number 2014/2022 on 28/06/2022 and Primary Health Care Research Institute of Catalonia with the registration number 22/170-P on 02/08/2022. Moreover, the consortium obtained the approval of the Helsinki University Hospital Ethics Committee (No HUS/119/2022). They also received approval from Social Services and Health Care of the City of Helsinki on 13.06.2022. Finally, the protocol in Prague was approved by the Ethics Committee of the Faculty of Humanities, Charles University on June 28, 2022.</p>", "<p id=\"Par89\">Throughout the RECETAS project, ethics review and approval will be obtained for all aspects of the study by the relevant local ethics committees before any work is conducted. Informed consent will be obtained from all study participants before enrollment in the study. (Appendix ##SUPPL##0##1##, ##SUPPL##1##2##, ##SUPPL##2##3##). Human subjects’ data generated throughout this project will be anonymized and safeguards will be in place to ensure protection of human subjects’ data. We will conduct a full ethics review of the project in partnership with the European Commission along the project.</p>", "<title>Consent for publication</title>", "<p id=\"Par90\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par91\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Explanation of the intervention process for the three trials of the RECETAS project</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>SPIRIT 2013 schedule of enrolment, interventions, and assessments for the RECETAS trials in Barcelona, Prague, and Helsinki</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Primary and secondary outcome measures, instruments, and assessment time points for the RECETAS trials for Barcelona, Prague, and Helsinki. Footer: *Primary outcomes are considered at post-intervention (T1), T2 and T3 are assessed as secondary outcomes; T0: Baseline assessment; T1: 3 months from baseline (post intervention); T2: 6 months from baseline (3 months after the end of the intervention); T3: 12 months from baseline (9 months after the end of the intervention)</p></caption></fig>" ]
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[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12889_2023_17547_MOESM1_ESM.pdf\"><caption><p><bold>Additional file 1.</bold></p></caption></media>", "<media xlink:href=\"12889_2023_17547_MOESM2_ESM.pdf\"><caption><p><bold>Additional file 2.</bold></p></caption></media>", "<media xlink:href=\"12889_2023_17547_MOESM3_ESM.pdf\"><caption><p><bold>Additional file 3.</bold></p></caption></media>", "<media xlink:href=\"12889_2023_17547_MOESM4_ESM.pdf\"><caption><p><bold>Additional file 4.</bold></p></caption></media>" ]
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Adv Soc Sci Res J. 2015;2(1) "], "ext-link": ["https://journals.scholarpublishing.org/index.php/ASSRJ/article/view/808"]}, {"label": ["28."], "surname": ["Kilgarriff-Foster", "O\u2019Cathain"], "given-names": ["A", "A"], "article-title": ["Exploring the components and impact of social prescribing"], "source": ["J Public Ment Health."], "year": ["2015"], "volume": ["14"], "issue": ["3"], "fpage": ["127"], "lpage": ["134"], "pub-id": ["10.1108/JPMH-06-2014-0027"]}, {"label": ["30."], "surname": ["Zantinge", "Verhaak", "Kerssens", "Bensing"], "given-names": ["EM", "PFM", "JJ", "JM"], "article-title": ["The workload of GPs: consultations of patients with psychological and somatic problems compared"], "source": ["Br J Gen Pract J R Coll Gen Pract."], "year": ["2005"], "volume": ["55"], "issue": ["517"], "fpage": ["609"], "lpage": ["614"]}, {"label": ["31."], "mixed-citation": ["Mygind L, Kjeldsted E, Hartmeyer RD, Mygind E, B\u00f8lling M, Bentsen P. Immersive Nature-Experiences as Health Promotion Interventions for Healthy, Vulnerable, and Sick Populations? A Systematic Review and Appraisal of Controlled Studies. Front Psychol. 2019;10. Available at: "], "ext-link": ["https://pubmed.ncbi.nlm.nih.gov/31130890/"]}, {"label": ["32."], "surname": ["Hari"], "given-names": ["J"], "source": ["Lost connections: uncovering the real causes of depression-and the unexpected solutions"], "year": ["2019"], "publisher-name": ["Bloomsbury USA"], "fpage": ["416"]}, {"label": ["34."], "mixed-citation": ["Santos-Tapia C, Hidalgo L, Jimenez-Arenas P, Casajuana C, Dom\u00e8nech S, Ballester-Lled\u00f3 A, Blancafort-Alias S. Co-Creating a Nature-Based Social Prescription Intervention in Urban Socioeconomically Deprived Neighbourhoods: A Case Study from RECETAS Project in Barcelona, Spain. Health & Social Care in the Community. 2023;2023."]}, {"label": ["36."], "mixed-citation": ["Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, Altman DG, Barbour V, Macdonald H, Johnston M, Lamb SE, Dixon-Woods M, McCulloch P, Wyatt JC, Chan AW, Michie S. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687. 10.1136/bmj.g1687."]}, {"label": ["37."], "surname": ["Jansson", "Savikko", "Pitk\u00e4l\u00e4"], "given-names": ["AH", "NM", "KH"], "article-title": ["Training professionals to implement a group model for alleviating loneliness among older people \u2013 10-year follow-up study"], "source": ["Educ Gerontol."], "year": ["2018"], "volume": ["44"], "issue": ["2-3"], "fpage": ["119"], "lpage": ["127"], "pub-id": ["10.1080/03601277.2017.1420005"]}, {"label": ["38."], "surname": ["de Jong-Gierveld", "Kamphuls"], "given-names": ["J", "F"], "article-title": ["The Development of a Rasch-Type Loneliness Scale"], "source": ["Appl Psychol Meas"], "year": ["1985"], "volume": ["9"], "issue": ["3"], "fpage": ["289"], "lpage": ["99"], "pub-id": ["10.1177/014662168500900307"]}, {"label": ["39."], "mixed-citation": ["Moore, GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, Moore L, O'Cathain A, Tinati T, Wight D, Baird J. Process evaluation of complex interventions: Medical Research Council guidance. bmj. 2015;350."]}, {"label": ["45."], "mixed-citation": ["Akhter-Khan SC, Au R. Why Loneliness Interventions Are Unsuccessful: A Call for Precision Health. Adv Geriatr Med Res. 2020;2(3):e200016. 10.20900/agmr20200016."]}]
{ "acronym": [ "FIN", "RCTs", "HRQOL", "ITT", "NBS", "NBSI", "RECETAS", "SPIRIT", "REC", "REDCAP", "MMSE", "WP" ], "definition": [ "Friends in Nature", "Randomized control trials", "Health-related quality of life", "Intention-to-treat.", "Nature-based solutions", "Nature-based social interventions", "Reimagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces", "Standard protocol items: recommendations for interventional trials", "Research ethic committee", "Research Electronic Data Capture", "Mini-mental State Examination", "Workpackage" ] }
45
CC BY
no
2024-01-14 23:43:47
BMC Public Health. 2024 Jan 13; 24:172
oa_package/b3/71/PMC10787456.tar.gz
PMC10787457
0
[ "<title>Background</title>", "<p id=\"Par10\">Floaters are visual disturbances that occur when the vitreous in the eye becomes cloudy, which can happen when the posterior vitreous detaches. Vitreous floaters can cause serious visual discomfort symptoms [##REF##21703388##1##, ##REF##26679984##2##]. In an electronic survey that recruited 603 smartphone users, 76% of the participants reported seeing floaters, while 33% complained of noticeable visual impairment because of them [##REF##23826541##3##]. In the past, observation and vitrectomy were the main methods for treating vitreous floaters. Although the majority of vitreous floaters patients are currently recommended for clinical observation, many still cannot tolerate the related visual symptoms and seek further treatment. Vitrectomy has a definite therapeutic effect, but as an invasive procedure, it has relatively more complications and higher costs and is still not accepted by most clinical practitioners [##REF##24589875##4##]. In recent years, ND: YAG laser vitreolysis has gained popularity as a fast, relatively inexpensive, and less invasive method for treating vitreous opacities and is increasingly being considered a viable option for managing vitreous floaters [##UREF##0##5##].</p>", "<p id=\"Par11\">In 2002, Delaney et al. [##REF##11913884##6##] applied YAG laser to treat 38 patients with vitreous floaters, and the results showed that 38% of patients experienced a moderate or greater subjective improvement in symptoms. Among them, 11 patients were unsatisfied with the outcome of the YAG laser and subsequently underwent vitrectomy. In 2017, Shah et al. [##REF##28727887##7##] conducted the first randomized controlled trial comparing YAG laser and sham laser treatment for vitreous floaters. The results showed that 53% of patients in the true laser group had a significant subjective improvement in symptoms, while there was no significant improvement in the sham laser group. There were no significant differences in adverse reactions between the two groups, further confirming the effectiveness and safety of the YAG laser in the treatment of vitreous floaters. Shah et al. believed that Delaney used a low energy intensity when treating vitreous floaters with the YAG laser, only cutting rather than vaporizing the opacities, which resulted in poor therapeutic effects. A recent long-term follow-up study showed that the therapeutic effect of the YAG laser could be maintained for up to 18 months [##REF##36169439##8##].</p>", "<p id=\"Par12\">Although numerous studies have demonstrated the efficacy and safety of YAG laser vitreolysis, there remains controversy among some researchers regarding its widespread clinical use [##REF##32135173##9##]. They argue that, as with any new treatment modality, moderate skepticism is warranted until further research demonstrates a favorable risk/benefit ratio. Additionally, Shah’s research found that objective improvement in patients’ vitreous floaters was 94%, while subjective improvement was only 53%, indicating a clear disconnect between objective and subjective responses that must be taken into account. On the efficacy front, the majority of current research does not rule out the placebo effect, as symptoms of vitreous opacities themselves may improve with gravity and neural adaptation. Complications of YAG laser are also worth paying attention to, such as lens damage, retinal hemorrhage, retinal vein occlusion, and postoperative high intraocular pressure [##REF##25308785##10##–##REF##33745529##13##]. To reduce intraoperative complications, YAG laser vitreolysis is recommended for patients with stable Weiss rings, with floaters located more than 2 mm away from the retina and more than 5 mm away from the lens [##REF##32086749##14##].</p>", "<p id=\"Par13\">To reduce intraoperative complications, current randomized controlled trials require inclusion criteria of patients with vitreous floaters lasting more than 6 months and completed posterior vitreous detachment [##REF##28727887##7##, ##REF##33148023##15##], which is not clinically practical. Many patients require intervention in the early stages of symptoms. There is a lack of research on the safety and efficacy of early YAG laser vitreolysis. Therefore, we undertook this clinical study to uncover that early YAG laser vitreolysis is both a safe and effective treatment option for vitreous floaters.</p>" ]
[ "<title>Methods/design</title>", "<p id=\"Par14\">The present prospective, randomized, controlled, double-blind, non-inferiority clinical trial aimed to evaluate the efficacy and safety of early YAG laser vitreolysis in treating symptomatic vitreous floaters. The clinical trial is presently being undertaken at Dongyang People’s Hospital, China. Ethical approval was obtained from the institutional ethics committee at the Dongyang People’s Hospital. Before enrollment, written informed consent was collected from the participants. The schedule for enrollment, intervention, data collection, and assessment was by the Standardized Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines (see Fig. ##FIG##0##1##). The study flow schedule is depicted in Fig. ##FIG##1##2##. We followed the SPIRIT reporting guidelines during the drafting of this article [##REF##23303884##16##].</p>", "<title>Participant eligibility</title>", "<title>Inclusion criteria</title>", "<p id=\"Par15\">Patients with a Weiss ring duration of less than 10 days and without additional eye complications will receive instructions to return to the hospital 1 month after the onset of symptoms. Subsequently, participants experiencing symptomatic floaters for precisely 1 month (28 to 32 days after the onset of symptoms) will be eligible for enrollment in the study. To be eligible for the study, the patient must rate their visual disturbance caused by floaters as at least 4 on a 0–10 scale, with 0 being no symptoms and 10 being debilitating symptoms. The symptomatic Weiss ring must be at least 2 mm from the retina and 5 mm from the posterior capsule of the crystalline lens, as measured on the B-scan. There is no minimum required distance from the intraocular lens for patients who have had cataract surgery (pseudophakic patients). The patient must be able to position themselves for the YAG laser procedure and accept the risks associated with the procedure, including but not limited to retinal detachment, intraocular hemorrhage, retinal damage, cataract formation, optic nerve damage, inflammation, and irreversible loss of vision. Additionally, the patient must be willing and able to comply with clinic visits and study-related procedures. If the patient has symptoms in both eyes, only one eye can be included in the study and randomized.</p>", "<title>Exclusion criteria</title>", "<p id=\"Par16\">The exclusion criteria are as follows: history of a retinal detachment, retinal tear, or uveitis in the study eye; history of macular edema, diabetic retinopathy, retinal vein occlusion, or aphakia in the study eye; history of glaucoma or high intraocular pressure, defined as having undergone glaucoma surgery in the eye being studied, or currently using two or more topical glaucoma medications in the eye being studied.</p>", "<title>Randomization and masking</title>", "<p id=\"Par17\">In this study, a stratified randomization method will be used to allocate participants to two groups in a 1:1 ratio, using SPSS v26.0 (SPSS Inc, Chicago, IL, USA). The randomization process incorporates minimization and involves the consideration of three study variables for group stratification: sex (male/female), age (&gt; 50/ ≤ 50 years), and crystal state (phakic eye/pseudophakic eye). A random allocation sequence will be created in advance and sealed in sequentially numbered opaque envelopes, allowing for randomization one at a time. Group allocation will be carried out by another researcher to ensure the randomization process is unbiased. All researchers involved in the study, including outcome assessors, statisticians, and data analysts, will be blinded to group assignment, but those providing the intervention will be informed as necessary. Before the trial, researchers will undergo comprehensive training in the randomization procedure and will be made aware of their responsibilities. The successful implementation and maintenance of the randomization and blinding methods will be validated to ensure the reliability and absence of bias in the trial results.</p>", "<p id=\"Par18\">The investigator is strongly advised to uphold the blinding to the greatest extent possible. The actual allocation should not be revealed to the patient or any other study personnel, including site personnel, monitors, or project office staff. There should also be no written or verbal disclosure of the code in any of the patient-related documents associated with the study.</p>", "<title>Recruitment</title>", "<p id=\"Par19\">At Dongyang People’s Hospital, more than 1000 patients seek treatment for vitreous floaters annually, ensuring an ample pool of participants for our studies. Participants will be recruited by ophthalmologists during outpatient visits, without any additional advertising. Interested patients will be invited to discuss the study details with an ophthalmologist. Those who meet all the inclusion criteria will receive complete information regarding their responsibilities and all procedures involved in the trial. Before enrollment, they will be asked to sign a written informed consent form. Insurance coverage, provided for all trial participants, is contracted to compensate for any harm that may occur during the final study visit.</p>", "<title>Intervention</title>", "<title>YAG vitreolysis procedure</title>", "<p id=\"Par20\">A Karickoff lens with goniosol will be used by the treating physician to perform YAG vitreolysis, with the number of shots determined based on clinical discretion. A focus offset may also be used if necessary, and the treatment will be conducted in single-shot mode with a maximum energy per pulse of 7 mJ. The endpoint of the treatment will be the vaporization of the Weiss ring into gas, as well as the fragmentation of any other vitreous opacities that are considered visually significant by the physician.</p>", "<title>Sham laser procedure</title>", "<p id=\"Par21\">The same procedure will be followed, but with the laser power turned down to 0.3 mJ and a separate lens covered by a filter that absorbs the power to ensure that no laser energy enters the eye.</p>", "<title>Primary outcome</title>", "<p id=\"Par22\">The study will measure the outcomes at 3, 6, 9, and 12 months. These outcomes include the subjective improvement in floater symptoms, which is rated on a scale of 0 to 10. A score of 0 represents no symptoms, while a score of 10 indicates symptoms that significantly impact daily life. The study also measures the mean change in the National Eye Institute Visual Functioning Questionnaire-25 (NEI VFQ-25), which is a self-reported questionnaire that evaluates a patient’s visual function and its effect on their quality of life. The VFQ-25 consists of 25 items, which assess different domains of vision-related quality of life, including general vision, near and distance activities, driving, social functioning, and mental health. The minimum score for the VFQ-25 is 0, indicating the worst possible visual function and quality of life, while the maximum score is 100, representing the best possible visual function and quality of life. Higher scores on the VFQ-25 indicate better outcomes, indicating that the patient has improved visual function and quality of life. To address multiple comparisons in our study, we applied a Bonferroni correction. This correction method adapts the significance level to maintain an overall alpha level of 0.05, effectively controlling for the heightened risk of type I error associated with multiple testing.</p>", "<title>Secondary outcome</title>", "<p id=\"Par23\">The secondary outcomes of the study encompass the objective assessment of changes through OCT and fundus photography. The objective evaluation of vitreous floater improvement using OCT and fundus photography is categorized into five levels: worsening, no change, mild improvement, significant improvement, and complete improvement. The objective evaluation will be conducted at 3, 6, 9, and 12 months.</p>", "<p id=\"Par24\">Other secondary outcomes include the incidence and severity of ocular and systemic adverse events, such as retinal tears, retinal hemorrhage, retinal detachment, lens damage, and other related adverse events. The incidence rates of these adverse events will be recorded immediately after each laser treatment and at 1-month post-treatment.</p>", "<title>Sample size calculation</title>", "<p id=\"Par25\">The sample size is determined a priori based on calculations assuming a modest improvement of 30% in symptoms in the YAG group compared to 10% in the sham group [##REF##28727887##7##, ##REF##33148023##15##]. This results in a sample of 66 patients with a standard deviation of 25%, an alpha level of 0.05, and a statistical power of 0.9. To account for a 5% rate of lost follow-up, it was decided to include 70 subjects in the study.</p>", "<title>Data collection, management, and monitoring</title>", "<p id=\"Par26\">Before the trials commence, all investigators undergo comprehensive training on the clinical trial protocol, data management, and indicator evaluation methodology. Throughout the study, investigators diligently collect and record data in the participants’ medical records. All adverse events are carefully documented in the electronic case report form (CRF).</p>", "<p id=\"Par27\">Participants who cannot be followed up for the entire study duration are considered dropouts. Participants have the option to withdraw from the study voluntarily in cases of intolerable side effects or poor treatment efficacy. Additionally, participants can withdraw from the study at any time for any reason. The investigators have the authority to withdraw participants from the study to prioritize their safety.</p>", "<p id=\"Par28\">Any modifications to the study protocol require prior approval from the institutional ethics committee at Dongyang People’s Hospital. Once approved, these changes must be documented in the trial registry and subsequently included in the final research data report. Significant protocol amendments will be effectively communicated to trial participants through various channels, including written notifications, verbal explanations, or informational sessions. Participants will be given opportunities to seek clarification, ask questions, or express any concerns they may have.</p>", "<p id=\"Par29\">During the experiment, concurrent treatments such as chronic diabetes, hypertension, anxiolytics, and antidepressant drugs are accepted. After all the follow-ups, participants are asked about receiving any other interventions during the study period, and this information is reported in the study results.</p>", "<p id=\"Par30\">To minimize data loss, all participants are provided with guidance when they sign the informed consent form and commit to attending the scheduled treatment dates. Participants receive an appointment card to attend sessions. An evaluator is responsible for notifying and monitoring the participants every week (via telephone contact, WeChat, and/or email) and accompanying them during the research.</p>", "<p id=\"Par31\">To ensure data quality control, the data manager conducts regular and timely data monitoring. When adding a new patient to the database, their identifying data is recorded on a printed form, which is not stored on the server. On this form, the participant’s name is represented by a combination of four English letters (the initials of their Chinese name pronunciation). This form is securely stored in a locked space, accessible only to the principal investigator, and may be utilized to reveal personal data if the need arises for unblinding purposes. Access to the final dataset is restricted solely to the principal investigator and the statistician, ensuring confidentiality and maintaining the integrity of the data. The data management team will maintain ongoing communication with the investigators regarding the progress of the trial, data consistency, instances of missing data, and any violations of time windows. If needed, queries for missing data and requests for clarification of inconsistencies or discrepancies will be issued.</p>", "<p id=\"Par32\">The study will be overseen by the Data and Safety Monitoring Board (DSMB), comprising physicians, ethicists, medical statisticians, and a clinical manager. Their role involves regular monitoring, scheduled every 3 months. The DSMB will review safety data and clinical effectiveness reports to make informed decisions on whether the clinical trial should proceed.</p>", "<title>Statistics analysis</title>", "<p id=\"Par33\">A comprehensive analysis is performed to delineate the demographic and clinical characteristics of the patient population. The normality of the variables is assessed using the Shapiro–Wilk test. The evaluated variables are depicted in tabular form, displaying both absolute and relative frequency distributions. Associations are examined utilizing either Pearson’s chi-square test or Fisher’s exact test, as warranted. The statistical significance of mean differences among quantitative variables is assessed through the paired and unpaired <italic>t</italic>-student tests. To assess variations across different time points within a group, the analysis of variance (ANOVA) with repeated measures is employed.</p>", "<p id=\"Par34\">Continuous data are presented as mean ± standard deviation (SD), while categorical data are represented as counts (percentages). All analyses follow a two-tailed approach, with a significance level of 0.05. The statistical software package SPSS 17 (IBM Corporation, Armonk, NY) is employed for conducting data analysis, by established procedures.</p>", "<p id=\"Par35\">In instances of data discontinuity, missing data will be handled by the “intention-to-treat” principle for conducting inferential statistical analysis. Missing data will be addressed through a dual strategy involving the last observation carried forward (LOCF) method and multiple imputation (MI). Additionally, sensitivity analyses will be conducted to evaluate the influence of various imputation methods on the study outcomes.</p>" ]
[]
[ "<title>Discussion</title>", "<p id=\"Par36\">The objective of this study is to evaluate the efficacy and safety of YAG laser vitreolysis in the management of symptomatic vitreous floaters and to compare the disparities in both efficacy and safety between early and delayed YAG laser vitreolysis. Previous studies demonstrated that YAG laser vitreolysis was a potential treatment for vitreous floaters [##REF##36169439##8##, ##REF##34778916##17##, ##REF##31471088##18##]. The findings from these randomized controlled trials have demonstrated the effectiveness of YAG laser vitreolysis in alleviating symptoms associated with vitreous floaters, with minimal occurrence of adverse effects. However, participants in these trials typically required the vitreous floater to remain stable for an extended period, often lasting 6 months or more. To the best of our knowledge, this study is the first randomized controlled double-blind trial that compared the safety and efficacy of early versus delayed YAG laser vitreolysis for vitreous floaters.</p>", "<p id=\"Par37\">Vitreous floaters were usually recommended for observation [##REF##26679984##2##]. Upon diagnosis, patients expressing concerns about floaters are commonly treated conservatively with reassurance and the expectation that, with time, they will adapt to the visual symptoms, or that the floaters will settle inferior to the visual axis. Nevertheless, some vitreous floaters can cause significant visual symptoms, such as a 67% decrease in contrast sensitivity in patients [##REF##24296397##19##]. This results in a decline in health-related quality of life and significant anxiety among patients [##UREF##0##5##]. Therefore, some patients have a strong need to seek a solution early in the disease. In contemporary practice, the primary interventions for treating floaters are pharmacological vitrectomy [##REF##29503926##20##] and Nd: YAG laser vitreolysis [##REF##28570745##21##]. In the past, vitrectomy was generally considered to have higher efficacy than laser vitreolysis [##REF##25784107##22##]; however, it posed potential risks to the retina, including retinal tears following the surgical procedure and the development of cataracts shortly after surgery [##REF##31047219##23##, ##REF##21616208##24##]. Given that laser vitreolysis is a less invasive procedure, it undoubtedly represents a better choice for patients with vitreous floaters who require early treatment. At present, there is a noticeable absence of relevant studies concerning early laser vitreolysis. Consequently, we conducted this trial to elucidate the efficacy and safety of early laser vitreolysis for vitreous floaters.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Vitreous floaters are a common ocular condition that affects individuals of all ages. Although vitreous floaters are typically benign, they can significantly impair visual acuity and quality of life. Laser vitreolysis, which uses an Nd: YAG laser to vaporize collagenous vitreous opacities, is increasingly being used as a treatment option. However, there is currently a lack of evidence regarding its efficacy and the appropriate timing of its application. This study aims to evaluate the efficacy and safety of early intervention with YAG laser vitreolysis in treating symptomatic vitreous floaters.</p>", "<title>Methods</title>", "<p id=\"Par2\">The present study is a randomized, controlled, double-blind clinical trial. A total of 70 participants with symptomatic floaters for 1 month were prospectively recruited. These participants will be randomly assigned to two groups, with 35 individuals in each group: the early treatment group and the delayed treatment group. Participants assigned to the early treatment group will undergo YAG laser vitreolysis immediately, followed by a sham laser treatment 3 months later. On the other hand, participants assigned to the delayed treatment group will receive a sham laser treatment and then undergo YAG laser vitreolysis 3 months later. The follow-up time points will be 1, 3, 6, and 12 months from randomization. Primary outcomes will be participants’ self-reported improvement in visual disturbance on a scale of 1 to 10 and their scores on the National Eye Institute Visual Functioning Questionnaire 25 (NEI VFQ-25). Secondary outcomes will be an objective evaluation of the effectiveness of the treatment in reducing vitreous floaters through OCT and fundus photography and tracking any adverse events related to the eyes or overall health.</p>", "<title>Discussion</title>", "<p id=\"Par3\">This clinical trial aims to evaluate the effectiveness of YAG laser vitreolysis in treating symptomatic vitreous floaters and assess the safety of performing early intervention with YAG laser vitreolysis.</p>", "<title>Trial registration</title>", "<p id=\"Par4\">ClinicalTrials.gov <ext-link ext-link-type=\"uri\" xlink:href=\"https://clinicaltrials.gov/study/NCT05800353\">NCT05800353</ext-link>. Registered on 10 March 2023.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13063-024-07924-1.</p>", "<title>Keywords</title>" ]
[ "<title>Trial status</title>", "<p id=\"Par38\">This is the first version of the protocol 2023.01 (published 19.09.2023). Recruitment for the study commenced in November 2022 and was initially planned to conclude by December 2023. However, due to the slow pace of recruitment, it was extended to conclude by December 2024. As of 19 September 2023, a total of 32 participants had been enrolled.</p>", "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We wish to extend our heartfelt gratitude to all research assistants and nursing staff who played pivotal roles in the practical organization and execution of this study.</p>", "<title>Authors’ contributions</title>", "<p>ZHS is the Chief Investigator; he conceived the study and led the proposal and protocol development. ZY prepared the consent form and was responsible for obtaining informed consent. ZGJ, JYH, and CFL contributed to the study design and development of the proposal. All authors read and approved the final manuscript. All authors are affiliated with the Dongyang People’s Hospital.</p>", "<title>Funding</title>", "<p>The research was financially supported by the Jinhua Key Science and Technology Program (2023–3-016). Jinhua City Bureau of Science and Technology, 0579–82270003. This funding source played no part in the study’s design and will not be involved in its execution, data analysis, data interpretation, or the decision to submit the results. This study is sponsored by the Dongyang People’s Hospital, Zhejiang, China. Telephone: 0579–86856789.</p>", "<title>Availability of data and materials</title>", "<p>The study findings will be extensively shared through publications in open-access journals and presentations at conferences, both nationally and internationally. The data supporting the study results can be obtained from the corresponding author upon a reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par39\">Approved by the Institutional Ethical Committee of Dongyang People’s Hospital and the reference number is Dongrenyi 2023-YX-424. Informed consent will be acquired from all study participants at the time of their recruitment.</p>", "<title>Consent for publication</title>", "<p id=\"Par40\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par41\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Standardized Protocol Items: Recommendations for Interventional Trials (SPIRIT)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Flow of participants</p></caption></fig>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13063_2024_7924_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13063_2024_7924_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"13063_2024_7924_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1. </bold></p></caption></media>" ]
[{"label": ["5."], "mixed-citation": ["Garc\u00eda BG, Orduna Mag\u00e1n C, Alvarez-Peregrina C, Villa-Collar C, S\u00e1nchez-Tena M\u00c1. Nd:YAG laser vitreolysis and health-related quality of life in patients with symptomatic vitreous floaters. Eur J Ophthalmol. 2021:11206721211008036."]}]
{ "acronym": [ "NEI VFQ-25", "OCT", "CRF", "ANOVA", "SD" ], "definition": [ "National Eye Institute Visual Functioning Questionnaire 25", "Optical coherence tomography", "Case report form", "Analysis of variance", "Standard deviation" ] }
24
CC BY
no
2024-01-14 23:43:47
Trials. 2024 Jan 13; 25:48
oa_package/5a/07/PMC10787457.tar.gz
PMC10787458
38216903
[ "<title>Introduction</title>", "<p id=\"Par5\">Acne vulgaris is a prevalent and persistent inflammation of the pilosebaceous unit that often arises during puberty and may or may not subside as puberty comes to a close [##REF##23210645##1##]. While males are more prone to severe forms during puberty, females tend to develop acne vulgaris more frequently as they age [##REF##26955297##2##]. Acne vulgaris is most commonly found in areas with abundant sebaceous glands, such as the face, proximal upper extremity, neck, and trunk [##UREF##0##3##]. The severity of the disease can range from self-limiting types that resolve without scarring to severe forms that leave complications such as atrophic scars or post-inflammatory hyperpigmentation. The complications can negatively impact self-image and quality of life, leading to higher rates of depression, anxiety, and even suicidal thoughts [##REF##34812859##4##].</p>", "<p id=\"Par6\">The primary objective of treatment is to enhance appearance while minimizing the potential for scarring and psychological distress [##UREF##0##3##]. Topical agents are the preferred approach for addressing mild to moderate acne due to their lower incidence of adverse reactions. Systemic agents may be necessary in cases where topical treatments are ineffective or when severe acne is present [##REF##26955297##2##].</p>", "<p id=\"Par7\">Isotretinoin is a prescription-only drug derived from vitamin A. It is effective in treating various causes of acne by reducing inflammation and comedones and decreasing follicular keratinization, sebum production, neutrophil chemotaxis, and the amount of <italic>Cutibacterium acnes</italic> in the follicles [##REF##30276133##5##]. Isotretinoin is primarily prescribed for severe cases of acne vulgaris, but it may also be recommended for moderate forms where there is evidence of scarring, previous treatment failure, or psychological distress related to acne [##UREF##0##3##, ##REF##33085149##6##, ##REF##21398228##7##]. Adverse effects of this medication are typically short-lived and vary depending on the dosage, including pain, mucocutaneous dryness, and erythema [##REF##33409936##8##]. Furthermore, it’s important to note that severe side effects such as teratogenicity, elevated cholesterol levels, depressive symptoms, and liver dysfunction have been associated with its use [##REF##32107726##9##]. Ultimately, the benefits of Isotretinoin in treating acne should be carefully considered alongside the potential risks [##REF##16924051##10##, ##REF##11568740##11##].</p>", "<p id=\"Par8\">Although Isotretinoin has the potential to treat acne effectively, there are various controversial opinions surrounding this medication that are often based on insufficient data or anecdotes [##REF##32107726##9##]. In light of this, our study aimed to examine the knowledge and attitudes of general practitioners (GPs) in Fars province, Iran, regarding the prescription of Isotretinoin for acne vulgaris. This investigation is vital for enhancing patient health and preventing undesirable side effects.</p>" ]
[ "<title>Methods and materials</title>", "<title>Study design and participants</title>", "<p id=\"Par9\">This study was a cross-sectional online survey among GPs practicing in Fars province, Iran, conducted in August the first 2021 for three weeks to investigate their knowledge and attitude regarding the administration of Isotretinoin for acne vulgaris. Inclusion criteria included GPs currently working in Fars province who consented to participate in the study, and those who did not have consent were excluded.</p>", "<p id=\"Par10\">The minimum required sample size for our study was calculated based on a survey by Carmody et al. by assuming a confidence interval of 95% and a margin of error of 0.5% to be 211, taking into consideration that 7680 GPs are working in Fars province (1.6 GPs per 1000 people) [##REF##32784222##12##].</p>", "<title>Study area</title>", "<p id=\"Par11\">Fars province is one of the thirty-one provinces of Iran located in the southwest of the country with a population of over 4.7 million; it is considered to be the medical center of the south of Iran with many referrals from neighboring provinces and countries around the Persian Gulf such for various medical and health matter. As one of the pioneers in implementing the referral-based healthcare program in Iran, Fars province has an extensive network of primary healthcare facilities and secondary and tertiary referral hospitals across the region providing health services to its residents.</p>", "<title>Questionnaire and data collection</title>", "<p id=\"Par12\">By reviewing related documents and articles, this study implemented two questionnaires based on the survey conducted by Carmody et al., one for GPs who prescribed Isotretinoin and another for those who did not [##REF##32784222##12##]. Demographic information such as age and gender, along with related questions regarding interest in the field of dermatology, being a member of a dermatology association, participation in dermatology courses, and work experience under the supervision of a dermatologist, were included at the beginning of each questionnaire. Moreover, fifteen questions in those who prescribe Isotretinoin in their practice about indication and its management (Table ##TAB##0##1##) were inquired and in those who do not prescribe Isotretinoin, ten questions regarding their hesitancy and concerns as well as conditions in which they would support its prescription were also included (Table ##TAB##1##2##).</p>", "<p id=\"Par20\">\n\n</p>", "<p id=\"Par26\">\n\n</p>", "<p id=\"Par13\">The questionnaires were designed online via Porsline <italic>(</italic><ext-link ext-link-type=\"uri\" xlink:href=\"https://www.porsline.ir/\">https://www.porsline.ir/</ext-link><italic>)</italic> with fixed-choice responses, and the questionnaire link was distributed on social networks (e.g., Email, Telegram, WhatsApp, and Instagram) related to GPs working in Fars province.</p>", "<title>Statistical analysis</title>", "<p id=\"Par14\">The obtained information was statistically analyzed using SPSS version 26 (IBM, USA). The normal distribution of data was checked with the Komarov-Shapiro test. Analysis was performed by calculating the data’s mean, percentage (%), and ± standard deviation (SD). The Chi-square and T-test were used to compare the variables, and the significance level of the test was considered to be 0.05. We also utilized multiple regression analysis to evaluate factors correlated with Isotretinoin administration based on the participants’ variables.</p>" ]
[ "<title>Results</title>", "<p id=\"Par15\">Among 668 GPs who viewed the questionnaire, we received 308 completed forms (46%). The mean age of the participants was 31.8 ± 8.8 (range: 24–67), and 145 (47.1%) were male. Among them, 153 (49.7%) were interested in the field of dermatology. Also, 10 participants (2.3%) were members of dermatology associations, and 47 (15.3%) had completed dermatology training courses. In addition, 31 participants (10.1%) had work experience under the supervision of a dermatologist. Based on the results of our study, 85 (27.6%) of GPs prescribed isotretinoin in primary care. Table ##TAB##2##3## demonstrates the overall features of the participants in our study and compares the characteristics of GPs who prescribe and those who do not prescribe Isotretinoin.</p>", "<p id=\"Par16\">\n\n</p>", "<p id=\"Par17\">It is worth mentioning that older physicians tend to prescribe Isotretinoin more than younger ones (<italic>P</italic> value = 0.002). In addition, those who were interested in the field of dermatology (OR: 1.71; CI95%: 1.03–2.85; <italic>P</italic> value = 0.036) and also those who participated in dermatology courses (OR: 4.23; CI95%: 2.22–8.07; <italic>P</italic> value &lt; 0.001) and had work experience under the supervision of a dermatology specialist (OR: 3.22; CI95%: 1.51–6.84; <italic>P</italic> value = 0.002) were more willing to prescribe Isotretinoin.</p>", "<p id=\"Par18\">We further investigated higher Isotretinoin administration based on multiple regression analysis among the participants’ factors including age, sex, dermatology field interest, participation in dermatology courses, work experience under the supervision of a dermatologist, and being a member of a dermatology association. Based on our results, only higher age (OR: 1.042; CI95%: 1.013–1.072; <italic>P</italic>-value:0.004) and attending dermatological courses (OR: 3.280; CI95%: 1.592–6.755; <italic>P</italic>-value:0.001) were significantly correlated with more frequent Isotretinoin administration.</p>", "<p id=\"Par19\">The responses regarding the questionnaire on isotretinoin prescription are demonstrated in Table ##TAB##0##1##.</p>", "<p id=\"Par21\">According to the answers, most GPs (90.6%) had prescribed Isotretinoin to less than ten people. Also, the interest in treating patients with skin problems (60%) is one of the main reasons for prescribing this medication. The most indications for prescribing are moderate to severe acne (62.4%) and nodulocystic acne (54.1%). Moreover, 22.4% of the participants stated the reason for the prescription was the patient’s request, and according to the analyzed data, Isotretinoin was mainly prescribed for women.</p>", "<p id=\"Par22\">Disturbance in liver function tests (92.9%) and untrustworthy contraceptive methods (71.8%) were the major factors that prevented isotretinoin prescription. In most cases, pregnancy tests were performed once a month before each prescription. Also, barrier contraceptives were the most prescribed contraceptive method. 38.8% of participants were observed not to refer the patient to a psychiatrist if there was a history of depression before starting treatment, and only 14.1% refused to prescribe Isotretinoin if there was a history of depression. Almost all physicians evaluated liver function tests among blood tests. It is worth mentioning that evaluating tests such as complete blood count (CBC), fasting blood sugar (FBS), and thyroid function test (TFT) also had a high proportion. The distribution of blood tests is demonstrated in Fig. ##FIG##0##1##.</p>", "<p id=\"Par23\">\n\n</p>", "<p id=\"Par24\">Among the participants, 223 (72.4%) did not prescribe Isotretinoin, demonstrating their responses in this regard in Table ##TAB##1##2##. Concerns regarding liver dysfunction (54.7%), teratogenicity (37.2%), and drug unfamiliarity (31.4%) were, respectively, the most common reasons among physicians not prescribing Isotretinoin.</p>", "<p id=\"Par25\">Furthermore, due to the reluctance of the majority of the physicians to prescribe this drug, the recommendations and instructions of the relevant organizations (49.8%), training in this field (46.2%), and the guidance and support of dermatologists if needed (46.2%) were the essential encouraging factors for prescribing this drug. Also, these physicians believed that those who completed postgraduate education courses in dermatology (47.1%) or had work experience under the supervision of dermatologists (36.8%) would be more eligible to prescribe the drug than others. Additionally, physicians who did not prescribe Isotretinoin believed that their dermatologist colleagues did not support the widespread use of Isotretinoin in the primary care units.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par27\">The overall results indicated that most of the GPs do not resort to prescribing Isotretinoin. Notably, interest in the dermatology field, dermatologic courses partake, experience working under a dermatologist’s supervision, and older age, all contributed significantly to prescribing Isotretinoin more in primary care units. Furthermore, it was observed that those who did prescribe Isotretinoin tended to do it rather scarcely (less than ten times each year). Notably, while most GPs fulfilled in prescribing Isotretinoin based on indications, a number of them also prescribed it upon the patient’s request. Almost all participants were aware of requesting necessary lab data for patients, such as LFT or lipid profile; however, many also requested unnecessary lab work, such as TFT, CBC, or FBS. Lastly, several GPs overlooked enlightening patients regarding using reliable methods of contraception.</p>", "<p id=\"Par28\">Most GPs who refrained from prescribing Isotretinoin were apprehensive due to the adverse effects, such as teratogenicity or impaired liver function, and the lack of a well-ordered system to monitor them. Most of them (51.1%) demonstrated an unwillingness to prescribe Isotretinoin. They believed that it is unsafe to prescribe Isotretinoin in primary health units. Neither the patients nor the physicians would profit from it. At the same time, dermatologists would not support its prescription in primary health care, and prescribing should be based upon dermatologic guidelines and under their supervision. In Iran, the need for a nationally organized guideline related to the prescription of Isotretinoin has made general physicians uncertain about the prescription of this drug as to why the majority believed that this drug should only be prescribed by a specialist. Furthermore, they believed that the broad prescription of these drugs was not in the patient’s interest. Meanwhile, the existence of national and pharmaceutical guidelines in Ireland encourages Irish GPs to be more willing to prescribe this drug with support from specialists and believe this drug can be prescribed without risks in patients in primary care [##REF##32784222##12##]. While the debate continues regarding whether patients with acne vulgaris should primarily be managed by GPs in an outpatient setting or by dermatology specialists, the appropriate approach largely depends on the healthcare system’s workload and accessibility within each respective country. One feasible method suggests that patients undergo their initial consultation with a specialist for a comprehensive examination and the initiation of treatment, particularly considering the potential link between acne vulgaris and various dermatoendocrinological disorders [##REF##21198949##13##]. This approach aims to reduce misdiagnoses and overlooked cases. Given the diverse nature of acne, potentially linked to syndromes (PAPASH, SAPHO) or dermatoendocrinological disorders (PCOS, HAIR-AN), the decision to start isotretinoin emphasizes the need for a dermatologist’s examination. This is crucial to avoid missing syndromic components or exacerbating underlying conditions. Such a strategy is practical in settings where an unreliable system for monitoring adverse effects and laboratory work impedes GPs from prescribing isotretinoin. Nonetheless, its success hinges on the implementation of a well-organized system for GP follow-up and patient tracking, thereby ensuring a secure and effective treatment process. In high-volume settings, it becomes imperative for GPs to deepen their understanding of isotretinoin, encompassing its potential side effects and associated conditions. By raising awareness of concurrent diseases and potential side effects, GPs can facilitate prompt and early referrals to specialists, thereby creating a safe and structured environment for acne treatment. Importantly, this approach also serves to alleviate the workload of specialists in Iran.</p>", "<p id=\"Par29\">Since acne is one of the chief complaints that patients present with in primary health units, and considering the GPs’ role in treating acne in primary care settings, it is crucial that they are provided with sufficient access and information regarding Isotretinoin. The prescription of Isotretinoin worldwide varies depending on their health care system’s policy. In the UK, with a referral-based health system, this drug can only be prescribed by a specialist, whereas in other countries, such as the Netherlands, GPs can prescribe this drug according to the guidelines. Moreover, in New Zealand, primary care physicians have been prescribing Isotretinoin without funding restrictions since 2009, facilitating access to this medication for low-income groups that geographically had less access to specialists. GPs participated in 58% of isotretinoin prescriptions in 2012 in New Zealand [##REF##21250961##14##–##UREF##2##17##]. In Iran, Isotretinoin is not currently covered by insurance. However, only 10% of participants who did not prescribe this drug stated that the lack of insurance prevents the prescription. This may be because the price of this drug in Iran is lower than the average in other countries. Conclusively, insurance policies should be reevaluated, and further insurance coverage should be planned for the doctors who took dermatologic courses and know the drug instructions.</p>", "<p id=\"Par30\">Physicians who prescribed Isotretinoin were observed to request unnecessary lab tests for the patients, including thyroid function tests, CBC, and FBS, in addition to necessary ones such as liver function tests and lipid profiles, and most physicians performed these tests once a month. Accordingly, Carmody et al. observed that most patients on Isotretinoin underwent more blood tests than was recommended, while some patients did not have enough tests done [##REF##32784222##12##]. An evidence-based approach to Isotretinoin laboratory monitoring indicates that baseline lipid panel and LFT should be taken, and the approach to monitoring intervals defers from that. If the baseline laboratory data are normal, it is recommended that the tests be repeated two months after therapy, and if that is in the normal range, no further testing is required. However, if the results fail to be normal, continuing monitoring with dosage alteration is needed [##REF##27189824##18##]. All in all, failure to comply with relevant guidelines by physicians in conducting lab tests costs both the patients and the healthcare system.</p>", "<p id=\"Par31\">Considering that most of the doctors who prescribed Isotretinoin were aware of the side effects of this drug on liver function and blood lipid profile, many of them were not aware of the possibility of its association with mental problems. This result was in line with a previous study on Irish doctors who neglected to consider psychiatry issues when prescribing Isotretinoin [##REF##32784222##12##]. While the association between Isotretinoin and teratogenicity is clinically evident, its connection to mental complications is a matter of debate. In the 1990s, with the extent of using Isotretinoin, neuropsychiatric side effects emerged in the shapes of anxiety and depression. Suicidal thoughts, impulsivity, and the Food and Drug Administration (FDA) implemented a warning regarding this new adverse reaction [##REF##37168254##19##]. There is a controversial relationship between isotretinoin therapy for acne and depression. Mental alteration has been reported in patients who used Vitamin A, Etretinate, or Isotretinoin, while no reports have been made regarding other retinoids such as Bexarotene [##REF##30281982##20##, ##REF##28705050##21##]. A survey of 1419 people concluded that 17.2% of people treated with this drug required mental health counseling services [##REF##16406201##22##]. Meanwhile, several studies did not demonstrate a correlation between Isotretinoin and an increased risk of depression and, in addition, revealed that treating acne improved symptoms of depression [##REF##28291553##23##]. However, a global study into Isotretinoin revealed that Isotretinoin improved depression while it deteriorated suicidal ideations [##REF##36273659##24##]. Moreover, a recent meta-analysis by Tan et al. including more than 1,600,000 participants revealed a low absolute risk and no increase relative risk of psychiatric disorders and suicide attempts in people taking isotretinoin. In reality, those who took isotretinoin had a lower risk of suicide attempts in 2 to 4 years following administration [##UREF##3##25##]. Nevertheless, while recent population base studies had promising results regarding the effect of Isotretinoin on psychiatric disorders, clinicians should be vigilant and monitor patients in a holistic approach for signs of mental illnesses.</p>", "<p id=\"Par32\">Among the limitations of this study, the following points can be mentioned. The number of GPs surveyed in this research is undersized and may only represent some GPs working in the province. For this reason, studies with larger populations are recommended in the future. In this study, the mean age of GPs were young, probably because the questionnaire was online, which may not include the work experience of more experienced and older doctors. Physicians who currently prescribe Isotretinoin or have a particular interest in dermatology were more likely to respond so that it could cause some bias.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par33\">According to the findings of this study, many physicians are hesitant to prescribe this particular medication. Potential solutions to address this issue include increasing physician awareness through additional training under dermatology specialists’ guidance and establishing national guidelines to guide their prescribing decisions. Additionally, healthcare organizations in Iran should develop more comprehensive monitoring protocols to ensure that lab tests and patient follow-ups are conducted in accordance with established guidelines, thereby instilling greater confidence among general practitioners when it comes to prescribing Isotretinoin.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Since general practitioners manage acne-related referrals, there needs to be more information in Iran about how drugs such as Isotretinoin are prescribed and the treatment plan. Thus, this study aimed to evaluate general practitioners s’ practices and attitudes in prescribing Isotretinoin for acne vulgaris in primary care.</p>", "<title>Methods</title>", "<p id=\"Par2\">This web-based cross-sectional descriptive study was conducted using two questionnaires designed with the target population of GPs working in Fars province in 2021 regarding the prescription of Isotretinoin. Moreover, demographic information, questions about interest in dermatology, and participation in dermatology workshops were gathered.</p>", "<title>Results</title>", "<p id=\"Par3\">A total of 308 complete questionnaires were obtained. According to our results, 85 (27.6%) GPs prescribed Isotretinoin in primary care. Based on our results, higher age (OR: 1.042; CI95%: 1.013–1.072; <italic>P</italic>-value:0.004) and attending dermatological courses (OR: 3.280; CI95%: 1.592–6.755; <italic>P</italic>-value:0.001) were significantly correlated with more frequent Isotretinoin administration. Among GPs who do not prescribe Isotretinoin, the most common causes are concerns about liver dysfunction (54.7%), teratogenic concerns (37.2%), and lack of familiarity with the drug (31.4%) respectively.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The results of this study depicted the reluctance of most physicians to prescribe Isotretinoin and factors such as taking part in supplementary courses under the supervision of dermatologists and following national guidelines that could encourage them to prescribe Isotretinoin.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>This study was the subject of Parisa Hosseinpour’s MD degree thesis.</p>", "<title>Author contributions</title>", "<p>P.H. and A.E. designed the study. P.H. and A.P. collected the data. R.S. and A.E. analyzed data. A.E., G.G., and F.P. reviewed the literature and drafted the manuscript. All authors proofread and accepted the final version of the manuscript.</p>", "<title>Funding</title>", "<p>No monetary fund was received for this case series.</p>", "<title>Data availability</title>", "<p>The present study’s findings are available on request from the corresponding author. They are not publicly available due to privacy and ethical restrictions.</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to Participate</title>", "<p id=\"Par35\">This survey was performed in accordance with the Declaration of Helsinki and was approved by the Medical Ethics of Islamic Azad University of Medical Sciences (Kazeroon Branch) (Ethical code: IR.IAU.KAU.REC.1400.025). The purpose of this research was thoroughly explained to the participants, and they were assured that their information would be kept confidential by the researcher. In conducting this research, no coercion was imposed on participants to participate in the study. To comply with ethical considerations, informed consent was obtained from all participants in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par36\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par34\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Laboratory results evaluated by general practitioners regarding blood examination prior to isotretinoin prescription</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Responses of general practitioners who prescribe Isotretinoin toward their management and practice</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Question</th><th align=\"left\">Answer</th><th align=\"left\">Frequency (%); <italic>n = 85</italic></th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"4\">In the past year (2020), how many patients did you prescribe Isotretinoin for?</td><td align=\"left\">0–10</td><td align=\"left\">77 (90.6)</td></tr><tr><td align=\"left\">10–50</td><td align=\"left\">6 (7.1)</td></tr><tr><td align=\"left\">50–100</td><td align=\"left\">2 (2.4)</td></tr><tr><td align=\"left\">More than 100</td><td align=\"left\">0</td></tr><tr><td align=\"left\" rowspan=\"8\">What are your main reasons for starting Isotretinoin in a primary care setting?</td><td align=\"left\">Interest in treating patients with dermatologic disorders</td><td align=\"left\">51 (60)</td></tr><tr><td align=\"left\">The long wait for dermatologist visits</td><td align=\"left\">13 (15.3)</td></tr><tr><td align=\"left\">Experience in working in an aesthetic medicine clinic</td><td align=\"left\">8 (9.4)</td></tr><tr><td align=\"left\">No response to prior treatments</td><td align=\"left\">5 (6.0)</td></tr><tr><td align=\"left\">Financial incentive</td><td align=\"left\">3 (3.5)</td></tr><tr><td align=\"left\">Indication for resistant nodulocystic acne</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\">According to my previous experiences, I prescribe for those with severe acne</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">16 (18.8)</td></tr><tr><td align=\"left\" rowspan=\"6\">What did you prescribe Isotretinoin for?</td><td align=\"left\">Moderate to severe acne</td><td align=\"left\">53 (62.4)</td></tr><tr><td align=\"left\">Nodulocystic acne</td><td align=\"left\">46 (54.1)</td></tr><tr><td align=\"left\">No response to oral antibiotics</td><td align=\"left\">41 (48.2)</td></tr><tr><td align=\"left\">Patient’s request</td><td align=\"left\">19 (22.4)</td></tr><tr><td align=\"left\">Acne accompanied by an ulcer</td><td align=\"left\">5 (5.9)</td></tr><tr><td align=\"left\">Psychologic complications due to having acne</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\" rowspan=\"3\">Which gender group would you prescribe Isotretinoin for?</td><td align=\"left\">Females</td><td align=\"left\">22 (25.9)</td></tr><tr><td align=\"left\">Males</td><td align=\"left\">7 (8.2)</td></tr><tr><td align=\"left\">Both</td><td align=\"left\">56 (65.9)</td></tr><tr><td align=\"left\" rowspan=\"8\">What are the reasons you refuse to prescribe Isotretinoin?</td><td align=\"left\">Labs indicating liver failure</td><td align=\"left\">79 (92.9)</td></tr><tr><td align=\"left\">Untrustworthy contraceptive methods</td><td align=\"left\">61 (71.8)</td></tr><tr><td align=\"left\">Alcoholism</td><td align=\"left\">45 (52.9)</td></tr><tr><td align=\"left\">Central nervous system disorders</td><td align=\"left\">29 (34.1)</td></tr><tr><td align=\"left\">Current depression</td><td align=\"left\">23 (27.1)</td></tr><tr><td align=\"left\">Previous history of depression</td><td align=\"left\">12 (14.1)</td></tr><tr><td align=\"left\">Abnormal lipid profile</td><td align=\"left\">4 (4.8)</td></tr><tr><td align=\"left\">Pregnancy and fertile groups</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\" rowspan=\"4\">How would you decide on Isotretinoin dosage?</td><td align=\"left\">Based on weight</td><td align=\"left\">40 (47.1)</td></tr><tr><td align=\"left\">General starting dose</td><td align=\"left\">39 (45.9)</td></tr><tr><td align=\"left\">Based on acne severity</td><td align=\"left\">34 (40.0)</td></tr><tr><td align=\"left\">Based on gender</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\" rowspan=\"6\">At what intervals would you visit female patients?</td><td align=\"left\">Every month</td><td align=\"left\">52 (61.2)</td></tr><tr><td align=\"left\">Every two months</td><td align=\"left\">12 (14.1)</td></tr><tr><td align=\"left\">Every three months</td><td align=\"left\">12 (14.1)</td></tr><tr><td align=\"left\">Only the first session</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\">With intervals of more than three months</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\" rowspan=\"6\">At what intervals would you visit male patients?</td><td align=\"left\">Every month</td><td align=\"left\">41 (48.2)</td></tr><tr><td align=\"left\">Every two months</td><td align=\"left\">15 (17.6)</td></tr><tr><td align=\"left\">Every three months</td><td align=\"left\">13 (15.3)</td></tr><tr><td align=\"left\">Only the first session</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\">With intervals of more than three months</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\" rowspan=\"6\">In what intervals would you request pregnancy tests?</td><td align=\"left\">Each month before prescription</td><td align=\"left\">44 (51.8)</td></tr><tr><td align=\"left\">Only the first session</td><td align=\"left\">21 (24.7)</td></tr><tr><td align=\"left\">With intervals of more than a month</td><td align=\"left\">12 (14.1)</td></tr><tr><td align=\"left\">Never</td><td align=\"left\">6 (7.1)</td></tr><tr><td align=\"left\">In the case of pregnancy, I would not prescribe</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\">I have not had a female patient before</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\" rowspan=\"6\">What methods would you choose for contraception?</td><td align=\"left\">Barrier contraception</td><td align=\"left\">43 (50.6)</td></tr><tr><td align=\"left\">Oral contraceptive drugs (OCP)</td><td align=\"left\">24 (28.2)</td></tr><tr><td align=\"left\">Both intra-uterine devices (IUD) and OCP</td><td align=\"left\">21 (24.7)</td></tr><tr><td align=\"left\">Long-term contraceptive methods like progesterone injections or IUD</td><td align=\"left\">14 (16.5)</td></tr><tr><td align=\"left\">I would not prescribe anything</td><td align=\"left\">12 (14.1)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">6 (7.1)</td></tr><tr><td align=\"left\" rowspan=\"4\">Would you refer patients with a previous history of depression to a specialist before starting Isotretinoin?</td><td align=\"left\">No</td><td align=\"left\">33 (38.8)</td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">22 (25.9)</td></tr><tr><td align=\"left\">If there is a possibility of having depression, I would not prescribe Isotretinoin</td><td align=\"left\">20 (23.5)</td></tr><tr><td align=\"left\">It depends on the patient</td><td align=\"left\">10 (11.8)</td></tr><tr><td align=\"left\" rowspan=\"2\">Would you request blood tests before starting Isotretinoin?</td><td align=\"left\">Yes</td><td align=\"left\">79 (92.9)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">6 (7.1)</td></tr><tr><td align=\"left\" rowspan=\"5\">What type of blood tests would you request?</td><td align=\"left\">Liver function tests</td><td align=\"left\">79 (92.9)</td></tr><tr><td align=\"left\">Lipid profile</td><td align=\"left\">57 (67.1)</td></tr><tr><td align=\"left\">Complete blood count</td><td align=\"left\">57 (67.1)</td></tr><tr><td align=\"left\">Fasting blood sugar</td><td align=\"left\">36 (42.4)</td></tr><tr><td align=\"left\">Thyroid function tests</td><td align=\"left\">28 (32.9)</td></tr><tr><td align=\"left\" rowspan=\"7\">After starting treatment, at what interval would you request blood tests?</td><td align=\"left\">Every month</td><td align=\"left\">31 (36.5)</td></tr><tr><td align=\"left\">Once after 6–8 weeks</td><td align=\"left\">7 (8.2)</td></tr><tr><td align=\"left\">Every two months</td><td align=\"left\">14 (16.5)</td></tr><tr><td align=\"left\">Every three months</td><td align=\"left\">16 (18.8)</td></tr><tr><td align=\"left\">Intervals of more than three months</td><td align=\"left\">8 (9.4)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\">One month after, then every two months</td><td align=\"left\">1 (1.2)</td></tr><tr><td align=\"left\" rowspan=\"6\">For how long would you prescribe Isotretinoin in each visit?</td><td align=\"left\">Less than a month</td><td align=\"left\">11 (12.9)</td></tr><tr><td align=\"left\">One to three months</td><td align=\"left\">30 (35.3)</td></tr><tr><td align=\"left\">Three to six months</td><td align=\"left\">35 (41.2)</td></tr><tr><td align=\"left\">Six to nine months</td><td align=\"left\">3 (3.5)</td></tr><tr><td align=\"left\">Nine to twelve months</td><td align=\"left\">4 (4.7)</td></tr><tr><td align=\"left\">More than twelve months</td><td align=\"left\">2 (2.4)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Responses of general practitioners regarding not prescribing Isotretinoin in their practice</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Question</th><th align=\"left\">Response</th><th align=\"left\">Frequency (%); N = 223</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"17\">Why would you not prescribe Isotretinoin?</td><td align=\"left\">Not being aware that GPs have permission to prescribe it</td><td align=\"left\">58 (74)</td></tr><tr><td align=\"left\">Worries regarding liver dysfunction</td><td align=\"left\">122 (54.7)</td></tr><tr><td align=\"left\">Worries regarding its teratogenicity</td><td align=\"left\">83 (37.2)</td></tr><tr><td align=\"left\">Lack of knowledge of the drug</td><td align=\"left\">70 (31.4)</td></tr><tr><td align=\"left\">Worries regarding abnormal lipid profile</td><td align=\"left\">46 (20.6)</td></tr><tr><td align=\"left\">I am not interested</td><td align=\"left\">47 (21.1)</td></tr><tr><td align=\"left\">Being wary of the legal complaints</td><td align=\"left\">37 (16.6)</td></tr><tr><td align=\"left\">No coverage by insurance companies</td><td align=\"left\">23 (10.3)</td></tr><tr><td align=\"left\">Worries regarding mucocutaneous dryness</td><td align=\"left\">22 (9.9)</td></tr><tr><td align=\"left\">Worries regarding workload</td><td align=\"left\">10 (4.5)</td></tr><tr><td align=\"left\">Being wary of suicidality</td><td align=\"left\">8 (3.6)</td></tr><tr><td align=\"left\">Not having relevant patients</td><td align=\"left\">8 (3.2)</td></tr><tr><td align=\"left\">I believe only dermatologists should prescribe it</td><td align=\"left\">10 (3.1)</td></tr><tr><td align=\"left\">There was no need for my patients to start Isotretinoin</td><td align=\"left\">7(2.8)</td></tr><tr><td align=\"left\">Not having accurate follow-up</td><td align=\"left\">2 (0.8)</td></tr><tr><td align=\"left\">Drug side effects</td><td align=\"left\">2 (0.8)</td></tr><tr><td align=\"left\">Not in my experience field</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\" rowspan=\"2\">Are you interested in prescribing Isotretinoin in your future primary care visits?</td><td align=\"left\">No</td><td align=\"left\">114 (51.1)</td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">109 (48.9)</td></tr><tr><td align=\"left\" rowspan=\"11\">What would persuade you to prescribe Isotretinoin?</td><td align=\"left\">Guideline from health care systems</td><td align=\"left\">111 (49.8)</td></tr><tr><td align=\"left\">Complementary educations</td><td align=\"left\">103 (46.2)</td></tr><tr><td align=\"left\">The guidance of a dermatologist, if needed</td><td align=\"left\">103 (46.2)</td></tr><tr><td align=\"left\">Proper support from the Food and Drug Administration (FDA) and forensic medicine</td><td align=\"left\">67 (30)</td></tr><tr><td align=\"left\">Financial aid</td><td align=\"left\">16 (7.2)</td></tr><tr><td align=\"left\">Proper follow-up</td><td align=\"left\">2 (0.8)</td></tr><tr><td align=\"left\">Proper knowledge of the drug</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">Higher efficacy compared to other drugs of choice</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">Patient’s request</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">Indication for starting Isotretinoin</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">30 (13.4)</td></tr><tr><td align=\"left\" rowspan=\"2\">Do you believe that Isotretinoin should only be administered by a specialist?</td><td align=\"left\">Yes</td><td align=\"left\">122 (54.7)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">101 (45.3)</td></tr><tr><td align=\"left\" rowspan=\"9\">In your opinion, what are the requirements for GPs who prescribe Isotretinoin?</td><td align=\"left\">Complementary education in Dermatology</td><td align=\"left\">105 (47.1)</td></tr><tr><td align=\"left\">Previous experience in working under a dermatologist supervision</td><td align=\"left\">82 (36.8)</td></tr><tr><td align=\"left\">being a member of dermatology associations</td><td align=\"left\">21 (9.4)</td></tr><tr><td align=\"left\">Interest in the dermatology field</td><td align=\"left\">18 (8.1)</td></tr><tr><td align=\"left\">Being aware of the drug information (indication, blood tests, and follow-up)</td><td align=\"left\">7 (2.8)</td></tr><tr><td align=\"left\">Obeying the guideline</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">Insufficient education in this regard</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">No response in first-line treatment options</td><td align=\"left\">1 (0.4)</td></tr><tr><td align=\"left\">None of the above</td><td align=\"left\">76 (34)</td></tr><tr><td align=\"left\" rowspan=\"2\">Are you aware that Isotretinoin is being prescribed in primary care centers?</td><td align=\"left\">Yes</td><td align=\"left\">109 (48.9)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">114 (51.1)</td></tr><tr><td align=\"left\" rowspan=\"2\">Do you believe that primary care settings can prescribe Isotretinoin safely?</td><td align=\"left\">Yes</td><td align=\"left\">105 (47.1)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">118 (52.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">Do you believe there are safety measures in the primary care setting for prescribing Isotretinoin?</td><td align=\"left\">Yes</td><td align=\"left\">134 (60.1)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">89 (39.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">Would it be beneficial if Isotretinoin were used vastly in primary care settings?</td><td align=\"left\">Yes</td><td align=\"left\">107 (48)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">116 (52)</td></tr><tr><td align=\"left\" rowspan=\"2\">Would the specialists support Isotretinoin usage in primary care settings?</td><td align=\"left\">Yes</td><td align=\"left\">55 (24.7)</td></tr><tr><td align=\"left\">No</td><td align=\"left\">168 (75.3)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Overall demographic features, interests, and experience of general practitioners in the dermatology field in our study based on the prescription of Isotretinoin in their practice</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"2\">Variables</th><th align=\"left\" rowspan=\"2\">Total; <italic>N = 308</italic></th><th align=\"left\" colspan=\"2\">Isotretinoin prescription</th><th align=\"left\" rowspan=\"2\"><italic>P</italic>-value*</th></tr><tr><th align=\"left\">\n<bold>No;</bold>\n<italic>n = 223</italic>\n</th><th align=\"left\"><bold>Yes</bold>; <italic>n = 85</italic></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\">Age (year); mean ± standard deviation</td><td align=\"left\">31.81 ± 8.81</td><td align=\"left\">30.75 ± 8.02</td><td align=\"left\">34.56 ± 10.14</td><td align=\"left\">\n<bold>0.002</bold>\n</td></tr><tr><td align=\"left\" rowspan=\"2\">Gender; n (%)</td><td align=\"left\">\n<italic>Male</italic>\n</td><td align=\"left\">145 (47.1)</td><td align=\"left\">107 (73.8)</td><td align=\"left\">38 )26.2)</td><td align=\"left\" rowspan=\"2\">0.607</td></tr><tr><td align=\"left\">\n<italic>Female</italic>\n</td><td align=\"left\">163 (52.9)</td><td align=\"left\">116 (71.2)</td><td align=\"left\">47 (28.8)</td></tr><tr><td align=\"left\" rowspan=\"2\">Interest in the field of dermatology; n (%)</td><td align=\"left\">\n<italic>No</italic>\n</td><td align=\"left\">153 (49.7)</td><td align=\"left\">119 (77.8)</td><td align=\"left\">34 (22.2)</td><td align=\"left\" rowspan=\"2\">\n<bold>0.036</bold>\n</td></tr><tr><td align=\"left\">\n<italic>Yes</italic>\n</td><td align=\"left\">155 (50.3)</td><td align=\"left\">104 (67.1)</td><td align=\"left\">51 (32.9)</td></tr><tr><td align=\"left\" rowspan=\"2\">Being a member of dermatology associations; n (%)</td><td align=\"left\">\n<italic>No</italic>\n</td><td align=\"left\">298 (96.8)</td><td align=\"left\">218 (73.2)</td><td align=\"left\">80 (26.8)</td><td align=\"left\" rowspan=\"2\">0.146</td></tr><tr><td align=\"left\">\n<italic>Yes</italic>\n</td><td align=\"left\">10 (3.2)</td><td align=\"left\">5 (50)</td><td align=\"left\">5 (50)</td></tr><tr><td align=\"left\" rowspan=\"2\">Participation in dermatology courses; n (%)</td><td align=\"left\">\n<italic>No</italic>\n</td><td align=\"left\">261 (84.7)</td><td align=\"left\">202 (77.4)</td><td align=\"left\">59 (22.6)</td><td align=\"left\" rowspan=\"2\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">\n<italic>Yes</italic>\n</td><td align=\"left\">47 (15.3)</td><td align=\"left\">21 (44.7)</td><td align=\"left\">26 (55.3)</td></tr><tr><td align=\"left\" rowspan=\"2\">Work experience under dermatologist supervision; n (%)</td><td align=\"left\">\n<italic>No</italic>\n</td><td align=\"left\">277 (89.9)</td><td align=\"left\">208 (75.1)</td><td align=\"left\">69 (24.9)</td><td align=\"left\" rowspan=\"2\">\n<bold>0.002</bold>\n</td></tr><tr><td align=\"left\">\n<italic>Yes</italic>\n</td><td align=\"left\">31 (10.1)</td><td align=\"left\">15 (48.4)</td><td align=\"left\">16 (51.6)</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>Bold values indicate a significant association</p><p>*Independent sample t-test or Chi-Square/Fisher’s exact test</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12875_2023_2260_Fig1_HTML\" id=\"d32e1396\"/>" ]
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[{"label": ["3."], "mixed-citation": ["Leung AK, Barankin B, Lam JM, Leong KF, Hon KL. Dermatology: how to manage acne vulgaris. Drugs Context. 2021;10."]}, {"label": ["16."], "mixed-citation": ["Bruinsma MDRW, Jaspar AHJ, Van der Zee HH, Van Vugt SF, Verhoeven ICL, Verstappen V en, Wiersma TJ. NHG: The Dutch College of General Practitioners. NHG Standard. Acne. 2017 [Available from: "], "ext-link": ["https://richtlijnen.nhg.org/standaarden/acne"]}, {"label": ["17."], "surname": ["Oakley"], "given-names": ["A"], "article-title": ["Managing acne in primary care"], "source": ["BPJ"], "year": ["2013"], "volume": ["51"], "fpage": ["16"], "lpage": ["27"]}, {"label": ["25."], "mixed-citation": ["Tan NKW, Tang A, MacAlevey NCYL, Tan BKJ, Oon HH. Risk of Suicide and psychiatric disorders among isotretinoin users: a meta-analysis. JAMA Dermatol 2023;29:e234579."]}]
{ "acronym": [ "CBC", "FBS", "FDA", "GP", "IUD", "LFT", "OCP", "TFT" ], "definition": [ "Complete Blood Count", "Fasting Blood Sugar", "Food and Drug Administration", "General Practitioner", "Intra Uterine Device", "Liver Function Tests", "Oral Contraceptive", "Thyroid Function Tests" ] }
25
CC BY
no
2024-01-14 23:43:47
BMC Prim Care. 2024 Jan 13; 25:27
oa_package/ce/fc/PMC10787458.tar.gz
PMC10787459
38216921
[ "<title>Introduction</title>", "<p id=\"Par2\">Cancer is the second leading cause of death worldwide and claims approximately one out of six deaths. The heterogeneity in cancer with complex and immuno-suppressive tumor microenvironment is the real challenge to treat the disease. Acquired therapeutic resistance and the process of metastasis further aggravates the outcome due to poor prognosis and so accounts for major cause of cancer related deaths [##REF##23664091##18##]. Despite our growing understanding of the disease, the worldwide diagnosed new cases and deaths are expected to increase in the future. For 2018, International agency for Research on cancer (IARC), estimated 18.0 million new cases and 9.5 million deaths worldwide (Fig. ##FIG##0##1##). Nonetheless, this number is expected to increase gradually up to 27.5 million new cases and 16.3 million deaths in year 2040.</p>", "<p id=\"Par3\">Treatment of cancer mostly involves combination of surgery with chemo or radiation therapy. To control the side effects of conventional systemic chemotherapy, targeting molecules are prescribed to block cell proliferation and/or modulate immune response of patients having significant impact on our existing therapeutics in cancer care. Monoclonal antibodies (mAbs) are very important entities out there in the market along with small molecule inhibitors (SMIs) for targeted therapy of cancer, the former with a better specificity coupled with biological activity. The larger size of the antibodies minimizes the unwanted diffusion through plasma-membrane associated with small molecules playing a crucial role in specific targeting of the biomolecules avoiding the side effects [##REF##16929325##16##, ##REF##30570109##39##, ##REF##21935441##47##]. The global monoclonal antibody therapeutics market was estimated at $100B USD in 2017 which is expected to reach around $219B USD by 2023 growing at a CAGR of around 12.5% during 2017 to 2023 (Zion market research).</p>", "<p id=\"Par4\">Paul Ehrlich’s concept of “magic bullet”, originated back in nineteenth century, inspired many others leading to the discovery of antibody’s ability to recognize the target antigen on the cell surface without harming the individual. The effort of using antibody for cancer treatment started with immunization of animals but the attempt to get anti-sera with some degree of cancer specificity could not get much success [##REF##18469827##45##]. The development of inbred mice and cytotoxic assay for cell surface reactivity of alloantibodies contributed in better understanding of cell surface differentiation antigens leading to distinction between normal and malignant cells. Later, development of hybridoma technology discovered by Kohler and Milstein in 1975 met the success with analytical tools such as fluorescence-activated cell sorting (FACS) [##REF##23118261##29##, ##REF##22896759##40##]. The term hybridoma was suggested by Leonard Herzenberg for combining immortalization of the myeloma cells with development of selection techniques for antibody producing B cells; the two important inventions together. For the first time, antigen specific monoclonal antibodies could be developed from immortalized B lymphocytes of immunized mice spleen. The technology proved to be a weapon in dissecting the surface proteins of malignant versus healthy cells leading to greater insight into tumorigenesis [##REF##22437872##41##]. But these mice monoclonal antibodies were not of much use for cancer patients because of the immunological response generating human anti-mouse antibody (HAMA) when injected in human resulting in rapid inactivation and clearance from patient serum. This also restricted multiple administration of the murine antibody required for the treatment. The advancement in recombinant technology empowered our scientists to produce chimeric, humanized, and human antibodies (Fig. ##FIG##1##2##) that geared up our fight against cancer and the current list of the FDA approved monoclonal antibodies reflects the revolution in patient care (Table ##TAB##0##1##).</p>", "<title>Phage display technology in development of therapeutic antibody</title>", "<p id=\"Par5\">Human antibodies are the most preferred one for patient care which can be generated in transgenic animals, generally mice or rat, using hybridoma technology after introducing the human immunoglobulin loci while knocking down their own counterpart. To eliminate the necessity of injecting the antigen in animals, phage display technology, discovered in 1985 by George P. Smith, was exploited as <italic>in-vitro</italic> antibody selection method by Sir George P Winter which gave the privilege of easy access to the coding sequence of the antibody for further manipulation. For the discovery of this elegant method of producing pharmaceuticals, George P. Smith and Sir George P. Winter shared one-half of the 2018 Nobel Prize in Chemistry. The first human antibody Adalimumab (Humira) using phage display technology was approved in USA in 2002 for the treatment of arthritis and Crohn’s disease which inactivates tumor necrosis factor-alpha (TNF-α) [##UREF##0##9##, ##REF##31894001##28##]. The human antibody display library is prepared from rearranged V-gene repertoires isolated from B-cells and/or lymphoid tissues RNA. Depending upon the need of antibody generation, the library can be naïve or immune based on the B-cells/lymphoid tissue isolation sources that can be either a healthy human or a patient. VH and VL repertoires undergoes natural <italic>in-vivo</italic> affinity maturation during the disease, so antibodies isolated from immune libraries have better affinity towards the disease targets while the naïve library can be used for selection against any antigens. To increase the variability of the library, which is important for selecting antibodies against diverse antigens, B-cells or tissues from multiple individuals are pooled together considering the type of library. Antibodies against toxic or non-immunogenic antigens can also be generated by this method [##REF##32983137##1##, ##REF##29890762##25##]. However, these antibodies are produced in <italic>E. coli</italic> where they are not glycosylated which might affect their binding and pharmacokinetics once expressed in eukaryotic system where post-translational modifications like glycosylation occurs. To overcome the problem, eukaryotic display systems like yeast display and mammalian cell display systems were developed [##REF##31544850##3##, ##REF##33759431##49##]. Recently, Rafteryet. al., has reported a workflow called PhageXpress for rapid selection of phage display library combined with Oxford Nanopore Technology, MinION sequencer. The high throughput technology uses electro-hydrodynamic manipulated solution for selection of enhanced target binders and minimizes non-specific interactions [##REF##31712799##36##]. Development of recombinant technology made it easy to further manipulate the antibody formats based on requirements e.g., single-chain variable fragments (sc-Fv), diabodies (bivalent scFvs), single domain antibodies (sDAb or Nanobodies), Fabsetc (Fig. ##FIG##2##3##) which is gradually changing the spectrum of therapeutic modalities in cancer treatment and beyond.</p>", "<title>Factors affecting antibody therapeutic efficacy</title>", "<p id=\"Par6\">Therapeutic antibodies targeting cancer cells bind specifically to the cell surface proteins ectopically expressed on the malignant cells (tumor-associated antigens) through variable region of Fab domain. The mere binding is not always sufficient to execute all the biological functions and so binding of the other components to Fc-region of the antibody broadens functionality of the molecule boosting therapeutic efficacy (Fig. ##FIG##2##3##). The constant regions of heavy chains, which form crystallizable fragment (Fc), play important role in effector function of the antibodies where immune cells expressing Fc-receptor (FcR) or complements bind and regulate the immune response. The direct mode of action involves binding of the antibody to the target cell-surface receptor leading to interruption of the signaling pathway or stimulating functions culminating in apoptosis induction with inhibition of cell proliferation. When antibody needs support of other component which binds to the Fc-region of the antibody, it is considered as indirect function. Depending upon the binding components, the mechanism of this indirect way of functioning can either be antibody-dependent cellular cytotoxicity (ADCC) or antibody-dependent cellular phagocytosis (ADCP) or complement dependent cytotoxicity (CDC) (Fig. ##FIG##3##4##). ADCC and ADCP varies in the FcγR-types interacting with Fc region of the antibody. NK cells are the major immune cell population participating in ADCC where FcγRIIIa binds to the cell bound antibodies and release of perforin and granzymes lyses the target cells whereas in ADCP, macrophages expressing activating FcγRIIa interacts with the Fc region of the antibody bound opsonized target culminating in phagocytosis of the target cells. For CDC, activation of compliment cascades and binding of their component to the cell bound antibody is required leading to membrane disruption and lysis of the target. These binding components help to execute the function based on the avidity of the multivalent antigen–antibody interactions readout [##REF##22896759##40##, ##REF##22437872##41##]. Out of the five isotypes of the antibodies based on the heavy chains (IgG, IgD, IgE, IgA, IgM), IgG is the most abundant antibody class in our blood serum which is the most common format for therapeutic antibodies. The isotypes of antibodies are defined by the Fc-region of the heavy-chain which is composed of non-covalent association of CH2 and CH3 with critical residues near hinge region. The interaction between Fc-region of the IgG antibody and the Fcγ-receptors (FcγRs) (type 1 FcR) present on immune cells (e.g., natural killer cells, macrophages, monocytes etc.) mediates cellular effector functions killing the cancer cells [##REF##29379493##2##]. It is the CH2 domain of the IgG which binds to FcγR of the effector cells or complements to attack the target with different mechanism depending on the binding components. Based on the sequence of the IgG heavy-chain subclass (IgG1, IgG2, IgG3, IgG4), CH2 domain of the Fc-fragment affects the Fc-FcγR engagement and so differential effector functions. The sequence homology among these subtypes is 90% with major differences in hinge region and CH2 domain. More precisely, IgG1 antibodies contain an N-glycosylation site at highly conserved asparagine-297 (N297) residue in the CH2-domain which affects the Fc-mediated effector functions. The binding conformation of the Fc-domain is regulated by a core hepta-saccharide glycan which gets modified (glycosylation) during malignancies affecting the Fc-FcγR interaction (Fig. ##FIG##2##3##) and so the immunological response [##REF##34476207##55##, ##REF##31861777##56##]. The abundance of IgG subtypes depends on the cytokine milieu and nature of the antigen as well, where the latter can induce glycan modification on the specific antibody regulating the downstream response. Engineering the IgG Fc to engage the activating type 1 FcγR (FcγRI, FcγRIIa, FcγRIIIa) or genetic manipulation of inhibiting type 1 FcγR (FcγRIIb) on effector cells can modulate the cytotoxic effect of anti-tumor antibodies independent of the cell type recognized by Fab domain. Tafasitamab, an antibody against CD19, affinity for FcγRIIIa binding was improved by Fc- engineering (mutation S239D/I332E) to enhance ADCC [##REF##33212886##27##]. Alteration in IgG glycosylation has significant effect on effector functions (ADCC, CDC) of the antibody. Although Fab mediated pathways e.g. induction of apoptosis by rituximab or downregulation/ blocking of receptor mediated pathways by transtuzumab/cetuximab along with Fc mediated pathways e.g. CDC or ADCC, are proposed mechanism based on the in-vitro experiments, the engagement of activating type 1 FcγR has been shown to be an absolute requirement for tumor targeting antibodies capable of depleting the target cells in-vivo including rituximab (anti-CD20), trastuzumab (anti-HER/neu), and cetuximab (EGFR) [##REF##28446061##5##, ##REF##18064051##32##, ##REF##25045879##35##]. Absence of fucose core or presence of galactose induces ADCC, CDC, and ADCP [##REF##11986321##42##, ##REF##32698317##54##]. Obinutuzumab (anti-CD20) antibody, approved by FDA in 2013, was engineered for reduced fucosylation (a fucosylated antibody) to increase ADCC with enhanced binding to activating type 1 FcγIIIa receptors present on NK cells. This was achieved by expressing the antibody in an engineered eukaryotic cell line (CHO) with blocked fucosylated oligosaccharides formation and this modification extended the survival of chronic lymphocytic leukemia (CLL) patients by a year in comparison to rituximab which was unmodified anti-CD20 monoclonal antibody [##REF##19459844##6##, ##REF##35844552##11##]. However, a recent study has shown that Obinutuzumab, a glycoengineered antibody, can bind to only one binding site of CD20 dimer and does not facilitate complement activation whereas Rituximab and ofatumumab binds to two binding sites formed by dimerization of the antigen CD20, each Fab from two different molecules, facilitating avidity interactions and complement activation. This shows potential of Fab homotypic interactions for avidity-engineering of therapeutic antibodies rather than Fc-Fc interactions [##UREF##3##24##].</p>", "<p id=\"Par7\">Although all these IgG variants bind to FcγRs, IgG1 is used mostly for cancer therapy because it has the highest affinity to all FcγRs for mediating ADCC. IgG1 and IgG3 both are also able to fix complement to execute CDC, but the latter has serum half-life of 5–7.5 days relative to the 21 days half-life of human IgG1, IgG2 and IgG4. Neonatal FcR (FcRn), totally unrelated to the classical FcRs but structurally related to the family of MHC class I, binds to the specific residues of the antibodies located near CH2-CH3 junction and regulates IgG half-life. Fc sialylation has also been shown to increase serum half-life of therapeutic antibodies [##REF##30683704##4##]. The increased risk of immunogenicity due to significantly greater polymorphism of the long hinge region of IgG3 which is also subject to proteolysis and short serum half-life requiring frequent administration of the biological drug have restricted the therapeutic use of this subclass of IgG [##REF##29890762##25##]. However, IgG2 and IgG4 have very low affinity for activating FcRIIIa in comparison to IgG1 and cannot fix complement and so cannot recruit immune cells in effector functions [##REF##29375935##15##]. With increasing number of IgG4 isotype, (e.g., PD-1 antibodies) it forms the second largest subclass after IgG1 for approved therapeutic antibodies and most of these IgG4 antibodies have constant heavy chain modification. Recent studies indicate weak effector function associated with this subclass [##REF##31556789##8##].</p>", "<title>Antibody as a drug targeting modality</title>", "<p id=\"Par8\">Antibodies are also used to control the side effects of payloads (drugs, toxins or cytokines) administered for therapeutic purposes. Such armed antibodies are targeted to the antigen ectopically expressed on the surface of the cancer cells. These antigens may or may not have biological roles in cancer progression unlike the targets for naked antibodies. The antigen–antibody interaction induces receptor-mediated antibody internalization culminating in antibody endocytosis.</p>", "<p id=\"Par9\">For antibody targeted drug delivery, an ideal antigen should have significant differential ectopic expression on the surface of malignant cells in comparison to the non-malignant one. The effectiveness of these modalities depends on antigen characteristics and expression. The antigen should have minimum or no shedding in blood to avoid antigen–antibody binding in blood circulation which might reduce the therapeutic efficacy of the antibody on the intended site. Also, the antigen should be highly and homogeneously expressed on tumor surface with an ability to internalize the antigen–antibody complex through receptor-mediated endocytosis. Here, binding affinity of the antibody along with density of the antigen is important for these modalities as the rate of internalization of the antigen–antibody complex affects the therapeutic efficacy. Different antibody–drug conjugates (ADC) have been shown to be effective in different range of antigen density depending upon the characteristics of the antigen. For example, Gemtuzumabozogamicin (anti-CD33) has been shown effective in a range of 5000 to 10,000 receptor/cell; however, trastuzumabemtansine (T-DM1) requires more than 2 million receptors/cell. Therapeutic efficacy of such modalities is not always positively correlated with the presence of higher density of the antigen on cell surface, but it is the rate of cellular internalization of antigen–antibody complex which determines the cytotoxicity depending upon renewed expression and continuous loop of antigen internalization [##REF##21869836##7##, ##REF##33081383##13##, ##REF##17991300##17##] (Fig. ##FIG##4##5##).</p>", "<p id=\"Par10\">Based on the expression level of tumor associated antigen, “linker stability” and associated “bystander effects” of the released payload are two important aspects to be considered to maintain the effectiveness of the modality. Bystander killing of the neighboring cells happens with the released drug in extracellular space either before or after cellular internalization of the antibody by linker-cleavage. The membrane permeability of the endocytosed payload or its metabolite depend on hydrophilicity of the molecules adding to the bystander effect which is advantageous for targeting heterogeneously expressed tumor antigen. ADCs with cleavable-linkers, which include chemically labile (di-sulphide and pH dependent) and enzyme labile (peptide-based) linkers, will have associated bystander effect and so is used for heterogeneously expressed tumor antigens.</p>", "<p id=\"Par11\">Studies also indicate that cellular internalization of such ADCs are dispensable for achieving the desired cytotoxicity as cleavage of the linker may occur in the more acidic tumor-microenvironment because of enhanced glycolysis and lactate generation in comparison to the normal tissue. Additionally, enhanced Cathepsin B production by tumor and associated cells as well as reducing tumor environment due to release of thiols by dead tumor cells can be reasoned for cleavage of peptide and di-sulphide bonds of drug conjugates respectively [##REF##29065110##44##].</p>", "<p id=\"Par12\">Modalities with non-cleavable (commonly a thioether) linker such as ado-trastuzumabemtansine (T-DM1) are internalized and the antibody (transtuzumab) is degraded in the lysosome, rather than linker, to release the payload inside the target cell. The potent tubulin binding maytansine derivative, DM1, do not enter surrounding cells because of the positive charge on it which prevents penetration through the cell membrane. Such modalities are good for targeting high and homogeneously expressed antigen on tumor surface with reduced or minimum bystander effect [##UREF##2##23##, ##REF##29065110##44##]. Since the rate of monoclonal antibody uptake is very low in tumor cells i.e., approximately 0.003 to 0.08% of injected dose per gram in a tumor, the payload should be super-toxic to eradicate maximum tumor cells even with minimum delivery efficiency. Conventional anti-tumor drugs such as doxorubicin, etoposide is not of much consideration for the purpose because of the impaired cytotoxicity under hypoxic condition prevalent in solid tumors. Mostly used payloads in ADCs affect DNA synthesis e.g., Calicheamicin and Duocarmycin (DNA damaging agents) effective for both proliferating or non-proliferating cells and microtubule disrupting agents inhibiting mitosis cell division to block cell proliferation [##REF##33722856##50##].</p>", "<p id=\"Par13\">Along with linkage stability, homogeneity of the drug conjugation and drug to antibody ratio (DAR) are also important factors which can affect the end result. DAR represents the number of drug molecules conjugated with a single antibody and is directly correlated with cytotoxicity and pharmacokinetics of the ADC. This is affected by many other variables including the site of conjugation and design of the linker. Because of increased hydrophobicity associated with higher DAR, the ADCs cytotoxicity is compromised in <italic>in-vivo</italic> or clinical settings which can be improved with connecting hydrophilic groups to the drug-linker such as PEG or PHF [##REF##30800238##31##].</p>", "<p id=\"Par14\">Gemtuzumabozogamicin (anti-CD33) and Inotuzumabozogamicin (anti-CD22) both used the same non-specific conjugation chemistry, but the former was withdrawn in 2010 due to associated toxicity with serious liver condition at higher dose and reintroduced in 2017 with lower recommended dose for better clinical outcome. Calicheamin, which induces double-strand DNA breaks and is a potent cytotoxic anti-tumor agent, was introduced in the clinic as Gemtuzumabozogamicin conjugate in 2000. Everything between the two conjugates (Gemtuzumab and Inotuzumab) including isotypes of IgG (IgG4) were similar except the targeting antigens. It has also been demonstrated that Gemtuzumabozogamicin induced cell death was not only Calicheamin mediated but CD33 signaling also contributed unlike Inotuzumabozogamicin where CD22 signaling had no role. However, the half-life of these conjugates was found to be different in human and is attributed to the heterogeneity of the preparation and nonspecific release of the drug in circulation [##REF##30294716##10##, ##REF##31068807##46##]. As host effector function is not required in ADCs mediated cytotoxicity so IgG4 isotypes can be a better choice for such entities. However, it has been shown that IgG4 has relatively low affinity for FcγR than IgG1, but it can bind with FcγRIIIa in non-fucosylated form [##REF##27216702##12##]. Binding to FcγRs is not always good for ADCs but can be undesirable as in case of T-DM1 (IgG1) binding with FcYRIIa leading to thrombocytopenia [##REF##32570117##26##]. So multiple factors play diverse role affecting the cytotoxicity of a modality especially in <italic>in-vivo</italic> or clinical settings and the strategy varies on case-by-case basis.</p>", "<title>Resistance for antibody therapy</title>", "<p id=\"Par15\">Development of therapeutic antibodies has revolutionized cancer treatment, but the improved outcomes have sometimes their own challenges. Resistance against therapy is a major concern which can either be attributed to some mutation present in the tumor before start of the treatment or may be acquired under continuous immune selection pressure of the treatment resulting in subsequent alteration in signaling of the survival pathways. FDA approved Cetuximab and panitumumab both antibodies against ectodomain of EGFR targeting the same epitope for the treatment of metastatic colorectal cancer. Therapeutic resistance has been observed for cetuximab but not for panitumumab in patients with mutation (S492R) in ectodomain of EGFR which affects binding of cetuximab but not of panitumumab [##REF##22270724##30##, ##REF##27658254##43##]. Activating mutation in oncogenes like K-Ras, BRAF, PIK3CA have been predictive to cetuximab (anti-EGFR) resistance in colorectal cancer treatment. Mutations in HER2 does not affect the binding of transtuzumab but the tumor loses sensitivity to it because of continued activation of PI3K/AKT pathway [##REF##31308740##22##, ##REF##32698317##54##]. Also, any activating mutation in PI3K/AKT/mTOR pathway molecules decreases the sensitivity and increases the resistance to transtuzumab. It has been shown that such tumors can be better treated with transtuzumab in combination with PI3K/AKT inhibitor which is also effective against cancer stem cells (CSC), a population hypothesized to be responsible for therapy resistance and cancer reoccurrence [##UREF##4##38##].</p>", "<p id=\"Par16\">Therapy resistance can also originate in tumors transitioning phenotypically from epithelial to mesenchymal (EMT) state resulting in loss of cell-to-cell contact and become more migratory in nature promoting stem cells characteristics. Resistance to cetuximab (anti-EGFR) in head and neck cancer and oral squamous cell carcinoma has been observed because of EMT transition and loss of EGFR expression was also noticed. Activation of EMT pathway has been shown to be the key predictor of cetuximab resistance in K-Ras wild-type colorectal cancer [##REF##26870189##20##, ##REF##21104905##33##].</p>", "<p id=\"Par17\">Since ADCC is important for antibody mediated cytotoxicity to cancer cells where immune cells interacts with Fc domain of antibody, so alteration in expression of the interacting molecules on the immune cells surface affect the end results. Relative ratio of activating (FcYRI, FcYRIIA and FcYRIII) versus inhibiting (FcYRIIB) receptors expression on immune cells and preferred Fc domain interacting moieties determine the level of cytotoxicity. Polymorphism in FcYRIIa and/or FcYRIII affects the clinical success of rituximab, transtuzumab and cetuximab based on their affinity to Fc domain of IgG. NK cells are crucial for ADCC, and it has been shown that cross-linking of FcYRIIIA (CD16) compromises the efficacy of therapeutic antibodies in cancer [##REF##28387358##52##]. Avidity i.e., cumulative effect of multiple non-covalent interactions (affinities) of antigen–antibody on the cell surface, plays an important role in deciding the threshold of antibody-based effector function activation. Amivantamab, a bispecific antibody targeting EGFR and mesenchymal-epithelial transition (MET) receptor, has a low-level core fucosylation and enhanced FcγRIIIa binding leading to ADCC induced cancer cell death. In tumors with EGFR mutation and MET mutation/amplification, a crosstalk has been reported between the two pathways and such tumors are also resistant to other available therapies. Simultaneous blocking of the two pathways by the bispecific antibody shows increased selectivity and synergistic effect which can be explained by avidity effect [##REF##32414908##53##]. Lower or heterogeneous expression of antigen and inhibition of complement dependent cytotoxicity have also been reasoned for antibody mediated therapeutic resistance in cancer [##REF##20065642##37##]. The former also affects antibody drug conjugates (ADC) modalities efficacy. Loss of CD30 and lower expression of HER2 has been reported for compromised efficacy of brentuximabvedotin and transtuzumab-DM1 (T-DM1) [##REF##21869836##7##].</p>", "<title>Antibodies in immuno-modulation</title>", "<p id=\"Par18\">Tumor microenvironment composed of extracellular matrix proteins, fibroblasts and mesenchymal stromal cells along with infiltrating immune cells, plays an important role in tumor progression by manipulating immune cells. Under the influence of tumor derived factors, these immune cells once suppressed become pro-tumorigenic rather than anti-tumorigenic. Because of the absence of activating FcγRs on T lymphocytes, antibodies cannot directly recruit T cells. However, bi-specific T cell engager (BiTE) binds to a tumor antigen at one end and simultaneously binds CD3 molecule on T cells leading to T-cell activation without co-stimulatory signal like CD28. Here, tumor cells play indispensable role which is engaged by one of the single-chain variable fragment (scFv) connected by a linker to another scFv engaging T-cell. IgG2 and IgG4 are considered for development of these modalities as IgG1 has been found toxic for activated T cells leading to elimination of the later [##REF##33941237##48##]. Blinatumomab is such a BiTE approved for the treatment of acute lymphoblastic leukemia (ALL) in 2014.</p>", "<p id=\"Par19\">Another strategy of activating T-cells against tumor comprises of genetic modification of T-cells with chimeric antigen receptor (CAR) using scFv as an antigen recognizing molecule while making the T cells cytotoxicity independent of MHC restrictions like BiTE. Kymriah (Novartis) and Yescarta (Kyte-Gilead) are two FDA approved (2017) therapies for treatment of B-cell malignancy. The strategies, being MHC independent, circumvents the escape mechanisms of tumor like downregulation of MHC I molecules, loss of co-stimulating molecules, upregulation of anti-apoptotic molecules etc. In 2020, CAR T cells (Tecartus) got FDA approval as the first cell-based gene therapy modality for the treatment of acute lymphoblastic leukemia (ALL)and mantle cell lymphoma (MCL). Apart from this, checkpoint inhibitor antibodies are used for activating endogenous T-cells against tumor e.g., CTLA-4, PD-1 antibodies etc. Studies have shown that polymorphism in FcYRIIa and FcYRIIIa affects the associated affinity for Fc and in turn, the efficacy of antibodies irrespective of tumor types and antigens illustrating the importance of ADCC in clinical success of these molecules [##UREF##1##21##].</p>", "<p id=\"Par20\">Since avidity plays crucial role in execution of some effector functions so bi-specific and multi-specific antibody formats are having therapeutic advantages. Increasing level of target occupancy of antibody on the cell surface and so density of the antibody favoring different level of avidity triggers Fc-mediated effector function at different occupancy saturation levels [##REF##35790857##34##].</p>", "<title>Future prospective</title>", "<p id=\"Par21\">Recombinant constructs of antibodies targeting multiple antigens at a time (multi-specific antibody) are being developed for better efficacy. Apart from antibody–drug conjugates, antibody- small interfering RNA (siRNA) conjugates and antibody-cytokines fusion protein modalities are getting increased attention [##REF##35132063##19##]. Because of the associated cytokines release syndrome, the innovative CAR T cell therapy for cancer has its own challenges. To circumvent the hurdles, researchers are trying to use extracellular vesicles mostly exosomes carrying CAR after stimulating the engineered cells (T cells, dendritic cells, NK cells etc.) with antigen. These exosomes do not express PD1 molecule and so avoids immunosuppression by cancer cells but can inhibit tumor growth in antigen dependent manner [##REF##33808685##14##, ##REF##35152990##51##].</p>" ]
[]
[]
[]
[ "<title>Conclusions</title>", "<p id=\"Par22\">Antibodies are great success as a biological therapeutic drug especially in last few years for cancer therapy. The potential of these molecules is reflected in the market value of the monoclonal antibodies in cancer therapy which is expected to hit around USD 159.96 billion by 2030 from USD 62.2 billion in 2021. The major fraction of the market share is dominated by humanized antibodies (39.66% in 2021) as developing mouse monoclonal is relatively easy and cost effective. Additionally, other platforms to develop human antibodies along with genetic engineering techniques are the major driving force for the market. There is therapeutic resistance developed against some of these molecules but because of the minimum side effects, promising efficacy in combination therapy and ability to redirect the immune cells against cancer cells, more monoclonal antibodies are expected to get approval for better patient care.</p>" ]
[ "<p id=\"Par1\">The developments of antibodies for cancer therapeutics have made remarkable success in recent years. There are multiple factors contributing to the success of the biological molecule including origin of the antibody, isotype, affinity, avidity and mechanism of action. With better understanding of mechanism of cancer progression and immune manipulation, recombinant formats of antibodies are used to develop therapeutic modalities for manipulating the immune cells of patients by targeting specific molecules to control the disease. These molecules have been successful in minimizing the side effects instead caused by small molecules or systemic chemotherapy but because of the developing therapeutic resistance against these antibodies, combination therapy is thought to be the best bet for patient care. Here, in this review, we have discussed different aspects of antibodies in cancer therapy affecting their efficacy and mechanism of resistance with some relevant examples of the most studied molecules approved by the US FDA.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>MK, drafted and wrote the manuscript, AJ, SKS, reviewed and edited the manuscript, SH, reviewed, revised, and restructured the manuscript.</p>", "<title>Funding</title>", "<p>Not applicable.</p>", "<title>Availability of data and materials</title>", "<p>Not applicable.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par23\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par24\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par25\">Authors declare no competing interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Estimated number of cancer new cases and death in 2018 by World Health Organization (WHO). For 2018, the estimated number of new cancer cases and death due to the malignancy in the world was 18 and 9.5 million respectively</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Transition of Monoclonal antibody from mouse to human. <bold>Murine</bold>: These antibodies originate in mice and so are mice proteins. The names of these molecules end in -omab. <bold>Chimeric</bold>: These are engineered antibodies in which constant regions of both chains are of human origin; however, the variable domain origin is different but not synthesized. The names of the modality end in -ximab. <bold>Humanized</bold>: These engineered molecules have everything of human origin except CDR regions of variable domain of both the chains that might be synthesized one too. The names of the treatments end in –zumab. <bold>Human</bold>: These are fully human proteins and the names of the molecules end in -umab</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Antibody and its recombinant formats. Fab region recognizes the receptor on the cell surface and Fc region is required for effector function of the antibody. Modifications in the core glycan region is made to affect the binding with the immune cell receptors affecting ADCC, ADCP, CDC. Different small formats scFv, bispecific or singe domain antibody are used for different purposes according to the need to achieve effective therapeutic outcome</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Antibody mode of action. 1. Antibodies directly bind to the receptors on the cell surface and blocks the signaling pathway required for cancerous growth, induce apoptosis or block binding of the legend inducing uncontrolled cell growth. Some of these antibodies inhibit binding of immune cell receptors to cancer cells e.g., PD-L1, PD-1, called immune checkpoint inhibitors. 2. Others, require binding of complement components or immune cells to the Fc region of the antibody to eliminate cancerous cells through CDC, ADCC and ADCP. 3. Recombinant formats (scFv or bispecific antibodies) are used for activation of T cells for cancer therapy. 4. The antibody can be loaded with cytotoxic payloads either as antibody drug-conjugates (ADC) or can be incorporated in liposomes or virosomes or exosomes surface for specific delivery of the cargo</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Antibody drug conjugate (ADC). The cytotoxic payload is attached to the antibody with a linker. The antibody recognizes the antigen on the cell surface and is internalized through endocytosis. In the lysosome the linker is cleaved, and the payload is released in the cytosol which is toxic to the cell. The free payload or released drug in the cytosol can also diffuse out of the target cells which can lead to bystander effect along with the drug released after cleavage of the linker once the antibody is bound to the target antigen but not internalized into the cell</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>FDA approved antibodies for cancer treatment</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Antigen</th><th align=\"left\">Antibody</th><th align=\"left\">Type</th><th align=\"left\">Tumor types</th><th align=\"left\">Year</th></tr></thead><tbody><tr><td align=\"left\" rowspan=\"5\">CD20</td><td align=\"left\">Rituximab</td><td align=\"left\">Chimeric IgG1</td><td align=\"left\"><p>B-cell NHL</p><p>CLL</p></td><td align=\"left\"><p>1997</p><p>2010</p></td></tr><tr><td align=\"left\"><p>Ibritumomab</p><p>Tiuxetan</p></td><td align=\"left\"><p>Mouse IgG1</p><p>Conjugated to <sup>90</sup>Y</p></td><td align=\"left\">NHL</td><td align=\"left\">2002</td></tr><tr><td align=\"left\">Tositumomab</td><td align=\"left\">Mouse IgG conjugated to <sup>131</sup>I</td><td align=\"left\">NHL</td><td align=\"left\">2003</td></tr><tr><td align=\"left\">Ofatumumab</td><td align=\"left\">Human IgG1</td><td align=\"left\">CLL</td><td align=\"left\">2009</td></tr><tr><td align=\"left\"><p>Oblinutuzumab</p><p>(Glycoengineered)</p></td><td align=\"left\">Humanized IgG1</td><td align=\"left\">NHL,CLL</td><td align=\"left\">2013</td></tr><tr><td align=\"left\" rowspan=\"2\">CD22</td><td align=\"left\"><p>Inotuzumab</p><p>Ozogamicin</p></td><td align=\"left\">Humanized IgG4 conjugated to calicheamicin class of toxin (binds to minor groove of DNA)</td><td align=\"left\">ALL</td><td align=\"left\">2017</td></tr><tr><td align=\"left\"><p>Moxetumomab</p><p>Pasudotox</p></td><td align=\"left\">Murine IgG1(dsFv)</td><td align=\"left\">Hairy cell leukemia</td><td align=\"left\">2018</td></tr><tr><td align=\"left\">CD30</td><td align=\"left\"><p>Brentuximab</p><p>vedotin</p></td><td align=\"left\">Chimeric IgG1 conjugated to monomethyl auristatinE (an anti-tubulin agent)</td><td align=\"left\">ALCL, Hodgkin lymphoma</td><td align=\"left\">2011</td></tr><tr><td align=\"left\">CD33</td><td align=\"left\"><p>Gemtuzumab</p><p>ozogamicin</p></td><td align=\"left\">Humanized IgG4 conjugated to Calicheamicin (1st FDA approved Ab-conjugate)</td><td align=\"left\">Acute myeloid leukemia</td><td align=\"left\">2000</td></tr><tr><td align=\"left\" rowspan=\"2\">CD38</td><td align=\"left\">Daratumumab</td><td align=\"left\">Human IgG1</td><td align=\"left\">Multiple myeloma</td><td align=\"left\">2015</td></tr><tr><td align=\"left\">Isatuximab</td><td align=\"left\">Chimeric IgG1</td><td align=\"left\">Multiple myeloma</td><td align=\"left\">2020</td></tr><tr><td align=\"left\">CD19/CD3</td><td align=\"left\">Blinatumomab</td><td align=\"left\">Bispecific T-cell engager (BiTES)</td><td align=\"left\">ALL</td><td align=\"left\">2014</td></tr><tr><td align=\"left\">CD3/BCMA</td><td align=\"left\">Teclistamab</td><td align=\"left\">Bispecific T-cell engager (BiTES)</td><td align=\"left\">Relapsed multiple myeloma</td><td align=\"left\">2022</td></tr><tr><td align=\"left\">B- cell maturation antigen (BCMA)</td><td align=\"left\">Belantamabmafodotin</td><td align=\"left\">Humanized IgG1 conjugated to auristatin F</td><td align=\"left\">Relapsed multiple myeloma</td><td align=\"left\">2020</td></tr><tr><td align=\"left\" rowspan=\"2\">CD19</td><td align=\"left\">Tafasitamab</td><td align=\"left\">Humanized IgG1</td><td align=\"left\">Diffuse large B-cell lymphoma</td><td align=\"left\">2020</td></tr><tr><td align=\"left\">Loncastuximabtesirine</td><td align=\"left\"><p>Humanized IgG1</p><p>conjugated to pyrrolobenzodiazepine (PBD)</p></td><td align=\"left\">Diffuse large B-cell lymphoma</td><td align=\"left\">2021</td></tr><tr><td align=\"left\">CD52</td><td align=\"left\">Alemtuzumab</td><td align=\"left\">Humanized IgG1</td><td align=\"left\">CLL</td><td align=\"left\">2001</td></tr><tr><td align=\"left\" rowspan=\"3\">HER2</td><td align=\"left\">Trastuzumab</td><td align=\"left\">Humanized</td><td align=\"left\">Metastatic breast cancer, gastric cancer</td><td align=\"left\">1998</td></tr><tr><td align=\"left\">Ado-trastuzumabemtansine</td><td align=\"left\">Humanized</td><td align=\"left\">Metatstatic breast cancer</td><td align=\"left\">2013</td></tr><tr><td align=\"left\">Pertuzumab</td><td align=\"left\">Humanized</td><td align=\"left\">Metastatic breast cancer</td><td align=\"left\">2012</td></tr><tr><td align=\"left\" rowspan=\"3\">PD-L1</td><td align=\"left\">Atezolizumab</td><td align=\"left\">Humanized IgG</td><td align=\"left\">Urothelial carcinoma, metastatic non-small cell lung cancer</td><td align=\"left\">2016</td></tr><tr><td align=\"left\">Avelumab</td><td align=\"left\">Full human</td><td align=\"left\">Metastatic markel cell carcinoma</td><td align=\"left\">2017</td></tr><tr><td align=\"left\">Durvalumab</td><td align=\"left\">Full human</td><td align=\"left\">Urothelial carcinoma</td><td align=\"left\">2017</td></tr><tr><td align=\"left\" rowspan=\"3\">EGFR</td><td align=\"left\">Cetuximab</td><td align=\"left\">chimeric</td><td align=\"left\">Colorectal cancer</td><td align=\"left\">2004</td></tr><tr><td align=\"left\">Panitumumab</td><td align=\"left\">Fully human (IgG2)</td><td align=\"left\">Colorectal cancer</td><td align=\"left\">2006</td></tr><tr><td align=\"left\">Necitumumab</td><td align=\"left\">Fully human</td><td align=\"left\">Non-small cell lung carcinoma</td><td align=\"left\">2015</td></tr><tr><td align=\"left\">EGFR and mesenchymal- epithelial transition (MET)receptor</td><td align=\"left\">Amivantamab</td><td align=\"left\">Human bispecific IgG1</td><td align=\"left\">NSCLC wit EGFR exon 20 insertion mutation</td><td align=\"left\">2021</td></tr><tr><td align=\"left\">VEGF</td><td align=\"left\">Bevacizumab</td><td align=\"left\">Humanized</td><td align=\"left\">Lung cancer, glioblastoma, colorectal cancer</td><td align=\"left\">2004</td></tr><tr><td align=\"left\">VEGFR2</td><td align=\"left\">Ramucirumab</td><td align=\"left\">Fully human</td><td align=\"left\">Gastric cancer, colorectal cancer, hepatocellular carcinoma</td><td align=\"left\">2014</td></tr><tr><td align=\"left\" rowspan=\"2\">CTLA-4</td><td align=\"left\">Ipilimumab</td><td align=\"left\">Fully human</td><td align=\"left\">Metastatic melanoma</td><td align=\"left\">2011</td></tr><tr><td align=\"left\">Tremelimumab</td><td align=\"left\">Human IgG2</td><td align=\"left\">Hepatocellular carcinoma</td><td align=\"left\">2022</td></tr><tr><td align=\"left\" rowspan=\"4\">PD-1</td><td align=\"left\">Pembrolizumab</td><td align=\"left\">Humanized IgG4</td><td align=\"left\">Metastatic melanoma, NSCLC, stomach cancer</td><td align=\"left\">2014</td></tr><tr><td align=\"left\">Nivolumab</td><td align=\"left\">Human IgG4</td><td align=\"left\">Melanoma, lung cancer, colon cancer, liver cancer, Hodgkin lymphoma</td><td align=\"left\">2014</td></tr><tr><td align=\"left\">Cemiplimab</td><td align=\"left\">Human IgG4</td><td align=\"left\">Myeloma, lung cancer, CSCC</td><td align=\"left\">2018</td></tr><tr><td align=\"left\">Dostarlimab</td><td align=\"left\">Humanized IgG4</td><td align=\"left\">Endometrial cancer</td><td align=\"left\">2021</td></tr><tr><td align=\"left\">RANK-L</td><td align=\"left\">Denosumab</td><td align=\"left\">Human IgG2</td><td align=\"left\">Secondary bone cancer</td><td align=\"left\">2010</td></tr><tr><td align=\"left\" rowspan=\"2\">GD2</td><td align=\"left\">Dinutuximab</td><td align=\"left\">Chimeric IgG1</td><td align=\"left\">Neuroblastoma</td><td align=\"left\">2015</td></tr><tr><td align=\"left\">Naxitamab</td><td align=\"left\">Humanized IgG1</td><td align=\"left\">Relapsed neuroblastoma in bone or bone marrow</td><td align=\"left\">2020</td></tr><tr><td align=\"left\">SLAMF7</td><td align=\"left\">Elotuzumab</td><td align=\"left\">Humanized</td><td align=\"left\">Multiple myeloma</td><td align=\"left\">2015</td></tr><tr><td align=\"left\">PDGFRA</td><td align=\"left\">Olaratumab</td><td align=\"left\">Human</td><td align=\"left\">Soft tissue sarcoma</td><td align=\"left\">2016</td></tr><tr><td align=\"left\">TROP-2</td><td align=\"left\">Sacituzumab govitecan</td><td align=\"left\">Humanized IgG1 conjugated to topoisomerase I inhibitor (SN-38)</td><td align=\"left\">Triple negative breast cancer, Emtastatic urothelial cancer</td><td align=\"left\">2021</td></tr><tr><td align=\"left\">Folate receptor- α (FR-α)</td><td align=\"left\">Mirvetuximabsoravtansine-gynx</td><td align=\"left\">Humanized IgG1 conjugated to DM4, tubulin-targeting compound</td><td align=\"left\">Ovarian cancer</td><td align=\"left\">2022</td></tr></tbody></table></table-wrap>" ]
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[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["9."], "surname": ["Frenzel", "K\u00fcgler", "Helmsing", "Meier", "Schirrmann", "Hust", "D\u00fcbel"], "given-names": ["A", "J", "S", "D", "T", "M", "S"], "article-title": ["Designing human antibodies by phage display"], "source": ["Transfusion Med hemother"], "year": ["2017"], "volume": ["44"], "issue": ["5"], "fpage": ["312"], "lpage": ["318"], "pub-id": ["10.1159/000479633"]}, {"label": ["21."], "surname": ["Koch", "Tesar"], "given-names": ["J", "M"], "article-title": ["Recombinant Antibodies to Arm Cytotoxic Lymphocytes in Cancer Immunotherapy"], "source": ["Transfusion Med Hemother: offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie"], "year": ["2017"], "volume": ["44"], "issue": ["5"], "fpage": ["337"], "lpage": ["350"], "pub-id": ["10.1159/000479981"]}, {"label": ["23."], "surname": ["Kovtun", "Audette", "Ye", "Xie", "Ruberti", "Phinney", "Leece", "Chittenden", "Bl\u00e4ttler", "Goldmacher"], "given-names": ["YV", "CA", "Y", "H", "MF", "SJ", "BA", "T", "WA", "VS"], "article-title": ["Antibody-drug conjugates designed to eradicate tumors with homogeneous and heterogeneous expression of the target antigen"], "source": ["Can Res"], "year": ["2006"], "volume": ["66"], "issue": ["6"], "fpage": ["3214"], "lpage": ["3221"], "pub-id": ["10.1158/0008-5472.CAN-05-3973"]}, {"label": ["24."], "surname": ["Kumar", "Planchais", "Fronzes", "Mouquet", "Reyes"], "given-names": ["A", "C", "R", "H", "N"], "article-title": ["Binding mechanisms of therapeutic antibodies to human CD20"], "source": ["Science (New York, NY)"], "year": ["2020"], "volume": ["369"], "issue": ["6505"], "fpage": ["793"], "lpage": ["799"], "pub-id": ["10.1126/science.abb8008"]}, {"label": ["38."], "surname": ["Rexer", "Arteaga"], "given-names": ["BN", "CL"], "article-title": ["Optimal targeting of HER2-PI3K signaling in breast cancer: mechanistic insights and clinical implications"], "source": ["Can Res"], "year": ["2013"], "volume": ["73"], "issue": ["13"], "fpage": ["3817"], "lpage": ["3820"], "pub-id": ["10.1158/0008-5472.CAN-13-0687"]}]
{ "acronym": [], "definition": [] }
56
CC BY
no
2024-01-14 23:43:47
J Biomed Sci. 2024 Jan 12; 31:6
oa_package/48/46/PMC10787459.tar.gz
PMC10787460
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Lung function tests have evolved from tools for physiological study to clinical investigations in assessing respiratory status. They have become a part of routine health examination in respiratory, occupational, sports medicine and public health screening [##UREF##0##1##]. Tests have been designated to indicate the extent of narrowing of airways, which can lead to breathing issues, decreased oxygen consumption, and an increased risk of respiratory infections. A simple but important test used to measure lung function is the Pulmonary function test (PFT) [##UREF##1##2##]. </p>", "<p id=\"Par6\">The PFT is a basic tool for assessing lung dysfunction, disease, and prognosis of treatment [##UREF##0##1##]. Peak expiratory flow rate (PEFR) is a PFT which measures the maximum speed of airflow attained by a forceful, complete expiration after complete inhalation [##UREF##1##2##, ##UREF##2##3##]. It was introduced by Hadron in 1942 and accepted in 1949 as an index in spirometry [##UREF##3##4##]. Notably, although PFT is acknowledged to provide valuable information it is not without its limitations. In this regard, it can be physically demanding for patients and dependent on patient effort, understanding of and cooperation with instructions as well as variations in technique. Intra individual variation in pulmonary function can also be attributed to circadian rhythm, host factors, size, age, past and present health, and geographic factors [##UREF##3##4##, ##UREF##4##5##]. Consequently, each country and region should have its own PEFR standard reference values [##UREF##5##6##]. </p>", "<p id=\"Par7\">Gender differences in airway behavior and clinical manifestations of airway disease have also been reported. The latter are attributed to biological and socio-cultural factors, such as body size, sex hormones, sex hormone receptors, and intracellular signaling pathways [##REF##17327578##7##, ##UREF##6##8##]. Ethnicity has also been shown to have an impact on lung function variation, with white populations having higher Forced Vital Capacity and Forced Expiratory Volume in 1 s (FEV1), and black Americans having smaller lung volumes [##UREF##2##3##, ##UREF##6##8##]. Additionally, increased weight decreases lung volume and capacities, this is due to increasing resistance to outflow of air through the airways. PEFR is positively correlated with height and inversely correlated with weight. Obesity is linked to decreased PFTs due to its restrictive effect on the lung and chest wall [##REF##17327578##7##, ##REF##13846051##9##, ##UREF##7##10##]. Notably, studies have reported a significant increase in PEFR with age in children, with boys having higher values than girls. The relationship between age and PEFR in children is complex and may be influenced by sex, ethnicity, physical activity levels, and the method used to measure PEFR [##UREF##6##8##, ##REF##12848205##11##, ##REF##1519841##12##]. </p>", "<p id=\"Par8\">The present study was designed to measure the PEFR of boys and girls attending a single private primary and secondary school in Tanzania and examine how it correlates with anthropometric measurements. The data was then used to derive a prediction formula which can potentially be used in this population. The developed PEFR prediction formula based on anthropometric measurements in Tanzanian school children serves as a crucial tool for identifying potential lung dysfunction and respiratory complications, facilitating simpler respiratory assessment and timely interventions.</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par9\">The analytical cross-sectional study was conducted at Aga Khan Mzizima School, encompassing both primary and secondary school children in Dar es Salaam, Tanzania. The school opened in 1993, and its private setting accommodates students of various ethnicities and backgrounds. It predominantly comprises students from families of middle to upper socio-economic status. The study was carried out during a designated school asthma screening camp held from June 7th to June 10th, 2022. This camp served as an opportune platform to gather data pertaining to respiratory health among students.</p>", "<p id=\"Par10\">The study was approved by the Aga Khan University, East Africa Ethics Review Committee (approval no. AKU/2023/03/fb/05/03), aimed primarily to observe the correlation of peak expiratory flow rate with anthropometric determinants in a population of children attending a single private primary and secondary school in Tanzania.</p>", "<p id=\"Par11\">All students from primary and secondary school who consented to participate in the screening camp were recruited while excluding students who were known to have a respiratory condition such as asthma or had symptoms consistent with asthma.</p>", "<p id=\"Par12\">The sample size for estimating correlation between variables was used.</p>", "<p id=\"Par13\">n = [(Zα/2 + Zβ) / C(r)]2 + 3 where: n is the sample size needed ,Zα/2 is the critical value of the standard normal distribution at the desired level of significance for a 2-sided test (i.e., 1.96 for α = 0.05), Zβ is the critical value of the standard normal distribution at the desired power level (1- β) (i.e., 1.282 for β = 0.1) ,Cr is Fisher’s transformation and is equal to 0.5 × ln[(1 + r)/(1-r)], r is the expected correlation coefficient (0.7) [##REF##12848205##11##].</p>", "<p id=\"Par14\">Cr = 0.5 × ln[(1 + r)/(1-r)] = 0.5 × ln [(1 + 0.7)/ (1-0.7)] = 0.5 × ln [1.7/0.3] = 0.5 × ln 5.67 = 0.5 × 0.75 = 0.3769.</p>", "<p id=\"Par15\"><italic>n</italic> = 77, Inflate of 10% was added to the sample size accounting for spoiled records or missing data (<italic>n</italic> + 8). Therefore, the minimum sample size required for the study was 85 students; All eligible students attending the asthma screening camp were enrolled in the study using a census sampling approach, encompassing those who met the eligibility criteria, provided consent, and were affiliated with the school for convenience.This inclusive approach not only exceeded the minimum sample size but also significantly enhanced the statistical power of the analysis. By incorporating data from all eligible participants, the study aimed to maximize its statistical strength, ensuring a robust investigation into the relationship between anthropometric variables and PEFR.</p>", "<p id=\"Par16\">Data collection was overseen by medical professionals from Aga Khan Hospital during a dedicated school asthma screening camp. Prior to the screening, parents or guardians received screening questionnaires and consent forms. Only children with parental consent participated in the screening, subsequently being enrolled in the study.</p>", "<p id=\"Par17\">Throughout the screening process, essential variables like age, height, and weight were documented for each participant. The study focused on PEFR, a pivotal measure of lung function critical in diagnosing and managing respiratory conditions, notably asthma. PEFR assessments were conducted using a ‘breath-o-meter’ peak flow meter provided by Chemical Industrial &amp; Pharmaceutical Laboratories Ltd company. While seated, participants underwent three separate PEFR readings. Notably, the highest recorded value among these three measurements was considered as the participant’s PEFR. Capturing the maximum expiratory flow potential was the rationale behind selecting the highest among the three PEFR readings. This approach aimed to offer a more accurate representation of the participants’ respiratory capabilities during the assessment, considering PEFR as a key outcome variable.</p>", "<p id=\"Par18\">Independent t-test was used to examine differences in PEFR between Asian and African children and between boys and girls. Correlation coefficients were used to assess the relationship between PEFR and height, weight, age, and BMI. A prediction equation was generated using linear regression analysis. Statistical significance was set at 5%. All statistical data was analyzed using SPSS version 25.0.</p>" ]
[ "<title>Results</title>", "<p id=\"Par19\">A total of 370 school students were recruited between April to May 2022. Of these participants, 110 were excluded, of whom 6 had incomplete data, 40 had a known diagnosis of asthma and 64 had symptoms consistent with asthma. A total of 260 participants were enrolled in the study, as shown in the flow chart (Fig. ##FIG##0##1##).</p>", "<p id=\"Par20\">\n\n</p>", "<p id=\"Par21\">Of the participants, 133 (51.15%) were male, 169 (65%) were of Asian ethicinity and the mean age was 9.47 years (SD 1.78) with an age ranging from 6 to 17 years old. The mean was PEFR 238.32 L/min (SD 48.50). The sociodemographic and clinical parameters are summarized in Table ##TAB##0##1##.</p>", "<p id=\"Par22\">\n\n</p>", "<p id=\"Par23\">An Independent Sample t-test was conducted to compare PEFR between male and female pupils as well as across the 2 main ethnic groups, i.e., Asian, and African. The results of the two-tailed test indicated that there was no significant difference in PEFR between males (mean = 238.46, SD = 45.00) and females (mean = 238.18, SD = 52.09); t (258) = 0.96, p-value = 0.96.</p>", "<p id=\"Par24\">Similarly, no statistically apparent difference in PEFR was observed between Asian pupils (mean = 234.02, SD = 48.805) and African pupils (mean = 246.32, SD = 47.145), t-(258) = 1.96, p-value = 0.051.</p>", "<p id=\"Par25\">Table ##TAB##1##2## shows the Pearson correlation indicating the strength of the relationship between anthropometric parameters and PEFR, stratified between female and male participants. The results suggest that age, height, weight, and BMI were all statistically significantly correlated with PEFR. Notably the strongest correlation was found between height and PEFR for females and the weakest correlation was observed between BMI and PEFR for males. Interestingly all anthropometric measures were positively related with PEFR across both genders, i.e., as age, height, weight, and BMI increase so too does PEFR.</p>", "<p id=\"Par26\">\n\n</p>", "<p id=\"Par27\">A linear regression analysis was conducted separately for female and male students to explore the relationship between PEFR and height, using height as the independent variable and PEFR as the dependent variable. Even when considering potential additional variables like age or weight, the analysis revealed that the model’s predictive strength remained robust solely with height as a predictor. This decision was guided by the strong correlation observed between height and PEFR within the Tanzanian child population, rendering the inclusion of other variables unnecessary for enhancing predictive accuracy.</p>", "<p id=\"Par28\">Table ##TAB##2##3## presents results of a regression analysis showing that an increase in height (in meters) is significantly and positively associated with a dependent variable (PEFR), across both female and male children.</p>", "<p id=\"Par29\">\n\n</p>", "<p id=\"Par30\">Figure ##FIG##1##2##a and b below show the scatterplots of the linear regression model for male and female students respectively.</p>", "<p id=\"Par31\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par32\">This study provides valuable insights into the correlation between anthropometric variables (age, height, weight and BMI) and PEFR in school children from Dar es Salaam, Tanzania. The results show that age, height, weight, and BMI are significantly correlated with PEFR, with height demonstrating the highest correlation coefficient (<italic>r</italic> = 0.745, <italic>p</italic> &lt; 0.001).</p>", "<p id=\"Par33\">The strong correlation between height and PEFR in the Tanzanian child population aligns with previous research conducted in diverse populations. Studies conducted in various countries and age groups have consistently demonstrated a positive relationship between height and lung function parameters, including PEFR [##UREF##8##13##, ##UREF##9##14##]. This steadfast consistency across distinct demographic cohorts fortifies the applicability of the height-PEFR correlation and validates its reliability as a pragmatic tool for evaluating respiratory well-being. As a consequence, the adoption of height as a solitary predictor for estimating PEFR exhibits the potential to rationalize and simplify assessment protocols, particularly in settings characterized by limited resources, where access to specialized equipment might be constrained [##UREF##8##13##, ##UREF##9##14##]. .</p>", "<p id=\"Par34\">In this study, we observed a correlation coefficient of 0.672 between weight and PEFR, indicating a moderate correlation between these two variables. This finding suggests that there is a noticeable relationship between weight and lung function, where higher weight is associated with changes in PEFR. However, these results appear to be contrary to previous studies that have shown either no correlation or a weaker correlation between weight and lung function. This discrepancy may be attributed to the presence of adipose fat around the chest, which could limit lung compliance and volume, thereby potentially affecting the expected correlation [##UREF##0##1##, ##UREF##10##15##]. However, research is warranted to delve into the underlying mechanisms and potential contributing factors that may be driving this correlation. Specifically, investigating these aspects in the context of children’s lung function is of particular importance, as it can provide insights into the unique dynamics of respiratory development and potential health implications.</p>", "<p id=\"Par35\">Interestingly, the study reveals a weak correlation of 0.366 between BMI and PEFR, particularly among boys( <italic>r</italic> = 0.209). This finding suggests that it may be more informative to consider individual variables such as height rather than relying on a combined measure like BMI when assessing the relationship with lung function. This finding is in line with some previous studies but contradicts others that reported a significant association between BMI and lung function in children [##REF##12848205##11##]. The weak correlation observed in this study could be attributed to the high prevalence of overweight and obesity among participants, where the impact of excess weight on lung function becomes less discernible or diluted. Other factors such as body composition, fat distribution, or specific physiological mechanisms might also contribute to this weak correlation.</p>", "<p id=\"Par36\">Furthermore, it is worth noting that the overall correlation coefficients reported in our study were lower compared to some previous studies. For instance, a study conducted in Sri Lanka among healthy school children found very high correlations between PEFR and height, weight, and BMI (<italic>r</italic> = 0.89, 0.86, and 0.891, respectively) [##REF##17327578##7##]. Similarly, a study conducted in Nigeria among school children reported strong correlations between PEFR and height, weight (<italic>r</italic> = 0.77 and 0.76 respectively) [##REF##12848205##11##]. The relatively lower correlation coefficients in our study could be attributed to the smaller sample size and variations in the characteristics of the study population, such as age range, ethnicity, and environmental factors [##REF##17327578##7##]. </p>", "<p id=\"Par37\">The congruence between the study findings and prior research conducted by Seema S. et al., which also identified no statistically significant disparity in PEFR between males and females, underscores the consistency in these observations [##UREF##11##16##]. . This result shows there is no significant variation in PEFR between males and females, indicating that gender does not play a substantial role in influencing this respiratory measure. It provides valuable insights to healthcare professionals and helps them comprehend the impact of gender on PEFR within the confines of this study.</p>", "<p id=\"Par38\">However, it is essential to remain cautious and consider the potential influence of gender in other populations or for different health conditions. On the other hand, concerning the association between ethnicity and PEFR, our study did not find a statistically significant difference between Asian and African populations, which aligns with the findings of Whittaker A et al. 2005 [##UREF##10##15##, ##UREF##12##17##]. Nevertheless, it is essential to note that some studies have reported significant variations in PEFR across different ethnic groups, as indicated by Udupihille M et al. 1994 [##UREF##10##15##].Several factors could contribute to these variations, including genetic factors influencing lung function, disparities in environmental exposures such as air pollution and indoor air quality, socioeconomic status, lifestyle habits, cultural practices, and healthcare disparities.</p>", "<p id=\"Par39\">Based on the derived formula from the study, which establishes a significant relationship between PEFR and height, a prediction model has been developed. The formula, predictive equation for male <bold>PEFR = 279.169 (Height of Student in m) —134.12</bold> while predictive equation for female is <bold>PEFR = 318.32 (Height of Student in m) —195.69</bold>, the formula can be utilized to predict the PEFR of male and female individuals based on their height. The coefficient values indicate that height holds the strongest positive relationship with PEFR.</p>", "<p id=\"Par40\">Comparing the derived formula from this study to existing formulas used in Nigeria, USA, India, and Europe reveals intriguing findings. Our formula, PEFR = 293.04 (Height of Student in meters) —157.362, shares a notable similarity with the formula derived in Nigeria, PEFR = 345(Height) —222. Both formulas primarily rely on height as the predictor for PEFR, and interestingly, in both of these studies, height alone yields a high R² compared to when other variables are combined. The results obtained from our formula and the Nigerian formula exhibit a small difference in standard deviation, approximately +/- 10. This suggests that our formula yields similar results with a slight variation [##REF##12848205##11##]. </p>", "<p id=\"Par41\">However, when comparing our formula to those used in the USA (PEFR(l/min) = [Height,cm-100)*5] + 100 (22)) and India (PEFR(l/min) = (19.964 * age in years) —(0.0988 * height in cm) + 32.455 (23)), slight differences in standard deviation, around +/- 5, are observed when compared to our formula. Remarkably, even in the USA formula, where height alone is used in linear regression, it yields a higher R² compared to when combined with other variables. Intriguingly, in the Indian study, the author employed both age and height since the R² remains consistent whether combined or used as independent predictors. These formulas employed in children populations incorporate additional predictors such as age. Moreover, these variations may be attributed to differences in ethnicity and genetic factors, which can influence respiratory function [##UREF##4##5##]. </p>", "<p id=\"Par42\">The successful development of this prediction model as well as variability in results when comparing studies undertaken in different populations strongly advocates the importance of establishing a locally derived reference standard for PEFR in the Tanzanian child population and the broader East African region. This model’s effectiveness in estimating PEFR using only height, which is easily measurable, highlights its potential to significantly enhance healthcare practices in resource-limited settings. By implementing this formula, healthcare professionals in these regions can accurately estimate a child’s PEFR without the need for expensive and inaccessible equipment. This represents a crucial advancement, as traditional methods that rely on specialized devices can be cost-prohibitive and challenging to obtain, particularly in low-income or remote areas.</p>", "<p id=\"Par43\">In conclusion, this study provides valuable insights into the relationship between anthropometric variables and PEFR in school children from Dar es Salaam, Tanzania. The findings contribute to the existing body of knowledge and highlight the importance of locally derived reference standards for accurate PEFR estimation in this population. Further research is needed to explore additional factors and validate the prediction model in larger and more diverse populations.</p>", "<title>Limitations</title>", "<p id=\"Par44\">An important limitation lies in the study’s focus on school children from a sole institution in Dar es Salaam, Tanzania. As such, the findings might not be broadly representative of other populations, including those in rural areas or children from diverse socioeconomic backgrounds. This limitation impacts the generalizability of the results beyond the specific urban school setting under investigation.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par45\">The results of this study suggest that there is a strong correlation between peak expiratory flow rate (PEFR) and age, height, and weight, and a weaker correlation with body mass index (BMI) in school children from Dar es Salaam, Tanzania. These findings highlight the importance of anthropometric characteristics in predicting lung function in this population. The study also developed a predictive equation for PEFR in this population based on their anthropometric characteristics, which could be useful in clinical practice and research. Further research is needed to explore other factors that may affect lung function in this population, including environmental factors, lifestyle behaviors, and socioeconomic status.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Peak expiratory flow rate (PEFR) is an important tool for assessing lung function, which can be affected by environmental and physical factors such as altitude, nutrition, genetics, age, height, and weight. Conducting a study to assess the correlation between peak expiratory flow rate and anthropometric measurements in Tanzanian schoolchildren is crucial to derive a population-specific prediction formula and further simplify respiratory health assessment.</p>", "<title>Methods</title>", "<p id=\"Par2\">This cross-sectional study was conducted in a single center private primary and secondary school in Dar es Salaam, Tanzania using data from an asthma screening camp. Variables of interest were height, weight, Body Mass Index (BMI) and PEFR. Independent t-test was performed to identify any differences in mean flow rate values between different ethnicities and genders. Correlation coefficients (r) were used to observe the relationship between PEFR and anthropometric measurements. A prediction equation by gender was generated using linear regression analysis. Statistical significance was set at the 5% level. All statistical data was analyzed using SPSS version 25.0.</p>", "<title>Results</title>", "<p id=\"Par3\">The study involved 260 participants with a mean age of 9.5 years. Males were 51.2% and 65% of participants were of Asian ethnicity. PEFR was not observed to differ across the different ethnic groups and genders. Height was found to have the strongest correlation coefficient of 0.745, while BMI had the weakest correlation coefficient of 0.366. The strongest correlation was found with height for females (<italic>r</italic> = 0.787), while the weakest was with body mass index for boys (<italic>r</italic> = 0.203). The derived prediction equation for males was <bold>PEFR = 279.169 (Height of Student in meters) —134.12</bold>, while the predictive equation for females was <bold>PEFR = 318.32 (Height of Student in meters) —195.69</bold>.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">This study found a strong correlation between PEFR and anthropometric characteristics in school children from Dar es Salaam, Tanzania. A prediction equation by gender for PEFR was developed based on anthropometric characteristics. This equation may be applied in population-based studies or situations where peak flow meters are not readily available. Further research is needed to explore how well this prediction formula performs in other Tanzanian settings and to determine other factors that may affect lung function in this population.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>I would like to express my sincere appreciation to the pediatric doctors from Aga Khan hospital who assisted with data collection. Without their invaluable contributions, this work would not have been possible.</p>", "<title>Author contributions</title>", "<p>All authors made a significant contribution to the work reported including in the conception, study design, execution, acquisition of data, analysis, interpretation and implementation. All authors took part in drafting, revising, and critically reviewing the article. All authors approved the final document to be published and agreed to be accountable for all aspects of the work.</p>", "<title>Funding</title>", "<p>This research was conducted without external funding or financial support. The study design, data collection, analysis, interpretation of results, and writing of this dissertation were carried out solely by the author without any financial assistance.</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to Participate</title>", "<p id=\"Par48\">This study has received ethical approval from the Ethics Committee of the Aga Khan University, Ethical Review Committee, East Africa (AKU-ERC, EA) Reference number Ref: AKU/2023/03/fb/05/03 prior to initiation. The Ethics Committee ensures the protection of participants’ rights, safety, and welfare in accordance with established ethical guidelines and principles. All participants and their parents/legal guardians provided informed consent before participating in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par49\">Written consent for the publication of the research findings has been obtained from all legal guardians included in this study. Participants were informed about the purpose of the study, the nature of the data that would be collected, and the potential implications of publication. Confidentiality has been maintained, and any identifying information has been appropriately anonymized to protect the privacy of the participants.</p>", "<title>Data sharing statement</title>", "<p id=\"Par50\">The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Competing interests</title>", "<p id=\"Par46\">The authors report no conflicts of interest in this work.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Participant recruitment flow</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p><bold>a</bold>: Linear regression between male student PEFR and standardized residual of the Height. The regression equation derived from the linear regression above (Fig. 2), used to predict male PEFR based on height, is: <bold>PEFR = 279.169 (Height of Student in m) —134.12. b</bold>: Linear regression between female student PEFR and standardized residual of the Height. The regression equation derived from the linear regression above (Fig. 2), used to predict female PEFR based on height, is as outlined below: <bold>PEFR = 318.32 (Height of Student in m) —195.69</bold></p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Sociodemographic and clinical parameters of the study population</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variable</th><th align=\"left\" colspan=\"2\">Frequency</th><th align=\"left\" colspan=\"1\"/></tr></thead><tbody><tr><td align=\"left\">\n<bold>Age (Mean; SD)</bold>\n</td><td align=\"left\" colspan=\"2\">9.47 (1.78)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>Sex (n; %)</bold>\n</td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Male</td><td align=\"left\" colspan=\"2\">133 (51.15)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Female</td><td align=\"left\" colspan=\"2\">127 (48.85)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>Ethnicity (n; %)</bold>\n</td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Asian</td><td align=\"left\" colspan=\"2\">169(65.00)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">African</td><td align=\"left\" colspan=\"2\">91 (35.00)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>Height meters (mean; SD)</bold>\n</td><td align=\"left\" colspan=\"2\">1.35 (0.12)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>Weight kg (mean; SD)</bold>\n</td><td align=\"left\" colspan=\"2\">35.51 (13.02)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>BMI continuous (kg/m</bold>\n<sup><bold>2</bold></sup>\n<bold>) (mean; SD)</bold>\n</td><td align=\"left\" colspan=\"2\">19.19 (4.85)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>BMI categorical* (n; %)</bold>\n</td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Underweight:</td><td align=\"left\" colspan=\"2\">22 (8)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Healthy:</td><td align=\"left\" colspan=\"2\">113 (43)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Overweight:</td><td align=\"left\" colspan=\"2\">43 (17)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">Obese:</td><td align=\"left\" colspan=\"2\">82 (32)</td><td align=\"left\" colspan=\"1\"/></tr><tr><td align=\"left\">\n<bold>PEFR (mean; SD)</bold>\n</td><td align=\"left\" colspan=\"2\">238.32 (48.50)</td><td align=\"left\" colspan=\"1\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Pearson correlation of anthropometrical parameters with PEFR in the entire study group, female, and male subjects</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variable</th><th align=\"left\" colspan=\"2\">Total</th><th align=\"left\" colspan=\"2\">Female</th><th align=\"left\" colspan=\"2\">Male</th></tr><tr><th align=\"left\">Correlation<break/>coefficient (r)</th><th align=\"left\">P value</th><th align=\"left\">Correlation<break/>coefficient (r)</th><th align=\"left\">P value</th><th align=\"left\">Correlation<break/>coefficient (r)</th><th align=\"left\">P value</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\">0.697</td><td align=\"left\">0.000</td><td align=\"left\">0.745</td><td align=\"left\">0.000</td><td align=\"left\">0.648</td><td align=\"left\">0.000</td></tr><tr><td align=\"left\">Height</td><td align=\"left\">0.745</td><td align=\"left\">0.000</td><td align=\"left\">0.787</td><td align=\"left\">0.000</td><td align=\"left\">0.760</td><td align=\"left\">0.000</td></tr><tr><td align=\"left\">Weight</td><td align=\"left\">0.627</td><td align=\"left\">0.000</td><td align=\"left\">0.676</td><td align=\"left\">0.000</td><td align=\"left\">0.569</td><td align=\"left\">0.000</td></tr><tr><td align=\"left\">BMI</td><td align=\"left\">0.366</td><td align=\"left\">0.000</td><td align=\"left\">0.479</td><td align=\"left\">0.000</td><td align=\"left\">0.203</td><td align=\"left\">0.019</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Results of the linear regression analysis of PEFR and height (in meters)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variable</th><th align=\"left\">Unstandardized Beta coefficients</th><th align=\"left\">Standardized Beta Coefficients</th><th align=\"left\">p value</th><th align=\"left\">Standard error</th><th align=\"left\">95% CI</th></tr></thead><tbody><tr><td align=\"left\">Height (<bold>Male</bold>)</td><td align=\"left\">279.170</td><td align=\"left\">0.741</td><td align=\"left\">0.00</td><td align=\"left\">22.14</td><td align=\"left\">235.41– 322.93</td></tr><tr><td align=\"left\">Height (<bold>Female</bold>)</td><td align=\"left\">318.320</td><td align=\"left\">0.761</td><td align=\"left\">0.00</td><td align=\"left\">24.24</td><td align=\"left\">270.46–366.17</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>*BMI categories determined based on WHO BMI charts for age and sex</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12887_2023_4520_Fig1_HTML\" id=\"d32e323\"/>", "<graphic xlink:href=\"12887_2023_4520_Fig2_HTML\" id=\"d32e705\"/>" ]
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{ "acronym": [], "definition": [] }
17
CC BY
no
2024-01-14 23:43:47
BMC Pediatr. 2024 Jan 13; 24:42
oa_package/e3/0d/PMC10787460.tar.gz
PMC10787461
38217012
[ "<title>Background</title>", "<p id=\"Par7\">Laryngotracheal stenosis (LTS), defined as soft tissue narrowing of the proximal airway, currently has an estimated incidence of 0.6-2% [##REF##25573683##1##–##REF##11192899##3##]. The causes of LTS can be multifactorial in nature. In the pediatric and adult populations, acquired stenosis is most commonly secondary to prolonged intubation, tracheostomy, systemic disease, trauma, infection, or idiopathic causes [##REF##27767216##4##, ##REF##14631181##5##]. Surgical management of LTS can range from tracheostomy to endoscopic and open approaches [##REF##25573683##1##]. Despite advancements in endoscopic and open techniques, there are significant limits to current clinical approaches.</p>", "<p id=\"Par8\">Long-segment tracheal defects are defined as &gt; 50% in adults and &gt; 30% in children [##UREF##0##6##]. These defects cannot be repaired primarily because they require replacement tissue that is not currently available. A myriad of bioengineering approaches have created scaffolds that recapitulate the biological and mechanical properties of the native trachea [##REF##32064791##7##, ##REF##27411362##8##]. The success of these scaffolds is dependent in part on rapid epithelialization, which restores mucociliary clearance and prevents infection and inflammation [##REF##31035858##9##]. However, the optimal method for reepithelialization is unknown.</p>", "<p id=\"Par9\">We demonstrated that host-derived basal cells regenerate a surface airway epithelium (SAE) on a partially decellularized tracheal scaffold [##REF##37438368##10##]. This process requires 7–14 days and could be accelerated by pre-seeding the scaffold with patient-derived cells. Ex vivo methods of cell seeding include the use of induced pluripotent stem cell-derived basal cells and primary airway stem cells (basal cells) [##REF##23614471##11##]. Although both cell types can be expanded using current cell culture technology, the quality of the cell therapy product is likely to be dependent on the initial cell inoculum.</p>", "<p id=\"Par10\">Patients with long-segment tracheal defects can suffer from chronic airway disease, a situation that may compromise the regenerative potential of the host’s basal cells. In particular, stenotic regions of the airway exhibit abnormal epithelial morphology, including basal cell dysplasia [##REF##30171668##12##, ##REF##941106##13##]. We reported that the lifespan of the tracheobronchial basal cell is ~ 40 population doublings [##REF##21131442##14##], which is consistent with the Hayflick limit [##REF##13905658##15##]. Stem cell frequency decreases during wound healing and in vitro expansion, resulting in reduced regenerative potential [##REF##33187933##16##, ##REF##34546001##17##]. These decrements are associated with a decrease in the number of clone-forming stem cells, accumulation of cells with shortened telomeres, and suboptimal production of differentiated secretory and ciliated cells [##REF##36544928##18##]. Thus, a critical question is whether tracheobronchial stem cells from patients with airway disease have sufficient regenerative potential to support the cellularization of a graft and the production of a functional epithelium. We addressed this issue by assessing the phenotype and function of basal cells that were recovered from the airways of normal donors and those with chronic lung disease.</p>" ]
[ "<title>Methods</title>", "<title>Approvals</title>", "<p id=\"Par11\">This study was approved by the institutional review boards of two tertiary-level pediatric and adult hospitals (Nationwide Children’s Hospital IRB STUDY00000847, Ohio State University 2021N0027). Pediatric and adult patients undergoing scheduled direct laryngoscopy and bronchoscopy (DLB) were voluntarily recruited. Demographics of the patients recruited were recorded.</p>", "<title>Tracheal airway epithelial cell isolation</title>", "<p id=\"Par12\">Our methods are similar to those previously described [##REF##33187933##16##, ##REF##36544928##18##]. Briefly, endotracheal brush biopsies were collected using a cytology brush (Medical Packing Corporation, Camarillo, CA). Under direct visualization, the cytology brush was advanced and spun in a focal region of the trachea five times for approximately 10 s.</p>", "<p id=\"Par13\">Cells were liberated from the brushes using mechanical agitation in phosphate-buffered saline (PBS) supplemented with 10 µM β-mercaptoethanol (Acros Organics, NJ), 5 mM EDTA (Thermo Fisher, Waltham, MA), and 5 mM EGTA (Thermo Fisher, Waltham, MA). Cells were pelleted by centrifugation (2500 rpm, 5 min) and resuspended in 1 mL red blood cell lysis buffer (Invitrogen/Thermo Scientific, Waltham, MA) for 5 min. Lysis was then terminated by dilution with PBS (1:10) and the cells were repelleted. Cell pellets were then resuspended in culture medium (see below).</p>", "<title>Tracheal airway epithelial culture timeline</title>", "<p id=\"Par14\">Cells were cultured using the modified conditional reprogramming culture (mCRC) method [##REF##27144410##19##]. Accordingly, the cells were co-cultured on a feeder layer of irradiated NIH-3T3 fibroblasts (ATCC #CRL-1658) with F-medium (F<sub>med</sub>) supplemented with Rho-kinase inhibitor, Y-27632 (10 µM). Cultures were supplemented with an antibiotic/antifungal cocktail, which was reduced to 50% concentration on day 2 and discontinued on day 4 of culture. Culture medium was changed on a Monday-Wednesday-Friday schedule, and the plates were monitored for basal cell colony development. Cultures were discarded if colonies were not observed on culture day 14. Successful cultures (p0) were expanded at passage 1 (p1) and cryopreserved as frozen stocks at passage 2 (p2).</p>", "<title>Cytospin</title>", "<p id=\"Par15\">Cytospin preparations (20,000 cells per slide) were prepared as previously described [##REF##21131442##14##, ##REF##20522644##20##], fixed with 10% neutral-buffered formalin (NBF) for 10 min at room temperature, and stained for Keratin 5 (Covance Innovative Antibodies, Rabbit, 1:1000) and Keratin 14 (Thermo Scientific, Mouse, 1:500). Slides were counterstained with 1 µg/ml 4′,6-diamidino-2-phenylindole (DAPI). Images of at least 200 nucleated cells were acquired using Zeiss Imager.Z1 fluorescent microscope (Zeiss) and quantified using ImageJ software.</p>", "<title>Clone-forming cell frequency assay</title>", "<p id=\"Par16\">Clone-forming Cell Frequency (CFCF) was determined using a limiting dilution method that has been previously described [##REF##7009746##21##] and modified for use with airway tissues [##REF##21131442##14##]. Passage one cells were distributed to wells of a 96-well plate using two-fold dilution from 100 cells/well to 1 cell/well. Six replicates were seeded for each cell input. Following 9 days of culture, cells were fixed with NBF, and stained with Giemsa stain. Wells were scored as positive or negative for the development of colonies. Linear regression analysis was used to calculate the CFCF.</p>", "<title>Population Doubling Level calculation</title>", "<p id=\"Par17\">Population Doubling Level was calculated as: PDL = 3.32 (logXe – logXb), where Xe is the basal cell number obtained at passage and Xb is the basal cell number plated (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.atcc.org/resources/culture-guides/animal-cell-culture-guide\">https://www.atcc.org/resources/culture-guides/animal-cell-culture-guide</ext-link>). Cells were stained with trypan blue and counted using a hemacytometer [##REF##13905658##15##].</p>", "<title>Relative telomere length determination</title>", "<p id=\"Par18\">Telomere length was determined based on previously published methods [##REF##18476834##22##, ##REF##26972047##23##] with minor modifications [##REF##34546001##17##]. Specifically, cells were recoverd using the double trypsinization method. Genomic DNA (gDNA) was purified from 50,000 cells using the DNeasy Blood &amp; Tissue Kit (Qiagen Cat# 69506) and quantified using a Nanodrop 2000 spectrophometer (ThermoFisher, Welmington, DE). Both the telomere and 36B4 single copy gene control assays used 40 ng gDNA/reaction. Targets were amplified using previously reported standards and primers [##REF##18476834##22##]. For the telomere assay, the magnesium concentration in the PowerSYBR Green Master Mix (Applied Biosystems  Cat# 4367659) was lowered to a final concentration of 0.9625 mM through the addition of 0.5 M EDTA (0.0385 µL per 20 µL reaction). Previously published cycling parameters for telomeres [##REF##26972047##23##] and 36B4 [##REF##18476834##22##] were used. Jurkat (ATCC) and U1301 (human T-cell leukemia cell line (Sigma Cat# 01051619) were used as short and long telomere controls, respectively. A standard curve was generated for each experiment and was used to insure a linear relationship between DNA input and telomere length. Prior to analysis, the telomere standards were incubated at 95 °C with shaking for 5 min, and immediately placed on ice. Three technical replicates were generated for each standard curve point and biological sample. Relative telomere length was calculated according to the Telomere/Single copy gene control (T/S) ratio.</p>", "<title>Flow cytometry</title>", "<p id=\"Par19\">Human basal cells were resuspended at 10^7 cells/mL in BSA staining buffer (BD Pharmingen Cat# 554657). The cells were stained with APC-anti-CD151 (Biolegends Cat# 350406, 1:20) and EFlour 450-anti-CD49f (Invitrogen Ref# 48-0495-82, 1:20) for 30 min on ice. The cells were then washed with BSA staining buffer, fixed in NBF, and analyzed on a BD Pharmingen Fortessa-5 laser flow cytometer. Unstained cells served as a negative control. Flow data was analyzed using FlowJo.</p>", "<title>Correlation of clinical and culture phenotype</title>", "<p id=\"Par20\">Univariate chi-squared and t-test analyses were used to compare patient demographic and clinical characteristics between those who did and did not have squamous basal cells. Clinical characteristics included prematurity; significant pulmonary, cardiac, gastrointestinal, and/or neurological history; known chromosomal abnormalities; congenital defects in the head and neck (including supraglottic, glottic, subglottic, tracheal stenosis); and history of airway surgery. Prematurity was coded as an ordinal variable per World Health Organization guidelines, with a moderate to late preterm group (gestational age between 32 and 37 weeks), a very preterm group (28 to 32 weeks), and an extremely preterm group (less than 28 weeks).</p>", "<title>Statistical analysis</title>", "<p id=\"Par21\">All statistical calculations were conducted with Stata 17.0 (College Station, TX). Summary data are presented as the mean and standard deviation. Symbols represent the values from individual donors. Sample size is noted in the figure legends. Normally-distributed data were assessed by student’s t-test or 2-way ANOVA. Skewed data sets were assessed using the ROUT method and analyzed using GraphPad Prism, version 9.0.0 (GraphPad Software Inc., CA). A significance threshold of 0.05 was used. Specific analysis details for each data set and corresponding N for each experimental set are indicated in the figure legends.</p>", "<title>Power analysis</title>", "<p id=\"Par22\">Power analyses were completed with our pediatric population (total sample size of 48 patients), demonstrating that with our univariate chi-squared analyses with an error probability of 0.05 and power of 0.8, we would be able to detect a large effect size (<italic>r</italic> = 0.49). In our adult population (total sample size of 6 patients) with similar power analyses, we would be able to detect an effect size of 0.78. In order to detect a medium effect size (<italic>r</italic> = 0.3), we would need a total sample size of 143 patients in each of the pediatric and adult cohorts.</p>" ]
[ "<title>Results</title>", "<title>Pediatric donor characteristics</title>", "<p id=\"Par23\">This study included 48 pediatric patients and 6 adult patients. Male pediatric donors comprised 67% (<italic>N</italic> = 31) of the cohort and had a mean age of 3.5 years (standard deviation, S.D., 3.7 years). The mean female pediatric donor age was 3.4 (S.D. 3.5 years). The mean age did not vary for the two groups (<italic>p</italic> = 0.85). Mean body mass index (BMI) percentile was 51.6 (SE = 35). Prematurity was the most common comorbidity (62%, <italic>N</italic> = 30). Bronchoscopy was commonly performed for recurrent croup (<italic>N</italic> = 8, 17%), stridor (<italic>N</italic> = 8, 17%), or in conjunction with other surgical procedures (<italic>N</italic> = 6, 13%), including adenotonsillectomy for obstructive sleep apnea (<italic>N</italic> = 3, 50%). Full patient demographic information for the pediatric population is presented in Table ##TAB##0##1##.</p>", "<p id=\"Par24\">\n\n</p>", "<title>Adult donor characteristics</title>", "<p id=\"Par25\">Six adult donors were recruited for this study. The cohort was 50% (<italic>N</italic> = 3) male, with mean age of 55 years (SE 13.2 years). 50% (<italic>N</italic> = 3) of the patients underwent direct laryngoscopy (DL) for subglottic stenosis and 33% (<italic>N</italic> = 2) for tracheal stenosis. The final patient had a normal airway and was recruited as a healthy control. Additional patient characteristics of the adult population are detailed in Table ##TAB##1##2##.</p>", "<p id=\"Par26\">\n\n</p>", "<title>Basal cell number and phenotype</title>", "<p id=\"Par27\">Cytospin slides were generated from uncultured cells and stained for a pan-basal cell marker keratin 5 (K5) and a marker of basal cell activation keratin 14 (K14) (Fig. ##FIG##0##1##A). Regardless of age (pediatric vs. adult) or region sampled (normal vs. stenosis), basal cell number (K5+) and activation status (K5/K14+) were similar (Fig. ##FIG##0##1##B). These data indicate that the brush biopsy protocol recovered similar numbers of basal cells and that these metrics did not vary by age or region (Fig. ##FIG##0##1##C).</p>", "<p id=\"Par28\">\n\n</p>", "<p id=\"Par29\">As the brush biopsy contains a heterogenous population of epithelial cells including differentiated mucous-producing and ciliated cell types, cell isolates were cultured using the mCRC method which selects for basal cells. To determine if age or the region of airway stenosis sampling influenced basal cell expansion in vitro, cytospins were generated from passage 2 cells and stained for K5 and K14 (Fig. ##FIG##0##1##A). The percentage of basal cells increased with passage. Basal cell number (K5 + only) and activation state (K5/K14+) did not vary as a function of age (Fig. ##FIG##0##1##B) or airway region sampled (Fig. ##FIG##0##1##C).</p>", "<title>Regenerative capacity</title>", "<p id=\"Par30\">To estimate the therapeutic potential of cells that are recovered by brush biopsy, we determined the clone forming cell frequency at passage 1. This study used the limiting dilution assay and results were reported as the Clone-forming Cell Frequency (CFCFx1000, Fig. ##FIG##1##2##A). The mean CFCF was 195 +/- 210 (<italic>n</italic> = 33 donors). This value was lower than the CFCFx1000 for basal cells that were isolated by digestion of explanted tracheal tissue [##REF##30506964##24##]. The pediatric and adult groups and the normal or stenotic sampling sites had similar numbers of clone forming cells.</p>", "<p id=\"Par31\">\n\n</p>", "<p id=\"Par32\">To determine if these clone forming cells could be amplified, they were passaged and cell yield was determined (Fig. ##FIG##1##2##B). These results were benchmarked against a scaffold that would be used for the reconstruction of a pediatric airway [##REF##3484568##25##]. At passage 1, all samples contained sufficient cells to cellularize a 3.5 by 0.5 cm<sup>2</sup> graft scaffold at low cell density (~ 7000 cells/cm^2) and 98% could cellularize a scaffold at high cell density (~ 100,000 cells/cm^2). At passage 2, all samples contained sufficient cells for both recellularization models.</p>", "<p id=\"Par33\">To determine if these cells had reserve regenerative potential, we first calculated the number of populations doublings [##REF##13905658##15##]. At passage 1, most samples underwent 0–5 population doublings (Fig. ##FIG##1##2##C). However, cell number did not increase in 13 samples. At passage 2, all samples underwent 4 population doublings. The total number of population doublings was ~ 25% of basal cell life-span [##REF##20522644##20##].</p>", "<p id=\"Par34\">Finally, we used telomere length as a surrogate for biological age [##REF##30265166##26##]. DNA was recovered from cryopreserved p2 cells (48 pediatric and 5 adult subjects). Telomere length was analyzed using a modified PCR assay and is presented as the relative telomere length [##REF##34546001##17##]. Since telomere length varies as a function of chronological age and has been associated with lung diseases [##REF##36932145##27##], we evaluated pediatric and adult samples separately. At passage 2, the relative telomere length for pediatric samples was 2.3+/-0.42, and 41% of samples were in the short telomere range (the samples with a value &lt;/=1, Fig. ##FIG##1##2##D). Relative telomere length in adult samples was 1.6+/-0.3 and most samples were in the short telomere range (Fig. ##FIG##1##2##D). No significant differences were detected between normal or stenotic samples (Fig. ##FIG##1##2##E). Collectively, these data indicate that the airways of pediatric and adult 54 donors have sufficient regenerative capacity to recellularize an airway scaffold.</p>", "<title>Alteration of basal cell identity: squamous basal cells</title>", "<p id=\"Par35\">Culture morphology was qualitatively assessed at p1. Typical basal cells (normal phenotype) formed discrete colonies on the fibroblast feeder layer that were generally spherical or ovoid in shape and had distinct edges. Normal phenotype colonies required extensive trypsin exposure to remove them from the culture plate and to dissociate the cells into a single-cell suspension for passage and handling. Most pediatric donor collections yielded basal cell colonies of typical phenotype (59 of 69 samples, 85.5%, Fig. ##FIG##2##3##A). These cells expressed high levels of K5 and K14 (Fig. ##FIG##2##3##B, C).</p>", "<p id=\"Par36\">\n\n</p>", "<p id=\"Par37\">In contrast, squamous basal cells (Fig. ##FIG##2##3##F) were observed as morphological variants at p1. These colonies exhibited a diffuse lattice-like structure with poorly defined boundaries and expressed lower levels of K5 than typical cells (Fig. ##FIG##2##3##H, I). Both the number of K5 positive cells and the intensity of the staining were decreased relative to cells recovered from typical morphology colonies. Abnormal cells grew more rapidly than typical basal cells and were easily dislodged with trypsin. Ten cultures originating from seven pediatric patients (14.5%) contained squamous basal cell colonies at passage 1. Samples containing these abnormal cells were excluded from the previous data sets (Figs. ##FIG##0##1##, ##FIG##1##2## and ##FIG##2##3##).</p>", "<p id=\"Par38\">Cell phenotype was further evaluated using flow cytometry. Cells with a typical phenotype demonstrated high expression of the markers CD151 and CD49f (Fig. ##FIG##2##3##D, E), which are commonly expressed on epithelial basal cells [##REF##941106##13##]. In contrast, cells with the squamous basal cell phenotype had decreased or absent expression of these markers (Fig. ##FIG##2##3##K–J). Squamous basal cells from pediatric and adult donors exhibited similar morphology and marker expression profiles.</p>", "<p id=\"Par39\">A meta-analysis demonstrated that the presence of squamous basal cells correlated with the degree of prematurity, with 67% (<italic>N</italic> = 4) from donors having a history of extreme prematurity (&lt; 28 weeks, vs. 5% [<italic>N</italic> = 2], <italic>p</italic> = 0.001, see Table ##TAB##2##3##. Squamous basal cell isolates were also associated with significant pulmonary history (83% vs. 31%, <italic>p</italic> = 0.013), specifically bronchopulmonary dysplasia (67% vs. 17%, <italic>p</italic> = 0.006), as well as airway surgery (67% vs. 26%, <italic>p</italic> = 0.045), specifically tracheostomy placement (67% vs. 21%, <italic>p</italic> = 0.02). The presence of squamous basal cells was not associated with a history of laryngotracheal reconstruction or balloon dilation (33% vs. 10%, <italic>p</italic> = 0.1; 33% vs. 14%, <italic>p</italic> = 0.24; respectively). Subglottic stenosis as assessed by direct laryngoscopy and bronchoscopy approached significance (50% vs. 17%, <italic>p</italic> = 0.06).</p>", "<p id=\"Par40\">Squamous basal cells were observed in one adult patient with subglottic stenosis and two patients with tracheal stenosis. Adult samples containing these abnormal cells were excluded from the previous data sets (Figs. ##FIG##0##1##, ##FIG##1##2## and ##FIG##2##3##). The presence of squamous basal cells did not correlate with direct laryngoscopy findings (subglottic stenosis 50% vs. tracheal stenosis 100% vs. control 0%; <italic>p</italic> = 0.2) including aspiration, obstructive sleep apnea (OSA), past airway surgery, or current/previous tracheostomy (all <italic>p</italic> &gt; 0.05).</p>", "<p id=\"Par41\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par42\">Our study revealed that the airways of pediatric and adult donors have sufficient regenerative capacity to recellularize an airway scaffold. However, we identified squamous basal cells in a subset of donors and associated their presence with chronic lung disease and tracheostomy in the pediatric population.</p>", "<p id=\"Par43\">The basal cell is the tissue-specific stem cell of the conducting airway epithelium [##REF##20699479##28##]. Common pediatric airway diseases including bronchopulmonary dysplasia [##REF##28067830##29##] and laryngotracheal stenosis [##REF##30503025##30##] can result in epithelial injury from mechanical ventilation, direct trauma, infection, and inflammation. Repeated injury causes selective activation of basal cells [##REF##34546001##17##] and promotes proliferation. These events can lead to terminal differentiation and squamous metaplasia [##REF##15037544##31##–##REF##17965775##33##].</p>", "<p id=\"Par44\">In conditions such as chronic obstructive pulmonary disease (COPD), pathologic remodeling of the airway epithelium includes squamous metaplasia. This condition is likely to be the result of environmental exposures and a chronic inflammatory response and is thought to contribute to poor ciliary function and mucus clearance [##REF##20699479##28##]. Sustained pathogeneic squamous phenotype has been associated with the pathophysiology of tracheobronchial disorders with unknwon etiology, accompanied by recurrent infections, nodules formation, and absence of normal ciliated respiratory epithelium [##REF##35288560##34##]. Squamous metaplasia has also been reported in the proximal airways following intubation and tracheostomy placement. Although the clinical implications of squamous metaplasia remain unclear [##REF##941106##13##], McKeon’s group identified a squamous basal cell subtype that self-renewed and retained its phenotype across multiple passages and after transplantation into immunocompromised mice [##REF##15037544##31##]. We identified similar cells in our cohort and report that they are more prevalent in pediatric patients with bronchopulmonary dysplasia, subglottic stenosis, and those who underwent tracheostomy placement.</p>", "<p id=\"Par45\">The association between bronchopulmonary dysplasia and squamous basal cells requires further study. The observed correlations may be a consequence of direct trauma to the airway during intubation and surgery in combination with free radical changes from prolonged intubation. It is also possible that the squamous metaplasia phenotype is congenitally predisposed in certain pediatric patients, although the relationship was not clearly demonstrated [##REF##941106##13##]. If substantiated, this predisposition would explain why premature patients have significantly higher rates of squamous basal cells compared to their full-term peers [##REF##33302021##35##].</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par48\">Our data suggest that screening high-risk pediatric or adult population based on clinical risk factors and laboratory findings could define appropriate candidates for airway reconstruction with tracheal scaffolds.</p>" ]
[ "<title>Backgorund</title>", "<p id=\"Par1\">Tissue-engineered tracheal grafts (TETG) can be recellularized by the host or pre-seeded with host-derived cells. However, the impact of airway disease on the recellularization process is unknown.</p>", "<title>Methods</title>", "<p id=\"Par2\">In this study, we determined if airway disease alters the regenerative potential of the human tracheobronchial epithelium (hTBE) obtained by brushing the tracheal mucosa during clinically-indicated bronchoscopy from 48 pediatric and six adult patients.</p>", "<title>Results</title>", "<p id=\"Par3\">Our findings revealed that basal cell recovery and frequency did not vary by age or region. At passage 1, all samples produced enough cells to cellularize a 3.5 by 0.5 cm<sup>2</sup> graft scaffold at low cell density (~ 7000 cells/cm<sup>2</sup>), and 43.75% could cellularize a scaffold at high cell density (~ 100,000 cells/cm<sup>2</sup>). At passage 2, all samples produced the number of cells required for both recellularization models. Further evaluation revealed that six pediatric samples (11%) and three (50%) adult samples contained basal cells with a squamous basal phenotype. These cells did not form a polarized epithelium or produce differentiated secretory or ciliated cells. In the pediatric population, the squamous basal cell phenotype was associated with degree of prematurity (&lt; 28 weeks, 64% vs. 13%, <italic>p</italic> = 0.02), significant pulmonary history (83% vs. 34%, <italic>p</italic> = 0.02), specifically with bronchopulmonary dysplasia (67% vs. 19%, <italic>p</italic> = 0.01), and patients who underwent previous tracheostomy (67% vs. 23%, <italic>p</italic> = 0.03).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">In summary, screening high-risk pediatric or adult population based on clinical risk factors and laboratory findings could define appropriate candidates for airway reconstruction with tracheal scaffolds.</p>", "<p id=\"Par5\"><italic>Level of evidence.</italic> Level III Cohort study.</p>", "<title>Graphical Abstract</title>", "<p id=\"Par6\">\n\n</p>", "<title>Keywords</title>" ]
[ "<title>Future directions</title>", "<p id=\"Par46\">The rise of tissue engineering has provided promising techniques with the intention of creating viable tracheal replacement grafts [##REF##27411362##8##, ##REF##28544662##36##, ##REF##29800033##37##]. Successful grafting not only requires an optimal cell source and scaffold for integration but also the appropriate cellular microenvironment for complete epithelialization [##REF##27411362##8##]. Although our data indicate that brush biopsy cells have significant therapeutic potential, a subset of samples contained squamous basal cells that do not regenerate the epithelium. Further studies could determine if cell rejuvenation methods would improve the performance of samples with low-performance metrics.</p>", "<title>Study limitations</title>", "<p id=\"Par47\">We recognize that our understanding of the squamous basal cell phenotype is limited by sample size and that the study may be underpowered to detect smaller effect sizes, particularly those related to tracheal stenosis. We also acknowledge that our cross-sectional study design could be enhanced by a longitudinal study. Finally, we understand that our sampling method may have underestimated the frequency of squamous basal cells in pediatric and adult airways.</p>" ]
[ "<title>Author contributions</title>", "<p>LZ; KS; SR and TC wrote the main manuscript. LZ; NK; KM; JC, LM; AM; SR and TC contributed to the main manuscript. JC; LZ; NK; KM; JS; and CH prepared figures and tables. LZ; NK; KM; CH; JS; JC; LM; AM; SR and TC contributed to the data analysis. KM; CH and JS contributed to experimentation. JC; LM; AM; SR and TC served as scientific advisors. All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published.</p>", "<title>Funding</title>", "<p>National Institutes of Health, Grant/Award Number: NHLBI R01HL157039.</p>", "<title>Availability of data and materials</title>", "<p>Not applicable.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par49\">This study was approved by the institutional review boards of two tertiary-level pediatric and adult hospitals (Nationwide Children’s Hospital IRB STUDY00000847, Ohio State University 2021N0027). Pediatric and adult patients undergoing scheduled direct laryngoscopy and bronchoscopy (DLB) were voluntarily recruited. Demographics of the patients recruited were recorded.</p>", "<title>Consent for publication</title>", "<p id=\"Par50\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par51\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Similar basal cell yield and expansion potential in brush biopsies. <bold>A</bold> Representative immunostaining of cytospin-recovered cells demonstrates positive staining of basal cell markers (K5, green) and (K14, red) in pediatric (p0 <italic>n</italic> = 5, p2 <italic>n</italic> = 3) and adult (p0 <italic>n</italic> = 6, p2 <italic>n</italic> = 4) samples, after brushing from normal (p0 <italic>n</italic> = 6, p2 <italic>n</italic> = 4), and stenotic regions (p0 <italic>n</italic> = 5, p2 <italic>n</italic> = 3) at passage 0 (left panel) and passage 2 (right panel). <bold>B</bold> Bar graph showing the percentage of positive cells over total cell counts (DAPI, blue) count divided by age or <bold>C</bold> region of sample collection. Bars represent mean ± DLB: direct laryngoscopy and bronchoscopy S.D. Statistical analysis was performed using 2-way ANOVA with multiple-comparison test. *<italic>P</italic> &lt; 0.05, **<italic>P</italic> &lt; 0.01, ***<italic>P</italic> &lt; 0.001, ****<italic>P</italic> &lt; 0.0001</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Regenerative capacity of pediatric and adult basal cells. <bold>A</bold> Bar graph represents the Clone-forming Cell Frequency of pediatric and adult basal cells after 1 passage in culture (<italic>n</italic> = 30). <bold>B</bold> Prediction of the number of cells recovered after 1 or 2 passages in culture (<italic>n</italic> = 48) able to cellularize a scaffold at low density (LowD) or high density (HighD). <bold>C</bold> Bar graph of the in vitro population doubling after 1 or 2 passages in culture (p1 <italic>n</italic> = 35, p2 <italic>n</italic> = 35). <bold>D</bold> Relative telomere length of the basal cells of pediatric (<italic>n</italic> = 48), and adult (<italic>n</italic> = 6) donors divided by <bold>E</bold> Normal (<italic>n</italic> = 59) and stenotic (<italic>n</italic> = 18) region. Bars represent mean ± S.D. Statistical analysis was performed using paired, 2-tailed Student’s t-test</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Identification of squamous basal cells. <bold>A</bold> Normal tracheal basal cell colonies under 10x magnification form discrete colonies with distinct edges. Representative immunofluorescence staining demonstrates high levels of K5 (green) and K14 (red), markers associated with airway epithelial stem cells, at low <bold>B</bold> and high <bold>C</bold> magnification. Representative double staining with epithelial cell markers CD151 (α-CD151-APC) and CD49f (α-CD49f-eFlour-450) in normal <bold>D</bold> and stenotic <bold>E</bold> regions. <bold>F</bold> Squamous metaplasia cells under 10x magnification exhibit a diffuse growth pattern and no discrete edges.Representative immunofluorescence staining demonstrates high levels of K5 (green) and K14 (red), markers associated with airway epithelial stem cells, at low <bold>H</bold> and high <bold>I</bold> magnification. Representative double staining with epithelial cell markers CD151 (α-CD151-APC) and CD49f (α-CD49f-eFlour-450) in normal <bold>I</bold> and stenotic <bold>J</bold> regions</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Clinical characteristics of pediatric patients</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Pediatric Patients (<italic>N</italic> = 48)</th></tr></thead><tbody><tr><td align=\"left\">Age (years, [SD])</td><td align=\"left\">3.5 years [3.6]</td></tr><tr><td align=\"left\">Sex</td><td align=\"left\"/></tr><tr><td align=\"left\"> Male</td><td align=\"left\">32 (67%)</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">16 (33%)</td></tr><tr><td align=\"left\">Race</td><td align=\"left\"/></tr><tr><td align=\"left\"> White/Caucasian</td><td align=\"left\">37 (77%)</td></tr><tr><td align=\"left\"> Black/African American</td><td align=\"left\">8 (17%)</td></tr><tr><td align=\"left\"> Multi-racial/Other</td><td align=\"left\">3 (6%)</td></tr><tr><td align=\"left\"> BMI percentile (mean [SD])</td><td align=\"left\">51.6 [35]</td></tr><tr><td align=\"left\">Prematurity (gestational age at birth)</td><td align=\"left\"/></tr><tr><td align=\"left\"> At term</td><td align=\"left\">18 (38%)</td></tr><tr><td align=\"left\"> 32–37 weeks (moderate/late preterm)</td><td align=\"left\">18 (38%)</td></tr><tr><td align=\"left\"> 29–32 weeks (very preterm)</td><td align=\"left\">4 (8%)</td></tr><tr><td align=\"left\"> &lt; 28 weeks (extremely preterm)</td><td align=\"left\">8 (16%)</td></tr><tr><td align=\"left\">Primary clinical indications for DLB</td><td align=\"left\"/></tr><tr><td align=\"left\"> Recurrent croup</td><td align=\"left\">8 (17%)</td></tr><tr><td align=\"left\"> Stridor</td><td align=\"left\">8 (17%)</td></tr><tr><td align=\"left\"> Part of other procedure</td><td align=\"left\">6 (13%)</td></tr><tr><td align=\"left\"> Surveillance following airway surgery</td><td align=\"left\">5 (10%)</td></tr><tr><td align=\"left\"> Aspiration</td><td align=\"left\">5 (10%)</td></tr><tr><td align=\"left\"> Tracheal obstruction/lesion</td><td align=\"left\">4 (8%)</td></tr><tr><td align=\"left\"> Supraglottic obstruction/lesion</td><td align=\"left\">4 (8%)</td></tr><tr><td align=\"left\"> Dysphonia</td><td align=\"left\">4 (8%)</td></tr><tr><td align=\"left\"> Subglottic obstruction/lesion</td><td align=\"left\">3 (6%)</td></tr><tr><td align=\"left\"> Failure to extubate</td><td align=\"left\">1 (2%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Clinical characteristics of adult patients</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Adult Patients (<italic>N</italic> = 6)</th></tr></thead><tbody><tr><td align=\"left\">Age (years, [SE])</td><td align=\"left\">55 years [13.2]</td></tr><tr><td align=\"left\">Sex</td><td align=\"left\"/></tr><tr><td align=\"left\"> Male</td><td align=\"left\">3 (50%)</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">3 (50%)</td></tr><tr><td align=\"left\">Race</td><td align=\"left\"/></tr><tr><td align=\"left\"> White/Caucasian</td><td align=\"left\">3 (50%)</td></tr><tr><td align=\"left\"> Asian</td><td align=\"left\">1 (17%)</td></tr><tr><td align=\"left\"> Other</td><td align=\"left\">2 (33%)</td></tr><tr><td align=\"left\">Primary indication for DL<sup>a</sup></td><td align=\"left\"/></tr><tr><td align=\"left\">Subglottic stenosis</td><td align=\"left\">3 (50%)</td></tr><tr><td align=\"left\">Tracheal stenosis</td><td align=\"left\">2 (33%)</td></tr><tr><td align=\"left\">Control patient<sup>b</sup></td><td align=\"left\">1 (16%)</td></tr><tr><td align=\"left\">History of past airway surgery</td><td align=\"left\">3 (50%)</td></tr><tr><td align=\"left\">Current tracheostomy</td><td align=\"left\">1 (17%)</td></tr><tr><td align=\"left\">Future airway interventions required</td><td align=\"left\">3 (50%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Squamous basal cell phenotype associations with the pediatric population</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Normal Phenotype (<italic>N</italic> = 42)</th><th align=\"left\">Squamous metaplasia (<italic>N</italic> = 6)</th><th align=\"left\">p-value</th></tr></thead><tbody><tr><td align=\"left\">Age (years, [SD])</td><td align=\"left\">3.5 [3.7]</td><td align=\"left\">3.8 [1.2]</td><td char=\".\" align=\"char\">0.86</td></tr><tr><td align=\"left\">Sex</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">&gt; 0.99</td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">22 (52%)</td><td align=\"left\">4 (67%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Female</td><td align=\"left\">14 (48%)</td><td align=\"left\">2 (13%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Race</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.79</td></tr><tr><td align=\"left\"> White/Caucasian</td><td align=\"left\">32 (76%)</td><td align=\"left\">5 (83%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Black/African American</td><td align=\"left\">7 (17%)</td><td align=\"left\">1 (17%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> Multi-racial/Other</td><td align=\"left\">3 (7%)</td><td align=\"left\">0 (0%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> BMI percentile (mean [SE])</td><td align=\"left\">53 [5.3]</td><td align=\"left\">39 [16.6]</td><td char=\".\" align=\"char\">0.36</td></tr><tr><td align=\"left\">Prematurity</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.006**</td></tr><tr><td align=\"left\"> At term</td><td align=\"left\">17 (40%)</td><td align=\"left\">1 (17%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> 32–37 weeks (moderate/late preterm)</td><td align=\"left\">17 (40%)</td><td align=\"left\">1 (17%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> 29–32 weeks (very preterm)</td><td align=\"left\">4 (10%)</td><td align=\"left\">0 (0%)</td><td align=\"left\"/></tr><tr><td align=\"left\"> &lt; 28 weeks (extremely preterm)</td><td align=\"left\">4 (10%)</td><td align=\"left\">4 (67%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Significant pulmonary history</td><td align=\"left\">13 (31%)</td><td align=\"left\">5 (83%)</td><td char=\".\" align=\"char\">0.013**</td></tr><tr><td align=\"left\">Bronchopulmonary dysplasia</td><td align=\"left\">7 (17%)</td><td align=\"left\">4 (67%)</td><td char=\".\" align=\"char\">0.006**</td></tr><tr><td align=\"left\">Significant cardiac history</td><td align=\"left\">0 (0%)</td><td align=\"left\">1 (17%)</td><td char=\".\" align=\"char\">0.008**</td></tr><tr><td align=\"left\">History of previous airway surgery</td><td align=\"left\">11 (26%)</td><td align=\"left\">4 (67%)</td><td char=\".\" align=\"char\">0.045**</td></tr><tr><td align=\"left\">Previous tracheostomy</td><td align=\"left\">9 (21%)</td><td align=\"left\">4 (67%)</td><td char=\".\" align=\"char\">0.02**</td></tr><tr><td align=\"left\"> Previous laryngotracheal reconstruction</td><td align=\"left\">4 (10%)</td><td align=\"left\">2 (33%)</td><td char=\".\" align=\"char\">0.099</td></tr><tr><td align=\"left\"> Previous balloon dilation</td><td align=\"left\">6 (14%)</td><td align=\"left\">2 (33%)</td><td char=\".\" align=\"char\">0.24</td></tr><tr><td align=\"left\"> Findings on DLB<sup>a</sup></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Subglottic stenosis</td><td align=\"left\">7 (17%)</td><td align=\"left\">3 (50%)</td><td char=\".\" align=\"char\">0.06</td></tr><tr><td align=\"left\"> Tracheal stenosis</td><td align=\"left\">1 (2%)</td><td align=\"left\">1 (17%)</td><td char=\".\" align=\"char\">0.10</td></tr><tr><td align=\"left\"> Laryngomalacia</td><td align=\"left\">4 (10%)</td><td align=\"left\">0 (0%)</td><td char=\".\" align=\"char\">0.43</td></tr><tr><td align=\"left\"> Vocal cord nodules</td><td align=\"left\">3 (7%)</td><td align=\"left\">0 (0%)</td><td char=\".\" align=\"char\">0.50</td></tr><tr><td align=\"left\"> Average Relative Telomere Length [SE]</td><td align=\"left\">3.0 [1.5]</td><td align=\"left\">3.2 [1.9]</td><td char=\".\" align=\"char\">0.95</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>DLB</italic> direct laryngoscopy and bronchoscopy</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>DL direct laryngoscopy</p><p> <sup>b</sup>Surgery was for Zenker’s diverticulum repair. Tracheal brushing obtained as a control patient</p></table-wrap-foot>", "<table-wrap-foot><p>Univariate analyses were conducted, and statistically significant predictors were calculated with <italic>p</italic>&lt;0.05 and marked (**)</p><p><sup>a</sup>DLB: direct laryngoscopy and bronchoscopy</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["6."], "surname": ["Grillo"], "given-names": ["HC"], "source": ["Surgery of the Trachea and Bronchi"], "year": ["2004"], "publisher-name": ["BC Decker"]}, {"label": ["32."], "surname": ["Reynolds", "Hill", "Alsudayri", "Lallier", "Wijeratne", "Tan", "Chiang", "Cormet-Boyaka"], "given-names": ["SD", "CL", "A", "SW", "S", "ZH", "T", "E"], "article-title": ["Assemblies of JAG1 and JAG2 determine tracheobronchial cell fate in mucosecretory lung disease"], "source": ["JCI Insight"], "year": ["2022"], "volume": ["7"], "fpage": ["15"], "pub-id": ["10.1172/jci.insight.157380"]}]
{ "acronym": [], "definition": [] }
37
CC BY
no
2024-01-14 23:43:47
Respir Res. 2024 Jan 12; 25:28
oa_package/1e/7c/PMC10787461.tar.gz
PMC10787462
38216971
[ "<title>Background</title>", "<p id=\"Par5\">Asthma is one of the most common respiratory ailments worldwide [##UREF##0##1##]. It was estimated in 2019 that asthma affected 262 million people and caused 461,000 deaths [##UREF##1##2##]. In recent decades there has been a significant increase in the prevalence of asthma worldwide. According to the <italic>Global Burden of Disease</italic> study in 2015, between 1990 and 2015 the prevalence of the illness increased by 12% [##REF##28822787##3##].</p>", "<p id=\"Par6\">Asthma is manifested by bronchial hyper-response and variable obstruction of the air flow, which may be partially or totally reversible [##UREF##0##1##]. Its main symptoms are cough, wheezing, shortness of breath, pressure in the chest, and a limitation in the flow of expired air [##UREF##2##4##]. As it is a chronic illness, the aim in treatment is to reach and maintain control of the pathology and prevent future risk, especially of exacerbation, which may be life-threatening to the patient [##UREF##0##1##, ##UREF##2##4##].</p>", "<p id=\"Par7\">Despite widespread knowledge of the illness and of the available therapeutic options, asthmatic patients show poor control of the illness in 50% of cases [##UREF##3##5##]. Because of this, symptoms may be persistent and may include constant exacerbations that present a great future risk [##REF##15241342##6##, ##UREF##4##7##]. In part, poor control of the illness may be due to a lack of adherence and therapeutic compliance, to environmental exposures, and to poor control of comorbidities that directly affect asthma such as obesity, chronic sinusitis, allergic rhinitis, gastro-esophageal reflux, anxiety, and depression [##UREF##0##1##, ##UREF##5##8##].</p>", "<p id=\"Par8\">In recent years there has been an increase in the demand for telemedicine in combination with or as an alternative to face-to-face clinical care [##UREF##0##1##]. This has led to the creation and management of new models of patient care [##UREF##2##4##, ##UREF##6##9##]. Follow-up and monitoring control of patients with asthma in accordance with evidence-based recommendations must include in assessment a monitoring of symptoms and acute incidents, continuous assessment of causative agents and comorbidities that have an impact on control of the illness, changes in pulmonary function, the side effects of treatment, and, finally, the ability of patients to carry out personalized and predesigned action plans [##UREF##0##1##, ##UREF##2##4##, ##UREF##6##9##].</p>", "<p id=\"Par9\">Recent studies have highlighted the great potential of mobile applications to improve self-care of patients with asthma, as an efficient way to offer and share information, in addition to being of low cost and easily accessible to the population [##UREF##7##10##–##UREF##8##12##]. Despite this, owing to the diversity of interventions and their results in recent years, there is a lack of consensus regarding the type of intervention best suited to asthmatic patients and the tools needed to improve control of their illness [##UREF##7##10##–##UREF##10##15##].</p>", "<p id=\"Par10\">For this reason, the present project has set out to develop and use a telemedicine tool for global management of patients with asthma, in order to improve adherence to treatment, increase control of the illness, empower the patients, personalize their care, and increase the efficiency of the circuit, thereby improving the quality of care.</p>" ]
[ "<title>Method</title>", "<title>Design</title>", "<p id=\"Par12\">A simple-blind randomized clinical trial will be carried out, with 52 weeks of follow-up of patients with asthma. The study will have two arms: the control cohort will receive normal care, while the intervention group will additionally have access to the mobile application (ESTOI).</p>", "<title>Setting and subjects</title>", "<p id=\"Par13\">The study will be carried out in the pneumology service of the Bellvitge University Hospital in Barcelona, during the period 2023–2025. The participants will be asthmatic patients seen for the first time in the hospital out-patient clinic who fulfill the following selection criteria (Table ##TAB##0##1##).\n</p>", "<title>Calculation of the sample</title>", "<p id=\"Par14\">In order to calculate the sample size, a screening of 60 patients seen in the pneumology unit of the center was made with the ACT questionnaire, in order to learn the degree of current control of the asthma of those patients.</p>", "<p id=\"Par15\">With a CI of 95% and a standard deviation of 4.95, the average ACT score of the patients seen in our center was 18.43 ± 1.25. The calculation of the sample size was based upon the established aims. We used the Granmo 7.12 program for two independent averages, accepting an alpha risk of 0.05 and a beta risk of 0.2 in bilateral contrast. Some 54 subjects were determined to be needed for each group in order to detect a difference equal to or greater than 3 units in the ACT questionnaire [##UREF##11##16##, ##UREF##12##17##]. We assumed a common standard deviation of 4.95 (obtained by screening in our center) and calculated a rate of loss in follow-up of 20%.</p>", "<title>Sampling technique</title>", "<p id=\"Par16\">The patients will be included in the study by means of accidental probabilistic sampling. Assignment of the intervention to be carried out will be randomly made, according to a randomization grid designed using the software of random.org [##UREF##13##18##].</p>", "<title>Variables</title>", "<p id=\"Par17\">The main variable of the study will be ACT. Evaluation will be made of the participants in both groups, at the beginning of follow-up, at 6 months, and at 12 months. The results obtained will be compared. In addition, sociodemographic variables will be collected, such as age, sex, education level, and experience in the use of mobile applications. The study variables are detailed in Table ##TAB##1##2##.\n</p>", "<title>Procedure and instruments</title>", "<p id=\"Par18\">The project will be structured in three visits (Fig. ##FIG##0##1##, Flow chart).</p>", "<p id=\"Par19\">At the first visit, all of the participants will be seen by the out-patient pneumology unit for classification of their asthma, renewal of their inhalers, and preparation of orders for complementary tests. Following this, the control group will receive instructions provided by a nurse specialized in asthma concerning the illness, the treatment to follow, signs to watch out for, plan of action, and a review of the triggers of the illness. Meanwhile, the patients from the intervention group, in addition to this instruction, will also be included in the database of the ESTOI application and will be provided access to the patient homepage, where they may find all the information needed for the management of their asthma. Both groups will be provided with a Peak Flow device and will receive instruction on how to use it and record the results in a diary.</p>", "<p id=\"Par20\">At the conclusion of the first visit, all of the participants will be given an appointment for a second visit as well as a contact phone number to resolve any questions that may arise.</p>", "<p id=\"Par21\">At the conclusion of the third visit, the intervention group will complete a questionnaire to determine their satisfaction with the app that they used.</p>", "<p id=\"Par22\">All of the relevant data from the study will be collected in the case report form of each patient for subsequent analysis. The case report forms will be housed in the medical center in a locked room to which only the research team will have access.</p>", "<p id=\"Par23\">At each of the three visits in the study, the nurse specialized in asthma will be responsible for compiling the study questionnaires (ACT, TAI, AQLQ, and HADS) of all the patients, reviewing the records of withdrawal from medication, carrying out a FeNO test, doing spirometry with bronchodilator, ordering bloodwork, and making on-site PEF measurement. All of the data will be duly recorded in the case report forms.</p>", "<p id=\"Par24\">A nurse trained in telemedicine will be in charge of the management and monitoring of the patients using the application. The nurse will also be responsible for making appointments, reviewing the clinical records of all the patients included in the study, and managing the case report and informed consent forms. The nurse specialized in asthma will be responsible for administering the questionnaires, collecting the case report form data, and the carrying out of the blood tests and pulmonary function testing.</p>", "<title>ESTOI application for the management of asthmatic patients</title>", "<p id=\"Par25\">The mobile application ESTOI, created and managed by the research team of this study, is designed to provide, in a personalized manner, all of the tools normally used in a hospital for the management and control of asthma. ESTOI has a number of components that may be managed and modified by the researchers in response to the needs of each patient. It is available for both Android and IOS devices.</p>", "<p id=\"Par26\">In the first component, ‘CONTROL OF SYMPTOMS’, the participants respond to questions about their health that are designed in a personalized manner in order to learn of their current asthma state. Each month the ACT, TAI, number of exacerbations, and weight will be recorded, as well as, depending on the case, data on the control of symptoms of rhinitis, nasal polyposis, RGE, allergies, and smoking habit, if any. Depending on the results obtained from the questionnaire, the patient will be given recommendations or alerts in accordance with the seriousness of their situation, and the application will automatically alert the medical team when a serious worsening in control of the illness is detected, so as to allow for management of the situation and avoidance of future risk.</p>", "<p id=\"Par27\">In the second component, ‘HEALTH RECOMMENDATIONS’, all of the information that the patient needs to manage the pathology is shown, including how to control it and what to do in the event of a worsening of the symptoms. The recommendations that appear in this component will depend on the patient’s state and comorbidities; only information appropriate to the current state of the patient will be available to him or her.</p>", "<p id=\"Par28\">In the third component, ‘YOUR TREATMENT’, appears up-to-date, personalized information concerning current medication used by the patient to treat asthma, the dosage and times to take the medication, and, in the case of inhalers and biological therapy, a video explaining how they are to be administered. This component also includes the plan of action, showing the medication to be taken by the patient in the event of a worsening of the asthma, as well as in the event of an emergency. Both the treatment and the plan of action will be reviewed and modified, if necessary, at each patient visit to pneumology.</p>", "<p id=\"Par29\">In the fourth component, ‘PEAK FLOW’, the patient can record the measurements made using the Peak Flow Meter at home. The peak flow is calculated automatically in order to reveal whether there have been significant changes in the values for pulmonary function, so that treatment can be modified and adjusted to current needs without the need for the patient to visit a medical center.</p>", "<p id=\"Par30\">The fifth component, ‘NUTRITIONAL PLAN’, provides a guide to daily foods so that the individual may adapt the tools and advice to his or her needs.</p>", "<p id=\"Par31\">The sixth and final component, ‘MESSAGING’, provides for two-way communication between the participants and the members of the specialized asthma medical team, allowing for additional information to be provided and for questions to be answered.</p>", "<title>Analysis of the data</title>", "<p id=\"Par32\">The continuous variables are expressed as mean and standard deviation in case of normal distribution, and median and interquartile range in case of non-normal distribution. The qualitative variables are to be defined as frequencies and percentages. For comparison of the continuous variables the variance analysis method (ANOVA) or the Kruskal-Wallis test will be used. For analysis of the main assessment, the Chi-squared test will be used. Stepwise logistic regression models will be used to select the subgroup with parameters significantly associated with poor control of asthma. A priori, the factors to be included in the analysis are age, number of years suffering asthma, education level, IMC, smoking, environmental exposures, pre-BD FEV1, post-BD FEV1, FeNO, blood eosinophils, general and specific blood IgE, ACT, TAI, HAD, AQLQ, number of exacerbations, and control of comorbidities that affect asthma (GERD, rhinitis, nasal polyposis, overweight/obesity, and smoking). Statistical significance will be set at <italic>p</italic> &lt; 0.05.</p>" ]
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[ "<title>Discussion</title>", "<p id=\"Par33\">The present study represents an attempt to improve control of the illness, the quality of life of the patients at our center, and their adherence to the treatment for asthma, using telemedicine as the main tool, in combination with normal care. There is scientific evidence that carrying out more continuous follow-up of patients increases their knowledge of the pathology and of how to monitor it, improves communication between patient and professional, and personalizes resources in accordance with the needs of the individual, thereby empowering the patient to achieve greater control of his or her asthma [##UREF##0##1##, ##UREF##7##10##, ##REF##27880049##11##]. It has also been demonstrated that keeping the main comorbidities (allergies, obesity, rhinitis, nasal polyposis, GERD, and stress) under control is essential to improving the health of the patient with asthma [##UREF##0##1##, ##UREF##2##4##].</p>", "<p id=\"Par34\">There is at present a varied typology of interventions based on telemedicine to achieve improved management of the illness. The most frequently used, in terms of channel of communication, are online chats and meetings [##REF##27475032##26##, ##REF##28034579##27##], mobile applications [##REF##27489790##28##–##UREF##17##32##], SMS [##UREF##18##33##, ##REF##30063840##34##], and websites [##REF##30063840##34##–##UREF##20##36##]. In terms of content, they are remote monitoring by means of questionnaires and collecting of spirometric data [##REF##27489790##28##–##REF##30063840##34##], remote consulting with the health center by means of the tool [##REF##27475032##26##–##REF##27037722##29##, ##UREF##18##33##], and distance learning [##REF##27475032##26##, ##REF##28034579##27##, ##UREF##16##30##, ##UREF##17##32##, ##UREF##18##33##, ##UREF##19##35##, ##UREF##20##36##]. Of note, there are studies that focus on a single sphere of content, while others include more than one. The study that we are presenting here includes several of these interventions.</p>", "<p id=\"Par35\">In several studies telemedicine was used as a tool for controlling asthma and improving the quality of life of the users [##REF##27475032##26##–##UREF##20##36##]. However, it is difficult to establish standards for the content of an application for asthma given the diversity of the interventions and the variability of the results obtained from them [##REF##30055283##37##].</p>", "<p id=\"Par36\">In the studies that we analyzed it was demonstrated that interventions that used a mobile application to provide information to participants regarding inhaled therapy and a personalized plan of action improved control of the illness and adherence to treatment [##REF##27037722##29##, ##UREF##17##32##]. In contrast, in those studies not making using of a mobile application, but rather a website or SMS, the improvements were not significant, nor were there clinical benefits [##REF##30063840##34##–##UREF##20##36##]. Another point to make note of is that applications that include reminders sent by SMS, both for taking medication and for completing questionnaires, showed a much higher level of compliance than did the interventions that did not include reminders [##REF##27475032##26##, ##REF##30063840##34##]. Nemanic T et al. achieved a participant compliance level of 80% with ACT and 96% with PEF thanks to SMS reminders [##REF##30063840##34##].</p>", "<p id=\"Par37\">In terms of communication between the patient and the professionals, the applications that allowed the patient to maintain direct contact with the healthcare professionals achieved improved asthma self-management [##REF##28034579##27##, ##REF##27037722##29##]. They also produced a reduction in daytime symptoms, number of hospitalizations, and visits to the emergency room.</p>", "<p id=\"Par38\">Our intervention has sought to draw together elements from all the interventions that have achieved significant results and assemble them in a personalized application with which the patient will have available all the information needed to improve control over the illness, and through which the healthcare team can intervene in a much more efficient manner.</p>", "<title>Ethical considerations</title>", "<p id=\"Par39\">The study is in compliance with the principles of the Helsinki Declaration, and it was approved by the Ethical Committee of the Bellvitge University Hospital (reference ICPS023/22). The personal data obtained will be confidential (Organic Law 3/2018, December 5, governing protection of personal data and the guarantee of digital rights) which supersedes Organic Law 15/1999, December 5, on the protection of personal data, and by extension, in the UE (General Regulation (UE) 2016/679 on the protection of data). Total confidentiality of the data obtained is guaranteed by the assignment of an identification number to each patient and by the creation of a database specific to this study in which data will be included in an encoded format.</p>", "<p id=\"Par40\">All of the tests carried out by the patients in the present protocol are part of normal clinical practice in the treatment of patients with asthma. Therefore, participation in the study does not represent any additional risk to that associated with the normal care provided to asthmatic patients.</p>", "<p id=\"Par41\">The data collected for this study will be encoded and only the principal investigator of the study and his collaborators will be able to associate the data with the medical history of the patients. Therefore, the identity of the patients will not be revealed to anyone except in the event of a medical emergency or legal requirement thereof.</p>", "<p id=\"Par42\">Access to the personal information shall remain limited to the principal investigator of the study and his collaborators, as well as to the clinical research ethical committee when required to verify data and study procedures, at all times respecting the confidentiality of the data in accordance with the applicable legislation.</p>", "<title>Limitations</title>", "<p id=\"Par43\">As this is a single-center study, the results may not be representative of the general population, which limits our ability to extrapolate the findings to different clinical settings. In an attempt to offset this limitation, and to ensure that the results are as extrapolable as possible, we will use the standards laid out in the Spanish Guide for the Management of Asthma (GEMA) [##UREF##0##1##]. To learn the degree of control of the illness we will take into account the number of exacerbations suffered in the past year, the asthma symptoms measured with ACT [##REF##19240948##19##], and pulmonary function, using as measuring tools the PEF and the FEV1. With the aim of determining the degree of adherence to treatment we will use the TAI questionnaire and will review the electronic history of withdrawal from prescribed medication [##UREF##0##1##, ##REF##26230150##20##]. For quality of life, we will make recourse to the AQLQ and the HAD [##REF##7788082##21##, ##UREF##14##22##].</p>", "<p id=\"Par44\">Given that the proposed intervention has simple masking, the research team and the clinical staff will be aware at all times which patients belong to which group, and this could influence the behavior of the staff as well as the manner in which the results are evaluated. As a result of randomization, it may be difficult to ensure that the groups are completely comparable in all areas.</p>", "<p id=\"Par45\">Another limitation to bear in mind is the time stipulated for follow-up, which is limited and which may impede assessment of the effectiveness of the telemedicine program over the long-term in the control of asthma.</p>", "<p id=\"Par46\">Finally, the participants may not comply completely with the recommendations made to them, or they may abandon the study prematurely, which would cause skewing in the results and render assessment of the real effectiveness of the telemedicine program in the control of asthma difficult. In addition, assessment of the control of asthma often involves subjective measurement of symptoms and quality of life, which could be influenced by the individual perception of the participants.</p>" ]
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[ "<title>Background</title>", "<p id=\"Par1\">Asthma is one of the most common respiratory ailments worldwide. Despite broad understanding of the illness and of the available therapeutic options for it, patients with serious asthma suffer poor monitoring of their illness in 50% of cases.</p>", "<title>Aim</title>", "<p id=\"Par2\">To assess the impact of the implementation of a mobile application (ESTOI) to control asthma in patients diagnosed with the illness, their adherence to treatment, and their perceived quality of life.</p>", "<title>Methodology</title>", "<p id=\"Par3\">Randomized clinical trial with 52 weeks’ follow-up of patients with asthma seen in a specialized hospital for their treatment in Spain. Some 108 included patients will be divided into two groups. The intervention group will undergo more exhaustive follow-up than normal, including access to the ESTOI application, which will have various categories of attention: control of symptoms, health recommendations, current treatment and personalized action plan, PEF record, nutritional plan, and chat access with a medical team. The asthma control questionnaire ACT is the main assessment variable. Other variables to be studied include an adherence test for the use of inhalers (TAI), the number of exacerbations, maximum exhalation flow, exhaled nitric oxide test, hospital anxiety and depression scale, asthma quality-of-life questionnaire, forced spirometry parameters (FVC, FEV1, and PBD), and analytic parameters (eosinophilia and IGE). The data will be collected during outpatient visits.</p>", "<title>Trial registration</title>", "<p id=\"Par4\">This trial has registered at ClinicalTrials.gov (Identifier: NCT06116292).</p>", "<title>Keywords</title>" ]
[ "<title>Aim</title>", "<p id=\"Par11\">The aim of the present study is to assess the impact of the implementation of a mobile application (ESTOI) to control asthma in patients diagnosed with the illness, their adherence to treatment, and their perceived quality of life.</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Authors’ contributions</title>", "<p>Study conception: HCC; MME; EMGC. Project design: HCC; MME; EMGC. Writing of the work: HCC; EMGC; AMRO. Review: NF; AMRO; SS. All authors approve the submitted version and take responsibility for their own contributions.</p>", "<title>Funding</title>", "<p>This project received a grant in 2022 from the Colegio Oficial de Enfermeros de Barcelona [Official Nurses’ Association of the Province of Barcelona] (COIB) with project number 578/2022. The study protocol has undergone peer-review by founding body.</p>", "<title>Availability of data and materials</title>", "<p>No datasets were generated or analysed during the current study.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par47\">The study was approved by the Ethical Committee of the Bellvitge University Hospital (reference ICPS023/22) with the version V1.1, 02/05/22. It is confirmed that the informed consent of the patients and/or their legal guardian will be obtained prior to participating in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par48\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par49\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow chart CG: Control group; IG: Intervention group; BDR: Bronchodilator responsiveness</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Key inclusion, exclusion, and withdrawal criteria</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td colspan=\"2\">Key inclusion criteria</td></tr><tr><td colspan=\"2\"><p>• Age ≥ 18 years with a diagnosis of asthma based on GEMA 5.2, 2022 [##UREF##0##1##]</p><p>• Patients seen in the pulmonology service of the center.</p><p>• Patients who have not previously received asthma education.</p><p>• Capable of giving signed informed consent.</p></td></tr><tr><td colspan=\"2\">Key exclusion criteria</td></tr><tr><td colspan=\"2\"><p>• Patient does not have a mobile device with Android or IOS system.</p><p>• Lack of minimum technological knowledge for the use of the application (ESTOI).</p><p>• People participating or have participated in a clinical trial in the last 6 months.</p><p>• Patients diagnosed with other respiratory diseases except for obstructive sleep apnea (OSA), Asthma-COPD overlap syndrome (ACOS).</p><p>• Patient with palliative or severe chronic illness that limits life expectancy.</p></td></tr><tr><td colspan=\"2\">Key withdrawal criteria</td></tr><tr><td colspan=\"2\"><p>• Voluntary withdrawal from the study by the patient.</p><p>• Lost to follow-up.</p><p>• Death of the patient.</p></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Study variables</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th>Variable</th><th>Description</th><th>When will it be used?</th></tr></thead><tbody><tr><td><bold>Asthma Control Test (ACT)</bold></td><td>ACT is a 5-item questionnaire that assesses the level of control of asthma symptoms during the previous 4 weeks [##REF##19240948##19##].</td><td><p>CG at each visit (v1, v2, v3)</p><p>IG once a month (using the ESTOI app) and at each visit of the study (V1, V2, V3)</p></td></tr><tr><td><bold>Test of the Adherence to Inhalers (TAI)</bold></td><td>TAI is a 12-item questionnaire that assesses adherence to inhalers for patients with Asthma or COPD [##REF##26230150##20##].</td><td><p>CG at each visit (v1, v2, v3)</p><p>IG once a month (using the ESTOI app) and at each visit of the study (V1, V2, V3)</p></td></tr><tr><td><bold>Asthma Quality of Life Questionnaire (AQLQ)</bold></td><td>AQLQ is a 32-item questionnaire that assesses the quality of life of patients with asthma. Covers 4 dimensions (breathlessness, mood, social limitation and worrying) [##REF##7788082##21##].</td><td>Both groups (IG and CG) at each visit (V1, V2, V3)</td></tr><tr><td><bold>The Hospital Anxiety and Depression Scale (HADS)</bold></td><td><p>HADS is a questionnaire for detecting affective disorders in hospital settings with outpatients.</p><p>Is frequently used to evaluate populations with chronic diseases [##UREF##14##22##].</p></td><td>Both groups (IG and CG) at each visit (V1, V2, V3)</td></tr><tr><td><bold>Blood eosinophil count</bold></td><td>Eosinophils are actively involved in diseases caused by parasites and in allergic reactions. In the case of asthma, having eosinophils in range is usually an indicator of good control [##UREF##2##4##].</td><td>Both groups (IG and CG) at V1 and V3</td></tr><tr><td><bold>Immunoglobulin E (IgE)</bold></td><td>IgE is an antibody involved in airway inflammation and allergic reactions. It plays an essential role in modulating severity as a direct association between IgE concentrations and increased disease severity, bronchial hyperresponsiveness and reduced lung performance [##UREF##2##4##].</td><td>Both groups (IG and CG) at V1 and V3</td></tr><tr><td><bold>Exacerbation</bold></td><td>In asthma an exacerbation is considered a worsening of asthma symptoms that requires medical intervention and has at least 1 of the following 3 elements listed below for at least 2 consecutive days: Worsening of asthma signs/symptoms (dyspnea, wheezing, nocturnal awakenings, or chest tightness), increased use of rescue medication or deterioration of lung function [##UREF##0##1##].</td><td><p>CG at each visit (v1, v2, v3)</p><p>IG once a month (using the ESTOI app) and at each visit of the study (V1, V2, V3)</p></td></tr><tr><td><bold>Peak Expiratory Flow (PEF)</bold></td><td>PEF is the highest airflow achieved in a forced expiration after an also forced inspiration, measured using a Peak Flow Meter. It is used as a predictor of airway obstruction [##REF##15516464##23##].</td><td>Both groups (IG and CG) once a week (using the ESTOI app in case of IG) and at each visit of the study (V1, V2, V3)</td></tr><tr><td><bold>Forced vital capacity (FVC)</bold></td><td>FVC is the total volume of air that can be exhaled during a maximum effort of forced expiration without a time limit [##REF##16264058##24##].</td><td>Both groups (IG and CG) at each visit (V1, V2, V3)</td></tr><tr><td><bold>Forced expiratory volume in one second (FEV1)</bold></td><td>FEV1 is the volume of air exhaled in the first second under force after a maximal inhalation [##REF##16264058##24##].</td><td>Both groups (IG and CG) at each visit (V1, V2, V3)</td></tr><tr><td><bold>Bronchodilator Responsiveness (BDR)</bold></td><td>BDR determines the degree of airflow improvement after the administration of a Beta-2 adrenergic agonist. The test is considered positive when there is an increase from baseline values of FEV1 by at least 12% and 200 mL [##REF##16264058##24##].</td><td>Both groups (IG and CG) at each visit (V1, V2, V3)</td></tr><tr><td><bold>Fractional exhaled nitric oxide (FeNO)</bold></td><td>FeNO is a useful and noninvasive biomarker for eosinophilic airway inflammation, particularly in asthma [##UREF##15##25##].</td><td>Both groups (IG and CG) at each visit (V1, V2, V3)</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>CG</italic> Control group, <italic>IG</italic> Intervention group</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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37
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2024-01-14 23:43:47
BMC Pulm Med. 2024 Jan 13; 24:32
oa_package/86/d9/PMC10787462.tar.gz
PMC10787463
38216888
[ "<title>Introduction</title>", "<p id=\"Par2\">Ginseng (<italic>Panax ginseng</italic> C. A. Meyer) is an important medicinal plant that has been widely studied in recent years [##UREF##0##1##, ##REF##32517049##2##]. Ginsenosides are secondary metabolites and the main bioactive compounds that have medicinal value in ginseng [##REF##37575919##3##]. Elicitors act as specific signals that induce the expression of target genes in cells, thereby regulating the synthesis of secondary metabolites in plant cells [##REF##22459758##4##]. Methyl jasmonate (MeJA) is a volatile organic compound involved in plant defence and many different developmental processes, such as root growth, seed germination, fruit ripening, flowering and plant ageing [##REF##32172764##5##]. It acts as an interplant signalling molecule that activates defence genes encoding proteins and secondary compounds (such as anthocyanins and alkaloids) [##REF##32602544##6##]. The addition of exogenous MeJA has also been shown to increase the production of terpenoids in ginseng [##UREF##1##7##]. Due to its good and stable induction effect, MeJA has become one of the most commonly used inducers in the study of the ginsenoside synthesis pathway. In our study, MeJA was selected as an additional inducer to regulate ginsenoside biosynthesis.</p>", "<p id=\"Par3\">The TEOSINTE BRANCHED1, CYCLOIDEA, and PCF (TCP) transcription factor gene family, containing plant-specific transcription factors [##REF##31340456##8##], is widely involved in regulating plant seed germination [##REF##31325184##9##], axillary meristem development [##REF##17307924##10##–##REF##26119747##12##], flower organ development [##REF##26157444##13##], leaf morphogenesis [##UREF##3##14##], hormone signalling [##REF##30266918##15##], and the synthesis of secondary metabolites [##REF##24118612##16##–##REF##33931613##18##]. TCP was first discovered in the 20th century in three species: teosinte Branched1 (TB1) from maize (<italic>Zea Mays</italic>) [##REF##9087405##19##], CycloidEA (Cyc) from goldenseal [##REF##8893002##20##], and proliferative cytokine (PCF) from rice (<italic>Oryza sativa</italic>) [##REF##9338963##21##]. These gene family members all have a conserved TCP domain and a basic helix-loop-helix (bHLH) structure, which is mainly associated with DNA binding, protein interactions, and protein nuclear localization [##REF##10363373##22##]. Based on the characteristics of the conserved structural domains of TCP proteins, they can be further divided into class I (also known as PCF) and class II (including the CIN and CyC/Tb1 subfamilies) [##REF##19963426##23##].</p>", "<p id=\"Par4\">Some <italic>TCP</italic> gene family members can participate in the regulation of secondary metabolite synthesis in plants [##REF##35068346##24##]. Current studies on <italic>TCP</italic> and secondary metabolism mainly focus on transcriptome analysis [##REF##34343346##25##]. Li et al. studied miRJAW-resistant <italic>AtmTCP3</italic> transgenic plants and <italic>AtTCP3SRDX</italic> mutant plants with an inactivated <italic>AtTCP3</italic> gene [##REF##24118612##16##] and found that the seedlings and seeds of <italic>AtmTCP3</italic> plants had excessive accumulation of flavonols, anthocyanins and proanthocyanidins, while the levels of proanthocyanidins in <italic>TCP3SRDX</italic> plants decreased slightly. In addition, the R2R3-MYB protein activated late flavonoid biosynthesis genes by forming the terpolymer R2R3-MYB/bHLH (TCP3)/WD40 (MBW) complex, indicating that <italic>TCP</italic> can promote flavonoid biosynthesis. The <italic>TCP</italic> gene family has been extensively studied in other species, such as <italic>Arabidopsis</italic> [##REF##10363373##22##], rice [##REF##31002981##26##], cotton [##REF##30266918##15##], chrysanthemum [##REF##31569563##27##], soybean [##UREF##4##28##], tomato [##REF##24903607##29##], ginkgo [##REF##35068346##24##], bamboo shoots [##REF##35620688##30##], grapes [##REF##31664916##31##], Dendrobium [##REF##34638610##32##], orchids [##REF##26531864##33##], and ginseng [##REF##34472257##34##]. However, this gene family has not been screened for candidate genes involved in ginsenoside biosynthesis.</p>", "<p id=\"Par5\">In this study, 78 <italic>PgTCP</italic> transcripts under 28 <italic>PgTCP</italic> gene IDs were identified from the transcriptome database of ginseng and classified according to their domain information (CIN, PCF, and CYC/TB1). Then, we analysed the evolutionary relationships and conserved motifs of the <italic>PgTCP</italic> gene family, annotated them with GO function, and analysed expression patterns and coexpression networks based on PgTCP gene expression data. Then, the response of <italic>PgTCP</italic> gene family members to different treatment times of methyl jasmonate (MeJA) was explored. Finally, we identified a gene that was significantly related to ginsenoside biosynthesis.</p>" ]
[ "<title>Materials and methods</title>", "<title>Identification of the <italic>TCP</italic> gene family in ginseng</title>", "<p id=\"Par6\">To ensure the completeness and accuracy of the <italic>TCP</italic> gene family, we used different methods to identify the <italic>TCP</italic> gene family. First, the Jilin Ginseng Transcriptome Database [##UREF##5##35##] was used as a query sequence for searching ginseng <italic>TCP</italic> transcripts with an e value of 1 × 10<sup>–6</sup>. Second, the hidden Markov model (HMM) of <italic>TCP</italic> genes was downloaded from Pfam (Pfam ID: PF03634), and potential <italic>TCP</italic> genes were identified from the Jilin ginseng transcriptome database using HMMER (<ext-link ext-link-type=\"uri\" xlink:href=\"http://HMMER.janelia.org\">http://HMMER.janelia.org</ext-link>) with an <italic>E-value</italic> of 1.0E-06. Finally, TCP amino acid sequences were downloaded from the Plant Transcription Factor Database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://planttfdb.gao-lab.org/family.php?fam=TCP\">http://planttfdb.gao-lab.org/family.php?fam=TCP</ext-link>) as BLAST query sequences and use to search the Jilin ginseng transcriptome database. The results of the three methods were then combined, and duplicates were removed. The results were submitted to iTAK (<ext-link ext-link-type=\"uri\" xlink:href=\"http://itak.feilab.net/cgi-bin/itak/index.cgi\">http://itak.feilab.net/cgi-bin/itak/index.cgi</ext-link>) to exclude some spurious sequences. Finally, NCBI CD-Search (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ncbi.nlm.nih.gov/Stru-cture/cdd/wrpsb.cgi\">http://www.ncbi.nlm.nih.gov/Stru-cture/cdd/wrpsb.cgi</ext-link>) and SMART online tool (<ext-link ext-link-type=\"uri\" xlink:href=\"https://smart.embl.de/\">https://smart.embl.de/</ext-link>) were used to confirm the presence of the candidate gene transcripts in TCP conserved structural domains, and transcripts containing TCP conserved structural domains were selected and defined as <italic>PgTCP</italic> gene transcripts. Arabic numbers were added to <italic>PgTCP</italic>, e.g., <italic>PgTCP01</italic>, to indicate different gene serial numbers. A suffix (e.g., -01) was used to indicate different transcripts. The online software ExPASy-Prot Param tool (<ext-link ext-link-type=\"uri\" xlink:href=\"https://web.ExPASy.org/protparam/\">https://web.ExPASy.org/protparam/</ext-link>) was used to predict the basic physicochemical properties of the PgTCP proteins, including theoretical molecular weights (kDa) and isoelectric points (PI).</p>", "<title>Phylogenetic analysis, conserved domain and motif analysis of <italic>PgTCP</italic> transcripts</title>", "<p id=\"Par7\">To classify the <italic>PgTCP</italic> transcripts, we compared the 67 <italic>PgTCP</italic> transcripts with complete TCP structural domains with three other species. Dicots, monocots, and model plants were selected as outgroup species, and nine <italic>TCP</italic> genes of three species, <italic>Oryza sativa</italic> (<italic>Os</italic>), <italic>Arabidopsis thaliana</italic> (<italic>At</italic>), and <italic>Solanum lycopersicum</italic> (<italic>Sl</italic>), which were downloaded from NCBI for phylogenetic analysis with <italic>PgTCP</italic> genes. Phylogenetic trees were constructed using the maximum likelihood (ML) method in MEGA-X [##REF##27004904##36##], and bootstrap replicates were set to 2000. The final evolutionary trees were edited using the Evolview version 3.0 online website (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.evolgenius.info/evolview/#login\">https://www.evolgenius.info/evolview/#login</ext-link>) [##REF##31114888##37##]. We performed conserved motif analysis using MEME (<ext-link ext-link-type=\"uri\" xlink:href=\"http://meme.nbcr.net/meme/\">http://meme.nbcr.net/meme/</ext-link>) [##REF##16845028##38##]. The maximum and minimum conserved motif lengths were 10 and 50 amino acids, respectively.</p>", "<title>Protein structure analysis of the <italic>PgTCP</italic> gene family in ginseng</title>", "<p id=\"Par8\">SOPMA (<ext-link ext-link-type=\"uri\" xlink:href=\"https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html\">https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html</ext-link>) [##REF##8808585##39##] and SWISS-MODEL (<ext-link ext-link-type=\"uri\" xlink:href=\"https://swissmodel.ExPASy.org/\">https://swissmodel.ExPASy.org/</ext-link>), two online software programs, were used to analyse the protein secondary and tertiary structures of the amino acid sequences of PgTCP genes in ginseng, respectively.</p>", "<title>Chromosome localization and covariance analysis</title>", "<p id=\"Par9\">We used BLASTN to compare the above <italic>PgTCP</italic> genes with ginseng genomes [##REF##35393424##40##]. Identity ≥ 95%, coverage length ≥ 300 bp and <italic>E-value</italic> ≤ <italic>1.0E-100</italic> were used as criteria. The position of <italic>PgTCP</italic> transcripts on chromosomes was visualized using the MG2C online tool (<ext-link ext-link-type=\"uri\" xlink:href=\"http://mg2c.iask.in/mg2c_v2.1/index.html\">http://mg2c.iask.in/mg2c_v2.1/index.html</ext-link>). The <italic>PgTCP</italic> gene family and ginseng genome were subjected to covariance analysis, and the repeated genes of the <italic>PgTCP</italic> gene in the ginseng genome were analysed by the R package circlize34 to determine the pan transcription and core transcription of the <italic>PgTCP</italic> gene family in the ginseng genome.</p>", "<title>GO (Gene Ontology) annotation, functional classification, and analysis</title>", "<p id=\"Par10\">We annotated and classified the identified <italic>PgTCP</italic> transcripts in GO using Blast2GO version 6.0.3 [##REF##16081474##41##] and used the EVeen online tool (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.ehbio.com/test/venn/#/\">http://www.ehbio.com/test/venn/#/</ext-link>) for visualization and analysis. The results of annotation and GO classification were used to assess the functional differentiation of <italic>PgTCP</italic> genes. The chi-square test at level 2 was used to determine the number of <italic>PgTCP</italic> transcripts involved in specific functions and the number of transcripts involved in multiple functions, and R language was used to show the genetic ontological annotation of the ginseng <italic>TCP</italic> gene family.</p>", "<title>Expression pattern analysis of the <italic>PgTCP</italic> gene family</title>", "<p id=\"Par11\">To analyse the expression patterns of <italic>PgTCP</italic> transcripts, we determined the expression of <italic>PgTCP</italic> in 14 different tissues, 4 different aged stages (5, 12, 18, and 25 years) and 42 farm cultivars of 4-year-old ginseng roots. The expression heatmap and gene visualization heatmap were constructed using the R language package for <italic>PgTCP</italic> gene expression in 14 different tissues, 4 different aged stages of ginseng roots to show the spatiotemporal characteristics of <italic>PgTCP</italic>, and 4-year-old ginseng roots of 42 farm cultivars to reveal the characteristics among different genotypes.</p>", "<p id=\"Par12\">To further investigate the interaction characteristics between the expression of <italic>PgTCP</italic> genes in 42 farm cultivars, Spearman correlation coefficients were calculated using the R programming language and software (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.rproject.org/\">http://www.rproject.org/</ext-link>). Gene coexpression networks were constructed using BioLayout Express <sup>3D</sup> version 3.2 software [##REF##19798086##42##].</p>", "<title>Plant materials and methyl jasmonate treatment</title>", "<p id=\"Par13\">Ginseng hairy root was obtained from Jilin Engineering Research Center Ginseng Genetic Resources Development and Utilization. A 0.2 g sample of ginseng hairy root was inoculated into a 250 mL flask containing 150 mL 1/2 MS liquid medium, placed in a shaker at 22 °C and shaken at 110 rpm. On Day 23, MeJA was added to the culture vial. Each trial group included three replicates and one control. The dosage of MeJA was 200 µM. At each time point of 6, 12, 24, 48, 72, 96 and 120 h, three biological replicates and one blank control were collected, and the blank control was not treated with MeJA. Ginseng hairy root samples were quickly frozen in liquid nitrogen for subsequent experiments [##UREF##6##43##].</p>", "<title>RNA extraction and qRT‒PCR validation</title>", "<p id=\"Par14\">Total RNA of ginseng was extracted by the TRIzol method and reverse transcribed into cDNA. According to the basic principle of primer design, the most suitable primer was designed to perform qRT‒PCR on the cDNA of ginseng hairy root. <italic>GAPDH</italic> (glyceraldehyde-3-phosphate dehydrogenase) was selected as the internal reference gene based on the pretest screening, and fluorescence quantitative PCR was performed using the SYBR Premix Ex Taq™ II (Tli RNaseH Plus) kit. The reaction system was as follows: 5.0 µL SYBR PreMix Ex Taq II, 0.4 µL Sense Primer, 0.4 µL Anti primer, 0.5 µL cDNA and 3.7 µL ribonuclease-free water. The reaction conditions were as follows: predenaturation at 95 ℃ for 30 s; reaction at 95 ℃, 5 s; 60 ℃, 34 s, 40 cycles; solution curve 95 ℃, 15 s; 60 ℃, 1 min; 95 ℃, 15 s. Technical experiments were repeated three times for each group of samples, and the final results were calculated by the 2<sup>−ΔΔCT</sup> method [##REF##11328886##44##].</p>", "<title>Identification of candidate genes related to ginsenoside biosynthesis</title>", "<p id=\"Par15\">The expression data of <italic>PgTCP</italic> and the expression data of each mono saponin and total saponins in 42 farm cultivars of ginseng in Jilin Province were sorted. Pearson correlation coefficient analysis was conducted using SPSS software to calculate the correlation between <italic>PgTCP</italic> and ginsenoside synthesis, and the closely related genes were screened out. The expression data of <italic>PgTCP</italic> genes significantly related to ginsenoside synthesis and the gene expression data of 16 key enzymes involved in the ginsenoside synthesis pathway were sorted. Pearson correlation coefficient analysis was conducted using SPSS software to calculate the correlation between <italic>PgTCP</italic> and key enzyme-encoding gene expression. Closely related genes were screened out. Spearman’s correlation coefficients were calculated using the R programming language and software (<ext-link ext-link-type=\"uri\" xlink:href=\"http://www.rproject.org/\">http://www.rproject.org/</ext-link>). BioLayout Express<sup>3D</sup> version 3.2 software was used to construct the coexpression network of the <italic>PgTCP</italic> gene and ginsenoside synthesis key enzyme-encoding genes and visualize the gene interaction network.</p>", "<title>Characteristic analysis of the <italic>PgTCP26-02</italic> gene involved in ginsenoside biosynthesis</title>", "<p id=\"Par16\">Protein secondary structure analysis of the amino acid sequence of <italic>PgTCP26-02</italic> was performed by SOPMA (<ext-link ext-link-type=\"uri\" xlink:href=\"https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html\">https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html</ext-link>) online software. Using SWISS-MODEL (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.swissmodel.ExPASy.org/\">https://www.swissmodel.ExPASy.org/</ext-link>), online software was used to analyse the tertiary structure of the protein based on the amino acid sequence of PgTCP26-02. Phylogenetic trees were constructed with the neighbour-joining (NJ) method in MEGA-X using the protein sequences of PgTCP26-02 and those of other species, and the bootstrap replicates were set to 2000. The protein sequences of PgTCP26-02 and the other three species were aligned using DNAMAN software.</p>", "<p id=\"Par17\">In addition, to further analyse the expression pattern of the <italic>PgTCP26-02</italic> gene, TBtools version 2.012 [##REF##37740491##45##] was used to generate a heatmap of <italic>PgTCP26-02</italic> gene expression in ginseng roots of 4 different ages (5, 12, 18, 25 years old), 14 different tissues of 4-year-old ginseng and 42 farm cultivars of 4-year-old ginseng to observe the expression of the <italic>PgTCP26-02</italic> gene in ginseng more clearly and intuitively.</p>" ]
[ "<title>Results</title>", "<title>Genome-wide identification of the <italic>TCP</italic> gene family in ginseng</title>", "<p id=\"Par18\">A total of 574 transcript sequences containing TCP structural domains were identified from the Jilin Ginseng Transcriptome Database using different methods after removing repetitive sequences. After iTAK filtering for spurious sequences, conserved structural domain analysis by NCBI CD-Search and SMART online software, 496 conserved structural domains among the 574 transcripts were incomplete or had no open reading frame (ORF), and the remaining 78 transcripts contained TCP structural domains in their ORFs. Therefore, these 78 transcripts were used for subsequent analysis. The 78 Jilin Ginseng <italic>PgTCP</italic> transcripts were classified as 28 <italic>PgTCP</italic> genes, named <italic>PgTCP01</italic>-<italic>PgTCP28</italic>. Different transcripts of the same gene were distinguished by numerical suffixes (e.g., − 01). These transcripts ranged in length from 229 to 3140 and in amino acid numbers from 29 to 435 for the complete open reading framework (ORF) (Table S##SUPPL##0##1##).</p>", "<title>Structural characteristics and phylogeny of <italic>PgTCP</italic> genes</title>", "<p id=\"Par19\">We constructed a phylogenetic tree by selecting 67 <italic>PgTCP</italic> transcripts with intact TCP structural domains and 9 transcripts of other species (Table S##SUPPL##1##2##). The results are shown in Fig. ##FIG##0##1##A. <italic>PgTCP</italic> transcripts were divided into class I (PCF) and class II, which were further divided into the CYC/TB1 class and CIN class.</p>", "<p id=\"Par20\">To understand the sequence characteristics of PgTCP proteins, the online tool MEME was used to analyse its conserved domain. The results showed that motif number ranged from 1 to 8 in subfamily members of different <italic>PgTCP</italic> genes (Fig. ##FIG##0##1##B). The conserved structural domains of TCP were classified into three types, namely, the TCP superfamily, TCP2 and TCP, which were expressed in all 67 <italic>PgTCP</italic> family members. These results suggest that <italic>PgTCP</italic> genes are functionally similar.</p>", "<title>Protein structure analysis of <italic>PgTCP</italic> transcription factors in ginseng</title>", "<p id=\"Par21\">Five genes from each of the three isoforms of the <italic>PgTCP</italic> gene family were selected and analysed for their secondary structures as well as tertiary structures. The predicted secondary structures of the 15 proteins showed that the TCP proteins consisted of four parts: α-helix, extended chain, random coiled coil, and β-turn. The ginseng TCP protein had the highest proportion of irregularly coiled structures, followed by α-helix structures (Table ##TAB##0##1##). As shown in Fig. ##FIG##1##2##, the tertiary structure of ginseng TCP-encoded proteins was as follows: ginseng TCP protein contains alpha helix, beta turn, and random coil structures. Different proteins have different structures, indicating that their functions are also different, further indicating the functional diversity of TCP gene family members.\n</p>", "<title>Chromosome distribution and covariance analysis</title>", "<p id=\"Par22\">Of the 78 <italic>PgTCP</italic> genes, 63 were localized on Chinese ginseng genome chromosomes after comparison with 24 ginseng chromosomes. Among the 63 <italic>PgTCP</italic> genes localized to the Chinese ginseng genome, no TCP members were identified on chromosomes 4, 5, 7, 8, 9, 13, and 16, as shown in Fig. ##FIG##2##3##A. In ginseng, the chromosomal distribution of <italic>PgTCP</italic> members was uneven. Chromosome 2 contained the most <italic>PgTCP</italic> members (13). Covariance analysis showed that members of the <italic>TCP</italic> gene family had undergone gene replication in ginseng (Fig. ##FIG##2##3##B).</p>", "<title>GO functional categorization and GO term enrichment of <italic>PgTCP</italic> genes</title>", "<p id=\"Par23\">In living organisms, genes usually have multiple functions. We performed GO annotation of 78 <italic>PgTCP</italic> transcripts (Table S##SUPPL##2##3##). We found that all 78 transcripts had at least one of three major functions: 74 were biological processes (BP), 47 were cellular components (CC), and 77 were molecular functions (MF). Only one function was labelled in 1 transcript, two major functions were labelled in 34 transcripts, and three major functions were labelled in 43 transcripts (Fig. ##FIG##3##4##A). At level 2, 6 sublevels, GO:0065007 (biological regulation), GO:0032502 (developmental process), GO:0050789 (regulation of biological process), GO:0009987 (cellular process), GO:0032501 (multicellular organismal process), and GO:0008152 (metabolic process), were enriched in BP, 1 sublevel, GO:0110165 (cellular anatomical entity), was enriched in CC, and 2 sublevels, GO:0005488 (binding) and GO:0140110 (transcription regulator activity), were enriched in MF (Fig. ##FIG##3##4##B).</p>", "<title>Expression characteristics and pattern of <italic>PgTCP</italic> genes</title>", "<p id=\"Par24\">To further understand the regularity of <italic>PgTCP</italic> gene expression in ginseng, we retrieved the expression data of 78 <italic>PgTCP</italic> gene transcripts from 42 farm cultivars (S1—S42), 14 different tissues (fibre root, leg root, main root epiderm, main root cortex, rhizome, arm root, stem, leaf peduncle, leaflet pedicel, leaf blade, fruit peduncle, fruit pedicel, fruit flesh, and seed), and four different ages (5, 12, 18, and 25 years) of ginseng roots (Table S##SUPPL##3##4##) and plotted heatmaps.</p>", "<p id=\"Par25\">The results showed that 29 transcripts (37%) were not expressed in the roots of ginseng at 4 different ages. Heatmaps of the remaining gene expression showed that 22 <italic>PgTCP</italic> transcripts were expressed in all 4 age groups (28%), and 49 <italic>PgTCP</italic> transcripts (62%) were expressed in at least one age group (Fig. ##FIG##4##5##A). <italic>PgTCP20-06</italic>, <italic>PgTCP26-01</italic>, <italic>PgTCP18</italic>, <italic>PgTCP24-8</italic>, <italic>PgTCP14</italic>, <italic>PgTCP20-03</italic>, <italic>PgTCP17-02</italic>, <italic>PgTCP17-01</italic> and <italic>PgTCP20-04</italic> were highly expressed.</p>", "<p id=\"Par26\">Among 78 transcripts, 3 transcripts were not expressed in 14 different tissues of four-year-old ginseng, and heatmap results after the deletion of nonexpressed transcripts showed that 14 transcripts (18%) were expressed in all 14 tissues and 75 <italic>PgTCP</italic> transcripts were expressed in at least one tissue (96%) (Fig. ##FIG##4##5##B). <italic>PgTCP20-03</italic> and <italic>PgTCP20-06</italic> were expressed at higher levels.</p>", "<p id=\"Par27\">The heatmap analysis of 42 farm cultivars of 4-year-old ginseng roots showed that 67 <italic>PgTCP</italic> transcripts were expressed in at least one cultivar (86%) (Fig. ##FIG##4##5##C). The <italic>PgTCP23</italic>, <italic>PgTCP26-01</italic>, <italic>PgTCP26-02</italic>, <italic>PgTCP20-03</italic>, and <italic>PgTCP20-06</italic> genes had high expression levels in 42 farm cultivars, and the expression levels of 11 transcripts in all cultivars were zero. This indicates that there are regional differences in the expression of <italic>TCP</italic> gene family members in ginseng.</p>", "<title>Coexpression network of <italic>PgTCP</italic> transcripts</title>", "<p id=\"Par28\">To investigate whether there are correlations between different gene types in <italic>PgTCP</italic> transcripts, coexpression network analysis was performed for <italic>PgTCP</italic> transcript expression levels in 42 cultivars. Sixty-seven transcripts expressed in at least one of 42 cultivars were selected for coexpression network analysis. The coexpression network results showed that at <italic>P</italic> ≤ <italic>5.0E-02</italic>, the 67 transcripts formed a coexpression network with 254 edges and 66 nodes (Fig. ##FIG##5##6##A), and the network contained 8 clusters (Fig. ##FIG##5##6##B). We counted the nodes and edges of this network at increasingly stringent <italic>P values</italic>, and at <italic>P</italic> ≤ <italic>1.0E-08</italic>, the <italic>PgTCP</italic> transcripts formed 2 nodes and 1 edge. To reflect the tightness of this network, we randomly selected another 78 transcripts from the ginseng transcriptome database as negative controls, and we removed those that were not expressed in the 42 farm cultivars and selected the remaining ones for coexpression network analysis (Fig. ##FIG##5##6##C-D). After three replicates, the mean was calculated, and at <italic>P</italic> ≤ <italic>5.0E-02</italic>, the <italic>PgTCP</italic> transcript formed a regulatory network consisting of 57 nodes and 159 edges, and at <italic>P</italic> ≤ <italic>1.0E-08</italic>, the <italic>PgTCP</italic> transcript formed 2 nodes and 1 edge. Thus, <italic>PgTCP</italic> transcripts are more likely to form a coexpression network than randomly selected transcripts.</p>", "<p id=\"Par29\">To further demonstrate the correlation between each pair of <italic>PgTCP</italic> transcripts, we constructed the network using a random sampling of two-thirds (52) of the total <italic>PgTCP</italic> transcripts and introduced a negative control as described above (Fig. ##FIG##5##6##E-F). When <italic>P</italic> ≤ 5.0E-02, 52 <italic>PgTCP</italic> transcripts formed a network of 120 edges and 41 nodes after removing unexpressed transcripts from 42 varieties, and at <italic>P</italic> ≤ <italic>1.0E-07</italic>, <italic>PgTCP</italic> transcripts formed 2 nodes and 1 edge, and the number of edges for the unknown transcripts was 0. These results suggest that there are significant coexpression interactions between <italic>PgTCP</italic> transcripts and that <italic>PgTCP</italic> transcripts form coexpression networks more easily than transcripts selected at random.</p>", "<title>Expression analysis of <italic>PgTCP</italic> genes under MeJA treatment in <italic>Panax ginseng</italic></title>", "<p id=\"Par30\">To determine the expression profile of the <italic>PgTCP</italic> gene under MeJA treatment, qRT‒PCR was performed on 15 transcripts randomly selected in 3.2 to explore the expression of the <italic>PgTCP</italic> gene under MeJA treatment at different times. As shown in Fig. ##FIG##6##7##, the expression levels of <italic>PgTCP</italic> genes in class I (PCF) were downregulated under MeJA treatment compared with the control, and the expression of most <italic>PgTCP</italic> genes showed an upwards and then downwards trend after MeJA treatment, reaching a peak at 60 h after induction. At 48 h after induction, the expression levels of the <italic>PgTCP09-03</italic>, <italic>PgTCP16-02</italic>, <italic>PgTCP20-03</italic>, <italic>PgTCP23</italic>, and <italic>PgTCP26-02</italic> genes were significantly downregulated compared with those of the control, and the relative expression levels of the <italic>PgTCP16-02</italic> and <italic>PgTCP23</italic> genes were significantly downregulated at all time points. In class II (CIN and CYC/TB1), almost all expression levels of <italic>PgTCP</italic> genes were upregulated compared with the control, and the expression of most <italic>PgTCP</italic> genes showed an upwards and downwards trend after MeJA treatment. Among the genes of the CIN subtype, the <italic>PgTCP04</italic>, <italic>PgTCP15-02</italic>, and <italic>PgTCP19</italic> genes peaked at 72 h after induction, and only the <italic>PgTCP04</italic> gene was significantly upregulated at 72 h. Among the CYC/TB1 subtypes, the relative expression levels of the <italic>PgTCP05</italic>, <italic>PgTCP07-01</italic>, and <italic>PgTCP21</italic> genes peaked at 72 h postinduction, and the <italic>PgTCP05</italic> and <italic>PgTCP21</italic> genes were significantly upregulated. The <italic>PgTCP14</italic> gene was significantly upregulated at 12 h postinduction and peaked at 12 h.</p>", "<title>Screening of <italic>TCP</italic> candidate genes involved in ginsenoside biosynthesis</title>", "<p id=\"Par31\">Ginsenoside is the main active ingredient of ginseng, but its content in ginseng is very low, so it is very important to study the synthetic pathway of ginsenoside. SPSS software was used to calculate the correlation between ginsenoside content and <italic>PgTCP</italic> gene expression in 42 farm cultivars (Table S##SUPPL##4##5##). Twenty-nine <italic>PgTCP</italic> genes were significantly correlated with ginsenoside content, among which 19 <italic>PgTCP</italic> genes were significantly positively correlated with saponin content, and 10 <italic>PgTCP</italic> genes were significantly negatively correlated with saponin content.</p>", "<p id=\"Par32\">Many key enzymes in ginsenoside synthesis have been cloned. The <italic>PgTCP</italic> gene may be correlated with key enzyme-encoding genes in the ginsenoside synthesis pathway. To explore the relationship between the <italic>PgTCP</italic> gene and key enzyme-encoding genes, SPSS software was used to calculate the correlation between the expression levels of key enzyme-encoding genes and the expression levels of 29 <italic>PgTCP</italic> genes significantly correlated with ginsenoside content (Table S##SUPPL##5##6##). A total of 19 genes were found to be significantly correlated with the expression of key enzyme-encoding genes. The expression levels of 16 <italic>PgTCP</italic> genes were positively correlated with the expression levels of key enzyme-encoding genes. The expression levels of three <italic>PgTCP</italic> genes were negatively correlated with the expression levels of key enzyme-encoding genes.</p>", "<p id=\"Par33\">Since the key enzyme-encoding genes of ginseng participate and are important in the ginsenoside synthesis pathway, it is particularly important to study the correlation between key enzyme-encoding gene expression and ginsenoside content. After screening, 19 <italic>PgTCP</italic> genes were found to be significantly correlated with both key enzyme-encoding genes of ginseng and ginsenoside content. However, based on the network, the <italic>PgTCP26-02</italic> gene was associated with more key enzyme-encoding genes (Fig. ##FIG##7##8##), which was finally selected for subsequent functional verification.</p>", "<title>Analysis of the <italic>PgTCP26-02</italic> gene involved in ginsenoside biosynthesis</title>", "<p id=\"Par34\">The secondary structure of <italic>PgTCP26-02</italic> was α helix 56 (21.71%). β turn 12 (4.65%); random coil 162 (62.79%); extended strand 28 (10.85%) (Fig. ##FIG##8##9##A). Tertiary structure modelling clearly shows that PgTCP26-02 contains the bHLH domain (Fig. ##FIG##8##9##B). To reveal the evolutionary relationship between <italic>TCP</italic> genes in different species, the 9 protein sequences of TCP family members of other species were downloaded from NCBI (Table S##SUPPL##6##7##). The phylogenetic tree was constructed using the PgTCP26-02 protein sequence and 9 TCP protein sequences from other species (Fig. ##FIG##8##9##C). PgTCP26-02 had the closest evolutionary relationship with maize ZmTCP16. At the protein level, PgTCP26-02 and other protein sequences contained the bHLH domain (Fig. ##FIG##8##9##D).</p>", "<p id=\"Par35\">To study the expression of the <italic>PgTCP26-02</italic> gene in ginseng, we retrieved the expression data of the <italic>PgTCP26-02</italic> gene from roots of 4 different ages of ginseng, 14 different tissues of 4-year-old ginseng and 42 farm cultivars of 4-year-old ginseng. To more intuitively reflect the expression level of the <italic>PgTCP26-02</italic> gene, we drew a gene expression heatmap. Among the 4 different aged stages of ginseng roots, the expression level of the <italic>PgTCP26-02</italic> gene was the highest in 25-year-old ginseng roots and was not expressed in 12-year-old ginseng roots and 18-year-old ginseng roots (Fig. ##FIG##9##10##A). Among the 14 different tissues of 4-year-old ginseng, <italic>PgTCP26-02</italic> was expressed in all of them, and the expression level of <italic>PgTCP26-02</italic> was higher in the main root epiderm and main root cortex (Fig. ##FIG##9##10##B). Among the 42 farm cultivars of 4-year-old ginseng roots, the <italic>PgTCP26-02</italic> gene was expressed in all farm cultivars (Fig. ##FIG##9##10##C).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par36\">TCP is a transcription factor family that is widespread and unique to plants and thus has been extensively studied. TCP transcription factors have been shown to be involved in plant growth and development, secondary metabolism and other biological processes in several species, such as <italic>Arabidopsis</italic>, rice, bamboo shoots, tomato, and ginkgo. However, the <italic>TCP</italic> gene family has not been intensively studied in ginseng. In this study, 28 <italic>TCP</italic> gene family members consisting of 78 <italic>TCP</italic> transcription factors named <italic>PgTCP</italic> were identified in the ginseng transcriptome database. Twenty-two <italic>TCP</italic> genes were identified in rice, 24 in <italic>Arabidopsis</italic> [##UREF##7##46##], 30 in tomato [##REF##24903607##29##], and 12 in ginkgo [##REF##35068346##24##]. Based on evolutionary analysis, <italic>TCP</italic> gene family members in ginseng were also classified into class I (PCF) and class II (CIN and CYC/TB1), and these results suggest that there seems to be no major differences in the number and classification of <italic>TCP</italic> gene family members in plants.</p>", "<p id=\"Par37\">Previous studies have shown that TCP transcription factors almost always have bHLH structures that can bind to DNA and participate in protein interactions and thus in plant growth and development, hormone signalling, and synthesis of secondary metabolites. The protein secondary structure analysis and tertiary structure modelling of <italic>PgTCP</italic> also revealed the existence of a bHLH domain in <italic>PgTCP</italic>, which indicated the functional diversity of the <italic>PgTCP</italic> gene. Ginseng is a tetraploid plant with 24 pairs of chromosomes, and most of the <italic>PgTCP</italic> gene family is distributed on Chinese ginseng chromosomes, with only a few chromosomes that do not have <italic>TCP</italic> transcription factors. Gene replication events are important events that drive the development of new biological functions. However, whole-genome replication of the <italic>PgTCP</italic> gene has also been found in ginseng, so the <italic>PgTCP</italic> gene family has many potential biological functions. Based on the results of GO functional annotation, 77 <italic>PgTCP</italic> transcripts were annotated as molecular functions (MF); thus, these genes may interact with other proteins or regulate the expression of downstream genes by binding enhancers to regulate ginseng growth and development. Seventy-four <italic>PgTCP</italic> transcripts were labelled as biological process (BP), and 47 <italic>PgTCP</italic> transcripts were labelled as cell component (CC), indicating that the <italic>PgTCP</italic> gene is not only a functional but also a structural gene in ginseng. In conclusion, the functions of <italic>PgTCP</italic> transcripts in Jilin ginseng are diverse.</p>", "<p id=\"Par38\">Analysis of the expression pattern of the <italic>PgTCP</italic> gene family yielded several interesting findings. First, the expression levels of <italic>PgTCP</italic> transcripts were analysed in 42 farm cultivars, and most transcripts were expressed very similarly in all cultivars, suggesting broad expression of <italic>PgTCP</italic> transcripts. However, the <italic>PgTCP</italic> gene also has specificity. <italic>PgTCP20-06</italic>, <italic>PgTCP20-03</italic>, and <italic>PgTCP23</italic> were expressed in all farm cultivars, <italic>PgTCP20-3</italic> was strongly expressed in S30, and <italic>PgTCP26-01</italic> and <italic>PgTCP26-02</italic> were highly expressed in the majority of farm cultivars. Second, approximately 62% of <italic>PgTCP</italic> transcripts were expressed at different times in ginseng roots at four different ages (5, 12, 18, and 25 years), and approximately 37% of <italic>PgTCP</italic> transcripts were not expressed at all four ages of ginseng. <italic>PgTCP09-04</italic> had a clear trend of increasing expression over time, and <italic>PgTCP24-21</italic>, <italic>PgTCP24-12</italic>, <italic>PgTCP18</italic> and <italic>PgTCP16-01</italic> showed a clear trend of decreasing expression over time. A total of 33 transcripts (42%), 35 transcripts (44%), 39 transcripts (50%), and 37 transcripts (47%) were expressed in 5-, 12-, 18-, and 25-year-old roots, respectively, and specifically, the <italic>PgTCP</italic> transcript had the lowest expression level in the 5-year-old roots. The specific expression of <italic>PgTCP</italic> transcripts in these 4 different ages indicated that not all <italic>PgTCP</italic> transcripts were structurally expressed in ginseng. Finally, most <italic>PgTCP</italic> genes were found to be expressed with tissue specificity in 14 different tissues of 4-year-old ginseng, and only 14 transcripts (18%) were expressed in all tissues, with <italic>PgTCP20-03</italic> and <italic>PgTCP20-06</italic> being expressed at higher levels in 14 ginseng tissues. In conclusion, the expression of <italic>PgTCP</italic> transcripts in ginseng is spatiotemporally specific.</p>", "<p id=\"Par39\">In 78 transcripts of the <italic>PgTCP</italic> gene family, the expression of most genes is regulated jointly, while only a few genes are regulated independently. Genes of the <italic>PgTCP</italic> gene family are more likely to form a coexpressed interaction network, and some closely related clusters are formed at <italic>P</italic> ≤ 0.05, some of which play a core role in the network, indicating that gene members of the <italic>PgTCP</italic> gene family are still functionally related to each other.</p>", "<p id=\"Par40\">We selected five <italic>PgTCP</italic> genes from each of the three isoforms PCF, CIN and CYC/TB1 as representatives to study their expression under MeJA treatment. The relative expression of genes in class I was downregulated after MeJA treatment. In contrast, the relative expression of most genes in the two isoforms of class II was upregulated after MeJA treatment. This indicates that the gene members of different isoforms of the <italic>PgTCP</italic> gene family differ under abiotic stress treatment. These results not only confirmed that the relative expression level of the <italic>PgTCP</italic> gene after MeJA treatment affected the hairy root of ginseng but also indicated the reliability of the results of systematic analysis in this study. These results also demonstrated that <italic>PgTCP</italic> gene expression in ginseng is not only time-specific but also responsive to the regulation of MeJA. This study provides a theoretical basis for studying <italic>TCP</italic> gene regulation of plant secondary metabolism.</p>", "<p id=\"Par41\">To further investigate the role of <italic>PgTCP</italic> in synthesizing secondary metabolites in ginseng, we identified a gene, <italic>PgTCP26-02,</italic> that is highly related to ginsenoside content in the <italic>PgTCP</italic> gene family. <italic>PgTCP26-02</italic> belongs to the class I (PCF) subfamily, and after MeJA treatment, the expression level of the <italic>PgTCP26-02</italic> gene showed a downwards trend, and the expression level of the <italic>PgTCP26-02</italic> gene in 42 farm cultivars was also negatively correlated with the expression level of key ginsenoside synthesis enzyme-encoding genes. Therefore, we preliminarily determined that the <italic>PgTCP26-02</italic> gene was related to ginsenoside biosynthesis, and the <italic>PgTCP26-02</italic> gene also became the next research object.</p>", "<p id=\"Par42\">Genes control protein synthesis through transcription and translation, and proteins are the embodiment and undertaking of life activities and are closely related to the exercise of biological functions. Therefore, we analysed the protein sequence structure of the <italic>PgTCP26-02</italic> gene, and the tertiary structure of the PgTCP26-02 protein showed that it had a typical bHLH structure. Phylogenetic analysis showed that <italic>PgTCP26-02</italic> had high homology with the <italic>TCP</italic> genes of other species. Through multiple sequence alignment, we found that all <italic>TCP</italic> genes have the bHLH domain, and there are approximately 20 basic regions of amino acid residues in the N-terminus of the bHLH domain and a helix-ring-helix region composed of approximately 40 amino acids in the C-terminus of the bHLH domain. The alkaline region has the ability to bind to the specific DNA sequence E-box (5'-CANNTG-3'), while the two α-helices of HLH can participate in protein‒protein interactions to form homologues or heterodimers. This gives the bHLH transcription factor the dual function of interacting with both DNA and proteins. Therefore, the <italic>PgTCP26-02</italic> gene containing a bHLH domain plays an important regulatory role in the secondary metabolism of ginseng.</p>", "<p id=\"Par43\">Through the analysis of the expression pattern of the <italic>PgTCP26-02</italic> gene, it was found that the <italic>PgTCP26-02</italic> gene had the highest expression in the roots of 25-year-old ginseng, and some studies showed that the saponin content in the roots of older ginseng was also higher than that in the roots of younger ginseng; therefore, we speculated that the <italic>PgTCP26-02</italic> gene was related to the synthesis of ginsenoside. The expression of the <italic>PgTCP26-02</italic> gene is tissue-specific in ginseng, and the expression level of the <italic>PgTCP26-02</italic> gene appears to be the most abundant in ginseng roots. As ginsenoside is the main active ingredient in the root of ginseng [##REF##32751233##47##], our results further support that the <italic>PgTCP26-02</italic> gene might be involved in regulating ginsenoside biosynthesis. We are currently studying the molecular mechanism of <italic>PgTCP26-02</italic> gene involvement in the regulation of ginsenoside synthesis in ginseng, aiming to better understand how <italic>TCP</italic> genes regulate plant secondary metabolism.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par44\">In this study, 28 <italic>PgTCP</italic> genes were screened from <italic>P. ginseng</italic> (ginseng), and their structure, evolution, function, expression pattern, and coexpression network were analysed. Additionally, the response of <italic>PgTCP</italic> genes to MeJA was investigated. Our results suggest that members of the <italic>PgTCP</italic> gene family are functionally diverse, showing differences in expression patterns in terms of tissue and temporal specificity. In addition, the <italic>PgTCP</italic> gene family appears to be involved in the plant response to MeJA treatment, further confirming the role of the <italic>TCP</italic> gene family in the MeJA stress response. The role of the <italic>TCP</italic> gene family in the secondary metabolism of ginseng was further confirmed and provided a theoretical basis for ginseng genetic breeding in the future. Genome-wide identification and integrated analysis of the <italic>TCP</italic> gene family controlling ginsenoside biosynthesis will provide a theoretical basis and enriched genetic resources for in-depth studies on functional genomics in <italic>P. ginseng</italic>.</p>" ]
[ "<p id=\"Par1\"><italic>Panax ginseng</italic> is an important medicinal plant, and ginsenosides are the main bioactive molecules of ginseng. The TCP (TBI, CYC, PCF) family is a group of transcription factors (TFs) that play an important role in plant growth and development, hormone signalling and synthesis of secondary metabolites. In our study, 78 <italic>PgTCP</italic> transcripts were identified from the established ginseng transcriptome database. A phylogenetic tree analysis showed that the 67 <italic>PgTCP</italic> transcripts with complete open reading frames were classified into three subfamilies, including CIN, PCF, and CYC/TB1. Protein structure analysis showed that <italic>PgTCP</italic> genes had bHLH structures. Chromosomal localization analysis showed that 63 <italic>PgTCP</italic> genes were localized on 17 of the 24 chromosomes of the Chinese ginseng genome. Expression pattern analysis showed that <italic>PgTCP</italic> genes differed among different lineages and were spatiotemporally specific. Coexpression network analysis indicated that <italic>PgTCP</italic> genes were coexpressed and involved in plant activities or metabolic regulation in ginseng. The expression levels of <italic>PgTCP</italic> genes from class I (PCF) were significantly downregulated, while the expression levels of <italic>PgTCP</italic> genes from class II (CIN and CYC/TB1) were upregulated, suggesting that <italic>TCP</italic> genes may be involved in the regulation of secondary metabolism in ginseng. As the <italic>PgTCP26-02</italic> gene was found to be related to ginsenoside synthesis, its predicted protein structure and expression pattern were further analysed. Our results provide new insights into the origin, differentiation, evolution and function of the <italic>PgTCP</italic> gene family in ginseng, as well as the regulation of plant secondary metabolism.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12870-024-04729-x.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>All authors thank the editor and reviewers for their valuable comments and suggestions for this manuscript. The author thanks the Department of Science and Technology of Jilin Province for the support.</p>", "<title>Authors’ contributions</title>", "<p>Mingzhu Zhao, Meiping Zhang and Yi Wang designed the experiments of the study. Chang Liu, Tingting Lv, Mingzhu Zhao and Kangyu Wang wrote and revised the main manuscript. Tao Liu, Mingming Liu, Jian Hu, Sizhang Liu, Yang Jiang and Yanhua Shen performed the experiments and contributed to data analysis. All authors reviewed and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by an award from the Bureau of Science and Technology of Jilin Province (20210402043GH).</p>", "<title>Availability of data and materials</title>", "<p>All ginseng data used for this study are available at the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI) under BioProject PRJNA302556. TCP amino acid sequences were downloaded from the Plant Transcription Factor Database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://planttfdb.gao-lab.org/family.php?fam=TCP\">http://planttfdb.gao-lab.org/family.php?fam=TCP</ext-link>). All ginseng materials are available through corresponding authors upon request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par45\">All ginseng samples and ginseng hairy root materials were stored at Jilin Agricultural University and Jilin Engineering Research Center Ginseng Genetic Resources Development and Utilization. All plant materials of ginseng were used in accordance with national and international standards and local laws and regulations. The use of all plant materials does not pose any risk to other species in nature. No specific permission is needed for the collection of all samples described in this study.</p>", "<title>Consent for publication</title>", "<p id=\"Par46\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par47\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Phylogenetic analysis and conserved motifs analysis. <bold>A</bold> Phylogenetic analysis of the <italic>PgTCP</italic> genes, the stars represents three exogenous species. <bold>B</bold> Conserved motif analysis of <italic>PgTCP</italic>, different colors represent different conserved motifs</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Tertiary structure analysis of ginseng <italic>TCP</italic> family members. The secondary structure elements include alpha helix, beta turn, and random coil. Purple represents the Alpha helix, green represents the Beta turn, gray represents the Random coil</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p><italic>PgTCP</italic> chromosome distribution and covariance analysis. <bold>A</bold> Distribution of ginseng <italic>TCP</italic> family members on ginseng chromosomes. <bold>B</bold> Covariance analysis of ginseng <italic>TCP</italic> gene family members in ginseng chromosomes. The red line represents tandem duplication of the same gene on different chromosomes</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Functional categorization and GO term enrichment of the <italic>PgTCP</italic> gene transcripts. <bold>A</bold> Venn network of the <italic>PgTCP</italic> gene transcripts among the biological process (BP), molecular function (MF) and cellular component (CC) functional categories. <bold>B</bold> The <italic>PgTCP</italic> transcripts are classified into nine functional categories at Subcategories (Level 2), including one CC functional categories (Blue), two MF functional category (Purple), and six BP functional categories (Yellow)</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Heatmaps analysis spatiotemporal expression patterns of <italic>PgTCP</italic> transcripts in <italic>Panax ginseng</italic>. <bold>A</bold> The <italic>PgTCP</italic> genes expression in the 4 different aged (5, 12, 18, 25 years) of ginseng roots. <bold>B</bold> The <italic>PgTCP</italic> genes expression in the 14 different tissues of 4-year-old ginseng. <bold>C</bold> The <italic>PgTCP</italic> genes expression in the 42 farm cultivars of 4-year-old ginseng roots</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Network analysis of the <italic>PgTCP</italic> genes expressed in the 4-year-old roots of 42 farm cultivars. <bold>A</bold> The co-expression network constructed from the 78 <italic>PgTCP</italic> transcripts. The network was constructed at <italic>P</italic> ≤ 5.0E-01. <bold>B</bold> The three clusters constituting the network. Different clusters are indicated by different colors. <bold>C</bold> Tendency that these <italic>PgTCP</italic> form a network, with the randomly-selected ginseng unknown genes as controls: variation in number of nodes. <bold>D</bold> Tendency that these Pgtcp transcripts form a network, with the randomly-selected ginseng unknown genes as controls: variation in number of edges. <bold>E</bold> Statistical analysis of variation in number of nodes in the network. <bold>F</bold> Statistical analysis of variation in number of edges in the network. Different capital letters, significant at <italic>P</italic> ≤ 0.01. Error bar, standard deviation for 20 replications</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Relative expression of <italic>PgTCP</italic> in methyl jasmonate-treated ginseng. <bold>A</bold> Relative expression of PCF isoforms of <italic>PgTCP</italic> in methyl jasmonate-treated ginseng. <bold>B</bold> Relative expression of CIN isoforms of <italic>PgTCP</italic> in methyl jasmonate-treated ginseng. <bold>C</bold> Relative expression of CYC/TB1 isoforms of <italic>PgTCP</italic> in methyl jasmonate-treated ginseng. X shows the time (h) of methyl jasmonate-treated of ginseng hairy roots; Y represents the relative expression levels of genes in the hairy roots of ginseng</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>Interaction network between <italic>PgTCP</italic> genes and ginsenoside synthesis key enzyme genes</p></caption></fig>", "<fig id=\"Fig9\"><label>Fig. 9</label><caption><p>Characterization of the <italic>PgTCP26-02</italic> gene. <bold>A</bold> Secondary structure of PgTCP26-02 protein. The blue, green, purple and red lines represent alpha helix, beta turn, random coil and extended strand. <bold>B</bold> Tertiary structure of PgTCP26-02 protein. <bold>C</bold> Evolutionary relationships between PgTCP26-02 protein and TCP protein in other species. <bold>D</bold> Amino acid sequence alignment of PgTCP26-02 to protein sequences of other species. In the red box are the bHLH domains</p></caption></fig>", "<fig id=\"Fig10\"><label>Fig. 10</label><caption><p>Heatmaps analysis spatiotemporal expression patterns of <italic>PgTCP26-02</italic> gene in <italic>Panax ginseng</italic>. <bold>A</bold> The <italic>PgTCP26-02</italic> gene expressed in the 4 different ages of ginseng roots. Red to green expression decreased in turn. <bold>B</bold> Expression of <italic>PgTCP26-02</italic> gene in 14 different tissues of ginseng. Red to green expression decreased in turn. <bold>C</bold> The <italic>PgTCP26-02</italic> gene expressed in the 42 farm cultivars of 4-year-old ginseng roots. Red, yellow and then green decreased in expression</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Secondary structure of PgTCP protein</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Protein ID</th><th align=\"left\" colspan=\"2\">Alpha helix</th><th align=\"left\" colspan=\"2\">Extended strand</th><th align=\"left\" colspan=\"2\">Beta turn</th><th align=\"left\" colspan=\"2\">Random coil</th></tr><tr><th align=\"left\"><bold>Number of amino acids</bold></th><th align=\"left\"><bold>%</bold></th><th align=\"left\"><bold>Number of amino acids</bold></th><th align=\"left\"><bold>%</bold></th><th align=\"left\"><bold>Number of amino acids</bold></th><th align=\"left\"><bold>%</bold></th><th align=\"left\"><bold>Number of amino acids</bold></th><th align=\"left\"><bold>%</bold></th></tr></thead><tbody><tr><td align=\"left\">PgTCP09-03</td><td align=\"left\">50</td><td align=\"left\">24.27</td><td align=\"left\">24</td><td align=\"left\">11.65</td><td align=\"left\">6</td><td align=\"left\">2.91</td><td align=\"left\">126</td><td align=\"left\">61.17</td></tr><tr><td align=\"left\">PgTCP16-02</td><td align=\"left\">92</td><td align=\"left\">24.34</td><td align=\"left\">42</td><td align=\"left\">11.00</td><td align=\"left\">18</td><td align=\"left\">4.76</td><td align=\"left\">226</td><td align=\"left\">59.79</td></tr><tr><td align=\"left\">PgTCP20-03</td><td align=\"left\">77</td><td align=\"left\">28.62</td><td align=\"left\">21</td><td align=\"left\">7.81</td><td align=\"left\">14</td><td align=\"left\">5.20</td><td align=\"left\">157</td><td align=\"left\">58.36</td></tr><tr><td align=\"left\">PgTCP23</td><td align=\"left\">32</td><td align=\"left\">14.41</td><td align=\"left\">37</td><td align=\"left\">16.67</td><td align=\"left\">10</td><td align=\"left\">4.50</td><td align=\"left\">143</td><td align=\"left\">64.41</td></tr><tr><td align=\"left\">PgTCP26-02</td><td align=\"left\">56</td><td align=\"left\">21.71</td><td align=\"left\">28</td><td align=\"left\">10.85</td><td align=\"left\">12</td><td align=\"left\">4.65</td><td align=\"left\">162</td><td align=\"left\">62.79</td></tr><tr><td align=\"left\">PgTCP13-01</td><td align=\"left\">41</td><td align=\"left\">13.23</td><td align=\"left\">36</td><td align=\"left\">11.61</td><td align=\"left\">8</td><td align=\"left\">2.58</td><td align=\"left\">225</td><td align=\"left\">72.58</td></tr><tr><td align=\"left\">PgTCP15-01</td><td align=\"left\">41</td><td align=\"left\">27.33</td><td align=\"left\">26</td><td align=\"left\">17.33</td><td align=\"left\">7</td><td align=\"left\">4.67</td><td align=\"left\">76</td><td align=\"left\">50.67</td></tr><tr><td align=\"left\">PgTCP22-04</td><td align=\"left\">47</td><td align=\"left\">13.20</td><td align=\"left\">44</td><td align=\"left\">12.36</td><td align=\"left\">10</td><td align=\"left\">2.81</td><td align=\"left\">255</td><td align=\"left\">71.63</td></tr><tr><td align=\"left\">PgTCP24-33</td><td align=\"left\">77</td><td align=\"left\">18.33</td><td align=\"left\">49</td><td align=\"left\">11.67</td><td align=\"left\">6</td><td align=\"left\">1.43</td><td align=\"left\">288</td><td align=\"left\">68.57</td></tr><tr><td align=\"left\">PgTCP25-25</td><td align=\"left\">25</td><td align=\"left\">33.33</td><td align=\"left\">19</td><td align=\"left\">25.33</td><td align=\"left\">6</td><td align=\"left\">8.00</td><td align=\"left\">25.00</td><td align=\"left\">33.33</td></tr><tr><td align=\"left\">PgTCP05</td><td align=\"left\">137</td><td align=\"left\">42,27</td><td align=\"left\">26</td><td align=\"left\">8.20</td><td align=\"left\">5</td><td align=\"left\">1.58</td><td align=\"left\">152</td><td align=\"left\">47.95</td></tr><tr><td align=\"left\">PgTCP07-01</td><td align=\"left\">33</td><td align=\"left\">22.76</td><td align=\"left\">9</td><td align=\"left\">6.21</td><td align=\"left\">8</td><td align=\"left\">5.52</td><td align=\"left\">95</td><td align=\"left\">65.52</td></tr><tr><td align=\"left\">PgTCP10</td><td align=\"left\">45</td><td align=\"left\">14.95</td><td align=\"left\">40</td><td align=\"left\">13.29</td><td align=\"left\">10</td><td align=\"left\">3.32</td><td align=\"left\">206</td><td align=\"left\">68.44</td></tr><tr><td align=\"left\">PgTCP14</td><td align=\"left\">41</td><td align=\"left\">12.20</td><td align=\"left\">41</td><td align=\"left\">12.20</td><td align=\"left\">12</td><td align=\"left\">3.57</td><td align=\"left\">242</td><td align=\"left\">72.02</td></tr><tr><td align=\"left\">PgTCP21</td><td align=\"left\">63</td><td align=\"left\">17.21</td><td align=\"left\">52</td><td align=\"left\">14.21</td><td align=\"left\">19</td><td align=\"left\">5.19</td><td align=\"left\">232</td><td align=\"left\">63.39</td></tr></tbody></table></table-wrap>" ]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM5\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM6\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM7\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Chang Liu and Tingting Lv contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12870_2024_4729_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig4_HTML\" id=\"MO4\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig5_HTML\" id=\"MO5\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig6_HTML\" id=\"MO6\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig7_HTML\" id=\"MO7\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig8_HTML\" id=\"MO8\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig9_HTML\" id=\"MO9\"/>", "<graphic xlink:href=\"12870_2024_4729_Fig10_HTML\" id=\"MO10\"/>" ]
[ "<media xlink:href=\"12870_2024_4729_MOESM1_ESM.xlsx\"><caption><p><bold>Additional file 1: Table S1.</bold> Basic information of <italic>PgTCP</italic> gene family.</p></caption></media>", "<media xlink:href=\"12870_2024_4729_MOESM2_ESM.xlsx\"><caption><p><bold>Additional file 2: Table S2.</bold> The identified genes used as evolutionary controls for <italic>PgTPC</italic> gene phylogenetic analysis.</p></caption></media>", "<media xlink:href=\"12870_2024_4729_MOESM3_ESM.xlsx\"><caption><p><bold>Additional file 3: Table S3.</bold> The classification, annotation and GO functional categorization of the <italic>PgTCP</italic> gene transcripts.</p></caption></media>", "<media xlink:href=\"12870_2024_4729_MOESM4_ESM.xlsx\"><caption><p><bold>Additional file 4: Table S4.</bold> The expressions of the PgTCP gene transcripts in 14 tissues, 42 cultivars' roots and 4 aged roots (TPM).</p></caption></media>", "<media xlink:href=\"12870_2024_4729_MOESM5_ESM.xlsx\"><caption><p><bold>Additional file 5: Table S5.</bold> Significance analysis of correlation between <italic>PgTCP</italic> and ginsenoside.</p></caption></media>", "<media xlink:href=\"12870_2024_4729_MOESM6_ESM.xlsx\"><caption><p><bold>Additional file 6: Table S6.</bold> Significance analysis of <italic>PgTCPs</italic> expression levels with key enzyme genes.</p></caption></media>", "<media xlink:href=\"12870_2024_4729_MOESM7_ESM.xlsx\"><caption><p><bold>Additional file 7: Table S7.</bold> Protein sequences of foreign species.</p></caption></media>" ]
[{"label": ["1."], "surname": ["Hemmerly"], "given-names": ["TE"], "article-title": ["A ginseng farm in Lawrence County"], "source": ["Tennessee Econ Bot"], "year": ["1977"], "volume": ["31"], "issue": ["2"], "fpage": ["160"], "lpage": ["162"], "pub-id": ["10.1007/BF02866586"]}, {"label": ["7."], "surname": ["Balusamy", "Rahimi", "Sukweenadhi", "Kim", "Yang"], "given-names": ["SRD", "S", "J", "Y", "D"], "article-title": ["Exogenous methyl jasmonate prevents necrosis caused by mechanical wounding and increases terpenoid biosynthesis in Panax ginseng"], "source": ["Plant Cell Tissue Organ Cult"], "year": ["2015"], "volume": ["123"], "issue": ["2"], "fpage": ["341"], "lpage": ["348"], "pub-id": ["10.1007/s11240-015-0838-8"]}, {"label": ["11."], "surname": ["Min", "Chen", "Zhang", "Li", "Liu", "Li", "Ju", "Fang"], "given-names": ["Z", "L", "Y", "Z", "M", "WP", "Y", "Y"], "article-title": ["VvBRC inhibits shoot branching in grapevine"], "source": ["Sci Hortic"], "year": ["2021"], "volume": ["289"], "fpage": ["110370"], "pub-id": ["10.1016/j.scienta.2021.110370"]}, {"label": ["14."], "surname": ["Sarvepalli", "Nath"], "given-names": ["K", "U"], "article-title": ["Interaction of TCP4-mediated growth module with phytohormones"], "source": ["Plant Signal Behav"], "year": ["2014"], "volume": ["6"], "issue": ["10"], "fpage": ["1440"], "lpage": ["1443"], "pub-id": ["10.4161/psb.6.10.17097"]}, {"label": ["28."], "surname": ["Feng", "Xu", "Liu", "Zhang", "Hu", "Gong"], "given-names": ["Z", "S", "N", "G", "Q", "Y"], "article-title": ["Soybean TCP transcription factors: evolution, classification, protein interaction and stress and hormone responsiveness"], "source": ["Plant Physiol Bioch"], "year": ["2018"], "volume": ["127"], "fpage": ["129"], "lpage": ["142"], "pub-id": ["10.1016/j.plaphy.2018.03.020"]}, {"label": ["35."], "surname": ["Wang", "Jiang", "Sun", "Lin", "Yin", "Wang", "Zhang"], "given-names": ["K", "S", "C", "Y", "R", "Y", "M"], "article-title": ["The spatial and temporal transcriptomic landscapes of Ginseng, Panax ginseng C"], "source": ["A Meyer Sci Rep"], "year": ["2016"], "volume": ["5"], "issue": ["1"], "fpage": ["18283"], "pub-id": ["10.1038/srep18283"]}, {"label": ["43."], "surname": ["Li", "Wang", "Zhao", "Li", "Jiang", "Zhu", "Chen", "Wang", "Sun", "Chen"], "given-names": ["L", "K", "M", "S", "Y", "L", "J", "Y", "C", "P"], "article-title": ["Selection and validation of reference genes desirable for gene expression analysis by qRT-PCR in MeJA-treated ginseng hairy roots"], "source": ["PLoS One"], "year": ["2019"], "volume": ["14"], "issue": ["12"], "fpage": ["e226168"], "pub-id": ["10.1371/journal.pone.0226168"]}, {"label": ["46."], "surname": ["Yao", "Ma", "Wang", "Zhang"], "given-names": ["X", "H", "J", "DB"], "article-title": ["Genome-wide comparative analysis and expression pattern of TCP gene families in Arabidopsis thaliana and Oryza sativa"], "source": ["J Integr Plant Biol"], "year": ["2007"], "volume": ["49"], "issue": ["6"], "fpage": ["885"], "lpage": ["897"], "pub-id": ["10.1111/j.1744-7909.2007.00509.x"]}]
{ "acronym": [], "definition": [] }
47
CC BY
no
2024-01-14 23:43:47
BMC Plant Biol. 2024 Jan 13; 24:47
oa_package/43/e3/PMC10787463.tar.gz
PMC10787464
0
[ "<title>Introduction</title>", "<p id=\"Par30\">The population of older adults is increasing rapidly, both in numbers and as a share of the total. According to the World Population Prospects report published in 2022, the share of the global population at ages 65 and above is projected to rise from 10% in 2022 to 16% in 2050 [##UREF##0##1##]. This demographic change necessarily requires novel eldercare strategies that can efficiently cope with the growing burden of healthcare and medical costs [##REF##33755570##2##]. One particular challenge is the healthcare of aging people with frailty. Frailty is characterized by decreased physiologic reserves and resistance, increased vulnerability to acute stressors, and an overall decline in functional capacity [##REF##36188769##3##–##REF##27634957##5##]. In most cases, it is related to aging, disability, and comorbidity - however, because of its complexity and multidimensionality, it is a difficult term to conceptualize [##REF##24004497##6##]. Fried et al. [##UREF##1##4##] first developed a phenotype of frailty, which defines it as a clinical syndrome considering various symptoms and signs with a distinct focus on musculoskeletal function. Currently, this is the most frequently used approach for identifying affected patients in clinical practice and research settings [##REF##27634957##5##, ##REF##26362356##7##]. The Fried phenotype includes five criteria to determine if a person is frail or not: Exhaustion, self-reported unintentional weight loss, low physical activity, as well as objective measures of weak grip strength and slow gait speed. Individuals with three or more present criteria are considered as „frail“, those with one or two criteria as „pre-frail“, and those with no criteria of the above as „non-frail“. As frail older adults are particularly prone to falls, report particularly frequently on fear of falling, and frequently suffer from postural stability disorders and gait abnormalities [##REF##15468016##8##–##REF##14687346##10##], a detailed assessment of selected biomechanical parameters of gait could provide new insights as to how interventions might be designed to improve ambulatory capabilities in this vulnerable population.</p>", "<p id=\"Par31\">Gait initiation (GI) is the transient phase from a quiet standing posture to steady state walking [##REF##10575076##11##–##REF##29184756##15##]. It requires the integration of different sensory information from the somatosensory, vestibular, and visual systems, as well as the coordination of multiple skeletal muscles [##REF##16271566##16##, ##REF##27656138##17##]. Deficits in these functional areas lead to an increased potential risk for falls [##UREF##3##18##–##REF##27965561##20##]. Since most falls in older persons occur due to the inability to respond appropriately to an impaired balance and its ineffective compensation [##REF##11809584##21##], parameters during GI may be sensitive indicators for detecting previously hidden issues and diseases.</p>", "<p id=\"Par32\">GI can be described by two main phases: As shown in Fig. ##FIG##0##1##, after the preparatory (postural) phase (also called “anticipatory postural adjustments”), follows the phase of actual stepping (“execution phase”) [##REF##11959411##22##–##REF##10668774##24##]. During the preparatory phase, the center of mass (CoM) decouples from the center of pressure (CoP), thereby giving the body the necessary momentum to fall forward about the ankle joint [##REF##10200394##25##–##UREF##4##27##]. This phase can be divided into two sub-phases: a release phase and an unloading phase [##UREF##5##28##]. During the release phase, the CoP is shifted toward the swing leg, resulting in an increasing horizontal ground reaction force thereby accelerating the CoM in the opposite direction [##REF##9862305##29##]. It lasts until the farthest posterolateral movement of the CoP (① in Fig. ##FIG##0##1##), and its change in direction marks the beginning of the following unloading phase. Here, the CoP moves rapidly toward the stance leg (② in Fig. ##FIG##0##1##), thus unloading the swing leg for step execution (③ in Fig. ##FIG##0##1##) [##UREF##4##27##]. The second main phase, the execution phase, starts as soon as the swing leg is no longer in contact with the ground and ends with the toe-off of the initial stance leg. It can be subdivided into a single support phase and a double support phase. The single support phase lasts from the toe-off of the swing leg until it contacts the ground again (④ in Fig. ##FIG##0##1##), leading to the double support phase which ends with the toe-off of the prior stance leg ⑤ in Fig. ##FIG##0##1## [##UREF##4##27##].</p>", "<p id=\"Par33\">Previous studies that have utilized GI to evaluate postural control have been mostly limited to age-related changes without considering the interindividual differences regarding health status and functioning [##REF##15196517##9##]. In addition, previous studies have mainly focused on biomechanical parameters during the preparatory phase, omitting parameters during the actual execution of the very first step. However, impairments of measurable parameters during step execution have been shown to correlate with fall events [##REF##25128155##30##–##REF##22955865##32##]. Therefore, examining all sub-phases of GI in frail older individuals is crucial for a deeper understanding of the effects of frailty on motor patterns in this fall-prone population. This analysis could also provide the basis for improved diagnostics and targeted therapies, ultimately reducing the incidence of falls and improving the overall quality of life for this vulnerable population.</p>", "<title>Aim</title>", "<p id=\"Par34\">This study examines whether spatial and temporal parameters of gait initiation differ between groups of older adults with different levels of frailty, and whether fear of falling, and balance ability are correlated with the height of lifting the food during gait initiation. We hypothesize that, due to poor physical function, the different sub-phases, and, consequently, the total duration of GI is elongated, and the first step length is shortened in older adults with frailty compared to age-mates without frailty. Regarding the maximum foot clearance during the first step, two opposite assumptions are conceivable: Either, also because of poor physical condition, the foot is raised lower or, because of increased fear of falling and lower confidence in balance, it is higher as a protective mechanism.</p>" ]
[ "<title>Methods</title>", "<title>Participants</title>", "<p id=\"Par35\">All participants were grouped based on the score of Fried’s Frailty phenotype model [##UREF##1##4##] into the groups “Non-frail” (<italic>n</italic> = 36, frailty score = 0), “Pre-frail” (<italic>n</italic> = 14, frailty score = 1 or 2), and “Frail” (<italic>n</italic> = 11, frailty score = 3, 4 or 5) (see Table ##TAB##0##1## for details).\n</p>", "<p id=\"Par36\">Included in the study were participants able to walk without walking aids. Exclusion criteria were: cognitive impairment (<underline>&lt;</underline> 24 points in the Mini-Mental-Status-Test (MMSE) according to Folstein et al. [##REF##1202204##34##] or a severely limited mobility that precludes independent care (e.g., bedridden). The latter was determined during a screening interview and was considered fulfilled if the participant was largely able to move independently within the home. Participants with severe visual impairments, uncontrolled cardiovascular disorders, uncontrolled Parkinson’s syndrome, acute chronic obstructive bronchitis, or acute states of confusion (e.g., delirium) were also not eligible to participate in this study.</p>", "<p id=\"Par37\">All participants gave their written and oral consent. The study was approved by the independent medical Ethics Committee at the RWTH Aachen Faculty of Medicine (ethics committee number 142/18).</p>", "<title>Instruments</title>", "<p id=\"Par38\">The study was performed in the motion analysis laboratory of the department of geriatric medicine of the university hospital RWTH Aachen, Germany. A three-dimensional optical motion capture system (Qualisys AB, 5+ series, Göteburg, Sweden) with 10 cameras tracked the marker trajectories at 120 Hz. In total, 52 reflective markers were placed at anatomical landmarks on participants’ bodies following a prescribed marker set protocol [##UREF##7##35##]. The calibrated anatomical system technique (CAST) was used to place and determine the movement of segments. The measurements were done using Qualisys Track Manager (Version 19.1, Qualisys AB, Gothenburg, Sweden). After markers labeling at the Qualisys Track Manager software, raw data were exported to .c3d for further analysis with the software Visual 3D (Version 6.0, C-Motion. Inc., Germantown, MD, USA). Force data were recorded by two force plates (Bertec Corporation, Columbus, Ohio, USA), which were embedded in the surface in the middle of a 10-m walkway. The movement and force data were filtered using a fourth-order low-pass Butterworth filter with a cut-off frequency of 5 Hz.</p>", "<title>Frailty assessment</title>", "<p id=\"Par39\">In all participants, the five criteria of Fried’s phenotype of frailty [##UREF##1##4##] were assessed before GI data collection: unintentional weight loss, subjectively perceived fatigue, low physical activity, slow walking speed, and muscle weakness. For this purpose, questions were first asked about unintentional weight loss of more than 5 kg within the last year and about subjectively perceived fatigue. Last-mentioned was done by the “Fatigue assessment according to Fried”, which takes up two questions of the Center for Epidemiologic Studies Depression Scale [##REF##3950011##36##]. Using a short version of the Minnesota Leisure Time Physical Activity Questionnaire [##REF##748370##37##], physical activity was assessed by asking about various leisure time activities within the last 4 weeks. Walking speed was measured over a 4.57 m walking distance, and finally, to detect possible muscle weakness, strength measurement of the dominant hand was performed three times with calculation of the mean value. We used Fried’s cut-off values to assess the grip strength. One point was awarded for each deficit in one of the five categories. If one to two categories are fulfilled, the classification as “pre-frail” is made, from three as “frail”. Moreover, to evaluate the fear of falling and the balance ability of the old participants, the questionnaires of the Falls Efficacy Scale-International (FES-I) [##UREF##8##38##, ##REF##16900450##39##] and the Activities-Specific Balance Confidence Scale (ABC) [##UREF##9##40##, ##REF##18327692##41##] were collected before starting the GI trials.</p>", "<title>Experimental protocol to analyze gait initiation</title>", "<p id=\"Par40\">For the measurement process, each participant was initially asked to stand quietly on a force platform in a relaxed posture on both legs. Both feet were then placed in a parallel position on the first force plate with the toes close to the second one. The width was not dictated and should correspond to their natural stance. Acquisition of force and motion data was triggered, just before the participants received a verbal cue, to begin walking. In response to the cue, they initiated gait with their leading leg at their usual walking pace until the end of the movement lab which corresponded to a walking distance of about 4 m. To become familiar with the experimental protocol, each participant first performed a practice trial. The practice trial was then immediately followed by five data collection trials. Each participant had the opportunity to take a break after a trial to avoid any exhaustion effects. For the study, every participant wore comfortable clothing, including a t-shirt, shorts, and anti-slip socks.</p>", "<title>Calculation of the biomechanical parameters</title>", "<p id=\"Par41\">To describe GI, it was subdivided into the four sub-phases described above. Parameters, including the duration of the release phase (s), unloading phase (s), single support phase (s), and double support phase (s), were calculated. We used specific events to automatically identify the distinct phases by using the analysis software Visual 3D. The start of GI, and therefore also of the release phase, was defined to be 0.15 s before the minimum velocity of the CoP in the walking direction. The furthest point of posterolateral CoP displacement then marked the beginning of the unloading phase. The following single support phase started as soon as the toes of the swinging leg lost contact with the ground. The last sub-phase, the double support phase, was defined by the recontact of the heel of the swinging leg with the ground and ended with the lift-off of the toes of the initial stance leg.</p>", "<p id=\"Par42\">The total duration of GI and the percentages of each sub-phase on the total duration of a respective study participant were calculated separately.</p>", "<p id=\"Par43\">The length of the first step (m) was calculated between the first toe off-event of the swing phase and the initial contact of the foot with the force plate.</p>", "<p id=\"Par44\">The maximum foot clearance (max. FC) during the first step (m) was calculated by the maximum value of displacement of a marker at the midfoot. The marker is a virtually created marker, whose position was determined centrally, i.e. at a 50% distance between the real markers at the toe and heel of the feet.</p>", "<title>Statistical analysis</title>", "<p id=\"Par45\">Descriptive statistics (mean and standard deviation (SD)) were calculated for demographic data (age, height, weight, and BMI) and each determined parameter from the arithmetic mean values of the five trials per person. Between-group differences in the total duration of GI, the durations of the four sub-phases, the step length of the first step, and the max. FC were tested with a one-way analysis of variance (ANOVA) for continuous variables. Bonferroni-adjusted post-hoc analysis was used during follow-up testing.</p>", "<p id=\"Par46\">Since the duration of the sub-phases is also affected by a change in the total duration of the GI, we found that the relative durations of the sub-phases to the total duration of the GI is another interesting aspect to illuminate. Therefore, we additionally calculated the relative proportion (%) of the phase durations of the sub-phases in relation to the total duration of the GI. Therefore, group differences in the percentages of the different phase durations of GI were tested statistically with a one-way multivariate analysis of variance (MANOVA). Follow-up tests on separate univariate ANOVAs were conducted when appropriate. The level of significance was 0.05.</p>", "<p id=\"Par47\">In addition to comparing the max. FC during the first step between groups, we also investigated the results of the FES-I and ABC for a possible correlation with this parameter. This was done for all participants (<italic>n</italic> = 61) to determine if there is an correlation between max. FC and fear of falling and/or confidence in balance, regardless of the participant’s frailty score. For this purpose, Spearman’s rank correlation was computed for each case. The interpretation of the effect strength was based on the classification according to Cohen [##UREF##6##33##]. Accordingly, the effect limits are 0.10–0.29 (weak), 0.30–0.49 (moderate), and greater or equal to 0.5 (strong).</p>", "<p id=\"Par48\">All statistical tests were performed using IBM SPSS Statistics Version 27 (Armonk, New York, USA).</p>" ]
[ "<title>Results</title>", "<p id=\"Par49\">Of initially 92 adults measured, 31 participants were not included in the data analysis due to insufficient data acquisition and/or quality and the application of exclusion criteria. Ultimately, the data of <italic>n</italic> = 61 participants aged 65 years and older were analyzed. The female to male ratio was 20/16, 8/6, and 2/9 for the non-frail, pre-frail and frail group, respectively. There were no significant differences between the groups with respect to height, weight, and BMI, but age and the scores FES-I and ABC (Table ##TAB##0##1##). Pre-frail people were not significantly older than the non-frail participants, but the mean age of the frail group was 6 years higher than that of the non-frail group (about 79 compared to 73 years) which was significant (Table ##TAB##1##2##). The frail group showed a significantly higher FES-index than the non-frail group, and a significantly increased ABC index than both, non-frail and pre-frail group.\n</p>", "<p id=\"Par50\">The GI variables unloading phase duration, double support phase duration, the total duration, and length of step 1 showed significant differences between the three groups (Table ##TAB##0##1##). For release phase duration, single support phase duration, and maximum FC during the first step, the differences between groups were not significant.</p>", "<p id=\"Par51\">Post-hoc tests with Bonferroni corrections revealed that the unloading and double support and, in consequence, total duration of GI was significantly longer in the frail than the non-frail group (Table ##TAB##1##2##, Fig. ##FIG##1##2##a). The pre-frail group values were in-between the values of the two other groups without significant differences to both. A one-way MANOVA found no significant differences between the groups regarding the percentages of the sub-phases, <italic>F</italic>(6, 112) = 1.782, <italic>p</italic> = 0.109, partial η<sup>2</sup> = 0.087). However, on closer inspection of the percentage distribution of the individual sub-phases, it becomes evident that there is a notable increase in the percentage of the unloading phase and double support phase, while there is a corresponding decrease in the percentage of the release phase and single support phase with increasing frailty (Fig. ##FIG##1##2##b). The length of the first step of pre-frail and frail people was significantly smaller than that of the non-frail group (Table ##TAB##1##2##).</p>", "<p id=\"Par52\">Spearman’s rank correlation was computed to assess the relationship between the max. FC during the first step and both questionnaires (FES-I and ABC) (see Fig. ##FIG##2##3## and Fig. ##FIG##3##4##). Between the FES-I and the max. FC a moderate negative correlation was found, <italic>r</italic>(59) = − 0.31, <italic>p</italic> = 0.016. Between the ABC and max. FC a moderate positive correlation was found, <italic>r</italic>(59) = 0.32, <italic>p</italic> = 0.012. The higher the fear of falling, or the lower the confidence in balance in old people, the lower the foot was lifted during the first step.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par53\">The main goal of this study was to describe and analyze the gait initiation task in old individuals during different frailty stages. Our hypotheses of increased duration for GI and a decreased first step length because of reduced physical function in frail people were supported by our results, whereas for the time no significant difference between pre-frail and frail patients was shown. Apart from the frailty status, older adults show increased duration for GI and shorter step length compared to the young reference group. Previous studies described a gait strategy involving decreased gait speed and shortened step length to stabilize dynamic balance [##REF##23949441##42##, ##REF##22717010##43##]. Slow gait speed in general is one of the most established parameter for defining individuals as pre-frail or frail [##REF##23949441##42##], and has already been the focus of various previous gait analyses, e.g. [##REF##22717010##43##] or Kressig et al. [##REF##15196517##9##]. Notably, when we look at the results for the individual sub-phases, the absolute duration of the release phase during GI did not differ significantly between the groups and was even similar to the young reference group. However, by analyzing the percentage duration of the release phase on the total duration for GI, a noticeable shortening in pre-frail and frail older adults can be observed. During this phase, the CoP first shifts towards the swing leg thereby allowing a forward momentum. A shortening may cause insufficient weight transfer and movement thus leading to a more unstable GI that is prone to falls. The resulting lengthening of both, the percentage and absolute duration of the unloading phase, implies that the CoP moves more slowly toward the stance leg, which in turn leads to the overall slower gait of frail adults. Upon closer examination of the absolute times, the double support phase shows the most recognizable difference besides the total time, which is even more evident in comparison to the young reference group. Also, the percentage double support phase lengthens with increased frailty, and the percentage single support phase shortens. This in turn results in a decreased step length, as evidenced by the decreased step length associated with a higher frailty score. Among others Mbourou et al. [##REF##12457046##44##] and Kwon et al. [##UREF##10##45##] examined the duration of the double support phase during the GI task period in older fallers, all noticing a much smaller first step length and a longer duration of the double support phase congruent to our findings for frail participants. Besides the absolute time, also the percentage time of the double support phase on GI increased with frailty. Therefore, the lengthening of the double support period has a direct impact on gait characteristics and may be used in frail adults to stabilize their inefficient gait control.</p>", "<p id=\"Par54\">Taken together, our results suggest that frailty leads to a more cautious and conservative gait strategy. This is immediately evident when starting walking, as individuals with frailty tend to maintain dynamic balance by reducing gait velocity and taking shorter steps to prevent falls. Previous studies have already shown that older individuals walk more slowly and with shorter steps than young people [##REF##10200394##25##, ##REF##9862305##29##, ##UREF##11##46##]. Our research demonstrates that the frailty syndrome leads to a further deterioration of these parameters during GI. Additionally, we found that frailty is associated with a shortened portion of the release phase, indicating uncertainty in walking off. So, in the future, analysis of the GI or the very first step could be sufficient to identify biomechanical parameters that indicate increased gait insecurity and fall risk, without requiring a comprehensive gait analysis.</p>", "<p id=\"Par55\">Except for the first step length, a significant difference was always demonstrated between non-frail and frail adults, while the pre-frail and frail groups did not differ for any of the parameters.</p>", "<p id=\"Par56\">Nevertheless, there were clearly noticeable trends for the groups, which also allow conclusions to be drawn for older individuals with greater frailty: Frail patients experience significant delays in GI compared to non-frail counterparts, without a clear trend in maximum FC. Individuals with higher fear of falling tend to lower their max. FC, aiming to stay closer to the ground, potentially minimizing fall distance and aiding quick recovery. Additionally, a positive association with the ABC score suggests that lifting the foot requires adequate self-confidence in balance. However, the practicability of using FC as a frailty assessment tool remains uncertain.</p>", "<p id=\"Par57\">Some limitations of this study must be considered. In general, the participants should be more evenly distributed in the groups, and the small group size of pre-frail, respectively frail adults, should be considered. For instance, to improve scatter plot distribution, it would be valuable to include participants with higher FES-I and lower ABC scores. Another limitation worth mentioning is that the initial contact of the foot used to delimit one step may have been constituted with either the medial foot or the heel. Although this variability is characteristic of the gait initiation of frail elderly people and, therefore, the movement pattern of this population, it may have affected the temporal and spatial phases of gait initiation.</p>", "<p id=\"Par58\">Analyzing movement patterns of older adults and, particularly, frail individuals proved to be a challenging task. Nevertheless, we were able to identify significant trends. Notably, significant age differences exist between frailty groups, yet analyzing age independently lacks clinical utility. Future research should verify results’ transferability with larger samples, especially including severely frail participants.</p>", "<p id=\"Par59\">We found a moderate correlation between the fear of falling respectively the confidence in balance and the maximum food clearance during the first step. However, the correlation was driven by a single participant with very low confidence in balance respectively high fear of falling. Thus, final conclusions on these correlations should be based on data of a group with a more equal distribution of the fear of falling respectively confidence in balance.</p>", "<p id=\"Par60\">Recognizing that our results were derived from a controlled laboratory setting, their direct application to real-life scenarios might be limited. Our results are to be tested and verified with simpler measurement methods. Inertial sensors as simpler and cheaper devices may provide a valid and more realizable alternative for measuring e. g. overall GI time in clinical routine [##REF##22955865##32##, ##REF##25557982##47##, ##REF##22255828##48##]. Our results, gathered in a controlled lab setting and focusing on straight walking, may not directly apply to real-life scenarios. Factors like footwear, varied terrains, and changing directions in daily activities influence movement and balance differently. Thus, while our findings mark the initial phase for new diagnostic tools, their direct translation to everyday situations might be limited. Yet, these findings pave the way for developing and adapting diagnostic tools for everyday use.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par61\">In summary, we have found that prolonged times for GI and a shorter first step length are associated with higher frailty. Therefore, spatiotemporal parameters in GI exhibit potential as predictors of functional decline and fall risk associated with frailty. This insight could streamline the classification of frail patients, aiding in timely interventions to prevent physical decline and falls. However, while our study points to the potential of targeted exercise interventions, specifically focusing on improving GI times, randomized controlled trials are necessary to validate their efficacy in fall prevention among the elderly.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Gait initiation is challenging for older individuals with poor physical function, particularly for those with frailty. Frailty is a geriatric syndrome associated with increased risk of illness, falls, and functional decline. This study examines whether spatial and temporal parameters of gait initiation differ between groups of older adults with different levels of frailty, and whether fear of falling, and balance ability are correlated with the height of lifting the food during gait initiation.</p>", "<title>Methods</title>", "<p id=\"Par2\">Sixty-one individuals aged <underline>&gt;</underline> 65 years, classified by Fried frailty phenotype, performed five self-paced gait initiation trials. Data was collected using a three-dimensional passive optical motion capture system, consisting of 10 cameras with the ability to perceive reflective markers, and two force plates. The total duration of gait initiation and the duration of its four sub-phases, the first step length, and the maximum foot clearance during the first step were derived, and compared statistically between groups. Additionally, an association analysis was conducted between foot clearance and fear of falling, and confidence in balance in older individuals.</p>", "<title>Results</title>", "<p id=\"Par3\">Frail individuals had significantly longer unloading durations, and total durations of gait initiation compared to non-frail older adults. Additionally, they had shorter first step lengths compared to non-frail older adults. Pre-frail older adults also showed shorter steps compared to the non-frail group. However, there were no significant differences between groups for the maximum foot clearance during the first step. Nevertheless, the maximum foot clearance of older individuals correlated significantly with their fear of falling and confidence in balance.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Older adults with reduced physical function and signs of frailty mainly display longer duration of gait initiation and decreased first step length compared to non-frail older adults. The release phase is decreased as the double support phase is prolonged in frail patients. This information can guide the development of specialized exercise programs to improve mobility in this challenging motion between static and dynamic balance.</p>", "<title>Keywords</title>", "<p>Open Access funding enabled and organized by Projekt DEAL.</p>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We would like to thank all participants for taking part in this study and for their kind consent to the utilization of their data.</p>", "<title>Authors’ contributions</title>", "<p>JH performed the measurements. TL, JB, CB, and FH were involved in planning and supervising the work. JH and JB processed the experimental data and performed the analysis. JH took the lead in writing the manuscript and designed the figs. HS aided in interpreting the results and worked on the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>Open Access funding enabled and organized by Projekt DEAL. We would like to thank The Robert Bosch Stiftung, whose financial support in the funding project “Department of Geriatric Medicine, at the medical faculty of RWTH Aachen University” (grant number 32.5.1140.0009.0) made the establishment of the movement laboratory possible in the first place. Apart from this, the presented work did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.</p>", "<title>Availability of data and materials</title>", "<p>The raw data used to support the conclusion of this article are available from the corresponding authors upon request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par62\">The research related to human use complies with all the relevant national regulations, institutional policies and was performed under the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board (EK 142/18). All participants gave.</p>", "<p id=\"Par63\">their written and oral consent.</p>", "<title>Competing interests</title>", "<p id=\"Par64\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Phases of gait initiation</p><p><italic>Notes</italic>. Overview of the phases of gait initiation and the characteristic pattern of center of pressure (CoP, colored solid line), and center of mass (CoM, dashed black line) displacement during each sub-phase</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Graphic illustration of the changes in the durations</p><p><italic>Notes. </italic>Total duration of GI and its division into the four sub-phases in seconds (<bold>a</bold>), and, in comparison, the distribution of the percentages of the sub-phases (<bold>b</bold>) of total GI duration</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Correlation between the maximum foot clearance and the score of the Falls Efficacy Scale-International questionnaire</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Correlation between the maximum foot clearance and the score of the Activities-specific Balance confidence scale</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Means ± Standard Deviations of characteristics of the study participants and the GI variable per group and results of ANOVA on differences between the means</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th>Criteria</th><th>Non-frail (<italic>n</italic> = 36)</th><th>Pre-frail (<italic>n</italic> = 14)</th><th>Frail (<italic>n</italic> = 11)</th><th>F(2,58)</th><th><italic>p</italic></th><th>Effect size (η<sup>2</sup>)</th></tr></thead><tbody><tr><td><bold>Age (years)</bold></td><td>72.89 ± 6.02</td><td>75.07 ± 4.73</td><td>78.91 ± 7.62</td><td>4.22</td><td><bold>0.019</bold></td><td>0.13</td></tr><tr><td><bold>Height (cm)</bold></td><td>168.56 ± 7.37</td><td>166.86 ± 6.67</td><td>166.55 ± 9.58</td><td>0.43</td><td>0.653</td><td>0.02</td></tr><tr><td><bold>Weight (kg)</bold></td><td>73.55 ± 14.14</td><td>76.38 ± 16.93</td><td>74.66 ± 20.94</td><td>0.16</td><td>0.856</td><td>0.01</td></tr><tr><td><bold>BMI (kg/m</bold><sup><bold>2</bold></sup><bold>)</bold></td><td>25.71 ± 3.56</td><td>27.31 ± 5.04</td><td>26.76 ± 6.24</td><td>0.73</td><td>0.488</td><td>0.02</td></tr><tr><td><bold>Test scores</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td><bold>FES-I</bold></td><td>17.81 ± 1.72</td><td>19.31 ± 2.84</td><td>22.91 ± 7.71</td><td>7.90*</td><td><bold>&lt; 0.001</bold></td><td>0.22</td></tr><tr><td><bold>ABC</bold></td><td>95.44 ± 5.84</td><td>86.79 ± 10.21</td><td>68.70 ± 22.87</td><td>22.69</td><td><bold>&lt; 0.001</bold></td><td>0.44</td></tr><tr><td><bold>GI variables</bold></td><td/><td/><td/><td/><td/><td/></tr><tr><td><bold>Release phase duration (s)</bold></td><td>0.25 ± 0.04</td><td>0.23 ± 0.03</td><td>0.24 ± 0.05</td><td>1.32</td><td>0.274</td><td>0.04</td></tr><tr><td><bold>Unloading phase duration (s)</bold></td><td>0.28 ± 0.05</td><td>0.31 ± 0.09</td><td>0.34 ± 0.06</td><td>4.38</td><td><bold>0.017</bold></td><td>0.13</td></tr><tr><td><bold>Single support phase duration (s)</bold></td><td>0.40 ± 0.04</td><td>0.40 ± 0.05</td><td>0.43 ± 0.05</td><td>2.73</td><td>0.074</td><td>0.09</td></tr><tr><td><bold>Double support phase duration (s)</bold></td><td>0.16 ± 0.05</td><td>0.18 ± 0.05</td><td>0.21 ± 0.05</td><td>4.85</td><td><bold>0.011</bold></td><td>0.14</td></tr><tr><td><bold>Total duration (s)</bold></td><td>1.08 ± 0.11</td><td>1.12 ± 0.15</td><td>1.22 ± 0.13</td><td>6.05</td><td><bold>0.004</bold></td><td>0.17</td></tr><tr><td><bold>Step length step 1 (m)</bold></td><td>0.58 ± 0.08</td><td>0.50 ± 0.09</td><td>0.44 ± 0.07</td><td>14.13</td><td><bold>&lt;  0.001</bold></td><td>0.33</td></tr><tr><td><bold>Max. FC during the first step (cm)</bold></td><td>4.30 ± 1.26</td><td>3.79 ± 0.10</td><td>4.16 ± 1.29</td><td>0.92</td><td>0.403</td><td>0.03</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Results of the post-hoc tests for variables with significant differences between groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th rowspan=\"2\">Dependent variable</th><th rowspan=\"2\">Groups compared</th><th rowspan=\"2\">Mean difference</th><th colspan=\"2\">95% Confidence Interval</th><th rowspan=\"2\"><italic>p</italic></th></tr><tr><th>Lower Bound</th><th>Upper Bound</th></tr></thead><tbody><tr><td rowspan=\"3\"><bold>Age</bold></td><td>Non-frail - pre-frail</td><td>−2.18</td><td>−6.90</td><td>2.54</td><td>0.776</td></tr><tr><td>Non-frail - frail</td><td>−6.02</td><td>−11.18</td><td>−0.86</td><td><bold>0.017</bold></td></tr><tr><td>Prefrail - frail</td><td>−3.84</td><td>−2.20</td><td>9.87</td><td>0.367</td></tr><tr><td rowspan=\"3\"><bold>FES</bold></td><td>Non-frail - pre-frail</td><td>−1.50</td><td>−4.48</td><td>1.48</td><td>0.657</td></tr><tr><td>Non-frail - frail</td><td>−5.10</td><td>−8.28</td><td>−1.93</td><td><bold>&lt; .001</bold></td></tr><tr><td>Prefrail - frail</td><td>−3.60</td><td>−7.38</td><td>0.17</td><td>0.066</td></tr><tr><td rowspan=\"3\"><bold>ABC</bold></td><td>Non-frail - pre-frail</td><td>8.66</td><td>− 0.34</td><td>17.65</td><td>0.063</td></tr><tr><td>Non-frail - frail</td><td>26.74</td><td>16.90</td><td>36.58</td><td><bold>&lt; .001</bold></td></tr><tr><td>Prefrail - frail</td><td>18.08</td><td>−29.59</td><td>−6.58</td><td><bold>&lt; .001</bold></td></tr><tr><td rowspan=\"3\"><bold>Unloading phase duration (s)</bold></td><td>Non-frail - pre-frail</td><td>−0.03</td><td>−0.08</td><td>0.02</td><td>0.440</td></tr><tr><td>Non-frail - frail</td><td>−0.07</td><td>− 0.12</td><td>− 0.01</td><td><bold>0.018</bold></td></tr><tr><td>Prefrail - frail</td><td>−0.03</td><td>−0.10</td><td>0.03</td><td>0.601</td></tr><tr><td rowspan=\"3\"><bold>Double support phase duration (s)</bold></td><td>Non-frail - pre-frail</td><td>−0.02</td><td>−0.06</td><td>0.02</td><td>0.452</td></tr><tr><td>Non-frail - frail</td><td>−0.05</td><td>−0.09</td><td>− 0.01</td><td><bold>0.011</bold></td></tr><tr><td>Prefrail - frail</td><td>−0.03</td><td>−0.08</td><td>0.02</td><td>0.454</td></tr><tr><td rowspan=\"3\"><bold>Total GI duration (s)</bold></td><td>Non-frail - pre-frail</td><td>−0.04</td><td>−0.14</td><td>0.06</td><td>0.925</td></tr><tr><td>Non-frail - frail</td><td>−0.15</td><td>−0.26</td><td>− 0.04</td><td><bold>0.003</bold></td></tr><tr><td>Prefrail - frail</td><td>−0.11</td><td>−0.24</td><td>0.02</td><td>0.103</td></tr><tr><td rowspan=\"3\"><bold>Step length step 1 (m)</bold></td><td>Non-frail - pre-frail</td><td>0.09</td><td>0.02</td><td>0.15</td><td><bold>0.005</bold></td></tr><tr><td>Non-frail - frail</td><td>0.14</td><td>0.07</td><td>0.21</td><td><bold>&lt; .001</bold></td></tr><tr><td>Prefrail - frail</td><td>0.05</td><td>−0.03</td><td>0.13</td><td>0.375</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>Note. <italic>p</italic>-values &lt; 0.05 are indicated in bolt. For FES, the F-value is given for 2 and 57 degrees of freedom. According to Cohen [##UREF##6##33##], the limits for the size of the effect are 0.01 (small effect), 0.06 (medium effect) and 0.14 (large effect)</p></table-wrap-foot>", "<table-wrap-foot><p>Note. <italic>p</italic>-values &lt; 0.05 are indicated in bolt</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Laurentius and Hannah Lena Siebers these authors contributed equally to the work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"11556_2024_335_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"11556_2024_335_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"11556_2024_335_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"11556_2024_335_Fig4_HTML\" id=\"MO4\"/>" ]
[]
[{"label": ["1."], "mixed-citation": ["Department of Economic and Social Affairs; Gerland P, Hertog S, Wheldon M, Kantorova V, Gu D, Gonnella G, Williams I, Zeifman L, Bay G, Castanheira H, Kamiya Y, Bassarsky L, Gaigbe-Togbe V, Spoorenberg T. World Population Prospects 2022: Summary of Results Ten key messages. 2022. "], "ext-link": ["https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/wpp2022_summary_of_results.pdf"]}, {"label": ["4."], "surname": ["Fried", "Tangen", "Walston", "Newman", "Hirsch", "Gottdiener"], "given-names": ["LP", "CM", "J", "AB", "C", "J"], "article-title": ["Frailty in older adults: evidence for a phenotype"], "source": ["Gerontol A Biol Sci Med Sci."], "year": ["2001"], "volume": ["56"], "issue": ["3"], "fpage": ["146"], "lpage": ["156"], "pub-id": ["10.1093/gerona/56.3.M146"]}, {"label": ["12."], "surname": ["Carls\u00f6\u00f6"], "given-names": ["S"], "article-title": ["The initiation of walking"], "source": ["Cells Tissues Organs"], "year": ["1966"], "volume": ["65"], "fpage": ["1"], "lpage": ["9"], "pub-id": ["10.1159/000142864"]}, {"label": ["18."], "surname": ["Patla", "Frank", "Winter", "Bsc", "Prentice Bsc", "Prasad"], "given-names": ["AE", "JS", "DA", "R", "S", "S"], "article-title": ["Age-related changes in balance control system\u00a0: initiation of stepping"], "source": ["Clin Biomech."], "year": ["1993"], "volume": ["8"], "issue": ["4"], "fpage": ["179"], "lpage": ["184"], "pub-id": ["10.1016/0268-0033(93)90012-7"]}, {"label": ["27."], "surname": ["Richards"], "given-names": ["J"], "source": ["The comprehensive textbook of clinical biomechanics"], "year": ["2018"], "edition": ["2"], "publisher-name": ["Elsevier Health Sciences"]}, {"label": ["28."], "surname": ["Archer", "Winter", "Prince"], "given-names": ["SE", "DA", "F"], "article-title": ["Initiation of gait: a comparison between young, elderly, and Parkinson\u2019s disease subjects"], "source": ["Gait Posture."], "year": ["1994"], "volume": ["2"], "issue": ["1"], "fpage": ["56"], "pub-id": ["10.1016/0966-6362(94)90056-6"]}, {"label": ["33."], "surname": ["Cohen"], "given-names": ["J"], "source": ["Statistical Power Analysis for the Behavioral Sciences"], "year": ["1988"], "edition": ["2"], "fpage": ["79"], "lpage": ["81"]}, {"label": ["35."], "surname": ["Cappozzo", "Catani", "Della Croce", "Leardini"], "given-names": ["A", "F", "U", "A"], "article-title": ["Position and orientation in space of bones during movement: anatomical frame definition and determination"], "source": ["Clin Biomech."], "year": ["1995"], "volume": ["10"], "issue": ["4"], "fpage": ["171"], "lpage": ["178"], "pub-id": ["10.1016/0268-0033(95)91394-T"]}, {"label": ["38."], "mixed-citation": ["Tinetti ME, Richman D, Powell L. Falls efficacy as a measure of fear of falling. J Gerontol Psychol Sci. 1990;45:239\u201343. Available from: "], "ext-link": ["http://geronj.oxfordjournals.org/"]}, {"label": ["40."], "surname": ["Powell", "Myers"], "given-names": ["LE", "AM"], "article-title": ["The activities-specific balance confidence (ABC) scale"], "source": ["J Gerontol: Med Sci."], "year": ["1995"], "volume": ["50"], "issue": ["1"], "fpage": ["M28"], "lpage": ["M34"], "pub-id": ["10.1093/gerona/50A.1.M28"]}, {"label": ["45."], "surname": ["Kwon", "Kwon", "Park", "Kim"], "given-names": ["MS", "YR", "YS", "JW"], "article-title": ["Comparison of gait patterns in elderly fallers and non-fallers"], "source": ["Technology and health care"], "year": ["2018"], "publisher-name": ["IOS Press"], "fpage": ["427"], "lpage": ["436"]}, {"label": ["46."], "surname": ["Lu", "Amundsen Huffmaster", "Harvey", "MacKinnon"], "given-names": ["C", "SL", "JC", "CD"], "article-title": ["Anticipatory postural adjustment patterns during gait initiation across the adult lifespan"], "source": ["Gait Posture."], "year": ["2017"], "volume": ["1"], "issue": ["57"], "fpage": ["182"], "lpage": ["187"], "pub-id": ["10.1016/j.gaitpost.2017.06.010"]}]
{ "acronym": [ "ABC", "ANOVA", "BMI", "CAST", "cm", "CoM", "CoP", "df", "F(v1, v2)", "FC", "FES-I", "GI", "Hz", "Inc.", "MANOVA", "max.", "m", "MMSE", "n", "η2", "p", "R2", "s", "SD", "USA" ], "definition": [ "Activities-specific Balance confidence scale", "One-way analysis of variance", "Body mass index", "Calibrated anatomical system technique", "Centimeter", "Center of mass", "Center of pressure", "Degrees of freedom", "\nF-value with v1 and v2 degrees of freedom", "Foot clearance", "Falls Efficacy Scale-International", "Gait initiation", "Hertz", "Incorporated", "One-way multivariate analysis of variance", "Maximum", "Meter", "Mini-Mental State Examination", "Total number of individuals", "Effect size", "\np-value", "Coefficient of determination", "Second", "Standard deviation", "United States of America" ] }
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2024-01-14 23:43:47
Eur Rev Aging Phys Act. 2024 Jan 13; 21:1
oa_package/1e/1c/PMC10787464.tar.gz
PMC10787465
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[ "<title>Introduction</title>", "<p id=\"Par7\">Despite advances in modern materials and techniques, dental treatments will fail. Direct restorations and crowns fail for various reasons, and replacements constitute a larger proportion of treatment provided than the initial placement of restorations [##REF##11405031##1##]. For example, 5% of newly made dentures are replaced within two years, and 15% of root canal treatments require re-intervention or extraction within three years [##REF##25676179##2##, ##REF##32359852##3##]. Dental treatment that fails within a short time frame is a financial burden on the patient, dentist or public health system.</p>", "<p id=\"Par8\">Like other paid goods and services, dental patients will understandably want assurances and pose the question: “how long will this last?” Unfortunately, the answer to this question is seldom straightforward and not directly addressed in the literature. There are a number of important parameters, which include: the average longevity, CL<sub>50</sub> (clinical longevity time where 50% of treatments have failed), annual failure and success rates. However, none of these measures can predict how long a dental treatment will last.</p>", "<p id=\"Par9\">Some countries’ public health and insurance systems have policies regarding quality assurance in dentistry and remediation for failed treatment. A recommendation was made to the United Kingdom’s National Health Service in 2009 that the free replacement period for restorations should be three years, with the burden of cost on the provider [##UREF##0##4##]. In Mumbai, India, a social enterprise (Swasth) provides dental warranties of up to three years, provided patients come for preventative check-up appointments, which are more frequent for smokers. Anecdotally, they have found that the warranty incentivised patients to opt for more expensive treatment rather than extractions, access timely care and improve oral hygiene habits [##UREF##1##5##]. The Swedish guarantee insurance system covers most public and private dentists. For prosthetic treatment, retreatment is covered for two years for fixed prosthodontics and one year for removable prosthodontics [##REF##1624199##6##, ##REF##1476054##7##]. However, there is little formal longevity assurance for patients in private practice globally, including in New Zealand. Failed dental treatment is often repaired or replaced within a poorly defined timeline at the clinician’s discretion. A formal limited warranty in private dentistry is an emerging concept, but currently with poor uptake.</p>", "<p id=\"Par10\">Hopenwasser (2017) concluded that, since most practices are already providing replacement work for free, “why not make it into a positive marketing bonus?” [##UREF##2##8##]. This practice believes their warranty improves patient confidence and helps their recall program. Various practices in different countries, including New Zealand, advertise warranties on their websites, ranging from one to three years for composite resin restorations, up to five years for crown and bridgework, up to three years for dentures and five years for endodontic treatment. However, after a comprehensive review of the literature and to the authors’ knowledge, there are no empirical studies regarding dental warranties.</p>", "<p id=\"Par11\">Therefore, the rationale for this study was to provide data for the underinvestigated topic of dental warranties, which could be useful in informing practice and policy. The aims were to investigate and compare longevity estimates for dental treatment, expectations for free remedial treatment, and attitudes toward a formal dental warranty between dentists, students, and patients.</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par12\">This was a mixed-method cross-sectional survey using convenience sampling for participant recruitment. General dental practitioners were recruited at a monthly branch meeting of the Auckland Dental Association. Inclusion criteria included general dental practitioners who were currently in practice. Retired dentists, specialist dentists, and dentists who were practising in a purely academic or educational setting were excluded. All [##REF##1779219##27##] dental students who were undertaking their final year at the University of Otago, Auckland Dental Facility, were recruited. Patients aged 18 and over were recruited from the reception area of the Otago University, Auckland Dental Facility. Both new and existing patients were invited to complete the survey while awaiting their appointment in the reception area. Patients with experience working in the dental field were excluded from the survey. Patients were not excluded based on oral or general health status. As this was an exploratory pilot study, a sample size calculation was not undertaken.</p>", "<p id=\"Par13\">Two hard-copy surveys were developed, one for dentists and students and another for patients (see appendix). The surveys contained some multiple-choice options but the majority of responses required written answers in the dentist and student surveys. In addition, participant demographic characteristics were collected. Data were collected across four treatment modalities: direct restorative, crowns, dentures, and endodontic treatment. Questions for dentists and students included treatment longevity estimates; free remediation times; reasons for failure covered; and attitudes, length and conditions on warranties. This was a mixed-methods study with questions requiring quantitative and qualitative responses with a mixture of multi-choice and open-ended responses. The patient survey included diagrams and descriptions of each treatment type and questions related to previous treatment experience, and expectations about longevity and free remedial treatment.</p>", "<p id=\"Par14\">All participants were required to read the information sheet and provide written consent prior to taking part in the survey. Ethical approval for the study was obtained from the University of Otago Human Ethics Committee (D21/386). Participant anonymity was maintained as no identifiable data were collected for the purpose of analysis. Data collection occurred in a ten-day working period in July 2021.</p>", "<p id=\"Par15\">Ethnicity group data were cleansed prior to analysis and presented using prioritised ethnicity groups in accordance with Statistics New Zealand prioritisation guidelines [##UREF##3##9##]. Data were analysed using SPSS v27. No surveys were excluded from the analysis. Missing data were handled using pairwise deletion. Descriptive statistics included means and standard deviations (SD). Statistical evaluation of differences in the mean values according to the participant group (dentist, student, or patient) was performed with Mann-Whitney U tests. Chi-square tests compared dentists’ and students’ willingness to issue a warranty. Pearson correlation tests were used to analyse correlations between patient age and longevity estimates and dentists’ years in practice and longevity estimates, free remediation times, and warranty times. The level of significance was set at <italic>p</italic> &lt; 0.05. Qualitative data were analysed thematically to uncover underlying themes within the responses. This analysis involved a careful, manual coding process, where responses were initially examined to identify key concepts and ideas. These were then systematically organised and iteratively refined into broader themes that accurately captured the primary insights and perspectives expressed by the participants. Our thematic analysis was predominantly inductive, allowing themes to naturally emerge from the data without being constrained by preconceived categories. To illustrate the participants’ viewpoints, representative quotes have been selected.</p>" ]
[ "<title>Results</title>", "<title>Demographic findings</title>", "<p id=\"Par16\">Overall, 27 students, 28 dentists, and 43 patients responded to the survey. As a result of the convenience sampling method, the response rate was unknown. The mean age of the patients was 47.1 ± 15.4. Table ##TAB##0##1## shows participant characteristics. All students were final year dental students.</p>", "<p id=\"Par17\">\n\n</p>", "<title>Willingness to issue warranties</title>", "<p id=\"Par18\">The professional status and the willingness to issue warranties for various treatments are shown in Fig. ##FIG##0##1##. Crowns were perceived to be the most warrantable, followed by direct restorations, dentures and, lastly, endodontics. Significantly, more students were willing to issue a warranty on endodontic treatment than dentists (<italic>p</italic> = 0.04). Binary logistic regression showed age, gender, ethnicity, and years in practice were not significantly associated with willingness to issue a warranty.</p>", "<p id=\"Par19\">\n\n</p>", "<title>Reasons for free remediation</title>", "<p id=\"Par20\">The reasons for failure that would warrant free repair, replacement or refund of posterior composite resins and crowns are shown in Figs. ##FIG##1##2## and ##FIG##2##3##. Fractured or lost restoration and crowns are the predominant reasons for failure that warrant free remedial treatment or refund.</p>", "<p id=\"Par21\">\n\n</p>", "<p id=\"Par22\">\n\n</p>", "<title>Longevity estimates, free remediation and warranty times</title>", "<p id=\"Par23\">The professionals’ views on longevity, free remediation time and warranty period for direct restorations, crowns, dentures and endodontics are shown in Table ##TAB##1##2##. Only numerical responses were included in this table. Invalid or missing responses were excluded. Although students had lower estimates for posterior composite restoration longevity, there was no significant difference in the mean warranty time. There was no significant difference between dentist and student longevity estimates for crowns, but students’ mean remediation time was significantly lower. The students’ warranty times for crowns were too variable to draw any comparison with the dentists, as they ranged from six months to ten years. Students expected dentures to last nine years, significantly longer than dentists who expected their dentures to last 6.5 years. A Pearson correlation test showed no significant correlation between dentists’ years in practice and longevity estimates, remediation times or warranty times. Most dentists indicated they would remediate failed restorations and crowns, adjust dentures but would not reline dentures or refund for failed endodontics.</p>", "<p id=\"Par24\">\n\n</p>", "<p id=\"Par26\">Numerical data for patients’ previous experience, longevity estimates, and free remediation expectations are shown in Table ##TAB##2##3##. Patients expected posterior fillings to last much longer than dentists and students (<italic>p</italic> &lt; 0.01). There is little variation in longevity estimates across different treatment modalities. Patients expected all dental treatment to last around 11 years. There were a number of missing or invalid responses and non-numerical answers such as ‘don’t know’ or ‘forever’ in the patient questionnaire. The proportion of patients estimating treatment would last forever was 14% for posterior fillings and crowns, 19% for root canal treatment and 21% for dentures. These estimates, as well as missing or invalid responses, were excluded from statistical analysis. A Pearson correlation test was conducted between patient age and the expected longevity of the treatment. There was a moderate positive correlation between patient age and expected longevity of a posterior filling, r(28) = 0.476, <italic>p</italic> = 0.027; and between patient age and expected longevity of a crown r(28) = 0.528, <italic>p</italic> = 0.017. No significant associations were found between patient age and expected longevity of complete dentures or root canal treatment. Binary logistic regression showed age, gender and ethnicity were not significantly associated with an expectation of free remediation.</p>", "<p id=\"Par27\">\n\n</p>", "<title>Qualitative findings</title>", "<title>Direct restorations</title>", "<p id=\"Par28\">There was a general hesitancy about issuing warranties for direct restorative dentistry. Variability in patient factors that influence restoration survival was the main reason cited, but there were a few limited circumstances where it was thought to be more reasonable.</p>", "<p>\n\n</p>", "<p id=\"Par30\">The notion of a warranty is better received by students than dentists. Many perceived it to be only fair.</p>", "<p>\n\n</p>", "<p id=\"Par32\">Although fewer, some dentists agreed.</p>", "<p>\n\n</p>", "<p id=\"Par34\">Several students commented that they felt there needed to be further education in university about the subject of warranties.</p>", "<p id=\"Par35\">When asked what conditions might be placed about a direct restorative warranty, the most common condition listed by dentists related to patient attendance, stating that the patient must adhere to the prescribed examination and hygiene recall period and promptly attend an appointment to report any issues. In contrast, virtually no students felt patient attendance should be a warranty condition. Dentists and students agreed that adequate homecare should be included as a condition and that only certain modes of failure would be included. The consensus was that mechanical failure of the restoration due to operator error would be covered, but failure related to the underlying tooth would not. Dentists and students agreed that if there was a discussion relating to poor prognosis or if an alternative treatment was recommended but declined (i.e. a crown), this treatment would be excluded from warranty. In general, patients with parafunctional habits were excluded from warranty.</p>", "<title>Crowns</title>", "<p id=\"Par36\">Crowns were perceived to be more warrantable than direct restorative, although similar hesitations apply. Some dentists perceived a warranty on crowns to be more reliable as the material is generally also warranted by the laboratory. A few students commented that a crown warranty would be a good idea as it could be used as a marketing tool, attract more patients, and encourage patients to opt for more expensive treatment. Some students also thought a warranty would be mutually beneficial for the patient and the dentist.</p>", "<p>\n\n</p>", "<p id=\"Par38\">The same warranty conditions that applied for restorative dentistry were listed for crowns. This included patient attendance, adequate homecare, mechanical failure only, and not for teeth with poor prognoses. A few dentists would only offer a warranty if the providing laboratory also warranted the material.</p>", "<title>Dentures</title>", "<p id=\"Par39\">In general, dentists and students felt that a warranty on dentures was not appropriate. Dentists felt dentures were too difficult to warrant, largely because patients’ abilities to cope with dentures vary.</p>", "<p id=\"Par41\">Students’ viewpoints were more varied, with no consensus. However, a few of the students who left a comment responded positively to the notion.</p>", "<p>\n\n</p>", "<p id=\"Par43\">When asked to list conditions they would place on a warranty for dentures, dentists, and students felt the mode of failure and attendance at review appointments were most important. However, there was no real consensus about what modes of failure would be covered under warranty. Modes of failure that were discussed included fracture, general wear, and aesthetics. Some participants specifically included these in the warranty, while others explicitly excluded them.</p>", "<title>Endodontics</title>", "<p id=\"Par44\">Dentists and students were unanimous in their opposition to a warranty for endodontics. They felt that warranting endodontic treatment was risky, commenting on its ‘unpredictability’ as it ‘does not have a 100% success rate.’ The consensus was that the risk of failure should be strongly emphasised during the informed consent process and, therefore, not covered by a warranty. Dentists and students both felt that endodontic treatment is essentially a biological issue and, therefore, it is perceived as the riskiest treatment to warrant. The difficulty of cases and lack of confidence were expressed among students. Dentists commented that they refer difficult cases to specialists.</p>", "<p>\n\n</p>", "<p id=\"Par46\">Because most dentists and students would never consider a warranty of endodontic treatment, the conditions listed are essentially arbitrary. However, the consensus was that to be eligible for a warranty, a fault must be demonstrated within the initial endodontic treatment, and there would be a requirement for an indirect coronal restoration placed within a prescribed time frame.</p>" ]
[ "<title>Discussion</title>", "<title>Patient expectation of treatment longevity</title>", "<p id=\"Par47\">This survey found that patients’ longevity estimates were much more optimistic than dentists or students, with a significant proportion ranging from 14 to 21% expecting various dental treatments to last forever. There were significant disparities in expectations of posterior composite resin longevity between patients and practitioners found in the present study. Older patients tended to expect posterior fillings and crowns to last longer. In a study on dental implants, a significant proportion of patients perceived dental implant treatment as life-lasting. A lower education level was associated with some of these misconceptions [##REF##34346146##10##]. Educational level was not investigated in the present study but could be an area of future investigation. In another study on maxillofacial prostheses, optimistic patient expectations were again noted [##REF##15733133##11##]. This highlights some concerning and unrealistic expectations that some patients have around the longevity of dental treatment, which might be sources of dissatisfaction.</p>", "<title>Practitioner expectation of treatment longevity</title>", "<p id=\"Par48\">Dentists and students were asked to estimate how long their treatment would last but were not given a clinical scenario or patient profile, as in a previous study by Maryniuk and Kaplan (1986). In the context of warranties in the present study, this was deemed inappropriate, as a warranty would need to cover a range of scenarios. Patients will inevitably ask their providers how long they should expect treatment to last, but the answer may not be straightforward. Dentist and student longevity estimates are relevant because this should be reflected in their communication with patients. Disparities between practitioner longevity estimates and longevity reported in the literature may result in inaccurate information being relayed to the patient.</p>", "<p id=\"Par49\">The question “how long does treatment last?” is not directly addressed in the literature.</p>", "<p id=\"Par50\">In the search for treatment longevity, meta-analyses often report annual failure rates or success rates for a specified time interval based on Kaplan-Meier survival curves [##REF##26003655##12##–##REF##17594372##18##]. This data is difficult to understand for the patient and does not directly answer the question. Cross-sectional data reports median survival time or ‘clinical longevity time’ (CL<sub>50</sub>), the survival time for 50% of restorations, which may better answer the question, but these study designs have limitations [##REF##25676179##2##, ##REF##10933556##19##–##REF##29977023##21##]. No single parameter directly answers this question. In general, it appears that students and dentists are conservative in their estimates of the longevity of their own treatment. Studies of dentists and dental students show mean and median composite resin survival times of around 7.5-8 years [##REF##10933556##19##, ##REF##29999041##20##, ##REF##30517477##22##]. Dentists and students in the present study expected their posterior composite restorations to last 6.75 and 5.5 years, respectively. Approximately half of all crowns will last 15 years [##REF##29977023##21##] but dentists and students expected the longevity of their crowns to be around 11 years and 10 years, respectively. These estimates are similar to findings in a study of American dentists who estimated their cast restorations to last 12 years [##UREF##4##23##]. Although 14% of patients expected crowns to last forever, those who accepted the possibility of failure expected crowns to last 12 years, which is comparable to dentists’ expectations.</p>", "<p id=\"Par51\">Students expected dentures to last significantly longer than dentists, 9 years compared to 6.5 years. Compared to a recent meta-analysis, both groups are pessimistic about their denture longevity, as complete dentures had a mean longevity of 10.1 years [##REF##32359852##3##].</p>", "<p id=\"Par52\">Dentists expected their root canal treatments to last 8.5 years, while students expected them to last 10.3 years. Failure was not defined in the present study. There is a distinction between success rates (periapical healing) and survival rates (tooth survival) in the literature. In one study, median survival was 10 years (periapical healing) and 21 years (tooth survival), recognising that a tooth may serve in function for a considerable time despite the presence of a periapical lesion [##REF##22205268##13##]. The hesitancy towards warranting root canal treatment may be partially explained by the inconsistency of the definition of failure in the literature.</p>", "<p id=\"Par53\">It seems, then, that clinicians lack the information to answer the question “how long does it last?” accurately. Perhaps they are better equipped to answer, “how long <italic>should</italic> it last?”. While they might not be able to directly answer how long a treatment will last for a patient, they might have a better idea of the minimum acceptable length of service for their treatment.</p>", "<p id=\"Par54\">Failure for each treatment modality was not defined in the survey and could have been interpreted differently by the participants, resulting in inaccurate longevity estimates. However, in the context of warranties, clinicians would be required to define failure, which was left open for qualitative questioning.</p>", "<p id=\"Par55\">Expected longevity estimates may reflect a clinician’s skills, knowledge, and experience. Patient demographic, socioeconomic and behavioural factors have been demonstrated to influence restoration longevity [##REF##22192253##24##]. Students, compared to dentists, had lower expectations for treatment longevity. This might reflect a lower level of experience and confidence. However, they had higher estimates for the longevity of endodontic treatment and dentures. Dentists’ years in practice were not shown to be associated with longevity estimates. The student perspective may be more influenced by university education. In general, compared to the literature, both dentists and students in our study are pessimistic.</p>", "<title>Expectations for free remediation</title>", "<p id=\"Par56\">Patients expect free remediation for failed fillings, crowns, and endodontic treatment. dentists and students are prepared to meet these expectations within a specified time frame. However, most patients would not expect any free maintenance for dentures. Most dentists and students would adjust dentures for free within a specified time period, but a significant proportion would not reline for free. There is a large discrepancy in expectations for endodontic treatment. If root canal treatment failed and required specialist referral, roughly half of dentists and students would not offer a refund, but almost two-thirds of patients would expect a refund or free remedial treatment. In general, while most clinicians would provide free remediation for treatment that fails within a time frame, the patients appear to disagree about the length of this time frame. However, this difference was not shown to be statistically significant in this study. Remediation types (repair, replace or refund) were pooled into a single category for this study, but it is reasonable to believe that dentists might be more willing to repair or replace failed treatment than they are to refund. Similarly, patient expectations for different remediation types may differ. Further studies could examine patient expectations for differing remediation types.</p>", "<title>Willingness to issue warranties</title>", "<p id=\"Par57\">In general, most dentists are unwilling to issue dental warranties for any treatment. Students are more willing to issue warranties, with half willing to issue warranties for direct restorations and dentures, while two-thirds are willing to issue a warranty for crowns. The difference may be attributed to different practising environments or levels of experience. Students practice in a university environment, where patients pay for low-cost dentistry, and the liability of any free remedial treatment falls on the university. Most dentists in the survey operate in private practice and bear the financial burden of any free remedial treatment covered under warranty.</p>", "<title>Perceptions and conditions on warranty</title>", "<p id=\"Par58\">Crowns, in general, are perceived to be the most warrantable treatment by dentists and students, followed by direct restorations, dentures and, lastly, endodontic treatment. The hesitancy towards offering warranties on dental treatment is due to the variability in factors that influence treatment outcomes, which cannot all be attributed to the dentist. The consensus for direct restorations and crowns is that only mechanical failure of the material would be covered under warranty, and the patient must demonstrate adequate homecare. The most common condition listed by dentists was adherence to examination and hygiene recalls, but students felt this was inconsequential. This may reflect the lack of continuity of care and recall in undergraduate studies. Failures related to the underlying tooth, such as endodontic complications or secondary caries, were typically excluded from warranty. The suggested warranty period by dentists and students is approximately 18 months for restorations. These conditions in an 18-month warranty period would be relatively ‘safe’ for the clinician. The majority of failures that occur within the first year are due to endodontic complications. Recent reviews conclude that caries and fractures are the main reasons for failure, and both of these are typically present in later years [##REF##26003655##12##, ##REF##26116767##14##, ##REF##25048250##17##]. The most common reasons for crown replacement include crown fracture, aesthetics, and secondary caries [##REF##12736961##25##]. Under the most commonly agreed warranty conditions, failure due to crown fracture would be included, although aesthetics and secondary caries are generally excluded.</p>", "<p id=\"Par59\">Dentists felt it was too difficult to warrant dentures because of the variability of a patient’s ability to cope. They may be justified in their hesitance as relatively high failure rates of 5% within the first two years of denture provision may represent lost dentures, manufacturing defects, poor denture design, or immediate dissatisfaction [##REF##32359852##3##]. Ten to fifteen per cent of patients are dissatisfied with new and technically well-made dentures [##REF##8406961##26##].</p>", "<p id=\"Par60\">Only one in ten dentists and a third of students would consider issuing a warranty for endodontic treatment (<italic>p</italic> = 0.04). Therefore, the warranty period and conditions suggested are largely arbitrary. Hypothetically, if dentists and students were to offer a warranty on endodontic treatment, they would only cover failure where fault can be demonstrated in the initial endodontic treatment, and they would have prosthetic requirements. These conditions are reasonable, as intraoperative factors are the primary reasons for the persistence or progression of apical periodontitis [##REF##20158529##15##], and a crown increases the chances of periapical healing and tooth survival [##REF##22205268##13##] while significantly decreasing the chance of tooth fracture [##REF##1779219##27##].</p>", "<title>Limitations</title>", "<p id=\"Par61\">One challenge in writing the questionnaires is posing questions that are simple enough to be understood by the patient but can be compared to the dentist and student survey. Missing data particularly for the patient group, due to misinterpretation, or lack of knowledge around particular dental treatment modalities may introduce bias. A low proportion of patients had previous experience with crowns and dentures, rendering their responses partly invalid. However, these responses might mimic the scenario of a patient receiving that treatment for the first time and provide insight into the expectations of this specific patient group.</p>", "<p id=\"Par62\">Another important limitation was the study’s relatively small sample size, making it difficult to obtain statistically significant data even though a number of trends were detected.</p>", "<p id=\"Par63\">Any generalising from our findings should be done with caution. Dentistry in New Zealand is largely privately funded out-of-pocket, with limited provision for insurance-based payment or publicly funded dentistry. The perspectives on warranties for dentists who provide insurance-based or public-based dentistry require further investigation. Most patients in the study paid out-of-pocket but received heavily subsidised treatments, meaning they may have different expectations from full-fee paying patients in private practice. The opinions of students may also be influenced by this university environment.</p>", "<p id=\"Par64\">Furthermore, the sample was also not representative of dentists and patients in New Zealand. There may be selection bias due to the overrepresentation of female and less experienced dentists. Previous studies have demonstrated that female and less experienced dentists provided shorter longevity estimates [##REF##19039686##28##]. This might explain the conservative longevity estimates from dentists in this study. The ethnic distribution of participants in this study is not representative of the overall New Zealand population, so any generalising about ethnicity should be done cautiously.</p>", "<p id=\"Par65\">Despite these limitations, to the authors’ knowledge, this is the first study investigating perspectives on the notion of a dental warranty. Additionally, few studies have investigated patient expectations around treatment longevity and remediation for failed treatment. Therefore, identifying disparities in the dentist’s and the patient’s expectations, such as restoration longevity and failed root canal remediation, is clinically important as it highlights potential sources of patient dissatisfaction requiring better patient education and communication.</p>", "<title>Future research</title>", "<p id=\"Par66\">One of the strengths of this study is the breadth and large number of variables collected. It highlights several interesting observations that fuel curiosity for further research. Therefore, this study serves as a foundation for future research into dental warranties and patient education. The authors suggest that studies repeat the quantitative element with a larger, more representative sample size, with a revised questionnaire to reduce missing data. Data were not collected separately for remediation types (repair, replace or refund) in this study. It is valid to assume willingness for repair, replacement, and refund would be different. Future research could focus more closely on these types of remediation and analyse them separately with larger sample sizes.</p>", "<p id=\"Par67\">The patient survey should be further simplified to increase valid responses. Patients should be able to answer questions on treatments they have received in the past to increase the relevance of their expectations. Building on the qualitative findings in this study, interviews could be designed to further explore the perspectives on the notion of a dental warranty and understand some of the reasons for disparities. The present study has no qualitative element for patients, and an interview study design is recommended for future studies into patient expectations and perspectives.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par68\">Our study reveals that within New Zealand, dentists generally show reluctance to provide formal warranties on dental treatments, often citing the variability of factors affecting treatment outcomes. Conversely, dental students appear more inclined towards offering warranties. Both groups, however, demonstrate a willingness to offer free remediation or refunds for failed treatments, with the notable exception of root canal procedures. Interestingly, our findings indicate that patients typically hold more optimistic expectations regarding the longevity of dental treatments than both dentists and students, with older patients exhibiting even higher expectations. While these conclusions are primarily applicable to the population receiving dental services at Otago University, they may also provide valuable insights into broader trends in patient expectations and professional attitudes towards dental warranties, which could be relevant in similar healthcare contexts.</p>" ]
[ "<title>Objectives</title>", "<p id=\"Par1\">To investigate and compare estimates of the longevity of dental treatment, expectations for free remedial treatment, and attitudes about formal dental warranties among dentists, students, and patients.</p>", "<title>Materials and methods</title>", "<p id=\"Par2\">This is a mixed-method cross-sectional questionnaire survey with convenience sampling from dentists, dental students, and patients in New Zealand. A questionnaire was distributed to New Zealand dentists (<italic>n</italic> = 28) and final-year dental students (<italic>n</italic> = 27). A separate questionnaire was provided to patients in a university dental clinic (<italic>n</italic> = 43). Mann-Whitney U, Chi-square and Pearson Correlation, and Binary logistic regression tests were used to test for differences between groups and correlations amongst variables. Qualitative data were analysed thematically.</p>", "<title>Results</title>", "<p id=\"Par3\">Dentists believed that their posterior composite resin restorations would last longer (<italic>p</italic> = 0.014), would remediate failed crowns for longer (<italic>p</italic> = 0.002) and would provide longer crown warranties (<italic>p</italic> = 0.003) compared to students. Patients had higher expectations for restoration longevity and free remediation for failed treatment. Students were generally more willing to provide warranties. Crowns were perceived to be the most warrantable, while endodontic treatment was the least warrantable. Recall attendance, mechanical failure, and adequate oral hygiene were commonly proposed as warranty conditions for restorations and crowns. There was little consensus about complete dentures and endodontic treatment.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">There are significant disparities between the expectations of patients and clinicians regarding treatment longevity and free remediation times. Clinicians, in general, are willing to provide free remediation within a specified time frame, except for endodontic treatment, but are hesitant to provide formal dental warranties.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12903-024-03860-3.</p>", "<title>Keywords</title>" ]
[ "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Author contributions</title>", "<p>D.R. proposed the original idea. After modification in conjunction with B.L. and Z.M., B.L. collected the data and wrote the first draft of the manuscript. This was edited by Z.M., D.R. and B.L. with Z.M. assisting with the tables.</p>", "<title>Funding</title>", "<p>The study was self-funded by the authors.</p>", "<title>Data availability</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par70\">All participants were required to read the information sheet and provide written informed consent prior to taking part in the survey. Ethical approval for the study was obtained from the University of Otago Human Ethics Committee (D21/386).</p>", "<title>Consent for publication</title>", "<p id=\"Par71\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par69\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Professional status and willingness to issue warranties for various treatments. *<italic>p</italic> &lt; 0.05 Chi squared test</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Reasons for failure warranting free repair, replacement or refund of a posterior composite resin restoration by dentists and students</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Reasons for failure warranting free repair, replacement or refund of a crown by dentists and students</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Participant characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Dentist (%)</th><th align=\"left\">Student (%)</th><th align=\"left\">Patient (%)</th></tr></thead><tbody><tr><td align=\"left\">\n<bold>Ethnicity</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Māori</td><td align=\"left\"/><td align=\"left\">3 (11.1%)</td><td align=\"left\">8 (18.6%)</td></tr><tr><td align=\"left\">NZ European</td><td align=\"left\">8 (28.6%)</td><td align=\"left\">1 (3.7%)</td><td align=\"left\">16 (37.2%)</td></tr><tr><td align=\"left\">Pacific Islander</td><td align=\"left\">1 (3.6%)</td><td align=\"left\">6 (22.2%)</td><td align=\"left\">11 (25.6%)</td></tr><tr><td align=\"left\">Asian</td><td align=\"left\">18 (64.3%)</td><td align=\"left\">17 (63%)</td><td align=\"left\">4 (9.3%)</td></tr><tr><td align=\"left\">Other</td><td align=\"left\">1 (3.6%)</td><td align=\"left\"/><td align=\"left\">3 (7%)</td></tr><tr><td align=\"left\">Missing</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">1 (2.3%)</td></tr><tr><td align=\"left\">\n<bold>Gender</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Male</td><td align=\"left\">17 (60.7%)</td><td align=\"left\">14 (51.9%)</td><td align=\"left\">21 (48.8%)</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">11 (39.3%)</td><td align=\"left\">13 (48.1%)</td><td align=\"left\">22 (51.2%)</td></tr><tr><td align=\"left\">\n<bold>Practice</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Private Practice</td><td align=\"left\">24 (85.7%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">DHB/Community</td><td align=\"left\">3 (10.7%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">University</td><td align=\"left\">7 (25%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Years in Practice</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">0–9</td><td align=\"left\">12 (42.9%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">10–19</td><td align=\"left\">7 (25%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">20–29</td><td align=\"left\">4 (14.3%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">30+</td><td align=\"left\">5 (17.9%)</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">\n<bold>Total</bold>\n</td><td align=\"left\">28</td><td align=\"left\">27</td><td align=\"left\">43</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Professional’s views on the longevity, free remediation, and warranty times for various treatment modes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Treatment Mode</th><th align=\"left\">Provider</th><th align=\"left\">Mean Longevity (months ± SD,n)</th><th align=\"left\">Mean Remediation Time<sup>a</sup><break/>(months ± SD n)</th><th align=\"left\">Would Not Remediate<sup>a</sup><break/>(n)</th><th align=\"left\">Mean Warranty Time<break/>(months ± SD n)</th></tr></thead><tbody><tr><td align=\"left\">Posterior Composite</td><td align=\"left\">Dentist</td><td char=\"?\" align=\"char\">80.6 ± 27.8* (28)</td><td align=\"left\">16.0 ± 10.7 (25)</td><td align=\"left\">(0)</td><td char=\"?\" align=\"char\">17.0 ± 14.5 (26)</td></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td char=\"?\" align=\"char\">64.6 ± 24.9* (27)</td><td align=\"left\">13.5 ± 12.7 (25)</td><td align=\"left\">(2)</td><td char=\"?\" align=\"char\">19.8 ± 14.3 (27)</td></tr><tr><td align=\"left\">Anterior Crown</td><td align=\"left\">Dentist</td><td char=\"?\" align=\"char\">131.5 ± 44.4 (28)</td><td align=\"left\">37.2 ± 20.9* (24)</td><td align=\"left\">(4)</td><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td char=\"?\" align=\"char\">120.8 ± 55.4 (27)</td><td align=\"left\">23.9 ± 23.7* (22)</td><td align=\"left\">(5)</td><td align=\"left\"/></tr><tr><td align=\"left\">Posterior Crown</td><td align=\"left\">Dentist</td><td char=\"?\" align=\"char\">128.5 ± 50.2 (28)</td><td align=\"left\">37.5 ± 20.9* (24)</td><td align=\"left\">(4)</td><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td char=\"?\" align=\"char\">117.7 ± 48.0 (27)</td><td align=\"left\">24.4 ± 33.3* (22)</td><td align=\"left\">(5)</td><td align=\"left\"/></tr><tr><td align=\"left\">Crowns</td><td align=\"left\">Dentist</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\"?\" align=\"char\">49.1 ± 23.0* (26)</td></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\"?\" align=\"char\">40.7 ± 61.4* (26)</td></tr><tr><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Adjustment</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Dentures</td><td align=\"left\">Dentist</td><td char=\"?\" align=\"char\">78.5 ± 36.9* (22)</td><td align=\"left\">26.4 ± 76.8 (25)</td><td align=\"left\">(1)</td><td char=\"?\" align=\"char\">20.4 ± 18.1 (21)</td></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td char=\"?\" align=\"char\">112.4 ± 51.0* (27)</td><td align=\"left\">15.4 ± 36.5 (24)</td><td align=\"left\">(1)</td><td char=\"?\" align=\"char\">27.9 ± 22.2 (27)</td></tr><tr><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Reline</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\">Dentist</td><td align=\"left\"/><td align=\"left\">6.67 ± 4.1 (13)</td><td align=\"left\">(14)</td><td align=\"left\"/></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td align=\"left\"/><td align=\"left\">11.4 ± 9.7 (22)</td><td align=\"left\">(9)</td><td align=\"left\"/></tr><tr><td align=\"left\">Endodontics</td><td align=\"left\">Dentist</td><td char=\"?\" align=\"char\">102.7 ± 44.9 (25)</td><td align=\"left\">13.9 ± 7.2 (15)</td><td align=\"left\">(13)</td><td char=\"?\" align=\"char\">18.3 ± 16.1 (25)</td></tr><tr><td align=\"left\"/><td align=\"left\">Student</td><td char=\"?\" align=\"char\">124.5 ± 73.4 (24)</td><td align=\"left\">20.7 ± 19.2 (12)</td><td align=\"left\">(15)</td><td char=\"?\" align=\"char\">19.5 ± 18.8 (25)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Patient’s previous experience, longevity estimates and free remediation expectations</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Had Treatment %</th><th align=\"left\">Mean Longevity in<break/>months (n)</th><th align=\"left\">Expecting Free Remediation<sup>a</sup><break/>% (n)</th><th align=\"left\" colspan=\"2\">Mean Remediation Time in<break/>months (n)</th></tr></thead><tbody><tr><td align=\"left\">Fillings</td><td align=\"left\">100%</td><td align=\"left\">131.4 ± 103.9<sup>b</sup> (31)</td><td char=\".\" align=\"char\">74.40% (43)</td><td char=\"?\" align=\"char\">27.6 ± 41.0 (20)</td><td align=\"left\"/></tr><tr><td align=\"left\">Crowns</td><td align=\"left\">37.20%</td><td align=\"left\">145.7 ± 57.9 (21)</td><td char=\".\" align=\"char\">74.40% (41)</td><td char=\"?\" align=\"char\">34.5 ± 45.0 (20)</td><td align=\"left\"/></tr><tr><td align=\"left\">Dentures</td><td align=\"left\">18%</td><td align=\"left\">133.0 ± 80.5 (23)</td><td char=\".\" align=\"char\">30.20% (38)</td><td char=\"?\" align=\"char\">42.7 ± 58.9 (8)</td><td align=\"left\"/></tr><tr><td align=\"left\">Endodontics</td><td align=\"left\">60.50%</td><td align=\"left\">136.8 ± 64.9 (26)</td><td char=\".\" align=\"char\">62.80% (40)</td><td char=\"?\" align=\"char\">37.7 ± 85.4 (17)</td><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[ "<disp-quote><p id=\"Par29\">Dentist: “I consider restorative dentistry comparable to a medical device subject to uncontrolled biological complications. But there is always a place for warranty based on material/operator failure”.</p></disp-quote>", "<disp-quote><p id=\"Par31\">Student: “Warranties should be an integral part of honest and professional dental practice, and patients should be well aware of their right to warrantied goods and services from dentists”.</p></disp-quote>", "<disp-quote><p id=\"Par33\">Dentist: “I think if there was a standard dental warranty, it would increase trust in the profession as a whole and help with the management of patient expectations”.</p></disp-quote>", "<disp-quote><p id=\"Par37\">Student: “Good idea as patients will be more willing to spend more money on expensive treatment such as crown &amp; bridge work.”</p></disp-quote>", "<disp-quote><p id=\"Par40\">There are many possible clinical factors which may affect the patient’s satisfaction for dentures.</p></disp-quote>", "<disp-quote><p id=\"Par42\">“More suitable than a crown or restoration because natural tooth structure is not involved.”</p></disp-quote>", "<disp-quote><p id=\"Par45\">Dentist: “It is difficult to offer a clear warranty on a biological system.”</p></disp-quote>" ]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>" ]
[ "<table-wrap-foot><p>*<italic>p</italic> &lt; 0.05</p><p><sup>a</sup> defined as free repair, replacement, or refund for restorative and crowns; adjustment or reline for dentures; refund for specialist referral for endodontics</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>defined as repair, replacement or refund for fillings, crowns and endodontics, and maintenance for dentures</p><p><sup>b</sup> Mann Whitney U test of significance compared to professionals <italic>p</italic> &lt; 0.001</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12903_2024_3860_Fig1_HTML\" id=\"d32e480\"/>", "<graphic xlink:href=\"12903_2024_3860_Fig2_HTML\" id=\"d32e500\"/>", "<graphic xlink:href=\"12903_2024_3860_Fig3_HTML\" id=\"d32e510\"/>" ]
[ "<media xlink:href=\"12903_2024_3860_MOESM1_ESM.pdf\"><caption><p><bold>Supplementary Material 1:</bold> Dentist and student questionnaire</p></caption></media>", "<media xlink:href=\"12903_2024_3860_MOESM2_ESM.pdf\"><caption><p><bold>Supplementary Material 2:</bold> Patient questionnaire</p></caption></media>" ]
[{"label": ["4."], "mixed-citation": ["Department of Health. NHS dental services in England. An independent review led by Professor Jimmy Steele. 2009."]}, {"label": ["5."], "mixed-citation": ["Kalita A, Kapila S, Reich M. Delivering primary healthcare with quality and accountability in India: The case of Swasth. Working Paper 2: India Health Systems Project. 2020."]}, {"label": ["8."], "surname": ["Howard"], "given-names": ["H"], "article-title": ["Would you warranty your work?"], "source": ["Dent Econ"], "year": ["2017"], "volume": ["107"], "issue": ["3"], "fpage": ["40"]}, {"label": ["9."], "surname": ["Devlin", "Mason", "Yeh"], "given-names": ["M", "K", "L-C"], "source": ["Presenting ethnicity: comparing prioritised and total response ethnicity in descriptive analyses of New"], "year": ["2008"], "publisher-loc": ["Zealand Health Monitor surveys"], "publisher-name": ["Ministry of Health"]}, {"label": ["23."], "surname": ["Maryniuk", "Kaplan"], "given-names": ["GA", "SH"], "article-title": ["Longevity of restorations: survey results of dentists\u2019 estimates and attitudes"], "source": ["J Am Dent Association"], "year": ["1986"], "volume": ["112"], "issue": ["1"], "fpage": ["39"], "lpage": ["45"], "pub-id": ["10.14219/jada.archive.1986.0012"]}]
{ "acronym": [], "definition": [] }
28
CC BY
no
2024-01-14 23:43:47
BMC Oral Health. 2024 Jan 13; 24:74
oa_package/2d/45/PMC10787465.tar.gz
PMC10787466
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Despite the observed decrease in the epilepsy burden during the last years, epilepsy continues to be associated with high morbidity, mortality, and disability rates [##REF##30773428##1##]. Arrhythmias with varying clinical outcomes are expected in epilepsy patients [##REF##29018647##2##]. In 2015, we initiated a prospective study to evaluate the frequency and type of cardiac arrhythmias via long-term continuous cardiac monitoring in a large sample of patients (<italic>n</italic> = 193) with drug-resistant epilepsy [##REF##32911052##3##]. It is well-known that muscle artifacts, caused by prominent muscle contractions, are common during epileptic seizures and might compromise the ECG signal quality [##REF##10982552##4##, ##REF##19182282##5##], mimicking cardiac arrhythmias. This limitation of detecting pseudo-arrhythmia would compromise the implantable loop recorder (ILR) memory capacity. Foreseeing this critical limitation, our team of experienced cardiologists, cardiac electrophysiologists, and neurologists developed an ILR manual activation algorithm based on an analysis of the clinical pattern of epileptic seizures. Our algorithm is the first systemized approach to overcome this limitation. Moreover, it was tested in a large sample of patients, and here we present a detailed analysis of our algorithm’s real-world efficacy. We believe it can help improve the clinically relevant cardiac arrhythmia detection accuracy and the value of future studies on this subject.</p>" ]
[ "<title>Materials and methods</title>", "<p id=\"Par6\">The study design was detailly described previously [##REF##32911052##3##] Briefly, 193 patients (age 18–60 years) with video-EEG monitoring confirmed drug-resistant focal epilepsy, having at least one seizure per month, were consecutively enrolled in this prospective observative study and underwent a subcutaneous ILR implantation.</p>", "<p id=\"Par7\">The study protocol was developed following the principles of the Declaration of Helsinki. Initially, the National Ethics Committee of the Ministry of Healthcare of the Russian Federation approved it, and after that, the center’s local Ethics Committee. All patients signed the written informed consent before enrollment.</p>", "<p id=\"Par8\">The ILR (Reveal XT, Medtronic, USA) was implanted in the left parasternal area at the second intercostal or left axillary region. After ILR implantation and before hospital discharge, we case-by-case, considering the clinical pattern of epileptic seizures in each patient, trained the patients and their relatives on when, how, and how often to use the external activator.</p>", "<p id=\"Par9\">The follow-up duration was up to the end of the life of the ILR battery (approximately 36 months), with scheduled follow-up visits every 3 months. The ILR was removed after the completion of the study or per the patient’s request.</p>", "<title>The ILR activation algorithm</title>", "<p id=\"Par10\">The triggers of ILR autoactivation were cardiac pauses &gt; 3 seconds, bradycardia &lt; 45 beats per min(bpm), ventricular tachycardia (VT) &gt; 150 bpm, rapid ventricular tachycardia &gt; 180 bpm, atrial tachycardia (AT)/atrial fibrillation (AF). The length of stored ECG traces was 30 seconds before and after the automatic activation. For ATs, the programmed duration of the stored ECG recordings preceding the autoactivation was 120 sec.</p>", "<p id=\"Par11\">Patients and their relatives were instructed to initiate ECG recording using the manual activator device. Patients with focal onset-aware seizures (FAS) and patients with focal impaired awareness seizures (FIAS)/bilateral tonic-clonic seizures (TCS) without aura were recommended to use the activator once - just after the episode (Fig. ##FIG##0##1##). In these patients, we set the ILR algorithm to store three ECG traces for up to 6.5 minutes before and 1 minute after the activation (Fig. ##FIG##1##2##). Patients with FIAS and bilateral TCS with aura were advised to use the activator twice - during the aura and after the episode. The relatives of patients experiencing status epilepticus were instructed to use the activator during the episode and after regaining consciousness. Two ECG strips for up to 10 min before and 1.5 min after the activation were recorded.</p>", "<p id=\"Par12\">The following heart rhythm and rate changes were assessed: cardiac pauses &gt; 3 seconds, bradycardia &lt; 45 bpm, AT/AF, VT &gt; 150 beats/min, rapid ventricular tachycardia &gt; 180 beats/min, sinus tachycardia &gt; 100 bpm, sinus tachycardia &gt; 150 bpm, sinus arrhythmia – variations of PP interval &gt; 10%.</p>", "<title>Statistical analysis</title>", "<p id=\"Par13\">Statistical analysis was performed using SAS software (Version 9·4 software; SAS Institute, Cary, NC, USA). Continuous variables were presented as mean ± standard deviation (SD), median (Me), interquartile range (IQR), and categorical variables – as frequencies. Parametric and nonparametric tests (<italic>t</italic>-test and Kruskal–Wallis test) were used to compare two independent groups. The chi-square and 2-sided Fisher’s tests were used for the categorical variables’ comparison. A two-tailed <italic>p</italic>-value ≤0.05 was regarded as significant.</p>" ]
[ "<title>Results</title>", "<p id=\"Par14\">The median follow-up duration was 36 [3–36] months. In total, 6494 ECG traces were recorded and analyzed. 4826 of them were auto-triggered events; manual-activated events were 1668. The rate of positive events in the autoactivation group was 19.4% (936 ECG traces). The number of true positive events in the manual-activated group was 1209 (72.5%), statistically higher (19.4% vs. 72.5%, <italic>p</italic> &lt; 0.0001) than in the autoactivation group.</p>", "<p id=\"Par15\">The false-positive events were seizure-induced artifacts, mimicking pseudo-ventricular tachycardia/ventricular fibrillation (VT/VF) episodes, pseudo-AF (sinus arrhythmia mimicking AF), and nocturnal sinus bradycardia.</p>", "<title>The ILR external activation results and epilepsy type</title>", "<p id=\"Par16\">Figure ##FIG##2##3## presents the number of detected true-positive and false-positive events depending on epilepsy type.</p>", "<p id=\"Par17\">Manual-activated false-positive events were observed in approximately one-third of patients with impaired awareness seizures (225 from 738 (30.5%) in patients with FIAS and 216 from 781 (27.7%) in patients with bilateral TCS). The total number of false-positive events in the manual-activated group was 459. The highest rate of false-positive events was detected in patients undergoing epileptic status (13 from 18 to 61.5%); the lowest rate was in patients with FAS (5 from 131 to 3.8%).</p>", "<p id=\"Par18\">Further subanalysis in patients with impaired awareness seizures revealed a significantly higher rate of false-positive events in patients without aura both in FIAS and bilateral TCS groups (Table ##TAB##0##1##, Fig. ##FIG##3##4##).\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par19\">Here we present a real-world experience of the ECG ILR manual activation algorithm in patients with drug-resistant epilepsy. Our algorithm is the first systematized approach to overcome the ECG signal quality compromise [##REF##10982552##4##, ##REF##19182282##5##] in patients with epilepsy, which can mimic cardiac arrhythmias. Based on 6494 ECG traces, our analysis confirmed the high rate of false-positive arrhythmic events in epilepsy patients compromising the ILR memory capacity. In our study, the sensitivity of the built-in ILR autoactivation algorithm was only 19.4%. Such a result would be very far from satisfactory. Contrary to the built-in activation algorithm, the device’s external activation and the correct timing regarding the seizure allowed us to increase the true positive events’ registration rate to 72.5%, thus ensuring our work’s scientific and practical significance.</p>", "<p id=\"Par20\">Initially, the evaluation of ictal cardiac arrhythmias using the ILR was limited by a small sample [##REF##15610808##6##, ##REF##22709423##7##]. In 2004 Rugg-Gunn et al. [##REF##15610808##6##] presented the first results of the continuous evaluation of ictal cardiac arrhythmias via the ILR in 20 patients with focal epilepsy. In this study, in addition to ILR autoactivation, the patients/caregivers were instructed to use the manual activator once after the seizure. The ILR was programmed to store two preceding and subsequent ECG strips of 8 minutes and 2 minutes in length, respectively. The same single-activation approach was used later by M. van der Lende et al. [##REF##31637707##8##]. Although both studies included patients with focal to bilateral tonic-clonic seizures, the authors did not specify the instructions for manual activation depending on epilepsy type. In our research, person-mediated ILR activation once after the seizure was recommended for all patients with FAS and patients with FIAS without aura just after the episode. This approach confirmed its highest sensitivity in patients with FAS. The results for the patients suffering from impaired awareness seizures without aura were satisfactory, with a rate of false-positive events of approximately 40%. The probable cause of such results might be confusion as the relatives/caregivers could not precisely detect whether and when the episode was resolved. The exact cause might be responsible for the highest false-positive events rate in patients undergoing epileptic status.</p>", "<p id=\"Par21\">The rate of false-positive events in patients suffering from seizures with aura was significantly lower in patients with bilateral TCS. In our opinion, a more vivid manifestation of the clinical picture of epileptic seizure in these patients makes it easier to detect the beginning and the end of the epileptic episode.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par23\">The sensitivity of the built-in ILR autoactivation algorithm in patients with drug-resistant epilepsy is low and seriously compromises the true cardiac arrhythmia detection rate. Our ILR manual activation algorithm is feasible and efficient for improving clinically relevant cardiac arrhythmia detection accuracy.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The muscle artifacts, caused by prominent muscle contractions, mimicking cardiac arrhythmias, might compromise the ECG signal quality and the implantable loop recorder memory capacity in patients with epilepsy. We developed an epileptic seizures clinical pattern-based implantable loop recorder manual activation algorithm, presenting its real-world efficacy here.</p>", "<title>Methods</title>", "<p id=\"Par2\">One hundred ninety-three patients (18–60 years) with drug-resistant focal epilepsy were consecutively enrolled and underwent a subcutaneous loop recorder implantation. Patients with focal onset-aware seizures and patients with focal impaired awareness seizures /bilateral tonic-clonic seizures without aura were recommended to use the activator once - just after the episode. Patients with focal impaired awareness seizures/bilateral tonic-clonic seizures with aura, the caregivers of patients experiencing status epilepticus, were advised to use the activator twice - during the aura and after the episode/ regaining consciousness.</p>", "<title>Results</title>", "<p id=\"Par3\">Six thousand four hundred ninety-four ECG traces (4826 - auto-triggered events, 1668 - person-activated events) were recorded and analyzed. The rate of true positive events in the person-activated group was statistically higher than in the autoactivation group (72.5% vs.19.4%, <italic>p</italic> &lt; 0.0001). Person-activated false-positive events were observed in 30.5% of patients with focal impaired awareness seizures and 27.7% in patients with bilateral tonic-clonic seizures. The highest rate of false-positive events (61.5%) was detected in patients undergoing epileptic status, and the lowest rate (3.8%) - was in patients with focal onset aware seizures. The rate of false-positive events was significantly higher in patients with impaired awareness seizures without aura both in focal impaired awareness (45.5% vs. 19.3%, <italic>p</italic> &lt; 0.0001) and bilateral tonic-clonic seizure groups (38.8% vs. 5.9%, <italic>p</italic> &lt; 0.0001).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Arrhythmias with varying clinical outcomes are expected in epilepsy patients and have been monitored continuously. The specified loop recorder external activation algorithm can improve the clinically relevant cardiac arrhythmia detection accuracy in epilepsy patients and the value of future studies.</p>", "<title>Keywords</title>" ]
[ "<title>Limitations</title>", "<p id=\"Par22\">There are some possible limitations to our study. From the point of view of this paper, the most significant is that we did not use a remote monitoring system for patient management, which could enhance ILR data acquisition and assessment.</p>" ]
[ "<title>Authors’ contributions</title>", "<p>KD and SS conceived and developed the idea. KD, SS, and SB developed the study protocol. AT, SS, MKh, and GS contributed the data. AT analyzed the data and wrote the paper with support from KD and SS. SB helped to supervise the program. All authors discussed the results, contributed to the manuscript’s clinical revision, and approved the final manuscript. All authors agreed to be accountable for all aspects of the work.</p>", "<title>Funding</title>", "<p>This work was supported by the Russian Federation Ministry of Medical Healthcare Registry (8–3/2016).</p>", "<title>Availability of data and materials</title>", "<p>The data supporting this study’s findings are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par24\">We developed the study protocol per the Declaration of Helsinki, and the center’s Independent Ethics Committee approved it. All patients signed the written informed consent before enrollment. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.</p>", "<title>Consent for publication</title>", "<p id=\"Par25\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par26\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The implantable loop recorder epilepsy type-dependent external activation algorithm</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The manual ECG recording setup depends on the epilepsy type</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Person-activated ILR-detected true-positive and false-positive events in patients with different types of epilepsy</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Person-activated ILR false-positive events number in patients with impaired awareness seizures with and without aura</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>False-positive events rate in patients with impaired awareness seizures</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th>Epilepsy type</th><th>False-positive events rate</th><th><italic>p</italic>-value</th></tr></thead><tbody><tr><td>Focal impaired awareness seizures with aura</td><td>19.3%</td><td rowspan=\"2\"><italic>p</italic> &lt; 0.0001</td></tr><tr><td>Focal impaired awareness seizures without aura</td><td>45.5%</td></tr><tr><td>Bilateral tonic-clonic seizures with aura</td><td>5.9%</td><td rowspan=\"2\"><italic>p</italic> &lt; 0.0001</td></tr><tr><td>Bilateral tonic-clonic seizures without aura</td><td>38.8%</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>The comparative analysis between patients suffering from episodes with aura detected a statistically significant higher rate of false-positive events in the group of FIAS (59.8% vs. 38.2%, <italic>p</italic> &lt; 0.0001)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12872_2024_3721_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12872_2024_3721_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12872_2024_3721_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"12872_2024_3721_Fig4_HTML\" id=\"MO4\"/>" ]
[]
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{ "acronym": [], "definition": [] }
8
CC BY
no
2024-01-14 23:43:47
BMC Cardiovasc Disord. 2024 Jan 13; 24:42
oa_package/f0/25/PMC10787466.tar.gz
PMC10787467
38216880
[ "<title>Background</title>", "<p id=\"Par6\">Chronic kidney disease (CKD) is a progressive condition characterized by the gradual deterioration of kidney function over time. If left untreated, CKD can advance to end-stage renal disease (ESRD). CKD is typically diagnosed when there is evidence of kidney damage or reduced kidney function, as indicated by a glomerular filtration rate (GFR) below 60 mL/min/1.73 m², persisting for at least three months, regardless of its underlying cause. On the other hand, ESRD represents the most advanced stage of chronic kidney disease, resulting from a profound loss of kidney function, with a GFR falling to less than 15 mL/min/1.73 m² and lasting for at least three months. At this point, referred to as Grade 5 [##REF##15882252##1##], the primary treatment option becomes dialysis.</p>", "<p id=\"Par7\">ESRD represents a global health challenge, affecting thousands of patients and placing a significant burden on healthcare systems. This condition leads to a buildup of waste products in the blood, electrolyte imbalances, and fluid overload, all of which have profound consequences for patients. There are several treatment options available for ESRD, including hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation. These treatment approaches are primarily geared toward slowing the progression of the disease and addressing its associated complications. While kidney transplantation, though effective, is a complex and costly procedure that relies on the availability of suitable donors, dialysis has emerged as the primary treatment modality for ESRD patients [##REF##32733095##2##].</p>", "<p id=\"Par8\">CKD has numerous causes, including type 2 diabetes mellitus (T2DM), hypertension, chronic use of anti-inflammatory medications, chronic glomerulonephritis, and autoimmune diseases [##REF##19189903##3##]. The prevalence of CKD cases is on the rise, primarily due to the high incidence of non-communicable diseases, such as T2DM and hypertension, which can lead to kidney failure. The World Health Organization defines quality of life (QOL) as an individual’s perception of their position in life within the context of their culture and value systems, as well as in relation to their goals, expectations, standards, and concerns [##REF##9626712##4##]. On the other hand, malnutrition is characterized by deficiencies, excesses, or imbalances in an individual’s energy and nutrient intake, which can impact their overall health [##REF##14582032##5##]. In PD, the catheter insertion procedure involves placing the patient in a supine position, and whether general or local anesthesia is administered depends on the patient’s specific medical condition [##UREF##0##6##].</p>", "<p id=\"Par9\">Continuous ambulatory peritoneal dialysis (CAPD) is a dialysis method that does not require the use of a machine. Patients typically need to perform at least three sessions daily during their waking hours. CAPD offers the advantage of enabling patients to manage their dialysis regimen from the comfort of their homes or workplaces. In contrast, automated peritoneal dialysis (APD), also known as continuous cycling peritoneal dialysis, relies on a machine called a cycler to carry out each dialysis session. Patients can opt for a single extended session using the cycler while they sleep or multiple shorter sessions throughout the day [##UREF##1##7##]. Adjusting to dialysis schedules can significantly impact patients’ daily lives and overall well-being, affecting their social, physical, and psychological aspects [##REF##29720873##8##].</p>", "<p id=\"Par10\">A patient’s QOL is influenced by various factors, including their functioning, happiness, and perceptions of health across physical, psychological, and social domains [##REF##11532675##9##]. In chronic diseases, especially CKD, QOL, morbidity, and mortality are closely intertwined [##REF##14757401##10##, ##REF##11729250##11##].</p>", "<p id=\"Par11\">Studies have shown that CKD patients tend to have significantly lower QOL compared to healthy individuals, with this difference being more pronounced in the pre-dialysis stage, especially among older patients [##REF##10981210##12##, ##REF##12558720##13##]. Reduced functional status and QOL often coincide with declining GFR and an increase in uremic symptoms such as anorexia, weakness, fatigue, and muscle cramps [##UREF##2##14##]. Research has also indicated that nutritional status plays a role in dialysis patients’ QOL, although the existing body of evidence on dietary management’s impact remains limited.</p>", "<p id=\"Par12\">The approach to QOL in CKD patients, particularly those with end-stage renal disease, has shifted from merely ensuring survival to fostering a sense of well-being [##REF##16142573##15##]. The constraints imposed by CKD treatment frequently lead to a decline in QOL, which can be exacerbated by comorbidities and other health conditions. As the clinical condition and QOL of these individuals are closely linked to their overall health and survival, interventions are necessary to enhance their well-being. The connection between declining QOL and potentially manageable factors such as diabetes [##REF##15372417##16##], aging [##REF##12612983##17##], suboptimal dialysis, inflammation, and nutrition remains a topic of ongoing research. Initiation of dialysis has demonstrated varying effects on the QOL of end-stage renal disease (ESRD) patients, and studies have reported mixed results in the relationship between QOL and nutritional parameters due to limitations in patient sample sizes, non-ESRD-specific assessments, observation durations, and other variables [##UREF##3##18##, ##REF##10432414##19##].</p>", "<p id=\"Par13\">Numerous disease-specific health-related quality of life (HRQOL) questionnaires have been developed and validated for the dialysis population, including the Choices Health Experiences Questionnaire (CHEQ), World Health Organization Quality of Life Survey (WHOQOL), Kidney Disease Quality of Life (kDQOL), and Short Form (SF)-36 health survey.</p>", "<p id=\"Par14\">Numerous studies have extensively examined the QOL in patients with CKD who are undergoing renal replacement therapy, with a particular focus on transplant recipients and HD patients. In contrast, previous research on PD patients is notably limited. Therefore, the primary goal of this study is to evaluate the impact of PD on both patients’ nutritional status and overall QOL. This study aims to provide valuable insights to healthcare facilities offering PD, shedding light on its influence across various facets of a patient’s life, encompassing personal and occupational dimensions. Ultimately, our findings may contribute to cost savings, both for governments and individuals, by addressing the financial implications that may arise from lifestyle adjustments associated with the initiation of PD.</p>" ]
[ "<title>Methods</title>", "<title>Study design</title>", "<p id=\"Par15\">A cross-sectional study was conducted between October 2021 and January 2022 at An-Najah National University Hospital (NNUH) in Nablus, Palestine. The study included 74 patients who were receiving PD and were between 18 and 85 years old and had been receiving PD for at least 3 months. Patients who had received PD for less than 3 months and those under 18 years old were excluded from the study. The study protocol was approved by the Institution Review Board (IRB) at Al Najah National University and informed consent forms were signed by the participants.</p>", "<title>Variables and data collection tools</title>", "<title>Dependent variables</title>", "<p id=\"Par16\">The Malnutrition-Inflammation Score (MIS) rates inflammation and protein-energy wasting on a scale of 0 to 30. The results were calculated using an online calculator available at this website: <ext-link ext-link-type=\"uri\" xlink:href=\"http://www.touchcalc.com/calculators/mis\">http://www.touchcalc.com/calculators/mis</ext-link>. It comprises ten components divided into four sections: nutritional history, physical examination, BMI, and laboratory values. Each component has four levels of severity, ranging from 0 (normal) to 3 (severely abnormal). The following characteristics were considered when calculating the MIS score: change in weight, nutritional intake, gastrointestinal (GI) symptoms, functional capacity, co-morbidities, body composition, muscle wasting, BMI, serum albumin, and total iron-binding capacity. The total of all ten MIS components can vary from 0 (normal) to 30 (severely malnourished). A higher score indicates more severe levels of malnutrition and inflammation.</p>", "<p id=\"Par17\">The QOL score is a tool for assessing an individual’s quality of life across five domains: physical, psychological, social, economic, and spiritual. It evaluates the ability to perform tasks like walking, self-care, work, studying, or chores, as well as the experience of pain, discomfort, depression, or anxiety. Each item is scored from 0 (indicating poor health) to 4 (indicating good health). The scores for each item are then summed, and the domain scores are transformed to a 0-100 scale.</p>", "<title>Independent variables</title>", "<p id=\"Par18\">Numerous characteristics were collected to achieve the study’s objectives, including age in years, gender (male or female), place of residency (camp, village, or city), occupation, income, marital status, kidney transplant history (yes or no), ability to self-administer medication (yes or no), smoking status (yes or no), hypertension (yes or no), presence of pitting edema (yes or no), living arrangements (alone or with family), duration of dialysis (in years), dialysis frequency (per day), BMI, and other relevant factors.</p>", "<title>Data analysis</title>", "<p id=\"Par19\">R version 4.1.1 (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.r-project.org\">https://www.r-project.org</ext-link>) was utilized for data analysis. Group comparisons between the Malnutrition-Inflammation Score (MIS) and both quantitative and qualitative variables were conducted using the ANOVA test, Mann–Whitney test, or Kruskal test, depending on the statistical distribution of the variables. Pearson correlation (r) was employed to examine the association between MIS and quantitative features. Univariate and multivariate linear regression analyses were conducted to assess the relationship between QOL and MIS scores. In the multivariate analysis, MIS was adjusted for variables such as Dialysis period (years), diabetes, hypertension, living arrangements, and the presence of pitting edema. A two-sided P value of &lt; 0.05 was considered indicative of statistical significance. In the case of qualitative variables, some numerical features were also categorized, including age and BMI.</p>" ]
[ "<title>Results</title>", "<title>Demographics and characteristics of the study participants</title>", "<p id=\"Par20\">The study involved 74 participants, with a mean age of 50.5 ± 16.38 years. Approximately 36.49% were over 60 years old, and 55.41% were female. The majority (47.3%) resided in villages, followed by those in cities (44.59%), and the remainder in camps. A significant portion (77.03%) of the participants were unemployed, while a minority (24.32%) had completed undergraduate studies. Most participants (63.51%) had completed secondary education, with a small percentage having graduate education (8.11%) and the same percentage having no education beyond secondary school. Only 10.81% had received a kidney transplant, and 83.78% could manage their medication independently. Smoking was reported by 25.68% of participants. Over two-thirds (67.57%) were married, and more than half (51.35%) had been on dialysis for over a year. The majority (82.43%) underwent dialysis more than four times a day.</p>", "<p id=\"Par21\">Among the participants, the majority had a healthy weight (37.84%), while 32.43% were overweight, 22.97% were obese, and 6.76% were underweight. Approximately 54.05% had an income of less than 2000 NIS, 43.24% had incomes ranging from 2000 to 5000 NIS, and only two patients had incomes higher than 5000 NIS. About 32.34% of patients had mild pitting edema, and the vast majority (93.24%) lived with their families. Additionally, 64.86% had hypertension, and 39.19% were diabetic (Table ##TAB##0##1##).</p>", "<title>MIS score of participants</title>", "<p id=\"Par22\">The average MIS score for all participants was 7.5 ± 3.45. The results indicated a positive correlation between age and MIS (r = 0.2, <italic>p</italic> = 0.09), while Dialysis frequency/day (r = -0.03, <italic>p</italic> = 0.82) and BMI (r = -0.06, <italic>p</italic> = 0.58) showed negative correlations with MIS. Other variables demonstrated significant associations with MIS scores, including the ability to take medication independently (<italic>p</italic> = 0.04), mild pitting edema (<italic>p</italic> &lt; 0.001), and diabetes (<italic>p</italic> &lt; 0.001). Participants who couldn’t take their medication alone had a higher MIS score with a mean of 9.5 ± 3.32. Mild pitting edema was associated with higher MIS scores, with a mean of 9.46 ± 3.27, and diabetes was also associated with a higher MIS score, with a mean of 9.14 ± 3.52 (See Table ##TAB##0##1##, columns 3–7).</p>", "<p id=\"Par23\">\n\n</p>", "<title>MIS score relationship with the quality of life</title>", "<p id=\"Par24\">The average QOL score was 73.96 ± 27.06 and had a significant negative association with the MIS score (r = -0.65, <italic>p</italic> &lt; 0.001). This inverse relationship was particularly clear among participants with ages &lt; 60 (MIS: 7.02 ± 3.51 vs. QOL: 80 ± 22.53), city residency (MIS: 6.85 ± 3.05 vs. QOL: 78.48 ± 22.2), employed subjects (MIS: 6.18 ± 3.76 vs. QOL: 89.12 ± 18.05), graduate educational group (MIS: 6.33 ± 4.04 vs. QOL: 83.33 ± 28.87), participants with an income of more than 10,000 NIS (MIS: 4 ± N/A vs. QOL: 100 ± N/A), non-smokers (MIS: 7.35 ± 2.94 vs. QOL: 75.64 ± 24.96), participants undergoing dialysis more than 4 times a day (MIS: 7.18 ± 3.43 vs. QOL: 75.16 ± 26.16), participants who underwent a kidney transplant (MIS: 7.88 ± 3.18 vs. QOL: 78.12 ± 31.05), participants without pitting edema (MIS: 6.56 ± 3.16 vs. QOL: 82 ± 19.85), non-hypertensive participants (MIS: 7.04 ± 3.22 vs. QOL: 75.77 ± 26.18), and non-diabetic participants (MIS: 6.44 ± 3 vs. QOL: 84 ± 15.02).</p>", "<p id=\"Par25\">On the other hand, there was a direct relationship between MIS and QOL, indicating that lower MIS scores were associated with lower QOL scores. This was particularly evident in males (MIS: 7.45 ± 3.12 vs. QOL: 69.55 ± 27.82), those living alone (MIS: 6.2 ± 2.49 vs. QOL: 65 ± 12.75), those who were single (MIS: 7.08 ± 3.63 vs. QOL: 73.33 ± 29.59), those on dialysis for more than one year (MIS: 7.39 ± 3.36 vs. QOL: 72.24 ± 26.09), and those unable to take their medications independently (MIS: 9.5 ± 3.32 vs. QOL: 40 ± 28.68).</p>", "<p id=\"Par26\">In the multivariate model, the MIS values were adjusted for other factors such as the duration of dialysis, the presence of diabetes and hypertension, living arrangements, and pitting edema. The results showed that MIS, diabetic subjects, and mild pitting edema were independently associated with a lower QOL score. Based on the standardized coefficient, diabetes had the strongest influence, followed by pitting edema. As clearly shown in Table ##TAB##1##2##, QOL had a significant negative association with MIS (B = -3.91, <italic>P</italic> &lt; 0.001), diabetic subjects (B = -13.91, <italic>P</italic> = 0.01), and mild pitting edema (B = -11.09, <italic>P</italic> = 0.04), whereas it had a significant positive association with living alone (B = 19.33, <italic>P</italic> = 0.03).</p>", "<p id=\"Par27\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par28\">This study marks the first-ever report on the quality of life among PD patients in Palestine. The findings show that PD patients living in the West Bank region have a relatively high average QOL score, at 73.92 ± 27.06. More than 50% of participants scored 85 or higher, indicating a pretty good QOL. Age and occupation turned out to be important factors related to QOL, each with a P-value of 0.01. The study also found that factors like a patient’s ability to self-administer medication, the presence of pitting edema, and diabetes mellitus were significantly linked to both MIS and QOL. But it’s worth noting that the study has a limitation – the relatively small sample size. Also, some patients might be a bit hesitant to choose PD for dialysis due to concerns about peritonitis. Since this study only looks at data collected at one point in time, it can’t definitively establish cause-and-effect relationships.</p>", "<p id=\"Par29\">Previous research has shown strong links between QOL, MIS, and various related factors, highlighting how malnutrition can really impact a patient’s QOL [##REF##26034747##20##–##REF##34225818##22##]. In one study by Sohrabi et al., they looked at how malnutrition and inflammation affect the physical and mental aspects of health-related quality of life in HD patients. Two other studies had different goals: one checked the nutritional status of HD patients, and the other investigated how socio-demographic factors influence the nutritional status of Palestinian diabetic patients on HD therapy. The findings make it clear that there’s a significant negative link between MIS and QOL scores (<italic>p</italic> &lt; 0.001), meaning that patients with poor nutritional status have lower QOL scores. This lines up with a previous study in Palestine, showing that malnutrition is tied to lower QOL scores in diabetic patients on HD [##REF##34225818##22##]. This aligns with a prior study that demonstrated lower QOL scores among severely malnourished cancer patients when compared to those with milder malnutrition, emphasizing the significance of addressing malnutrition in healthcare [##REF##34080674##23##].</p>", "<p id=\"Par30\">On the other hand, our study showed a negative association between age and QOL, indicating that older age is associated with lower quality of life. Furthermore, around half of the participants (51.6%) were over 60 years old and were identified as being at risk for malnutrition. This finding aligns with a study conducted in Nepal involving 328 participants, which also identified a negative correlation between age and QOL [##UREF##4##24##]. Additionally, we observed a positive correlation between occupational and educational status and QOL, which mirrors the results of the Nepalese study, where individuals with higher occupational status and advanced educational degrees exhibited a notably higher QOL score [##UREF##4##24##].</p>", "<p id=\"Par31\">The current study found a negative association between diabetes and quality of life, which is consistent with preceding studies [##REF##34225818##22##, ##REF##33830978##25##, ##REF##11887244##26##]. A Spanish study reported that 58.1% of diabetic patients had a high risk of malnutrition and diabetes was associated with a lower quality of life [##REF##33830978##25##]. The findings of this study are consistent with a study conducted at Birmingham Heartlands Hospital in the UK, which found that diabetic patients had lower scores on the Mini Nutritional Assessment compared to the control group [##REF##11887244##26##]. This highlights the importance of proactive diabetes management for improved QOL of dialysis patients.</p>", "<p id=\"Par32\">Likewise, the findings in this study point to a clear negative link between low QOL scores, older patients, and women. These results align with a Tanzanian study that found a significant drop in QOL as people get older, with women reporting lower QOL scores than men [##UREF##5##27##]. In addition, a study conducted in Nigeria suggested that social support has a greater impact on the QOL of older adults than health-related factors [##REF##18982816##28##]. These results provide valuable insights into improving the well-being of specific patient demographics.</p>", "<p id=\"Par33\">In light of these results, health practitioners should pay special attention to the nutritional status of patients, particularly those with diabetes or who are older in age. Assessing and addressing malnutrition, as well as providing support for diabetes management, can potentially improve the quality of life for these patients. Additionally, health professionals should consider patients’ occupational and educational backgrounds when tailoring their care plans, as these factors appear to play a role in determining quality of life. These insights can guide healthcare providers in offering more personalized and effective care to their patients.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par34\">Based on this study, the quality of life (QOL) among peritoneal dialysis (PD) patients in Palestine is of particular significance. The research shows a relatively high average QOL score among PD patients in the West Bank, with over 50% experiencing favorable QOL. Age, occupation, medication dependency, and pre-existing conditions such as pitting edema and diabetes mellitus significantly impact QOL. Living with family positively correlates with QOL compared to living alone. These findings guide healthcare practitioners in enhancing PD patient care, emphasizing the importance of early detection of malnutrition, tailored approaches to nutritional support, and diabetes management for better QOL.</p>", "<title>Limitations</title>", "<p id=\"Par35\">The study’s limitations include the absence of a control population not undergoing PD for result comparison, and the relatively small sample size, necessitating caution when interpreting the findings. Further research with a larger sample size and additional variables is recommended. Additionally, some patients may show hesitancy in selecting PD due to peritonitis concerns, and the study’s cross-sectional design precludes definitive cause-and-effect relationship establishment.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">End-stage renal disease (ESRD) is a growing cause of morbidity worldwide. Protein malnutrition is common among patients with ESRD. Peritoneal dialysis (PD) offers greater lifestyle flexibility and independence compared to the widely used treatments for ESRD. This study aimed to assess the nutritional status and the quality of life (QOL) of Palestinian patients undergoing PD, as well as the variables affecting these two outcomes.</p>", "<title>Methods</title>", "<p id=\"Par2\">A cross-sectional study was conducted on patients receiving PD at An-Najah National University Hospital, Palestine. The malnutrition-inflammation scale (MIS) was used to measure malnutrition, and the QOL score was evaluated using the Dutch WHOQOL-OLD module. Univariate and multivariate linear regressions were performed to check the association between the QOL and MIS scores.</p>", "<title>Results</title>", "<p id=\"Par3\">The study included 74 patients who were undergoing PD, with an average age of 50.5 ± 16.38. The majority of the patients were females. The study found a significant correlation between malnutrition and lower quality of life (QOL) scores, as measured by the WHOQOL-OLD questionnaire (<italic>p</italic> &lt; 0.001). Furthermore, younger patients and those who had an occupation were more likely to report a good QOL (<italic>p</italic> = 0.01). Conversely, patients with pitting edema and diabetes were at higher risk of reporting a lower QOL (<italic>p</italic> &lt; 0.001).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Given the elevated risk of malnutrition and diminished QOL among elderly patients, those with pitting edema, and individuals with diabetes, it is imperative to conduct thorough assessments for these groups. We strongly recommend that general practitioners, dietitians, and specialists collaborate to develop tailored programs and interventions to provide these patients with the focused care and attention they require.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>The authors are grateful to Prof. Eric Vicaut (Biostatistics and Clinical Research Department, University Hospital Lariboisière, AP-HP, Université de Paris, Paris, France) for his insightful comments.</p>", "<title>Authors’ contributions</title>", "<p>I.A. and K.J. conceived and implemented the study; I.A., D.H., and M.S. provided resources. IA, DA, BS, DG, NN, and MH collected the data; I.A., D.A., B.S., D.G., and K.J. wrote the main manuscript; I.A., D.A., B.S., D.G., K.J., N.N., M.H propose the idea; I.A., D.H., M.S., A.A., K.J., D.A., B.S., D.G., N.N., M.H., M.A., I.N., and D.S. analyzed and wrote the final manuscript. D.H. corrected the final version. All authors reviewed the manuscript.</p>", "<title>Funding</title>", "<p>This research was funded by An-Najah National University, Nablus, Palestine. (NNU20/214)</p>", "<title>Data availability</title>", "<p>The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par37\">The study followed proper procedures and protocols, including obtaining approval from the Institutional Review Board at An-Najah National University to ensure compliance with ethical guidelines such as the Declaration of Helsinki and the US Federal Policy for the Protection of Human Subjects. Written informed consent was obtained from participants before collecting any samples or data. The participants’ identities were kept confidential, and all samples and data were processed anonymously.</p>", "<title>Consent for publication</title>", "<p id=\"Par38\">Not Applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par36\">The authors declare no conflict of interest.</p>" ]
[]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Population characteristics for participants and group comparison by MIS and QOL scores</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variable</th><th align=\"left\" rowspan=\"2\">n(%)</th><th align=\"left\" colspan=\"3\">MIS</th><th align=\"left\" colspan=\"3\">QOL</th></tr><tr><th align=\"left\">r[<italic>p</italic>]</th><th align=\"left\">Mean ± SD</th><th align=\"left\">\n<italic>p</italic>\n</th><th align=\"left\">r[<italic>p</italic>]</th><th align=\"left\">Mean ± SD</th><th align=\"left\">\n<italic>p</italic>\n</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"8\">\n<bold>MIS</bold>\n</td></tr><tr><td align=\"left\">n (Missing)</td><td align=\"left\">74(0)</td><td align=\"left\">1[&lt; 0.001]</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">-0.65[&lt; 0.001]</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">7.5 ± 3.45</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">min, max</td><td align=\"left\">1,15</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>QOL</bold>\n</td></tr><tr><td align=\"left\">n (Missing)</td><td align=\"left\">74(0)</td><td align=\"left\">-0.65[&lt; 0.001]</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">1[&lt; 0.001]</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">73.92 ± 27.06</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Median(Q1-Q3)</td><td align=\"left\">85(61.25-95)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">min, max</td><td align=\"left\">0,100</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Age</bold>\n</td></tr><tr><td align=\"left\">n (Missing)</td><td align=\"left\">74(0)</td><td align=\"left\">0.2[0.09]</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">-0.33[&lt; 0.001]</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">50.5 ± 16.38</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">min, max</td><td align=\"left\">18,85</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Age</bold>\n</td></tr><tr><td align=\"left\">&lt; 60</td><td align=\"left\">47(63.51%)</td><td align=\"left\"/><td align=\"left\">7.02 ± 3.51</td><td align=\"left\">0.09<sup>b</sup></td><td align=\"left\"/><td align=\"left\">80 ± 22.53</td><td align=\"left\">0.01<sup>a</sup></td></tr><tr><td align=\"left\">≥ 60</td><td align=\"left\">27(36.49%)</td><td align=\"left\"/><td align=\"left\">8.33 ± 3.25</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">63.33 ± 31.22</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Gender</bold>\n</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">41(55.41%)</td><td align=\"left\"/><td align=\"left\">7.54 ± 3.74</td><td align=\"left\">0.89<sup>b</sup></td><td align=\"left\"/><td align=\"left\">77.44 ± 26.25</td><td align=\"left\">0.21<sup>a</sup></td></tr><tr><td align=\"left\">Male</td><td align=\"left\">33(44.59%)</td><td align=\"left\"/><td align=\"left\">7.45 ± 3.12</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">69.55 ± 27.82</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Residency</bold>\n</td></tr><tr><td align=\"left\">Camp</td><td align=\"left\">6(8.11%)</td><td align=\"left\"/><td align=\"left\">7.83 ± 3.92</td><td align=\"left\">0.39<sup>c</sup></td><td align=\"left\"/><td align=\"left\">69.17 ± 33.83</td><td align=\"left\">0.81<sup>c</sup></td></tr><tr><td align=\"left\">Village</td><td align=\"left\">35(47.3%)</td><td align=\"left\"/><td align=\"left\">8.06 ± 3.72</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">70.43 ± 30.06</td><td align=\"left\"/></tr><tr><td align=\"left\">City</td><td align=\"left\">33(44.59%)</td><td align=\"left\"/><td align=\"left\">6.85 ± 3.05</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">78.48 ± 22.2</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Occupation</bold>\n</td></tr><tr><td align=\"left\">Employed</td><td align=\"left\">17(22.97%)</td><td align=\"left\"/><td align=\"left\">6.18 ± 3.76</td><td align=\"left\">0.09<sup>b</sup></td><td align=\"left\"/><td align=\"left\">89.12 ± 18.05</td><td align=\"left\">0.01<sup>a</sup></td></tr><tr><td align=\"left\">Unemployed</td><td align=\"left\">57(77.03%)</td><td align=\"left\"/><td align=\"left\">7.89 ± 3.29</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">69.39 ± 27.76</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Education</bold>\n</td></tr><tr><td align=\"left\">None</td><td align=\"left\">6(8.11%)</td><td align=\"left\"/><td align=\"left\">8.33 ± 3.78</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">45 ± 32.25</td><td align=\"left\">0.84<sup>c</sup></td></tr><tr><td align=\"left\">Secondary</td><td align=\"left\">47(63.51%)</td><td align=\"left\"/><td align=\"left\">7.89 ± 3.28</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">72.98 ± 27.79</td><td align=\"left\"/></tr><tr><td align=\"left\">Under graduate</td><td align=\"left\">18(24.32%)</td><td align=\"left\"/><td align=\"left\">6.39 ± 3.71</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">84.44 ± 14.84</td><td align=\"left\"/></tr><tr><td align=\"left\">Graduate</td><td align=\"left\">3(4.05%)</td><td align=\"left\"/><td align=\"left\">6.33 ± 4.04</td><td align=\"left\">0.20<sup>c</sup></td><td align=\"left\"/><td align=\"left\">83.33 ± 28.87</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Income</bold>\n</td></tr><tr><td align=\"left\">&lt; 2000</td><td align=\"left\">40(54.05%)</td><td align=\"left\"/><td align=\"left\">8.28 ± 3.34</td><td align=\"left\">0.28<sup>c</sup></td><td align=\"left\"/><td align=\"left\">63.38 ± 29.69</td><td align=\"left\">0.19<sup>c</sup></td></tr><tr><td align=\"left\">2000–5000</td><td align=\"left\">32(43.24%)</td><td align=\"left\"/><td align=\"left\">6.62 ± 3.48</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">85.94 ± 17.25</td><td align=\"left\"/></tr><tr><td align=\"left\">5000–10,000</td><td align=\"left\">1(1.35%)</td><td align=\"left\"/><td align=\"left\">8 ± 0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">85 ± 0</td><td align=\"left\"/></tr><tr><td align=\"left\">&gt; 10,000</td><td align=\"left\">1(1.35%)</td><td align=\"left\"/><td align=\"left\">4 ± 0</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">100 ± 0</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Smoke</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\">55(74.32%)</td><td align=\"left\"/><td align=\"left\">7.35 ± 2.94</td><td align=\"left\">0.55<sup>b</sup></td><td align=\"left\"/><td align=\"left\">75.64 ± 24.96</td><td align=\"left\">0.36<sup>a</sup></td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">19(25.68%)</td><td align=\"left\"/><td align=\"left\">7.95 ± 4.71</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">68.95 ± 32.64</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">Living arrangement</td></tr><tr><td align=\"left\">Alone</td><td align=\"left\">5(6.76%)</td><td align=\"left\"/><td align=\"left\">6.2 ± 2.49</td><td align=\"left\">0.38<sup>b</sup></td><td align=\"left\"/><td align=\"left\">65 ± 12.75</td><td align=\"left\">0.12<sup>b</sup></td></tr><tr><td align=\"left\">With family</td><td align=\"left\">69(93.24%)</td><td align=\"left\"/><td align=\"left\">7.59 ± 3.51</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">74.57 ± 27.76</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Marital status</bold>\n</td></tr><tr><td align=\"left\">Single</td><td align=\"left\">24(32.43%)</td><td align=\"left\"/><td align=\"left\">7.08 ± 3.63</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">73.33 ± 29.59</td><td align=\"left\">0.90<sup>a</sup></td></tr><tr><td align=\"left\">Married</td><td align=\"left\">50(67.57%)</td><td align=\"left\"/><td align=\"left\">7.7 ± 3.38</td><td align=\"left\">0.48<sub>b</sub></td><td align=\"left\"/><td align=\"left\">74.2 ± 26.08</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Dialysis period (Year)</bold>\n</td></tr><tr><td align=\"left\">&lt; 1</td><td align=\"left\">36(48.65%)</td><td align=\"left\"/><td align=\"left\">7.61 ± 3.6</td><td align=\"left\">0.66<sup>b</sup></td><td align=\"left\"/><td align=\"left\">75.69 ± 28.31</td><td align=\"left\">0.59<sup>a</sup></td></tr><tr><td align=\"left\">&gt;=1</td><td align=\"left\">38(51.35%)</td><td align=\"left\"/><td align=\"left\">7.39 ± 3.36</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">72.24 ± 26.09</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Dialysis frequency (day)</bold>\n</td></tr><tr><td align=\"left\">n (Missing)</td><td align=\"left\">74(0)</td><td align=\"left\">-0.03[0.82]</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">-0.05[0.67]</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">3.91 ± 0.53</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">min, max</td><td align=\"left\">3,6</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Dialysis frequency (day)</bold>\n</td></tr><tr><td align=\"left\">&lt; 4</td><td align=\"left\">13(17.57%)</td><td align=\"left\"/><td align=\"left\">9 ± 3.27</td><td align=\"left\">0.07<sup>b</sup></td><td align=\"left\"/><td align=\"left\">68.08 ± 31.46</td><td align=\"left\">0.40<sup>a</sup></td></tr><tr><td align=\"left\">&gt;=4</td><td align=\"left\">61(82.43%)</td><td align=\"left\"/><td align=\"left\">7.18 ± 3.43</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">75.16 ± 26.16</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Kidney transplant</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\">66(89.19%)</td><td align=\"left\"/><td align=\"left\">7.45 ± 3.5</td><td align=\"left\">0.75<sup>b</sup></td><td align=\"left\"/><td align=\"left\">73.41 ± 26.76</td><td align=\"left\">0.64<sup>a</sup></td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">8(10.81%)</td><td align=\"left\"/><td align=\"left\">7.88 ± 3.18</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">78.12 ± 31.05</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Taking medication alone</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\">12(16.22%)</td><td align=\"left\"/><td align=\"left\">9.5 ± 3.32</td><td align=\"left\">0.04<sup>b</sup></td><td align=\"left\"/><td align=\"left\">40 ± 28.68</td><td align=\"left\">&lt; 0.001<sup>b</sup></td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">62(83.78%)</td><td align=\"left\"/><td align=\"left\">7.11 ± 3.37</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">80.48 ± 21.4</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Pitting edema</bold>\n</td></tr><tr><td align=\"left\">Mild</td><td align=\"left\">24(32.43%)</td><td align=\"left\"/><td align=\"left\">9.46 ± 3.27</td><td align=\"left\">&lt; 0.001<sup>b</sup></td><td align=\"left\"/><td align=\"left\">57.08 ± 32.37</td><td align=\"left\">&lt; 0.001<sup>a</sup></td></tr><tr><td align=\"left\">None</td><td align=\"left\">50(67.57%)</td><td align=\"left\"/><td align=\"left\">6.56 ± 3.16</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">82 ± 19.85</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Hypertension</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\">26(35.14%)</td><td align=\"left\"/><td align=\"left\">7.04 ± 3.22</td><td align=\"left\">0.45<sup>b</sup></td><td align=\"left\"/><td align=\"left\">75.77 ± 26.18</td><td align=\"left\">0.67<sup>a</sup></td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">48(64.86%)</td><td align=\"left\"/><td align=\"left\">7.75 ± 3.58</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">72.92 ± 27.75</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>Diabetic</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\">45(60.81%)</td><td align=\"left\"/><td align=\"left\">6.44 ± 3</td><td align=\"left\">&lt; 0.001<sup>b</sup></td><td align=\"left\"/><td align=\"left\">84 ± 15.02</td><td align=\"left\">&lt; 0.001<sup>a</sup></td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">29(39.19%)</td><td align=\"left\"/><td align=\"left\">9.14 ± 3.52</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">58.28 ± 33.73</td><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>BMI</bold>\n</td></tr><tr><td align=\"left\">n (Missing)</td><td align=\"left\">74(0)</td><td align=\"left\">-0.06[0.58]</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">-0.24[0.04]</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Mean ± SD</td><td align=\"left\">26.22 ± 6.2</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">min, max</td><td align=\"left\">14.68,44.95</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"8\">\n<bold>BMI</bold>\n</td></tr><tr><td align=\"left\">Healthy Weight</td><td align=\"left\">28(37.84%)</td><td align=\"left\"/><td align=\"left\">7.64 ± 3.91</td><td align=\"left\">0.90<sup>c</sup></td><td align=\"left\"/><td align=\"left\">74.82 ± 26.99</td><td align=\"left\">0.79<sup>c</sup></td></tr><tr><td align=\"left\">Obese</td><td align=\"left\">17(22.97%)</td><td align=\"left\"/><td align=\"left\">8.65 ± 3.2</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">57.35 ± 29.27</td><td align=\"left\"/></tr><tr><td align=\"left\">Over Weight</td><td align=\"left\">24(32.43%)</td><td align=\"left\"/><td align=\"left\">6 ± 2.8</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">82.08 ± 23.68</td><td align=\"left\"/></tr><tr><td align=\"left\">Under Weight</td><td align=\"left\">5(6.76%)</td><td align=\"left\"/><td align=\"left\">10 ± 1.22</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">86 ± 6.52</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Univariate and multivariate linear regression for the association between QOL and MIS</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Crude Β (95% CI)</th><th align=\"left\">\n<italic>P</italic>\n</th><th align=\"left\">Adjusted Β (95% CI)</th><th align=\"left\">\n<italic>P</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">MIS</td><td align=\"left\">-5.09 (-6.49, -3.7)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">-3.91 (-5.42, -2.41)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">Dialysis period /year</td><td align=\"left\">-3.46 (-16.07, 9.15)</td><td align=\"left\">0.59</td><td align=\"left\">-2.57 (-11.48, 6.35)</td><td align=\"left\">0.57</td></tr><tr><td align=\"left\">Diabetic</td><td align=\"left\">-25.72 (-37.16, -14.29)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">-13.91 (-23.81, -4)</td><td align=\"left\">0.01</td></tr><tr><td align=\"left\">Hypertension</td><td align=\"left\">-2.85 (-16.06, 10.36)</td><td align=\"left\">0.67</td><td align=\"left\">1.31 (-8.1, 10.71)</td><td align=\"left\">0.78</td></tr><tr><td align=\"left\">Living arrangement (Alone)</td><td align=\"left\">9.57 (-15.49, 34.62)</td><td align=\"left\">0.45</td><td align=\"left\">-19.33 (1.45, 37.22)</td><td align=\"left\">0.03</td></tr><tr><td align=\"left\">Pitting edema (Mild)</td><td align=\"left\">-24.92 (-37.07, -12.76)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">-11.09 (-21.45, -0.72)</td><td align=\"left\">0.04</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><sup>a</sup> ANOVA test</p><p><sup>b</sup> Mann?Whitney U test</p><p><sup>c</sup> Kruskal?Wallis test</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["6."], "surname": ["Modaghegh", "Kazemzadeh", "Rajabnejad", "Nazemian"], "given-names": ["MH", "G", "Y", "F"], "article-title": ["Preperitoneal tunneling-a novel technique in peritoneal dialysis catheter insertion"], "source": ["Perit dialysis Int J Int Soc Perit Dialysis"], "year": ["2014"], "volume": ["34"], "issue": ["4"], "fpage": ["443"], "lpage": ["6"], "pub-id": ["10.3747/pdi.2011.00311"]}, {"label": ["7."], "mixed-citation": ["Njue E, Mkrttchyan A, Tang S. Automated cyclers for Peritoneal Dialysis. In: Appl Perit Dialysis: Springer. 2021:53\u20138."]}, {"label": ["14."], "surname": ["Caravaca", "Arrobas", "Pizarro", "Sanchez-Casado"], "given-names": ["F", "M", "JL", "E"], "article-title": ["Uraemic symptoms, nutritional status and renal function in pre\u2010dialysis end\u2010stage Renal Failure patients"], "source": ["Nephrol Dialysis Transplantation"], "year": ["2001"], "volume": ["16"], "issue": ["4"], "fpage": ["776"], "lpage": ["82"], "pub-id": ["10.1093/ndt/16.4.776"]}, {"label": ["18."], "mixed-citation": ["Morton AR, Meers C, Singer MA, Toffelmire EB, Hopman W, McComb J, MacKenzie TA. Quantity of dialysis: quality of life\u2013what is the relationship?. Am Soc Artif Intern Organs J 1 996;42(5):M713\u20137."]}, {"label": ["24."], "surname": ["Sharma", "Yadav", "Karmacharya", "Pandey"], "given-names": ["S", "DK", "I", "R"], "article-title": ["Quality of life and nutritional status of the geriatric population of the south-central part of Nepal"], "source": ["J Nutr Metabolism"], "year": ["2021"], "volume": ["2021"], "fpage": ["6621278"], "pub-id": ["10.1155/2021/6621278"]}, {"label": ["27."], "surname": ["Mwanyangala", "Mayombana", "Urassa", "Charles", "Mahutanga", "Abdullah", "Nathan"], "given-names": ["M", "C", "H", "J", "C", "S", "R"], "article-title": ["Health status and quality of life among older adults in rural Tanzania"], "source": ["Global Health Action"], "year": ["2010"], "volume": ["3"], "issue": ["1"], "fpage": ["2142"], "pub-id": ["10.3402/gha.v3i0.2142"]}]
{ "acronym": [ "CAPD", "CKD", "DM2", "ESRD", "GFR", "GI", "HD", "MIS", "PD", "QOL", "TIBC" ], "definition": [ "Continuous ambulatory peritoneal dialysis", "chronic kidney disease", "diabetes mellitus type 2", "End-stage renal disease", "glomerular filtration rate", "Gastrointestinal", "hemodialysis", "malnutrition-inflammation scale", "Peritoneal dialysis", "quality of life", "total iron-binding capacity" ] }
28
CC BY
no
2024-01-14 23:43:47
BMC Nephrol. 2024 Jan 12; 25:20
oa_package/29/57/PMC10787467.tar.gz
PMC10787468
38216931
[ "<title>Background</title>", "<p id=\"Par25\">Cardiovascular disease (CVD) is the leading cause of mortality worldwide, with China experiencing its devastating effects as the primary cause of death and premature mortality [##REF##23746901##1##]. The country is currently facing an urgent need to effectively address the increasing prevalence of CVD and the concurrent rise in patients suffering from coronary artery disease (CAD) [##REF##26466053##2##].</p>", "<p id=\"Par26\">China, a nation with a substantial population and a high prevalence of hypertension, has an estimated hypertensive population of no less than 200 million, based on comprehensive survey findings [##UREF##0##3##, ##UREF##1##4##]. Among this cohort, a substantial proportion, ranging from 68.3% to 80%, is diagnosed with H-type hypertension [##UREF##2##5##, ##REF##27359263##6##]. H-type hypertension, a disorder where essential hypertension coexists with hyperhomocysteinaemia, has been identified [##REF##34348647##7##]. The prevalence of cardiovascular events in patients with H-type hypertension is approximately five times greater compared to patients with hypertension alone and about 25–30 times greater compared to the general population [##REF##26333161##8##]. The incidence of acute myocardial infarction is significantly higher in individuals diagnosed with H-type hypertension compared to those with uncomplicated hypertension. Moreover, concentrations of Hcy are significantly elevated in patients experiencing acute myocardial infarction as opposed to those who do not exhibit this condition [##REF##29532755##9##], Moreover, It is worth noting that heightened Hcy levels are frequently linked to the presence of multiple vasculopathies [##REF##19298497##10##]. Individuals diagnosed with H-type hypertension are subject to a considerably elevated likelihood of experiencing an unfavorable prognosis, primarily due to the diffuse and unstable characteristics exhibited by atherosclerotic plaques [##REF##29433446##11##, ##UREF##3##12##]. There is a notable and statistically significant correlation between hypertension and insulin resistance [##REF##23314883##13##], especially among patients with H-type hypertension [##REF##35493612##14##]. The hyperglycemia and dyslipidemia resulting from IR act synergistically with elevated blood pressure, leading to the onset and progression of cardiovascular disease [##REF##29172743##15##].</p>", "<p id=\"Par27\">Insulin resistance (IR), denoting diminished sensitivity and responsiveness to the physiological actions of insulin, has been duly acknowledged as a defining feature of type 2 diabetes [##REF##32389340##16##]. In typical circumstances, the presence of insulin at physiological levels induces vasodilation and enhances vascular recovery through the augmentation of nitric oxide (NO) synthesis by endothelial cells (ECs) [##REF##19336687##17##, ##REF##33766485##18##], However, in the context of insulin resistance (IR), these beneficial effects of insulin may be diminished, and in fact, insulin may elicit vasoconstriction by promoting the production of vasoconstrictive agents such as endothelin and/or contributing to the development of pathological atherosclerosis. Metabolic syndrome, otherwise delineated as an agglomeration of metabolic aberrations, including dysglycemia, dyslipidemia, and hypertension [##REF##22923650##19##]. These aberrations have been firmly linked to an unfavorable prognosis for cardiovascular disease (CVD) [##REF##19336687##17##]. Such association between metabolic syndrome and cardiovascular disease has become not only conspicuous but also vigorous [##REF##28585193##20##]. the previous study unveil a robust, statistically significant correlation between insulin resistance (IR) and the risk of cardiovascular disease within a distinct group of individuals, specifically, those diagnosed with type 2 diabetes and suffering from insulin-resistant hypertension [##REF##33587660##21##]. A more effectual and uncomplicated index to measure insulin resistance and thus gauge cardiometabolic risk is METS-IR. It outstrips traditional obesity indices in prognosticating hypertension and MetS [##UREF##4##22##]. The intricate nexus between the onset and progression of cardiovascular disease and METS-IR, an evaluative biological index for insulin resistance, has been recently substantiated [##REF##37273533##23##, ##REF##29535168##24##]. Moreover, the triglyceride-glucose index, often referred to as the TyG index, is gaining recognition as a reliable alternative biomarker for insulin resistance (IR). A substantial body of research has furnished persuasive empirical data fortifying the relationship between the TyG index and the genesis and prognosis of cardiovascular disease [##REF##36357872##25##, ##REF##37330498##26##].</p>", "<p id=\"Par28\">Coronary artery angiography, known as the definitive diagnostic modality for coronary heart disease, exhibits a relatively low prevalence rate within primary healthcare facilities in China. This discrepancy primarily stems from the specialized knowledge and intricate procedural techniques required, as well as the invasive nature of the test. Currently, a notable absence exists in the realm of medical research regarding the availability of a biologically sound index that possesses a commendable level of specificity for evaluating the potential risks faced by patients afflicted with H-type hypertension in conjunction with coronary artery disease. Hence, it would be deemed a pioneering concept for the vast majority of primary care physicians and clinicians, who lack specialized expertise in cardiology, to effectively discern patients afflicted with coronary artery disease, particularly those presenting with more advanced stages of the condition, through a streamlined and easily accessible approach.</p>" ]
[ "<title>Methods</title>", "<title>Study population and design</title>", "<p id=\"Par29\">The present investigation was carried out as a cross-sectional observational study, adhering to the principles outlined in the Declaration of Helsinki. It is important to note that no data pertaining to patient privacy or identifiable attributes were collected for the purposes of this study. Furthermore, it is worth mentioning that the study protocol received approval from the Ethical Review Committee of Wuhan Third Hospital, located in the People's Republic of China. In accordance with ethical guidelines, written consent was duly obtained from all patients, ensuring that they were fully informed about the nature and purpose of the study, as well as the potential risks and benefits associated with their participation.</p>", "<p id=\"Par30\">The present study recruited individuals who were admitted to the Department of Cardiology at the Third Hospital of Wuhan City and underwent coronary angiography between the period of January 2021 and January 2023. The inclusion criteria for this study encompassed the following parameters: (1) Participants were required to be adults aged 18 years or older; (2) The diagnostic criteria for hypertension included a documented history of hypertension, current use of antihypertensive medication, or systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg; (3) The diagnostic criteria used to identify metabolic syndrome were based on the NCEP-ATP III criteria:fasting blood glucose ≥ 100 mg/dl, SBP or DBP ≥ 130 or ≥ 85 mmHg; HDL-C &lt; 50 mg/dl for women or &lt; 40 mg/dl for men; triglyceride ≥ 150 mg/dl; and waist circumference ≥ 80 cm for women or ≥ 94 cm for men) [##REF##35524263##27##]; (4) The subjects with ≥ 50% stenosis in at least one main stem lumen were diagnosed with CAD [##UREF##5##28##]; (5) All participants underwent coronary angiography as part of the study protocol. The exclusion criteria encompassed the following: (1) Patients presenting contraindications to coronary angiography or an inability to cooperate with vascular function tests; (2) Patients with concurrent acute infection, severe arrhythmia, pregnancy or lactation, as well as severe hematological and endocrine system diseases; (3) Patients with incomplete clinical data and coronary angiography. In recent times, there has been a notable utilization of pharmaceutical interventions centered around folic acid.</p>", "<title>Data collection and grouping</title>", "<p id=\"Par31\">The fundamental clinical data for each patient, encompassing sex, age, height, weight, heart rate, systolic blood pressure, diastolic blood pressure, as well as pertinent medical history such as hypertension, diabetes mellitus, atrial fibrillation, smoking history, and drug use history, was meticulously extracted from the patient's medical record by a proficient clinician with specialized training. The blood pressure was determined as the mean value of three consecutive measurements obtained from the patient's arm, utilizing an electronic sphygmomanometer, under the supervision of a skilled clinician. Prior to the assessment, the patient was instructed to observe a period of tranquil rest lasting no less than 10 min. The calculation of the body mass index (BMI) involves dividing an individual's weight by the square of their height.</p>", "<p id=\"Par32\">Blood samples were collected from the antecubital vein of fasting patients in the early morning for the purpose of laboratory test indications. The concentration of fasting plasma glucose (FPG) was determined using the hexokinase method. The levels of TGs, TC, HDL-C, and LDL-C, as well as the counts of leukocytes, neutrophils, and platelets, were quantified using the enzymatic method. Additionally, the concentrations of albumin, uric acid, and creatinine were determined using the same enzymatic approach. Furthermore, coronary angiography data were obtained and analyzed. The diagnostic criteria for H-type hypertension entail the inclusion of hypertensive patients who exhibit elevated plasma homocysteine concentrations of 15 mol/L [##REF##27908353##29##] the TyG index was calculated as = Ln[TG(mg/dL) × FBG (mg/dL)/2] [##REF##15871863##30##]. METS-IR is calculated as = (Ln [(2 × FPG) + TG] × BMI)/(Ln[HDL-C]) [##REF##37273533##23##]. The Gensini score, on the other hand, was determined by a skilled cardiovascular physician who evaluated the patient's coronary angiographic results.</p>", "<p id=\"Par33\">Based on the TyG index level, the study participants were categorized into four quartiles: Q1 (n = 80, TyG index ≤ 8.38), Q2 (n = 81, 8.38 &lt; TyG index ≤ 8.88), Q3 (n = 79, 8.88 &lt; TyG index ≤ 9.42), and Q4 (n = 80, TyG index ≥ 9.42). The study cohort was stratified into three distinct categories of stenosis severity, namely mild stenosis, moderate stenosis, and severe stenosis, employing a ternary approach based on the Gensini score. Specifically, individuals with a Gensini score of ≤ 32 were classified as belonging to the mild stenosis group (n = 114), those with a score ranging from 32 to 53 points were categorized as having moderate stenosis (n = 100), and participants with a score of ≥ 53 were assigned to the severe stenosis group (n = 106). Subsequently, the study cohort was stratified based on the Gensini score of the individuals. Those with a Gensini score exceeding 53 were categorized as having severe stenosis, comprising a total of 106 subjects. Conversely, individuals with a Gensini score equal to or below 53 were classified as not having severe stenosis, amounting to a population of 214 individuals.</p>", "<title>Statistical analysis</title>", "<p id=\"Par34\">The determination of the sample size (n) was conducted utilizing the established formula: n = z<sup>2</sup> p × (1−p)/e<sup>2</sup>. This calculation yielded a minimum sample size requirement of 317 patients, considering the estimated proportion of patients with severe coronary stenosis at 29% and a confidence level of 95%. The categorical variables within the baseline data of the study subjects were quantified in terms of numerical values and percentages. To evaluate the normality of the data, the Kolmogorov–Smirnov (K-S) test was employed. The means and standard deviations (SD) were calculated for continuous variables that followed a normal distribution, while medians (interquartile range) were computed for variables that exhibited skewness. A unidirectional analysis of variance (ANOVA) or Kruskal–Wallis test was employed to assess the differences among groups with respect to quantitative variables. The chi-squared test was employed to conduct a comparative analysis of categorical variables across different groups. The statistical analysis employed to examine the associations between quantitative parameters involved the utilization of Pearson's correlation test. The identification of risk factors was accomplished through the utilization of multi-way logistic regression analysis. Furthermore, the accuracy of the TyG indices in detecting both metabolic syndrome and coronary stenosis was evaluated by means of ROC curve analysis. The area under the curve (AUCs) was employed as a metric to determine the predictive value of the TyG indices for both metabolic syndrome and coronary stenosis. All statistical tests conducted in this study were two-tailed and analyzed using the SPSS software version 25.0 (SPSS, Inc., Chicago, IL, USA). A p-value of 0.05 was deemed to possess statistical significance.</p>" ]
[ "<title>Result</title>", "<title>Main clinical characteristics of the study population</title>", "<p id=\"Par35\">A total of 320 patients were included in this study, comprising of individuals with H-type hypertension and coronary artery disease (CAD) (n = 156), as well as non-H-type hypertensive patients with CAD (n = 164). The average age of the participants was 66.8 ± 10.4 years. Among them, 162 (50.1%) were male, with an average body mass index (BMI) of 23.9 ± 3.2 kg/m<sup>2</sup>. The average pulse rate was 76.6 ± 14.0 beats per minute, while the average homocysteine level was 17.5 ± 7.6 units. Additionally, the average TyG index was found to be 8.95 ± 0.81.</p>", "<title>Clinical and biochemical data characteristics according to TyG index quartile grouping</title>", "<p id=\"Par36\">The fundamental characteristics of the four groups are presented in Table ##TAB##0##1##. Significant differences were observed in various parameters including age, body mass index (BMI), diabetes mellitus (DM), white blood cell count (WBC), platelet count, albumin levels, glucose levels, triglyceride levels, high-density lipoprotein cholesterol (HDL-C) levels, low-density lipoprotein cholesterol (LDL-C) levels, urate levels, METS-IR index, Gensini score, number of vasculopathies, and the presence or absence of triple-vessel disease were higher in the group with a higher TyG (all P &lt; 0.05). The TyG index exhibited a significant positive correlation with several physiological parameters including body mass index (BMI), systolic blood pressure (SBP), heart rate, platelet count, albumin levels, triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and uric acid (P &lt; 0.05). The observed relationship exhibited a significant negative correlation with age (P &lt; 0.05) and high-density lipoprotein (HDL) levels (P &lt; 0.001). The prevalence of diabetes mellitus (DM) (P &lt; 0.001), H-type hypertension (P &lt; 0.05), triple vascular disease (P &lt; 0.001), and the metabolic syndrome (P &lt; 0.001) exhibited a greater occurrence among patients with an elevated TyG index.</p>", "<title>Relationship between TyG index and metabolic syndrome</title>", "<p id=\"Par37\">A total of 46 patients, accounting for 14.4% of the sample, exhibited a combined metabolic syndrome. Notably, the TyG quartile group displayed a higher proportion of Q3 and Q4 metabolic syndrome cases, as indicated in Table ##TAB##0##1##. Furthermore, within the Q4 group (TyG range 9.42–12.57), there was a greater concentration of metabolic syndrome cases. The TyG index demonstrated a significant association with METS-IR, with a correlation coefficient of 0.667 (p &lt; 0.001), as depicted in Fig. ##FIG##0##1##. Additionally, when predicting metabolic syndrome using the ROC curve, the area under the curve (AUC) for the TyG index (AUC = 0.943, 95% CI 0.918–0.967, p &lt; 0.001) surpassed that of METS-IR (AUC = 0.876, 95% CI 0.829–0.924, p &lt; 0.001), as illustrated in Fig. ##FIG##1##2##.</p>", "<title>Relationship between TyG index and the degree of coronary artery lesion stenosis</title>", "<p id=\"Par38\">According to the baseline characteristics of the trichotomous subgroups of the Gensini score shown in Table ##TAB##1##2##, patients in the high stenosis group (Gensini score ≥ 53) had higher levels of TyG index, homocysteine, fasting glucose, leukocytes, neutrophil ratio and blood creatinine, a higher prevalence of diabetes mellitus and metabolic syndrome, more frequent use of cigarettes and alcohol, and fewer people treated with ACEI/ARB drugs (all p values &lt; 0.05). In particular, the number of diseased vessels and triple lesions was significantly higher in the high stenosis group than in the low stenosis group (p &lt; 0.001).</p>", "<title>Relationship between H-type hypertension and the degree of coronary artery lesion stenosis</title>", "<p id=\"Par39\">As shown in Table ##TAB##1##2##, the degree of coronary stenosis and the likelihood of severe stenosis were significantly increased in patients with H-type hypertension compared to non-H-type hypertension (p &lt; 0.001). The correlation between TyG index and Gensini score was significantly higher in patients with H-type hypertension than in patients without H-type hypertension.</p>", "<title>Correlation of risk factors with gensini score in H-type and non-H-type hypertension groups</title>", "<p id=\"Par40\">The Gensini scores and risk factors were independently correlated in each of the groups, as presented in Table ##TAB##2##3##. In the cohort of individuals with H-type hypertension, several factors including BMI, FBP, TG, LDL-c, and METS-IR exhibited a positive correlation with the Gensini score, surpassing the levels observed in the non-H-type hypertension group (all p &lt; 0.01). Conversely, HDL-c demonstrated a negative association (r = − 0.408, p &lt; 0.001). Furthermore, the TyG index displayed a significantly stronger correlation with the Gensini score in the H-type hypertensive group (r = 0.766, p &lt; 0.001) compared to the non-H-type hypertensive group (r = 0.250, p &lt; 0.001).</p>", "<title>TyG index and coronary lesion severity and predictive value</title>", "<p id=\"Par41\">The prevalence of diabetes, metabolic syndrome, smoking history, and alcohol consumption history exhibited a significant increase in the severe stenosis group compared to the non-serious stenosis group (p &lt; 0.001) (Table ##TAB##1##2##). Conversely, the usage of ACEI/ARB class drugs displayed a significant decrease in the severe stenosis group compared to the non-serious stenosis group (p &lt; 0.001). Additionally, statistically significant differences were observed between the severe stenosis and non-severe stenosis groups in terms of TyG index, FBG, WBC, albumin, and blood creatinine (p &lt; 0.05). The number of coronary lesions (p &lt; 0.001) and the degree of stenosis (p = 0.02) exhibited a positive correlation with TyG index values (Table ##TAB##0##1##). Furthermore, the incidence of three lesions and severe stenosis was higher in the TyG index quartile Q4 subgroup compared to the Q1 subgroup (50.0 vs. 25.6, p = 0.021).</p>", "<p id=\"Par42\">The present study employed multinomial logistic regression analyses (Table ##TAB##3##4##) to examine the associations between TyG, degree of stenosis, and number of diseased vessels. The TyG index demonstrates a significant association with severe coronary stenosis, as evidenced by an odds ratio (OR) of 7.094 (95% confidence interval CI 4.801–10.484, p &lt; 0.0001). Furthermore, a significant association between the TyG index and multivessel disease is observed, with an OR of 3.982 (95% CI 2.648–5.990, p &lt; 0.0001). Following the appropriate adjustment for notable factors linked to coronary stenosis, including diabetes, smoking, and other relevant variables, it was observed that the TyG index remained significantly associated with an elevated likelihood of having diseased vessels (odds ratio [OR] 1.862, 95% confidence interval CI 1.036–3.348, p-value 0.05). Additionally, the TyG index was found to be strongly correlated with an increased prevalence of coronary stenosis (OR 4.000, 95% CI 2.411–6.635, p-value 0.0001).</p>", "<p id=\"Par43\">Figure ##FIG##2##3## illustrates the Receiver Operating Characteristic (ROC) curves pertaining to the TyG index and METS-IR index, both of which serve as predictive measures for severe stenosis in patients diagnosed with H-type hypertension. At a TyG index threshold of 9.13, the receiver operating characteristic (ROC) curve yielded an area under the curve (AUC) of 0.780 (95% confidence interval CI 0.722–0.838, p &lt; 0.0001). The sensitivity and specificity of the test were determined to be 73% and 52%, respectively. Moreover, the TyG index exhibited a relatively higher level of effectiveness in comparison to other indices, namely the METS-IR index and Hcy and TG, as demonstrated in Table ##TAB##4##5##. And the TyG index predicts the development of severe coronary stenosis in patients with H-type hypertension better than in those without (Fig. ##FIG##3##4##). The results of subgroup analyses revealed notable disparities in the prevalence of severe coronary stenosis across different demographic and clinical groups. TyG index was associated with an increased prevalence of developing severe coronary lesions in the subgroups of smokers and LDL &gt; 70 mg/dL, age ≤ 65 years, and BMI ≤ 24. Specifically, it was observed that males exhibited a significantly higher prevalence of severe coronary stenosis compared to females. Furthermore, patients diagnosed with H-type hypertension exhibited a significantly higher prevalence of severe coronary stenosis when compared to their counterparts without this condition (refer to Fig. ##FIG##4##5## for detailed findings).</p>" ]
[]
[ "<title>Conclusion</title>", "<p id=\"Par50\">In summary, our findings suggest that the TyG index serves as a reliable indicator for evaluating the extent of coronary artery disease (CAD) in individuals with H-type hypertension. Moreover, it emerges as an independent prognostic factor for both the severity of CAD and the presence of metabolic syndrome. Notably, a noteworthy association is observed between the TyG index and the number of coronary stenosis as well as the involvement of coronary vessels in the development of lesions. The TyG index presents itself as a viable and cost-effective biological index that holds potential for implementation across a diverse array of primary healthcare facilities within China. Its utilization can prove instrumental in the process of risk stratification and intervention, thereby mitigating the occurrence of unfavorable cardiovascular events among patients afflicted with H-type hypertension.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The TyG index, a prominent metric for assessing insulin resistance, has gained traction as a prognostic tool for cardiovascular disease. Nevertheless, the understanding of the prognostic significance of the extent of coronary artery stenosis in individuals afflicted with H-type hypertension remains limited.</p>", "<title>Methods</title>", "<p id=\"Par2\">A retrospective study was conducted at Wuhan Third Hospital, including a cohort of 320 inpatients who were diagnosed with hypertension in combination with coronary artery disease. The study period spanned from January 1, 2021, to February 1, 2023. The study cohort was stratified based on the severity of stenosis into three distinct groups: low stenosis, medium stenosis, and high stenosis, as determined by the Gensini score derived from coronary angiography findings. The present study aimed to investigate the association between the severity of coronary stenosis and the number of lesion branches, utilizing the TyG index as a testing indicator. The predictive ability of TyG for coronary lesion severity was assessed using logistic regression analysis.</p>", "<title>Results</title>", "<p id=\"Par3\">The results of our study indicate a positive correlation between elevated levels of TyG and an increased susceptibility to severe stenosis in individuals diagnosed with H-type hypertension. Upon careful consideration of potential confounding variables, it has been observed that the TyG index exhibits a robust association with the likelihood of severe stenosis in individuals with H-type hypertension (odds ratio [OR] = 4000, 95% confidence interval CI 2.411–6.635, p = 0.0001), as well as the prevalence of multivessel disease (OR = 1.862, 95% CI 1.036–3.348, p &lt; 0.0001). The TyG index demonstrated superior predictive ability for severe coronary stenosis in patients with H-type hypertension compared to those without H-type hypertension (area under the curve [AUC] = 0.888, 95% confidence interval CI 0.838–0.939, p &lt; 0.0001, versus AUC = 0.615, 95% CI 0.494–0.737, p &lt; 0.05).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The TyG index is an independent risk factor for the degree of coronary stenosis and a better predictor in patients with H-type hypertension combined with coronary artery disease.</p>", "<title>Keywords</title>" ]
[ "<title>Disscusion</title>", "<p id=\"Par44\">In the current investigation, a cohort of patients diagnosed with H-type hypertension was incorporated to explore the potential of the TyG index as a predictive tool for the emergence of severe stenosis in H-type hypertension. Our study has made a novel discovery by demonstrating a positive correlation between elevated levels of TyG and an increased likelihood of severe stenosis in individuals with H-type hypertension. Furthermore, we have accounted for potential confounding factors, such as smoking and the METS-IR index, and have found a significant association between the TyG index and the risk of severe stenosis in H-type hypertension patients (odds ratio [OR] 4.000, 95% confidence interval CI 2.411–6.635, p &lt; 0.0001). Additionally, we have observed a similar association between the TyG index and the presence of multivessel disease (OR 1.862, 95% CI 1.036, 3.348, p 0.001). Notably, our analysis of the receiver operating characteristic (ROC) curve indicates that the TyG index exhibits a favorable predictive value for the development of severe stenosis in patients with H-type hypertension. Furthermore, it possesses the potential to serve as a prognosticator for metabolic syndrome.</p>", "<p id=\"Par45\">Insulin resistance (IR) is characterized by the compromised functionality and impaired regulation of insulin-mediated glucose metabolism within various tissues, representing an aberrant physiological condition [##REF##19067533##31##]. This state serves as one of the initial indications of the onset of type 2 diabetes mellitus (T2DM) and cardiovascular ailments [##REF##28697184##32##]. Dysregulation of glucose and lipid metabolism is considered an important factor in the pathogenesis and aetiology of type 2 diabetes mellitus (T2DM) [##REF##34285405##33##, ##REF##27912756##34##], which also plays a key role in the development and progression of CAD [##REF##34037093##35##]. Numerous studies have demonstrated that the TyG index is a valuable indicator of a simple and effective predictor of coronary heart disease risk [##REF##36426222##36##]. An elevated TyG index is associated with greater odds of coronary stenosis [##REF##37415168##37##], plaque progression [##REF##29535168##24##], and more vascular lesions [##REF##27633375##38##], which is consistent with our findings. Thai et al. found that an increase in the TyG index identifies patients at high risk of coronary artery stenosis and correlates with the number and severity of stenoses [##REF##36050734##39##]. A dose–response relationship has also been observed between the TyG index and the severity of coronary heart disease [##REF##27633375##38##]. We also found that the TyG index, as a combined index based on glucose and TG levels, was more effective and sensitive in predicting the development of severe coronary artery disease in H-type hypertensive patients compared with the use of glucose and TG alone, which is in line with the findings of Zhao et al. [##REF##36050734##39##–##REF##36151571##43##]. The TyG index holds significant relevance in the evaluation of both type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD), and it additionally assumes a pivotal role in the context of CVD [##REF##19336687##17##, ##REF##31182490##44##].</p>", "<p id=\"Par46\">The TyG index has been identified as a reliable and valuable tool for evaluating the presence of type 2 diabetes and metabolic syndrome, as supported by previous research studies [##REF##23484163##45##, ##REF##33157117##46##]. An elevated TyG index is positively correlated with the severity of glucose and lipid metabolism disorders, as well as the increased prevalence of metabolic syndrome in patients. Consequently, the TyG index holds significant value as a predictive tool for metabolic syndrome, as evidenced by its high area under the curve (AUC) of 0.924 (95% CI 0.905–0.943, p &lt; 0.001). In a similar vein, the TyG index has been utilized to prognosticate non-alcoholic fatty liver disease (NAFLD) [##REF##36875382##47##], ischemic stroke [##REF##35778734##48##], atrial fibrillation [##REF##36510223##49##], carotid atherosclerosis [##REF##37208737##50##], as well as the onset of diseases within the realm of oncology [##REF##37254140##51##] and chronic kidney disease (CKD) [##REF##36452491##52##]. The present study aimed to investigate the association between the TyG index and the conventional etiology of cardiovascular disease. Intriguingly, our findings revealed a significant negative correlation between the TyG index and age, aligning with prior research conducted by Zhao et al. [##REF##32919465##40##, ##REF##33787913##53##]. In our study, we discovered a significant association between older age and lower levels of triglycerides, which played a significant role in contributing to this effect.</p>", "<p id=\"Par47\">Hypertension and diabetes play a synergistic role in cardiovascular disease, and control of blood pressure and blood glucose, as important risk factors for cardiovascular disease, is critical in the secondary prevention of cardiovascular. The interplay between hypertension and diabetes is known to exert a synergistic effect on the development and progression of cardiovascular disease. Given their significance as key risk factors, effective management of both blood pressure and blood glucose assumes paramount importance in the context of secondary prevention strategies for cardiovascular disease [##REF##31722708##54##]. The TyG index has been consistently demonstrated in numerous studies as an effective predictor of both prognosis and risk associated with cardiovascular disease [##REF##36357872##25##, ##REF##33787913##53##]. The majority of investigations conducted thus far have primarily focused on diabetic individuals, leaving a dearth of research pertaining to the prognostication of coronary artery disease severity in hypertensive patients, as well as the evaluation of the correlation between atherosclerosis, hyperuricemia, and stroke in patients afflicted with H-type hypertension [##REF##32641127##41##, ##REF##30110583##55##, ##REF##35190737##56##]. The present study provides novel evidence indicating that the TyG index exhibits promising predictive capabilities in assessing the severity of coronary artery disease (CAD) among individuals diagnosed with H-type hypertension. This finding represents a significant contribution to the existing body of knowledge in this field. The incidence of severe coronary stenosis exhibited a statistically significant elevation in patients diagnosed with H-type hypertension, as compared to patients without H-type hypertension. Nevertheless, the precise mechanism underlying the association between H-type hypertension and coronary artery disease (CAD) remains largely elusive, necessitating the need for additional investigations to validate this relationship.</p>", "<p id=\"Par48\">In our subgroup analysis, it was observed that the incidence of severe stenosis was found to be significantly higher in the male population as compared to the female population. This disparity may be attributed to the higher prevalence of risk factors associated with the development and progression of cardiovascular disease among men, including but not limited to unhealthy lifestyle behaviors such as smoking and alcohol consumption. Specifically, the prevalence of these risk factors was found to be 32.7% in men compared to 22.2% in women for smoking, and 11.7% in men compared to 5.7% in women for alcohol consumption. Males exhibit a propensity for heightened stress levels in comparison to females, and it is plausible that the presence of life stressors may serve as a contributing factor to this observed disparity [##REF##35173466##57##]. We also found a stronger interaction of smoking and elevated LDL with TyG index, and a stronger interaction of BMI ≤ 24 with TyG index compared to BMI &gt; 24. This may be related to the obesity paradox, where mild obesity, especially overweight, is associated with improved survival [##REF##17925521##58##], which needs to be confirmed by further relevant studies.</p>", "<p id=\"Par49\">The present investigation exhibits certain inherent limitations. This study is of a retrospective nature, thereby precluding the establishment of a definitive causal relationship between the TyG index and severe stenosis. Second, the underlying mechanism governing the progression of the TyG index and coronary artery disease (CAD) remains inadequately elucidated. Third, it is imperative to note that the subjects included in this study were derived exclusively from a singular region and exhibited a limited sample size. Consequently, it is crucial to validate these findings through a comprehensive multi-center and multi-regional study encompassing a substantial sample size. Additionally, it is important to acknowledge that solely the initial laboratory test results obtained upon admission were collected, and only subjects with a diagnosis of CAD were included in this study, potentially introducing certain selection biases. Hence, it is imperative to conduct further multicenter and prospective investigations to corroborate these observations.</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank all the investigators and subjects who participated in this project.</p>", "<title>Author contributions</title>", "<p>XZ conceived and designed the experiments and wrote the manuscript. XZ, CP, WL and YJ organized the data, conducted the analyses. YX and LD contributed to the quality control of data and finalization of the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study received the support of Grants from the National Natural Science Foundation of China (Research Grant #81871088) and Hubei Province Natural Science Fund (Research Grant # 2020CFB660), Hubei Province Health and Family Planning Scientific Research Project (Research Grant # WJ2019M006), Knowledge Innovation Project of Wuhan Science and Technology Bureau (Research Grant # 2023020201010189), Wuhan Municipal Population and Family Planning Commission Foundation (Research Grant # WX20A09 and WX16C03).</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analyzed in the study are available from the cor- responding author upon reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par51\">The study was approved by the medical ethics committee of Wuhan Third Hospital and all methods were performed in accordance with the applicable guidelines and regulations.</p>", "<title>Consent for publication</title>", "<p id=\"Par52\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par53\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Correlation between TyG index and METS-IR index</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>ROC curve of the TyG index and METS-IR in the detection of metabolic syndrome</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Receiver operating characteristic (ROC) curves for the TyG index and METS-IR index, both of which serve as predictive measures of severe stenosis in patients diagnosed with H-type hypertension</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>AUCs of the TyG index in predicting the development of severe coronary artery lesions in patients with and without H-type hypertension</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Subgroup analyses of the effect of the TyG index on the incidence of severe stenosis. Each subgroup analysis was adjusted for age, sex, BMI, smoking, alcohol consumption, LDL-C, H-type hypertension, if not stratified. TyG triglyceride glucose, <italic>BMI</italic> body mass index, <italic>LDL-C</italic> low-density lipoprotein cholesterol, <italic>CI</italic> confidence interval</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics of 4 groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variable</th><th align=\"left\">Q1 (n = 81)</th><th align=\"left\">Q2 (n = 80)</th><th align=\"left\">Q3 (n = 79)</th><th align=\"left\">Q4 (n = 80)</th><th align=\"left\">P value</th></tr></thead><tbody><tr><td align=\"left\">TyG index</td><td align=\"left\">8.00 ± 0.27</td><td align=\"left\">8.63 ± 0.14</td><td align=\"left\">9.14 ± 0.16</td><td align=\"left\">10.00 ± 0.55</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Age, years</td><td align=\"left\">69.3 ± 8.9</td><td align=\"left\">65.3 ± 10.9</td><td align=\"left\">67.3 ± 9.5</td><td align=\"left\">65.15 ± 11.7</td><td char=\".\" align=\"char\">0.036</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">33 (40.7)</td><td align=\"left\">44 (55.0)</td><td align=\"left\">40 (50.6)</td><td align=\"left\">45 (56.3)</td><td char=\".\" align=\"char\">0.188</td></tr><tr><td align=\"left\">BMI, kg/m2</td><td align=\"left\">22.7 ± 3.2</td><td align=\"left\">23.3 ± 2.9</td><td align=\"left\">24.6 ± 3.3</td><td align=\"left\">25.0 ± 2.7</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">SBP, mmHg</td><td align=\"left\">136.8 ± 25.5</td><td align=\"left\">140.9 ± 22.4</td><td align=\"left\">140.4 ± 21.8</td><td align=\"left\">141.2 ± 23.4</td><td char=\".\" align=\"char\">0.612</td></tr><tr><td align=\"left\">DBP, mmHg</td><td align=\"left\">80.5 ± 14.9</td><td align=\"left\">83.2 ± 14.6</td><td align=\"left\">82.0 ± 10.6</td><td align=\"left\">81.6 ± 11.6</td><td char=\".\" align=\"char\">0.613</td></tr><tr><td align=\"left\">Heart rate, bpm</td><td align=\"left\">73.3 ± 14.5</td><td align=\"left\">76.1 ± 14.3</td><td align=\"left\">78.1 ± 13.2</td><td align=\"left\">78.8 ± 13.8</td><td char=\".\" align=\"char\">0.064</td></tr><tr><td align=\"left\">Smoker</td><td align=\"left\">2 (2.5)</td><td align=\"left\">9 (11.3)</td><td align=\"left\">24 (30.4)</td><td align=\"left\">53 (66.3)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Drinker</td><td align=\"left\">0 (0)</td><td align=\"left\">2 (2.5)</td><td align=\"left\">3 (3.8)</td><td align=\"left\">23 (28.7)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">H-type hypertension</td><td align=\"left\">40 (49.4)</td><td align=\"left\">28 (35.0)</td><td align=\"left\">40(50.6)</td><td align=\"left\">46 (57.5)</td><td char=\".\" align=\"char\">0.035</td></tr><tr><td align=\"left\">METS-IR index</td><td align=\"left\">32.0 ± 5.7</td><td align=\"left\">35.2 ± 5.3</td><td align=\"left\">39.2 ± 6.2</td><td align=\"left\">45.3 ± 7.3</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Diabetes mellitus</td><td align=\"left\">13 (16.0)</td><td align=\"left\">21 (26.3)</td><td align=\"left\">25 (31.6)</td><td align=\"left\">36 (45.0)</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\">Metabolic syndrome</td><td align=\"left\">0(0)</td><td align=\"left\">0(0)</td><td align=\"left\">3(3.8)</td><td align=\"left\">43 (53.8)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"6\">Biochemical indicators</td></tr><tr><td align=\"left\"> WBC, 10<sup>9</sup>/L</td><td align=\"left\">5.7 ± 1.9</td><td align=\"left\">6.3 ± 2.1</td><td align=\"left\">6.4 ± 2.1</td><td align=\"left\">7.1 ± 1.9</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\"> Neutrophil ratio</td><td align=\"left\">65.9 ± 9.8</td><td align=\"left\">65.9 ± 10.6</td><td align=\"left\">65.6 ± 11.0</td><td align=\"left\">67.7 ± 9.2</td><td char=\".\" align=\"char\">0.533</td></tr><tr><td align=\"left\"> Platelet, 10<sup>9</sup>/L</td><td align=\"left\">199.5 ± 50.7</td><td align=\"left\">211.1 ± 61.1</td><td align=\"left\">227.1 ± 74.0</td><td align=\"left\">225.5 ± 54.4</td><td char=\".\" align=\"char\">0.013</td></tr><tr><td align=\"left\"> Albumin, g/L</td><td align=\"left\">40.9 ± 4.0</td><td align=\"left\">41.8 ± 4.2</td><td align=\"left\">42.2 ± 3.5</td><td align=\"left\">41.8 ± 3.4</td><td char=\".\" align=\"char\">0.171</td></tr><tr><td align=\"left\"> Homocysteine</td><td align=\"left\">18.1 ± 9.2</td><td align=\"left\">16.2 ± 6.7</td><td align=\"left\">17.5 ± 7.1</td><td align=\"left\">18.2 ± 7.1</td><td char=\".\" align=\"char\">0.129</td></tr><tr><td align=\"left\"> FPG, mg/dL</td><td align=\"left\">103.5 ± 19.2</td><td align=\"left\">117.4 ± 31.1</td><td align=\"left\">137.0 ± 37.6</td><td align=\"left\">200.0 ± 97.3</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> TC, mg/dL</td><td align=\"left\">147.1 ± 40.9</td><td align=\"left\">155.5 ± 44.2</td><td align=\"left\">167.4 ± 47.2</td><td align=\"left\">175.7 ± 49.2</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> TG, mg/dL</td><td align=\"left\">62.3 ± 18.2</td><td align=\"left\">101.6 ± 22.4</td><td align=\"left\">147.4 ± 41.6</td><td align=\"left\">293.0 ± 265.9</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> HDL-C, mg/dL</td><td align=\"left\">57.4 ± 17.3</td><td align=\"left\">49.6 ± 11.8</td><td align=\"left\">46.1 ± 10.9</td><td align=\"left\">37.8 ± 9.3</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> LDL-C, mg/dL</td><td align=\"left\">72.4 ± 29.1</td><td align=\"left\">85.7 ± 37.2</td><td align=\"left\">95.9 ± 39.5</td><td align=\"left\">98.6 ± 36.3</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> Uric acid, mg/dL</td><td align=\"left\">6.1 ± 1.9</td><td align=\"left\">6.1 ± 1.8</td><td align=\"left\">6.7 ± 1.8</td><td align=\"left\">6.9 ± 2.0</td><td char=\".\" align=\"char\">0.011</td></tr><tr><td align=\"left\"> SCr, mg/dL</td><td align=\"left\">79.4 ± 42.1</td><td align=\"left\">85.8 ± 60.3</td><td align=\"left\">81.0 ± 32.7</td><td align=\"left\">81.9 ± 27.2</td><td char=\".\" align=\"char\">0.804</td></tr><tr><td align=\"left\" colspan=\"6\">Coronary angiography</td></tr><tr><td align=\"left\"> Lesion vessels</td><td align=\"left\">0.7 ± 1.0</td><td align=\"left\">1.2 ± 1.2</td><td align=\"left\">1.4 ± 1.1</td><td align=\"left\">2.1 ± 1.0</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> Three-vessel disease</td><td align=\"left\">20 (24.7)</td><td align=\"left\">30 (37.5)</td><td align=\"left\">39 (49.4)</td><td align=\"left\">61 (76.3)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\"> Gensini score, (IQR)</td><td align=\"left\">30.5 (20.5,43.5)</td><td align=\"left\">32.0 (20.0,44.0)</td><td align=\"left\">42.5 (29.0,61.0)</td><td align=\"left\">66.5 (51.0,97.1)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\" colspan=\"6\">Medications use at discharge</td></tr><tr><td align=\"left\"> Antiplatelet</td><td align=\"left\">14 (17.3)</td><td align=\"left\">16 (20.0)</td><td align=\"left\">16 (20.3)</td><td align=\"left\">20 (25.0)</td><td char=\".\" align=\"char\">0.679</td></tr><tr><td align=\"left\"> Statin</td><td align=\"left\">8 (9.9)</td><td align=\"left\">6 (7.5)</td><td align=\"left\">9 (11.4)</td><td align=\"left\">8 (10.0)</td><td char=\".\" align=\"char\">0.870</td></tr><tr><td align=\"left\"> CCB</td><td align=\"left\">22 (27.2)</td><td align=\"left\">11 (13.8)</td><td align=\"left\">10 (12.7)</td><td align=\"left\">16 (20.0)</td><td char=\".\" align=\"char\">0.067</td></tr><tr><td align=\"left\"> Beta blockers</td><td align=\"left\">11 (13.6)</td><td align=\"left\">4 (5.0)</td><td align=\"left\">9 (11.4)</td><td align=\"left\">7 (8.8)</td><td char=\".\" align=\"char\">0.289</td></tr><tr><td align=\"left\"> ACEI/ARB</td><td align=\"left\">15 (18.5)</td><td align=\"left\">5 (6.3)</td><td align=\"left\">3 (3.8)</td><td align=\"left\">0 (0)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Clinical and biological characteristics according to the Gensini score tertiles and degree of CAD</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variable</th><th align=\"left\" colspan=\"4\">Gensini score tertiles</th><th align=\"left\" colspan=\"5\">Degree of CAD</th></tr><tr><th align=\"left\">Lowest tertile ≤ 32 (n = 114)</th><th align=\"left\">Mid tertile 32 ~ 53 (n = 100)</th><th align=\"left\">Highest tertile ≥ 53 (n = 106)</th><th align=\"left\">p value</th><th align=\"left\">Non-severe stenosis (n = 214)</th><th align=\"left\" colspan=\"2\">Sever stenosis (n = 106)</th><th align=\"left\" colspan=\"2\">p value </th></tr></thead><tbody><tr><td align=\"left\">TyG index</td><td align=\"left\">8.47 ± 0.51</td><td align=\"left\">8.94 ± 0.69</td><td char=\".\" align=\"char\">9.48 ± 0.86</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">8.7 ± 0.6</td><td align=\"left\" colspan=\"2\">9.5 ± 0.9</td><td align=\"left\" colspan=\"2\"> &lt; 0.001</td></tr><tr><td align=\"left\">Age, years</td><td align=\"left\">65.0 ± 10.6</td><td align=\"left\">67.0 ± 10.0</td><td char=\".\" align=\"char\">65.8 ± 10.3</td><td align=\"left\">0.165</td><td align=\"left\">67.3 ± 10.3</td><td align=\"left\" colspan=\"2\">65.7 ± 10.6</td><td align=\"left\" colspan=\"2\">0.181</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">53 (46.5)</td><td align=\"left\">54 (54.0)</td><td char=\".\" align=\"char\">55 (51.9)</td><td char=\".\" align=\"char\">0.521</td><td align=\"left\">107 (50.0)</td><td align=\"left\" colspan=\"2\">55 (51.9)</td><td align=\"left\" colspan=\"2\">0.751</td></tr><tr><td align=\"left\">BMI, kg/m<sup>2</sup></td><td align=\"left\">23.1 ± 3.1</td><td align=\"left\">24.4 ± 3.6</td><td char=\".\" align=\"char\">24.3 ± 2.7</td><td char=\".\" align=\"char\">0.005</td><td align=\"left\">23.7 ± 3.4</td><td align=\"left\" colspan=\"2\">24.3 ± 2.7</td><td align=\"left\" colspan=\"2\">0.136</td></tr><tr><td align=\"left\">SBP, mmHg</td><td align=\"left\">141.2 ± 28.0</td><td align=\"left\">138.2 ± 20.1</td><td char=\".\" align=\"char\">139.8 ± 20.4</td><td char=\".\" align=\"char\">0.784</td><td align=\"left\">139.8 ± 24.6</td><td align=\"left\" colspan=\"2\">139.8 ± 20.4</td><td align=\"left\" colspan=\"2\">0.998</td></tr><tr><td align=\"left\">DBP, mmHg</td><td align=\"left\">81.6 ± 15.4</td><td align=\"left\">82.5 ± 11.8</td><td char=\".\" align=\"char\">81.4 ± 11.4</td><td char=\".\" align=\"char\">0.567</td><td align=\"left\">82.0 ± 13.8</td><td align=\"left\" colspan=\"2\">81.4 ± 11.4</td><td align=\"left\" colspan=\"2\">0.698</td></tr><tr><td align=\"left\">Heart rate, bpm</td><td align=\"left\">75.5 ± 15.0</td><td align=\"left\">77.0 ± 13.2</td><td char=\".\" align=\"char\">77.3 ± 13.9</td><td char=\".\" align=\"char\">0.536</td><td align=\"left\">76.2 ± 14.2</td><td align=\"left\" colspan=\"2\">77.3 ± 13.9</td><td align=\"left\" colspan=\"2\">0.521</td></tr><tr><td align=\"left\">Smoker</td><td align=\"left\">9 (7.9)</td><td align=\"left\">30 (30.0)</td><td char=\".\" align=\"char\">49 (46.2)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">39 (18.2)</td><td align=\"left\" colspan=\"2\">49 (46.2)</td><td align=\"left\" colspan=\"2\"> &lt; 0.001</td></tr><tr><td align=\"left\">Drinker</td><td align=\"left\">2 (1.8)</td><td align=\"left\">7 (7.0)</td><td char=\".\" align=\"char\">19 (17.9)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">9 (4.2)</td><td align=\"left\" colspan=\"2\">19 (17.9)</td><td align=\"left\" colspan=\"2\"> &lt; 0.001</td></tr><tr><td align=\"left\">H-type hypertension</td><td align=\"left\">34 (29.8)</td><td align=\"left\">53 (53.0)</td><td char=\".\" align=\"char\">67 (63.2)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">87 (40.7)</td><td align=\"left\" colspan=\"2\">67 (63.2)</td><td align=\"left\" colspan=\"2\"> &lt; 0.001</td></tr><tr><td align=\"left\">METS-IR index</td><td align=\"left\">34.2 ± 6.0</td><td align=\"left\">38.5 ± 7.9</td><td char=\".\" align=\"char\">41.3 ± 8.1</td><td char=\".\" align=\"char\">0.067</td><td align=\"left\">36.2 ± 7.3</td><td align=\"left\" colspan=\"2\">41.3 ± 8.1</td><td align=\"left\" colspan=\"2\"> &lt; 0.001</td></tr><tr><td align=\"left\">Metabolic syndrome</td><td align=\"left\">2 (1.8)</td><td align=\"left\">6 (6.0)</td><td char=\".\" align=\"char\">38 (35.8)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\">8 (3.7)</td><td align=\"left\" colspan=\"2\">38 (35.8)</td><td align=\"left\" colspan=\"2\"> &lt; 0.001</td></tr><tr><td align=\"left\">Diabetes mellitus</td><td align=\"left\">20 (17.5)</td><td align=\"left\">33 (33.0)</td><td char=\".\" align=\"char\">42 (39.6)</td><td char=\".\" align=\"char\">0.001</td><td align=\"left\">53 (24.8)</td><td align=\"left\" colspan=\"2\">42 (39.6)</td><td align=\"left\" colspan=\"2\">0.006</td></tr><tr><td align=\"left\" colspan=\"10\">Biochemical indicators</td></tr><tr><td align=\"left\"> WBC, 10<sup>9</sup>/L</td><td align=\"left\">6.0 ± 2.0</td><td align=\"left\">6.5 ± 2.0</td><td char=\".\" align=\"char\">6.6 ± 2.2</td><td char=\".\" align=\"char\">0.065</td><td align=\"left\" colspan=\"2\">6.3 ± 2.0</td><td align=\"left\" colspan=\"2\">6.6 ± 2.2</td><td align=\"left\">0.130</td></tr><tr><td align=\"left\"> Neutrophil ratio, %</td><td align=\"left\">65.8 ± 10.8</td><td align=\"left\">66.5 ± 9.6</td><td char=\".\" align=\"char\">66.3 ± 10.2</td><td char=\".\" align=\"char\">0.819</td><td align=\"left\" colspan=\"2\">66.1 ± 10.2</td><td align=\"left\" colspan=\"2\">66.6 ± 10.1</td><td align=\"left\">0.702</td></tr><tr><td align=\"left\"> Platelet, 10<sup>9</sup>/L</td><td align=\"left\">211.2 ± 62.2</td><td align=\"left\">225.7 ± 65.9</td><td char=\".\" align=\"char\">211.3 ± 55.4</td><td char=\".\" align=\"char\">0.153</td><td align=\"left\" colspan=\"2\">218.0 ± 64.2</td><td align=\"left\" colspan=\"2\">211.3 ± 55.4</td><td align=\"left\">0.357</td></tr><tr><td align=\"left\"> Albumin, g/L</td><td align=\"left\">41.6 ± 3.7</td><td align=\"left\">41.9 ± 3.6</td><td char=\".\" align=\"char\">41.6 ± 4.1</td><td char=\".\" align=\"char\">0.083</td><td align=\"left\" colspan=\"2\">41.8 ± 3.7</td><td align=\"left\" colspan=\"2\">41.6 ± 4.1</td><td align=\"left\">0.646</td></tr><tr><td align=\"left\"> Homocysteine</td><td align=\"left\">16.4 ± 8.4</td><td align=\"left\">18.4 ± 8.1</td><td char=\".\" align=\"char\">17.8 ± 6.0</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\">17.3 ± 8.3</td><td align=\"left\" colspan=\"2\">17.8 ± 6.0</td><td align=\"left\">0.078</td></tr><tr><td align=\"left\"> FPG,mg/dl</td><td align=\"left\">111.2 ± 29.3</td><td align=\"left\">140.4 ± 64.5</td><td char=\".\" align=\"char\">168.7 ± 82.2</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\">124.8 ± 51.1</td><td align=\"left\" colspan=\"2\">168.7 ± 82.2</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"> TC, mg/dl</td><td align=\"left\">155.7 ± 42.8</td><td align=\"left\">158.5 ± 44.7</td><td char=\".\" align=\"char\">170.2 ± 51.1</td><td char=\".\" align=\"char\">0.051</td><td align=\"left\" colspan=\"2\">157.0 ± 43.6</td><td align=\"left\" colspan=\"2\">170.2 ± 51.1</td><td align=\"left\">0.017</td></tr><tr><td align=\"left\"> TG, mg/dl</td><td align=\"left\">98.3 ± 47.8</td><td align=\"left\">1138.3 ± 87.2</td><td char=\".\" align=\"char\">219.0 ± 246.8</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\">117.0 ± 71.7</td><td align=\"left\" colspan=\"2\">219.0 ± 246.8</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"> HDL-C, mg/dl</td><td align=\"left\">52.7 ± 15.0</td><td align=\"left\">47.5 ± 12.8</td><td char=\".\" align=\"char\">42.6 ± 13.7</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\">50.3 ± 14.2</td><td align=\"left\" colspan=\"2\">42.6 ± 13.7</td><td align=\"left\"> &lt; 0.001</td></tr><tr><td align=\"left\"> LDL-C, mg/dl</td><td align=\"left\">83.3 ± 33.5</td><td align=\"left\">86.0 ± 36.4</td><td char=\".\" align=\"char\">95.2 ± 40.3</td><td char=\".\" align=\"char\">0.047</td><td align=\"left\" colspan=\"2\">84.6 ± 34.8</td><td align=\"left\" colspan=\"2\">95.2 ± 40.3</td><td align=\"left\">0.016</td></tr><tr><td align=\"left\"> Uric acid, mg/dl</td><td align=\"left\">6.2 ± 1.8</td><td align=\"left\">6.3 ± 2.1</td><td char=\".\" align=\"char\">6.8 ± 1.8</td><td char=\".\" align=\"char\">0.047</td><td align=\"left\" colspan=\"2\">6.2 ± 2.0</td><td align=\"left\" colspan=\"2\">6.8 ± 1.8</td><td align=\"left\">0.015</td></tr><tr><td align=\"left\"> SCr, umol/L</td><td align=\"left\">85.4 ± 49.9</td><td align=\"left\">77.7 ± 37.6</td><td char=\".\" align=\"char\">82.4 ± 37.7</td><td char=\".\" align=\"char\">0.064</td><td align=\"left\" colspan=\"2\">81.8 ± 44.7</td><td align=\"left\" colspan=\"2\">82.4 ± 37.7</td><td align=\"left\">0.908</td></tr><tr><td align=\"left\" colspan=\"10\">Coronary angiography</td></tr><tr><td align=\"left\"> Lesion vessels</td><td align=\"left\">0.6 ± 1.0</td><td align=\"left\">1.1 ± 1.1</td><td char=\".\" align=\"char\">1.7 ± 1.2</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"2\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Three-vessel disease</td><td align=\"left\">28(24.6)</td><td align=\"left\">47(47.0)</td><td char=\".\" align=\"char\">75(70.8)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"2\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Gensini score, (IQR)</td><td align=\"left\">23.5 ± 4.3</td><td align=\"left\">41.9 ± 5.8</td><td char=\".\" align=\"char\">88.5 ± 34.1</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\"/><td align=\"left\" colspan=\"2\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"10\">Medication, n (%)</td></tr><tr><td align=\"left\"> Antiplatelet</td><td align=\"left\">23 (20.2)</td><td align=\"left\">18 (18.0)</td><td char=\".\" align=\"char\">25 (23.6)</td><td char=\".\" align=\"char\">0.606</td><td align=\"left\" colspan=\"2\">41 (19.2)</td><td align=\"left\" colspan=\"2\">25 (23.6)</td><td align=\"left\">0.357</td></tr><tr><td align=\"left\"> Statin</td><td align=\"left\">10 (8.8)</td><td align=\"left\">10(10.0)</td><td char=\".\" align=\"char\">11 (104)</td><td char=\".\" align=\"char\">0.915</td><td align=\"left\" colspan=\"2\">20 (9.3)</td><td align=\"left\" colspan=\"2\">11 (10.4)</td><td align=\"left\">0.769</td></tr><tr><td align=\"left\"> CCB</td><td align=\"left\">25 (21.9)</td><td align=\"left\">20 (20.0)</td><td char=\".\" align=\"char\">14 (13.2)</td><td char=\".\" align=\"char\">0.221</td><td align=\"left\" colspan=\"2\">45 (21.0)</td><td align=\"left\" colspan=\"2\">14 (13.2)</td><td align=\"left\">0.090</td></tr><tr><td align=\"left\"> Beta blockers</td><td align=\"left\">11 (9.6)</td><td align=\"left\">7 (7.0)</td><td char=\".\" align=\"char\">13 (12.3)</td><td char=\".\" align=\"char\">0.443</td><td align=\"left\" colspan=\"2\">18 (8.4)</td><td align=\"left\" colspan=\"2\">13 (12.3)</td><td align=\"left\">0.273</td></tr><tr><td align=\"left\"> ACEI/ARB</td><td align=\"left\">17 (14.9)</td><td align=\"left\">5 (5.0)</td><td char=\".\" align=\"char\">1 (0.9)</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td align=\"left\" colspan=\"2\">22 (10.3)</td><td align=\"left\" colspan=\"2\">1 (0.9)</td><td align=\"left\">0.002</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Correlation between gensini scores and risk factors of two groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Variable</th><th align=\"left\" colspan=\"2\">H-type hypertension</th><th align=\"left\" colspan=\"2\">Non- H-type hypertension</th></tr><tr><th align=\"left\">Correlation coefficient (r)</th><th align=\"left\">P value</th><th align=\"left\">Correlation coefficient (r)</th><th align=\"left\">P value</th></tr></thead><tbody><tr><td align=\"left\">TyG index</td><td char=\".\" align=\"char\">0.766</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td char=\".\" align=\"char\">0.250</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\">BMI, kg/m<sup>2</sup></td><td char=\".\" align=\"char\">0.240</td><td char=\".\" align=\"char\">0.003</td><td char=\".\" align=\"char\">0.082</td><td char=\".\" align=\"char\">0.291</td></tr><tr><td align=\"left\">FPG,mg/dl</td><td char=\".\" align=\"char\">0.442</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td char=\".\" align=\"char\">0.245</td><td char=\".\" align=\"char\">0.001</td></tr><tr><td align=\"left\">TG, mg/dl</td><td char=\".\" align=\"char\">0.297</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td char=\".\" align=\"char\">0.180</td><td char=\".\" align=\"char\">0.021</td></tr><tr><td align=\"left\">HDL-C, mg/dl</td><td char=\".\" align=\"char\">− 0.408</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td char=\".\" align=\"char\">− 0.167</td><td char=\".\" align=\"char\">0.032</td></tr><tr><td align=\"left\">LDL-C, mg/dl</td><td char=\".\" align=\"char\">0.254</td><td char=\".\" align=\"char\">0.001</td><td char=\".\" align=\"char\">− 0.006</td><td char=\".\" align=\"char\">0.936</td></tr><tr><td align=\"left\">Uric acid, mg/dl</td><td char=\".\" align=\"char\">0.211</td><td char=\".\" align=\"char\">0.008</td><td char=\".\" align=\"char\">0.011</td><td char=\".\" align=\"char\">0.893</td></tr><tr><td align=\"left\">METS-IR index</td><td char=\".\" align=\"char\">0.428</td><td char=\".\" align=\"char\"> &lt; 0.001</td><td char=\".\" align=\"char\">0.159</td><td char=\".\" align=\"char\">0.041</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Correlation between TyG index and number of diseased vessels and degree of stenosis</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"2\">Unadjusted OR (95% CI)</th><th align=\"left\">p value</th><th align=\"left\">Model 1 OR (95% CI)</th><th align=\"left\">p value</th><th align=\"left\">Model 2 OR (95% CI)</th><th align=\"left\">p value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"7\">Number of vessels with stenosis</td></tr><tr><td align=\"left\"> 0</td><td align=\"left\">1</td><td char=\".\" align=\"char\"/><td align=\"left\">1</td><td char=\".\" align=\"char\"/><td align=\"left\">1</td><td align=\"left\"/></tr><tr><td align=\"left\"> 1</td><td align=\"left\">2.032 (1.247–3.311)</td><td char=\".\" align=\"char\">0.004</td><td align=\"left\">1.160 (0.634–2.123)</td><td char=\".\" align=\"char\">0.630</td><td align=\"left\">1.476 (0.725–3.005)</td><td char=\".\" align=\"char\">0.283</td></tr><tr><td align=\"left\"> 2 or 3</td><td align=\"left\">3.982 (2.648–5.990)</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td align=\"left\">1.855 (1.118–3.077)</td><td char=\".\" align=\"char\">0.017</td><td align=\"left\">1.862 (1.036–3.348)</td><td char=\".\" align=\"char\">0.038</td></tr><tr><td align=\"left\" colspan=\"7\">Degree of coronary stenosis</td></tr><tr><td align=\"left\"> Low</td><td align=\"left\">1</td><td char=\".\" align=\"char\"/><td align=\"left\">1</td><td char=\".\" align=\"char\"/><td align=\"left\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\"> Mid</td><td align=\"left\">3.000 (2.048–4.393)</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td align=\"left\">2.610 (1.675–4.067)</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td align=\"left\">2.053 (1.248–3.379)</td><td char=\".\" align=\"char\">0.005</td></tr><tr><td align=\"left\"> Sever</td><td align=\"left\">7.094 (4.801–10.484)</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td align=\"left\">4.379 (2.798–6.854)</td><td char=\".\" align=\"char\"> &lt; 0.0001</td><td align=\"left\">4.000 (2.411–6.635)</td><td char=\".\" align=\"char\"> &lt; 0.0001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>AUCs of TG, Hcy, TyG index and METS-IR index predicting the occurrence of sever CAD</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variable</th><th align=\"left\">AUC(95%CI)</th><th align=\"left\">P value</th></tr></thead><tbody><tr><td align=\"left\">TG</td><td align=\"left\">0.732 (0.665,0.798)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">METS-IR index</td><td align=\"left\">0.733 (0.668,0.798)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">TyG index</td><td align=\"left\">0.795 (0.731,0.858)</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Hcy</td><td align=\"left\">0.509 (0.440,0.577)</td><td char=\".\" align=\"char\">0.821</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>Data are presented as the IQR, mean ± SD or n (%)</p><p><italic>BMI</italic> body mass index, <italic>SBP</italic> systolic blood pressure, <italic>DBP</italic> diastolic blood pressure, <italic>IQR</italic> interquartile range, <italic>WBC</italic> white blood cell, <italic>FPG</italic> fasting plasma glucose, <italic>TC</italic> total cholesterol, <italic>TG</italic> Triglycerides, <italic>HDL-C</italic> high-density lipoprotein cholesterol, <italic>LDL-C</italic> low-density lipoprotein cholesterol, <italic>SCr</italic> Serum creatinine concentration, <italic>CCB</italic> calcium channel blocker, <italic>ACEI</italic>, angiotensin-converting enzyme inhibitor, <italic>ARB</italic> angiotensin receptor blocker</p></table-wrap-foot>", "<table-wrap-foot><p>Data are presented as the IQR, mean ± SD or n (%)</p><p><italic>BMI</italic> body mass index, <italic>SBP</italic> systolic blood pressure, <italic>DBP</italic> diastolic blood pressure, <italic>IQR</italic> interquartile range, <italic>hs-CRP</italic> hypersensitive C-reactive protein, <italic>WBC</italic> white blood cell, <italic>FPG</italic> fasting plasma glucose, <italic>TC</italic> total cholesterol, <italic>TG</italic> Triglycerides, <italic>HDL-C</italic> high-density lipoprotein cholesterol, <italic>LDL-C</italic> low-density lipoprotein cholesterol, <italic>SCr</italic> Serum creatinine concentration, <italic>CCB</italic> calcium channel blocker, <italic>ACEI</italic>, angiotensin-converting enzyme inhibitor, <italic>ARB</italic> angiotensin receptor blocker</p></table-wrap-foot>", "<table-wrap-foot><p>Multinomial logistic regression analyses were performed</p><p><italic>Model 1</italic> Adjusted for diabetes mellitus, metabolic syndrome, smoking, <italic>Model 2</italic> Model 1 + adjusted for METS-IR</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2013_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12933_2023_2013_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12933_2023_2013_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"12933_2023_2013_Fig4_HTML\" id=\"MO4\"/>", "<graphic xlink:href=\"12933_2023_2013_Fig5_HTML\" id=\"MO5\"/>" ]
[]
[{"label": ["3."], "mixed-citation": ["Z. W, Z. C, L. Z, et al. Status of hypertension in China: results from the china"]}, {"label": ["4."], "mixed-citation": ["Hypertension survey, 2012\u20132015. Circulation, 2018."]}, {"label": ["5."], "surname": ["Guo", "Zhang", "Wang"], "given-names": ["QH", "YQ", "JG"], "article-title": ["Asian management of hypertension: Current status, home blood pressure, and specific concerns in China"], "source": ["J Clin Hypertens"], "year": ["2020"], "volume": ["22"], "issue": ["3"], "fpage": ["475"], "lpage": ["478"], "pub-id": ["10.1111/jch.13687"]}, {"label": ["12."], "surname": ["Lanter", "Sauer", "Davies"], "given-names": ["BB", "K", "DG"], "article-title": ["Bacteria present in carotid arterial plaques are found as biofilm deposits which may contribute to enhanced risk of plaque rupture"], "source": ["mBio"], "year": ["2014"], "volume": ["5"], "issue": ["3"], "fpage": ["01206"], "lpage": ["14"], "pub-id": ["10.1128/mBio.01206-14"]}, {"label": ["22."], "surname": ["Reaven"], "given-names": ["GM"], "article-title": ["Relationships among insulin resistance, type 2 diabetes, essential hypertension, and cardiovascular disease: similarities and differences"], "source": ["J Clin Hypertens"], "year": ["2011"], "volume": ["13"], "issue": ["4"], "fpage": ["238"], "lpage": ["243"], "pub-id": ["10.1111/j.1751-7176.2011.00439.x"]}, {"label": ["28."], "surname": ["Detection", "Adults"], "given-names": ["EEPO", "TOHBCI"], "article-title": ["Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III)"], "source": ["Circulation"], "year": ["2001"], "volume": ["106"], "issue": ["19"], "fpage": ["3143"], "lpage": ["3421"]}]
{ "acronym": [ "IR", "TyG index", "Mets", "CVD", "HTN", "BMI", "SBP", "DBP", "IQR", "WBC", "FPG", "TC", "TG", "HDL-C", "LDL-C", "SCr", "Hcy", "CCB", "ACEI", "ARB" ], "definition": [ "Insulin resistance", "Triglyceride–glucose index", "Metabolic syndrome", "Cardiovascular disease", "Hypertension", "Body mass index", "Systolic blood pressure", "Diastolic blood pressure", "Interquartile range", "White blood cell", "Fasting plasma glucose", "Total cholesterol", "Triglycerides", "High-density lipoprotein cholesterol", "Low-density lipoprotein cholesterol", "Serum creatinine concentration", "Homocysteine", "Calcium channel blocker", "Angiotensin-converting enzyme inhibitor", "Angiotensin receptor blocker" ] }
59
CC BY
no
2024-01-14 23:43:47
Cardiovasc Diabetol. 2024 Jan 12; 23:23
oa_package/9f/a0/PMC10787468.tar.gz
PMC10787469
38216932
[ "<title>Introduction</title>", "<p id=\"Par5\">Acute respiratory infections (ARIs) continue to be a leading cause of morbidity and mortality among children under the age of five worldwide [##UREF##0##1##]. The World Health Organization (WHO) estimates that, in 2022, there were 5 million deaths among children under the age of five caused by ARIs, which could have been prevented or treated. ARI is now a global problem of health policy interests [##UREF##0##1##, ##UREF##1##2##], accounting for approximately 20% of children’s deaths globally, with a significant proportion occurring in South Asia and sub-Saharan Africa. Acute respiratory infections (ARIs) account for 3.5% of the worldwide disease burden. They were the cause of 30–50% of all pediatric outpatient visits and resulted in over 30% of pediatric admissions in low- and middle-income countries [##UREF##0##1##]. According to UNICEF, in 2019, pneumonia alone was responsible for approximately 50% of under-five children’s deaths from all infectious diseases, indicating above 700,000 death tolls globally [##UREF##1##2##] and 20% of all deaths worldwide, mostly in South Asia and sub-Saharan Africa [##UREF##2##3##, ##UREF##3##4##]. Multiple studies have shown that Bangladesh, India, Indonesia, and Nepal are responsible for 40% of children’s deaths due to ARIs [##REF##10817802##5##, ##REF##23582727##6##]. The case fatality of severe pneumonia was found to be increasing while concomitant with measles infection and contributing to approximately 38% of measles deaths [##UREF##4##7##].</p>", "<p id=\"Par6\">Bangladesh successfully achieved the Millennium Development Goal (MDG) 4 by significantly reducing the child mortality rate to 46/1000 live births by 2015 and it reduced to 45/1000 live births in 2017-18 [##UREF##5##8##]. According to Bangladesh Sample Vital Statistics 2018, the major cause of death is pneumonia in children under the age of five, accounting for more than one-third of all deaths (34.4%) [##UREF##6##9##]. To achieve the target set by the Integrated Global Action Plan for the Prevention and Control of Pneumonia and Diarrhea (GAPPD) by 2025, which aims to reduce mortality from pneumonia in under-five children to fewer than 3 per 1000 live births [##UREF##2##3##].</p>", "<p id=\"Par7\">Several factors increase the risk of contracting and succumbing to acute respiratory infection (ARIs). These factors included poverty, malnutrition, low birth weight, inadequate breastfeeding, complementary food initiation, overcrowding, poor living conditions, insufficient sanitation, exposure to indoor and outdoor pollution, seasonal changes, and limited access to preventive and curative services [##REF##10817802##5##, ##REF##23582727##6##, ##UREF##7##10##, ##UREF##8##11##]. Recent observational studies found that household environmental factors, such as smoking, poor water quality, high dwelling density, and a lack of toilet facilities, contributed significantly to childhood acute respiratory infections (ARIs) [##UREF##9##12##, ##REF##33684561##13##].</p>", "<p id=\"Par8\">Multiple studies explored the role of different determinants of early childhood ARI in Bangladesh [##UREF##10##14##–##UREF##12##17##]. However, most of these studies had limitations due to their cross-sectional designs. Another issue was the need for more data on all potential predictors representing the diverse dimensions. Even though the investigations of multiple studies on whether environmental factors were potential risk factors for ARI [##UREF##2##3##, ##REF##10817802##5##, ##REF##23582727##6##, ##UREF##7##10##, ##UREF##8##11##], there was no clear evidence regarding the association with in-house environmental factors, especially for in-house toilet facilities, indoor smoking and crowding on ARI among children under-five years of age in our country. Hence, the study’s primary aim was to observe the association between in-house environmental factors where the children were nested and ARI. The study’s findings will give us the understanding to focus on the required areas to stem the problem in low-income settings of South Asia by advocating the improvement of behavioral and programmatic intervention programs.</p>" ]
[ "<title>Methods</title>", "<title>Study design and sampling technique</title>", "<p id=\"Par10\">We conducted a hospital-based matched case-control study at a specialized government-run tertiary children’s hospital (Dhaka Shishu Hospital) in Dhaka, Bangladesh, between March and September 2019. The study population consisted of children aged 6–59 months. We employed a rigorous matching process to ensure the comparability of cases and controls. Specifically, for each case (children with ARI), we selected a control from the same hospital, individually matched by age and gender. This matching process involved identifying a control who belonged to the same age category and shared the same gender as the corresponding case. In essence, each case was precisely paired with a control of the same age and gender, thus minimizing potential confounding variables. This stringent matching strategy was crucial to ensuring the comparability of cases and controls throughout the study. Study population.</p>", "<p id=\"Par11\">Cases were defined as children aged 6–59 months who were hospitalized in the pediatric department with specific symptoms, including mild running nose, cough, chest in-drawing, and fast and difficult breathing (11) and diagnosed by the physicians of the hospital using the ‘Integrated Management of Childhood Illness protocol’ [##UREF##13##18##]. In contrast, controls consisted of the children aged 6–59 months who had attended the outpatient department without ARI symptoms, and the healthy children accompanying the patients to the same hospital and having no ARI symptoms in the previous 30 days were defined as the control population. The children with compromised immune systems diagnosed in the past were not involved in the study to minimize any potential effect on the study results.</p>", "<title>Sample size estimation</title>", "<p id=\"Par12\">The sample size of the study was calculated using the following formula, assuming a 5% significance level (i.e., =1.96), 80% power (i.e., = 0.84) of the study, and a case-control ratio of 1:1 (<italic>r</italic>=1). The percentage of control under five years of age exposed to overcrowding was assumed to be 30.5% (i.e., =0.305) with an odds ratio (OR) of 2.06 based on an analytical cross-sectional study done in India [##REF##25810626##19##].</p>", "<p id=\"Par13\">Therefore, based on the standard statistical parameters indicated above, our study was initially planned with a minimum sample size of 141 cases and an equal number of controls. However, the availability of facilities and resources allowed us to expand our sample size to 348, comprising 174 cases and 174 controls. This increase in the sample size was a strategic decision taken to enhance the statistical power of our study. A larger sample size improves the reliability of our results and increases our sensitivity to identifying relationships.</p>", "<title>Data collection technique and quality control</title>", "<p id=\"Par14\">Once the parents or other caregivers of the children had provided written informed consent, the skilled and widely trained data collectors administered a semi-structured questionnaire (described in both English and Bengali) for data collection through frontal interviews. For both the case and control groups, we utilized a single questionnaire utilizing national standard tools [##UREF##14##20##, ##UREF##15##21##] and maintained WHO-recommended procedures, [##UREF##16##22##] and the data collected were checked and rechecked for their reliability and validity.</p>", "<title>Outcome variable</title>", "<p id=\"Par15\">Acute respiratory infection (ARI) was defined as the specific symptoms that were onset in the preceding 10 days from the day of the visit, including a mild running nose, cough, chest in-drawing, and fast and difficult breathing.</p>", "<title>Independent variables</title>", "<p id=\"Par16\">Data were collected on three sets of predictors: household environmental (exposure variables), sociodemographic, and mother-child characteristics.</p>", "<title>Household environmental (exposure variables)</title>", "<p id=\"Par17\">A group of variables was set for analysis to determine the effect of the household environment on ARIs among children under five. It included the place of residence (urban, rural), in-house crowding, in-house smoking habits by family members, cooking fuel, source of drinking water, shared toilets, and toilet facilities. The child’s residence had been identified as whether he/she was part of urban or rural living. In-house crowding was described as the total number of household members divided by the total number of bedrooms [##UREF##17##23##]. The number of members of the household was counted, asking, “How many members stay with the child in your house?” We categorized the in-house crowding into two following groups: &gt;3 and ≤ 3 people per bedroom [##REF##33684561##13##]. We assumed the cut point of 3.0 for in-house crowding categorization because we thought the child was staying with his/her parents.</p>", "<p id=\"Par18\">We further investigated several household environmental variables: the type of cooking fuel used and the in-house smoking habits of the family members in the house. The use of cooking fuel was classified into two groups: clean (natural gas, LPG or electricity) or unclean (biogas, wood, agricultural products, solid waste or coal) [##UREF##18##24##]. In-house smoking was determined by asking, “Do any of the adult members of your family smoke on the home premises?” We also took data on their source of drinking water, which was recorded as either tap or piped water or tube-well or surface water. In addition, two kinds of data were obtained from the provision of sanitation facilities in the house in which the children stayed. First, whether or not they used a communal toilet (more than five people use the same toilet) and second, the type of toilet they were using. The toilets were divided into two categories: improved (safe disposal of excreta without human contact, e.g. flush to the piped sewage system, septic tanks or pit latrines) and unimproved facilities (pit latrine without slab/platform, hanging/bucket toilet or open) [##UREF##19##25##].</p>", "<title>Other covariates</title>", "<p id=\"Par19\">The sociodemographic variables consisted of the child’s age (in months) and gender, the level of education for both parents, the mother’s occupation, and the family’s monthly income. Parental education was categorized by years of schooling (illiterate, <sc>1–5, 6–12</sc>, and <sc>12 +</sc> years). The mother’s occupation was classified as either a housewife or employed. We defined the employed mothers as those who received a monthly salary from their occupation. Family income was classified into three groups <sc>( &lt; = 10</sc>000, <sc>10,001–2</sc>5000, <sc>&gt; 2</sc>5000 BDT/month).</p>", "<p id=\"Par20\">Last, the maternal-child characteristics included birth order, gestational age (preterm/full-term), mode of delivery (cesarean section/normal), exclusive breastfeeding, nutritional status, and vaccination status (based on EPI schedule; completeness for age or no/incomplete). Preterm birth is defined as the birth of a child before completing 37 weeks of gestation, and full-term birth refers to a birth after 37 weeks [##UREF##20##26##]. Nutritional status was assessed by the mid-upper arm circumference (MUAC) and categorized into two groups: healthy (&gt; 13.5 cm) and malnourished ( &lt; = 13.5 cm). It was measured by MUAC (mid-upper arm circumference) tape at the midpoint between the tip of the shoulder and the tip of the elbow. The measurements were meticulously recorded with a precision of 0.1 cm. The tape fitted firmly but did not create any pit in the upper arm.</p>", "<title>Statistical analysis</title>", "<p id=\"Par21\">The questionnaires analyzed were checked for completeness, precision, and internal consistency, and the exclusion of incomplete or inaccurate data. The analytical software STATA was used to analyze the data. The descriptive statistics were presented as percentages and frequencies. We conducted bivariate and multivariate conditional logistic regression analyses to examine the association between in-house environmental factors and childhood ARI. The study employed a matched case-control design, where each case (children with ARI) was matched with a control (children without ARI) based on age and gender. This matching was essential to control for potential confounding variables and to ensure that cases and controls were comparable. Conditional logistic regression was well-suited for analyzing matched data because it takes into account the matched pairs and their characteristics. Furthermore, the outcome variable in this study was binary (ARI present or not present), which was suitable for logistic regression analysis. Conditional logistic regression further extended logistic regression to matched data, allowing researchers to examine the relationship between the predictors (in-house environmental factors, sociodemographic variables, etc.) and the binary outcome while accounting for the matching.</p>", "<p id=\"Par22\">We built our regression models iteratively, considering variables’ significance and potential confounding effects. Collinearity among all independent variables included in the study was assessed using the Variance Inflation Factor (VIF). Apart from “<italic>residence</italic>”, no other variable exhibited significant collinearity. As a result, these were retained and included in the subsequent conditional logistic regression model. This allowed us to accurately examine the relationship between these variables and the binary outcome. In both models, odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength and direction of associations and a <italic>p</italic>-value &lt; 0.05 was considered to determine statistical significance.</p>", "<title>Result</title>", "<p id=\"Par23\">The analysis considered three hundred and forty-eight children aged 6 to 59 months, with <sc>174</sc> cases and <sc>174</sc> controls. As a matched case-control study by age and gender, the distribution of boys (60.34%) and girls (39.66%) was similar in both the case and control groups. Most participants in each group were between the ages of <sc>2</sc>5–36 months (39.66% of cases and 39.08% of controls).</p>", "<title>Association of sociodemographic characteristics with childhood ARI</title>", "<p id=\"Par24\">We examined the impact of various sociodemographic characteristics on childhood ARI (acute respiratory infections) in the bivariate logistic regression model [Table ##TAB##0##1##<sc>].</sc> Approximately half of the mothers (<sc>47.1</sc>3% for cases and 50.57% for controls) completed <sc>6–12</sc> years of schooling. The correlation between maternal education and childhood ARI was almost significant (<italic>p</italic> = 0.05<sc>1</sc>), with children of mothers who completed 6–12 years of schooling having 39% lower odds of ARI compared to those with less-educated mothers. Almost 40% of the fathers and 23% of mothers completed more than 12 years of schooling. However, a closer examination revealed that children of more highly educated mothers (12 + educational years) and fathers with secondary education (6–12 years of schooling) demonstrated substantial decreased odds of childhood ARI by 66% (OR = 0.44, 95% CI: 0.<sc>24, 0.81</sc>; <italic>p</italic> = 0.008<sc>)</sc> and 76% (OR = 0.34, 95% CI: <sc>0.1</sc>5, 0.7<sc>2</sc>; <italic>p</italic> = 0.006<sc>)</sc> respectively, relative to illiterate parents (reference category).</p>", "<p id=\"Par25\">Furthermore, Approximately 52% of children were nested in households with monthly family income between BDT <sc>10,001</sc> and BDT <sc>2</sc>5000 in both cases (50.57%) and control (52.87%)groups. Children from families with a monthly income exceeding <sc>25,0</sc>00 BDT per month displayed 50% lower odds (OR = 0.50, 95% CI: 0.26, 0.94; <italic>p</italic> = 0.033) of ARIs than those from families with monthly incomes <sc>10</sc>,000 BDT or less. However, the mother’s occupation did not exhibit any significant association with childhood ARI [Table ##TAB##0##1##].</p>", "<p id=\"Par26\">\n\n</p>", "<title>Association of in-house environmental factors with childhood ARI</title>", "<p id=\"Par27\">We also investigated the influence of household environmental factors on ARIs among children aged 6–59 months, as demonstrated in the unadjusted model [Table ##TAB##1##2##]. The residence of the children exhibited a significant association with childhood ARI. Specifically, children residing in rural areas were more than twice as likely (OR = 2.12, 95% CI: 1.38, 3.28; <italic>p</italic> = 0.001) to experience ARIs compared to their urban counterparts (reference category). In particular, our data revealed that 53.45% of households in the case group had more than three individuals per bedroom, which was significantly higher than the 24.13% observed in the control group. Children living in overcrowded households with more than three people per bedroom faced 3.61 times higher odds of developing acute respiratory infections (ARIs) when compared to those in less crowded households with three people or fewer per bedroom (OR = 3.61, 95% CI: 2.29, 5.74; p = &lt; 0.001) in the unadjusted model. Furthermore, the use of unclean fuel by families increased the odds of ARIs among children by 2.41 times (OR = 2.41, 95% CI: 1.56, 3.73; p = &lt; 0.001) compared to those using clean fuels. Additionally, a significant proportion of family members in both case and control categories reported in-house smoking habits (40.23% in cases and 29.89% in controls). In households with in-house smokers, the risk of childhood ARI significantly increased by 58% when compared to households with nonsmokers or those without in-house smoking (OR = 1.58, 95% CI: 1.02, 2.47; <italic>p</italic> = 0.04). Approximately 45% of families relied on tube-well or surface water for drinking, which was associated with 2.45 times higher odds of childhood ARI (OR = 2.45, 95% CI: 1.59, 3.79; p = &lt; 0.001) compared to those consuming tap or piped water. Encouragingly, approximately three-fourths (75.86%) of families used improved sanitation facilities, signifying a positive trend. However, the utilization of unimproved toilet facilities significantly increased the risk of childhood ARI by 5.29 times (OR = 5.29, 95% CI = 3.03, 9.66; p = &lt; 0.001). Interestingly, the sharing of toilet facilities did not yield a significant increase in the risk of childhood ARI [Table ##TAB##1##2##].</p>", "<p id=\"Par28\">\n\n</p>", "<title>Association of maternal and child characteristics with childhood ARI</title>", "<p id=\"Par29\">We then assessed the effect of various maternal and child characteristics on childhood ARI in the bivariate logistic regression model [Table ##TAB##2##3##]. The data indicated that most children were firstborn in the family (33.91% among cases and 48.<sc>28%</sc> among controls). An intriguing trend became apparent – the odds of ARI increased with ascending birth order. The first- and second-born children had an effective defence against ARI related to third- or more-ordered children (OR = 0.31, 95% CI: 0.19, 0.58; p = &lt; 0.001 and OR = 0.38, 95% CI: 0.22, 0.69; <italic>p</italic> = 0.002, respectively). Most children were born after 37 weeks of gestation (54% in the case group and 68.39% in the control group). Remarkably, premature birth amplified the odds of ARI by a substantial 84% (OR = <sc>1</sc>.84, 95% CI: <sc>1.1</sc>9, <sc>2</sc>.86; <italic>p</italic> = 0.006) compared to full-term (reference category). Only 56.3<sc>2%</sc> of all children received exclusive breastfeeding. However, children who breastfed exclusively were 50% (OR = 0.50, 95% CI: 0.<sc>32</sc>, 0.77; <italic>p</italic> = 0.002) less likely to develop ARI than those not. Most children completed vaccination for age (79.31% for the group of cases and <sc>92.</sc>53% for the group of controls). The odds ratio indicated that children who did not receive immunization by the recommended age were 3.5 times (OR = 3.50, 95% CI: 1.80, 7.26; <italic>p</italic> &lt; 0.001) more inclined to develop ARI in comparison to their counterparts who received completely (the reference category). The majority of all children (47.13%) were delivered through the typical vaginal route (5<sc>2</sc>.30%). In a bivariate model, the nutritional status and mode of delivery among under-five children were not significantly correlated with ARI [Table ##TAB##2##3##].</p>", "<p id=\"Par30\">\n\n</p>", "<title>Conditional logistic regression: an adjusted model</title>", "<p id=\"Par31\">We finally conducted a multivariable conditional logistic regression analysis to estimate the adjusted odds ratios (AORs) for identifying potential in-house environmental factors. After adjusting the effect of household, maternal and child characteristics, we found that several factors remained significantly associated with childhood ARIs [Table ##TAB##3##4##].</p>", "<p id=\"Par32\">Unimproved toilets were significantly associated with increased odds of childhood ARI by 4.35 times (AOR = 4.35, 95% CI = <sc>2.14, 9.2</sc>6; <italic>p</italic> &lt; 0.001)). Crowded households with more than three people per bedroom also showed a significantly elevated risk of childhood ARI by 2.66 times while all other variables were kept constant (AOR <sc>= 2.</sc>66, 95% CI = <sc>1.</sc>5<sc>2</sc>, 4.7<sc>1</sc>; <italic>p</italic> &lt; 0.001) while adjusting the other covariates. Likewise, households with family members who smoked indoors also demonstrated increased odds of childhood ARIs by 1.74 times (AOR = 1.74, 95% CI: 1.01, 3.05, <italic>p</italic> = 0.04).</p>", "<p id=\"Par33\">The adjusted odds of childhood ARI were also found to be significant among maternal and child characteristics in the conditional logistic regression model; in terms of preterm birth by 2.44 times (AOR = 2.44, 95% CI: 1.43, 4.23; <italic>p</italic> &lt; 0.001) (AOR <sc>= 2.</sc>44, 95% CI: <sc>1</sc>.43, 4.<sc>23</sc>; <italic>p</italic> &lt; 0.001<sc>)</sc> and having three- or more-birth ordered children by 4.26 times (AOR = 4.<sc>26</sc>, 95% CI = <sc>2.</sc>07, 9.03; <italic>p</italic> &lt; 0.001), and in-house smoking <sc>(AOR = 1.</sc>74, 95% <sc>CI = 1.01</sc>, 3.05; <italic>p</italic> = 0.04).</p>", "<p id=\"Par34\">In addition, exclusive breastfeeding alone significantly minimizes ARI in under-five children (AOR = 0.48, 95% CI = 0<sc>.28, 0.82</sc>; <italic>p</italic> = 0.01<sc>)</sc> [Table ##TAB##3##4##].</p>", "<p id=\"Par35\">\n\n</p>" ]
[ "<title>Result</title>", "<p id=\"Par23\">The analysis considered three hundred and forty-eight children aged 6 to 59 months, with <sc>174</sc> cases and <sc>174</sc> controls. As a matched case-control study by age and gender, the distribution of boys (60.34%) and girls (39.66%) was similar in both the case and control groups. Most participants in each group were between the ages of <sc>2</sc>5–36 months (39.66% of cases and 39.08% of controls).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par36\">This case-control study, individually matched by age and gender- was conducted at a tertiary children’s hospital in Bangladesh and aimed to investigate the association of in-house environmental factors and acute respiratory infection among children aged 6–59 months in the country’s population where we identified that several household environmental factors had a critical role to developing childhood acute respiratory infection (ARI). The study encompassed 348 participants and performed both bivariate and multivariate conditional logistic regression models to explore the associations.</p>", "<p id=\"Par37\">Our study observed a substantial increase in ARI among children living in - crowded households with more than three persons per bedroom. Specifically, our findings indicated a 2.12-fold increase in the odds of ARI in such conditions (OR = 2.12, 95% CI: 1.38, 3.28). Even after adjusting all other variables, it remained unchanged. This aligned with previous research in Canada, which demonstrated a similar association where indoor CO<sub>2</sub> where indoor <sc>CO2</sc> levels increased with the number of indoor occupants, significantly elevating the risk of respiratory infections among young children [##UREF##21##27##]. Congested living conditions made spreading infections easier, increasing the risk of cross-infection when family members sneezed, coughed, or talked. Such houses were mostly ill-ventilated [##UREF##22##28##]. Studies revealed that poor ventilation in the house increases the odds of ARIs in young children [##UREF##23##29##, ##REF##29743893##30##]. However, indoor humidity was also influenced by reduced out-to-indoor airflow rates, which augmented the growth of microorganisms in the house, increasing the risk of ARI in the susceptible group [##UREF##24##31##]. The result of the study was consistent with other countries, such as India and Nigeria, where the variable overcrowding in the house was considered [##REF##25810626##19##, ##REF##24669339##32##].</p>", "<p id=\"Par38\">The present study also shed light on a significant association between unimproved toilet facilities and the increased odds of childhood ARI by 4.35 times (AOR = 4.35, 95% CI: 2.14, 9.26) after adjusting for the effect of other covariates. Our findings aligned with studies conducted in similar settings, including Bangladesh, India and Pakistan, which consistently reported similar results [##UREF##12##17##, ##REF##25810626##19##, ##REF##24664785##33##]. Unimproved toilets were primarily prevalent in rural areas where access to modern sanitation facilities was often limited or unavailable. These unimproved facilities were typically utilized by people with lower levels of education and financial means [##UREF##25##34##, ##UREF##26##35##]. The lack of access to improved sanitation not only increases the risk of ARIs but also contributes to a broader public health challenge by facilitating the transmission of infectious diseases.</p>", "<p id=\"Par39\">In Bangladesh, young children generally accompany their mothers while cooking. In our study, dirty cooking fuel was found to be significantly associated with ARIs. Such fuels were mostly used in rural areas. The analysis revealed higher odds of ARIs among children of rural dwellings than among children of urban dwellings and the findings were compatible with several studies [##REF##25810626##19##, ##UREF##27##36##]. Studies have also shown that irritant air pollutants, such as particulate matter, carbon monoxide, nitrogen dioxide, sulfur dioxide, and formaldehyde, are produced more in solid biomass fuel combustion than in clean fossil fuels. These toxic air pollutants generated within the house become trapped and have the potential to increase microbial infection susceptibility [##UREF##28##37##]. A meta-analysis conducted with the studies in rural households showed that exposure to solid biomass fuel significantly increased the risk of ARI among children by 3.53 times [##UREF##29##38##].</p>", "<p id=\"Par40\">The current study also brought to light the adverse impact of exposure to second hand smoke in children, increasing their susceptibility to acute respiratory infections (ARIs). This association was consistent with findings from various regions, Nepal, Bangladesh, and Cameroon [##UREF##7##10##, ##REF##24664785##33##, ##UREF##27##36##]. Second hand smoke, often found in households where family members smoke indoors, can impair the natural protective mechanisms against ARI in children [##UREF##30##39##]. However, it is noteworthy that not all studies reported such a link. A notable exception was found in the study conducted in Ethiopia [##UREF##28##37##], which did not find a significant association. Contextual factors, such as smoking prevalence and cultural practices, may influence these variations in findings.</p>", "<p id=\"Par41\">Furthermore, our findings aligned with a recent meta-analysis that revealed a concerning association. Pregnant women exposed to passive smoking at home amplify the risk of delivering preterm babies [##REF##26808045##40##]. Preterm children were particularly vulnerable to infections [##REF##36071597##41##]. The present study observed a 2.44-field elevated odds of ARI among the children with preterm birth (AOR = 2.44, 95% CI: 1.43, 4.23. Additionally, our findings underlined the heightened susceptibility of premature babies to infections, particularly during their first year of life [##REF##29382648##42##]. Preterm birth, a complex and multifaceted issue, is associated with an increased risk of various health challenges, including a higher likelihood of developing acute respiratory infections (ARIs). Our study indeed aligned with these trends as we observed significantly higher odds of ARI among preterm children under the age of five in a study conducted in India [##UREF##8##11##].</p>", "<p id=\"Par42\">Our study findings emphasized the vital role of parental education in reducing the occurrence of childhood ARIs. The health and well-being of children are intricately linked to their caregivers’ knowledge, attitudes, and practices regarding water, sanitation and hygiene (WASH) [##UREF##31##43##]. Studies from various regions have consistently demonstrated the protective association between parental education and a reduced risk of ARI. For instance, research conducted in Nigeria found a protective correlation between childhood ARI and parental education [##REF##24669339##32##]. Similarly, a study encompassing several developing nations indicated that maternal education played a pivotal role in reducing the risk of childhood ARI [##UREF##32##44##].</p>", "<p id=\"Par43\">Our study showed that a family with a relatively high income (exceeding 25,000 BDT/month) had significant protection against ARI among children under five in conditional logistic regression analysis. However, in-house environmental factors were regarded as an indication of social and economic disadvantage [##REF##11988443##45##]. Individuals with economic constraints were usually forced to live in a house with insufficient household environmental facilities for their necessities. Previous studies from Bangladesh also revealed such results [##UREF##10##14##–##UREF##12##17##].</p>", "<p id=\"Par44\">In our study, we found that those who were exclusively breastfed, properly immunized for age, and had fewer than two siblings (in cases of multiple births) had significantly lower odds of ARI in childhood. Studies from different countries have provided similar results [##UREF##7##10##, ##REF##24669339##32##, ##UREF##27##36##]. Having more siblings reduces the mothers’ attention on individual children, thus increasing the chance of different diseases. Immunoglobulins in breast milk help significantly reduce the risk of ARI in children. The healthy children had fewer odds of ARI, but the association was not significant, which contrasts with the findings of other countries [##UREF##27##36##, ##UREF##33##46##].</p>", "<p id=\"Par45\">Improving home ventilation is a low-cost strategy. It involves simply opening windows and doors to disperse excess <sc>CO</sc><sub><sc>2</sc></sub> and create an environment less conducive to the growth of harmful microorganisms. Additionally, discouraging indoor smoking is another low-cost measure that can reduce ARIs in children and help mitigate the risk of premature birth, which is also independently associated with ARIs. Supporting this, continuation of breastfeeding for at least six months and offering guidance to mothers with larger families is essential. Furthermore, the population-based approach prioritizes health education, especially in rural areas, to reduce reliance on unclean cooking fuels and promote improved sanitation facilities. Complementing these efforts, broader initiatives aimed at poverty reduction, social equity and establishing a supportive social welfare system can ensure that residents are not compelled to live in overcrowded, inadequate spaces due to sudden financial shocks.</p>", "<p id=\"Par46\">Our analysis had some limitations that need to be acknowledged. It was tertiary hospital-based research and, therefore, did not highlight the hidden aspect of the iceberg epidemic, including mother-child pairs who could not use hospital facilities or even primary health care. Recruiting controls at the hospital may have introduced a self-selection bias. Future research should use a longitudinal sample to confirm the causal relations between public and private hospitals nationwide. Further, research could comprehensively explore the causal relationships between various factors and ARI incidence.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par47\">The study hypotheses were adequately tested to confirm that in-house environmental factors in Bangladesh have an apparent, significant influence on childhood ARI, especially unimproved household sanitation facilities, in-house crowding (children living in a house where more than three people live in a bedroom), and in-house smoking, which were found to be important influencers in developing acute respiratory infection among under-five children. In addition, higher birth order and preterm birth were also found to play an important role in the development of ARI. Conversely, exclusive breastfeeding might significantly reduce ARIs in children under five in Bangladesh.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Acute respiratory infection (ARI) is one of the leading causes of morbidity and mortality among children under five globally, particularly in regions like South Asia and sub-Saharan Africa. Bangladesh has made substantial progress in reducing child mortality, yet pneumonia remains a significant contributor to under-five deaths. This study aimed to investigate the association between in-house environmental factors and childhood ARI, considering factors such as household crowding, smoking, and sanitation facilities.</p>", "<title>Methods</title>", "<p id=\"Par2\">This case-control study was conducted at a tertiary-level children’s hospital in Dhaka, Bangladesh, from March to September 2019. The study included children aged 6–59 months. Cases were children with ARI symptoms, while controls were children without such symptoms. Rigorous matching by age and gender was employed to ensure comparability. Data were collected through structured questionnaires, and bivariate and conditional logistic regression analyses were performed.</p>", "<title>Results</title>", "<p id=\"Par3\">Several household environmental factors were significantly associated with childhood ARIs. Children from overcrowded households <sc>(AOR = 2</sc>.66, 95% CI = <sc>1.52–4.</sc>7<sc>1</sc>; <italic>p</italic> &lt; 0.001), those using unclean cooking fuels (OR = 2.41, 95% CI: 1.56, 3.73; p = &lt; 0.001), those exposed to in-house smoking <sc>(AOR = 1.</sc>74, 95% CI <sc>= 1.01</sc>, 3.05; <italic>p</italic> = 0.04) and those with unimproved sanitation facilities faced higher odds (AOR = 4.35, 95% CI = <sc>2.14–9.26)</sc> of ARIs. Additionally, preterm birth and higher birth order were associated with an increased risk of ARI. In contrast, exclusive breastfeeding was a protective factor.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">In-house environmental factors, including sanitation, crowding and in-house smoking, significantly influence childhood ARIs. Additionally, birth order and preterm birth play a crucial role. Promoting exclusive breastfeeding is associated with a lower ARI risk among under-five children in Bangladesh. These findings can guide interventions to reduce ARIs in low-income regions, particularly in South Asia.</p>", "<title>Keywords</title>", "<p>Open access funding provided by Mid Sweden University.</p>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We would like to express our sincere gratitude to the children, families, dedicated physicians, and staff at Dhaka Shishu Hospital for their valuable cooperation in this study.</p>", "<title>Author contributions</title>", "<p>The manuscript was reviewed, accepted and approved by all contributors. Conceptualization and design: MDHH, KD. Data collection: MI, KI. Data curation: MDHH, MI, KI. Data analysis: MI, KI. Draft manuscript preparation: MI, KI, KD, MDHH. Review and editing: MDHH, KD. Supervision: MDHH. Critical review: KD.</p>", "<title>Funding</title>", "<p>Open access funding provided by Mid Sweden University. This study did not receive any funds from the public or any donor agency.</p>", "<p>Open access funding provided by Mid Sweden University.</p>", "<title>Data availability</title>", "<p>The data underlying the results presented in this study will be provided upon reasonable request to Dr Delwer H. Hawlader. Email: [email protected].</p>", "<title>Declarations</title>", "<title>Ethical approval</title>", "<p id=\"Par49\">This study was approved by the North South University Institutional Review Board (2019/OR-NSU/IRB-No.0701). All methods were performed following the relevant guidelines and regulations. Written informed consent was obtained from each child’s mother or father.</p>", "<title>Consent for publication</title>", "<p id=\"Par50\">Not Applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par6227\">The authors declare that they have no competing interests.</p>" ]
[]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Association of sociodemographic characteristics with childhood ARI: Unadjusted logistic regression model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Characteristics</th><th align=\"left\">Case<break/><italic>N</italic> = 174(%)</th><th align=\"left\">Control<break/><italic>N</italic> = 174 (%)</th><th align=\"left\">Unadjusted OR (95% CI)</th><th align=\"left\"><italic>p</italic> value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"5\">\n<bold>Child gender</bold>\n</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">105 (60.34)</td><td align=\"left\">105 (60.34)</td><td align=\"left\" rowspan=\"2\" colspan=\"2\">Matched variable</td></tr><tr><td align=\"left\">Female</td><td align=\"left\">69 (39.66)</td><td align=\"left\">69 (39.66)</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Child age (months)</bold>\n</td></tr><tr><td align=\"left\">6–12</td><td align=\"left\">22 (12.64)</td><td align=\"left\">17 (9.77)</td><td align=\"left\" rowspan=\"5\" colspan=\"2\">Matched variable</td></tr><tr><td align=\"left\">\n<sc>13–24</sc>\n</td><td align=\"left\">69 (39.66)</td><td align=\"left\">68 (39.08)</td></tr><tr><td align=\"left\">\n<sc>25–36</sc>\n</td><td align=\"left\">39 <sc>(22.41</sc>)</td><td align=\"left\">39 <sc>(22.41</sc>)</td></tr><tr><td align=\"left\">37–48</td><td align=\"left\">\n<sc>23 (13.21)</sc>\n</td><td align=\"left\">\n<sc>29 (13.22)</sc>\n</td></tr><tr><td align=\"left\">49–59</td><td align=\"left\"><sc>21 (12.</sc>07)</td><td align=\"left\"><sc>21 (12.</sc>07)</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Mother’s education</bold>\n</td></tr><tr><td align=\"left\">No Schooling<sc>/1</sc>–5 years</td><td align=\"left\">60 (34.48)</td><td align=\"left\">39 <sc>(22.41</sc>)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\"><sc>6–12</sc> years of schooling</td><td align=\"left\"><sc>82 (47.13</sc>)</td><td align=\"left\">88 (50.57)</td><td align=\"left\">0.<sc>61</sc> (0.37, 0.99)</td><td align=\"left\">0.<sc>051</sc></td></tr><tr><td align=\"left\"><sc>12</sc> + years of schooling</td><td align=\"left\"><sc>32 (1</sc>8.39)</td><td align=\"left\">47 <sc>(2</sc>7.<sc>01)</sc></td><td align=\"left\">0.44 <sc>(0.2</sc>4, 0.<sc>81)</sc></td><td align=\"left\">\n<bold>0.008*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Father’s education</bold>\n</td></tr><tr><td align=\"left\">Illiterate</td><td align=\"left\"><sc>25 (14.</sc>37)</td><td align=\"left\"><sc>14</sc> (8.05)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\"><sc>1–5</sc> years of schooling</td><td align=\"left\">43 <sc>(24.71)</sc></td><td align=\"left\"><sc>26 (1</sc>4.94)</td><td align=\"left\">0.93 (0.40, <sc>2.</sc>08)</td><td align=\"left\">0.854</td></tr><tr><td align=\"left\"><sc>6–12</sc> years of schooling</td><td align=\"left\">38 <sc>(21</sc>.84)</td><td align=\"left\">63 (36.<sc>21</sc>)</td><td align=\"left\">0.34 <sc>(0.1</sc>5, <sc>0.72)</sc></td><td align=\"left\">\n<bold>0.006*</bold>\n</td></tr><tr><td align=\"left\"><sc>12</sc> + years of schooling</td><td align=\"left\">68 (39.08)</td><td align=\"left\"><sc>71</sc> (40.80)</td><td align=\"left\">0.54 (0.<sc>25, 1.10)</sc></td><td align=\"left\">0.096</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Mother’s occupation</bold>\n</td></tr><tr><td align=\"left\">Employed</td><td align=\"left\"><sc>13</sc> (7.47)</td><td align=\"left\"><sc>11</sc> (6.<sc>32</sc>)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Housewife</td><td align=\"left\"><sc>161 (92</sc>.53)</td><td align=\"left\"><sc>163</sc> (93.68)</td><td align=\"left\">0.84 (0.36, <sc>1.92</sc>)</td><td align=\"left\">0.673</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Family monthly income</bold>\n</td></tr><tr><td align=\"left\"><bold>≤</bold> <sc>100</sc>00</td><td align=\"left\">60 (34.48)</td><td align=\"left\">44 <sc>(25.2</sc>9)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\"><sc>10,001–2</sc>5000</td><td align=\"left\">88 (50.57)</td><td align=\"left\"><sc>92 (52.</sc>87)</td><td align=\"left\">0.70 (0.43, <sc>1.1</sc>4)</td><td align=\"left\">0.<sc>153</sc></td></tr><tr><td align=\"left\">\n<sc>&gt; 25,000</sc>\n</td><td align=\"left\"><sc>26 (1</sc>4.94)</td><td align=\"left\">38 <sc>(21</sc>.84)</td><td align=\"left\">0.50 (0<sc>.26</sc>, 0.94)</td><td align=\"left\">\n<bold>0.033*</bold>\n</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Association of house-environmental factors with childhood ARI: Unadjusted logistic regression model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Characteristics</th><th align=\"left\">Case<break/><sc>n = 174</sc> (%)</th><th align=\"left\">Control<break/><sc>n = 174</sc> (%)</th><th align=\"left\">Unadjusted OR (95% CI)</th><th align=\"left\"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"5\">\n<bold>Residence</bold>\n</td></tr><tr><td align=\"left\">Urban</td><td align=\"left\"><sc>62</sc> (35.63)</td><td align=\"left\">94 <sc>(54.02</sc>)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Rural</td><td align=\"left\"><sc>112</sc> (64.37)</td><td align=\"left\">80 (45.98)</td><td align=\"left\"><sc>2.12 (1</sc>.38, 3<sc>.2</sc>8)</td><td align=\"left\">\n<bold>0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>In-house crowding</bold>\n</td></tr><tr><td align=\"left\"><bold>≤</bold> 3</td><td align=\"left\"><sc>81</sc> (46.55)</td><td align=\"left\"><sc>132</sc> (75.86)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">&gt; 3</td><td align=\"left\">93 (53.45)</td><td align=\"left\"><sc>42 (24.13</sc>)</td><td align=\"left\">3.<sc>61 (2.29</sc>, 5.74)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Cooking fuel</bold>\n</td></tr><tr><td align=\"left\">Clean</td><td align=\"left\">79 (45.40)</td><td align=\"left\"><sc>11</sc>6 (66.67)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Unclean</td><td align=\"left\">95 (54.59)</td><td align=\"left\">58 (33.33)</td><td align=\"left\"><sc>2.41 (1.</sc>56, 3.73)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>In-house Smoking habit by family members</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\"><sc>10</sc>4 (59.77)</td><td align=\"left\"><sc>122</sc> (70<sc>.11</sc>)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">70 (4<sc>0.2</sc>3)</td><td align=\"left\"><sc>52 (29.</sc>89)</td><td align=\"left\"><sc>1.</sc>58 <sc>(1.02, 2.</sc>47)</td><td align=\"left\">\n<bold>0.04*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Source of drinking water</bold>\n</td></tr><tr><td align=\"left\">Tap/piped water</td><td align=\"left\">76 (43.68)</td><td align=\"left\"><sc>11</sc>4 (65.5<sc>2</sc>)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Tube well/surface water</td><td align=\"left\">98 (56.<sc>32</sc>)</td><td align=\"left\">60 (34.48)</td><td align=\"left\"><sc>2.</sc>45 <sc>(1</sc>.59, 3.79)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Toilet facilities</bold>\n</td></tr><tr><td align=\"left\">Improved</td><td align=\"left\"><sc>10</sc>8 <sc>(62</sc>.07)</td><td align=\"left\"><sc>156</sc> (89.66)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Unimproved</td><td align=\"left\">66 (37.93)</td><td align=\"left\"><sc>18 (10.</sc>34)</td><td align=\"left\"><sc>5.2</sc>9 (3.03, 9.66)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Shared toilet</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\"><sc>12</sc>0 (68.97)</td><td align=\"left\"><sc>12</sc>9 (74.<sc>14)</sc></td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">53 (30.46)</td><td align=\"left\">45 <sc>(25.86)</sc></td><td align=\"left\"><sc>1.27</sc> (0.79, <sc>2.</sc>03)</td><td align=\"left\">0.<sc>324</sc></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Association of children and maternal characteristics with childhood ARI: Unadjusted logistic regression model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Characteristics</th><th align=\"left\">Case<break/><italic>N</italic> = 174 (%)</th><th align=\"left\">Control<break/><italic>N</italic> = 174 (%)</th><th align=\"left\">Unadjusted OR (95% CI)</th><th align=\"left\"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"5\">\n<bold>Birth order</bold>\n</td></tr><tr><td align=\"left\">≥ 3 born</td><td align=\"left\"><sc>61</sc> (35.06)</td><td align=\"left\">\n<sc>27 (15.52)</sc>\n</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">2nd born</td><td align=\"left\">54 (3<sc>1.</sc>03)</td><td align=\"left\">63 (36.<sc>21</sc>)</td><td align=\"left\">0.38 (0<sc>.22</sc>, 0.69)</td><td align=\"left\">\n<bold>0.00</bold>\n<bold><sc>2*</sc></bold>\n</td></tr><tr><td align=\"left\">1st born</td><td align=\"left\">59 (33.9<sc>1)</sc></td><td align=\"left\">84 (48.<sc>28)</sc></td><td align=\"left\">0.<sc>31</sc> (0.<sc>19</sc>, 0.58)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Gestational age</bold>\n</td></tr><tr><td align=\"left\">Full term</td><td align=\"left\">94 <sc>(54.02</sc>)</td><td align=\"left\"><sc>11</sc>9 (68.39)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Preterm</td><td align=\"left\">80 (45.98)</td><td align=\"left\">55 <sc>(31.61</sc>)</td><td align=\"left\"><sc>1.</sc>84 <sc>(1.1</sc>9, <sc>2.</sc>86)</td><td align=\"left\">\n<bold>0.006*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Mode of delivery</bold>\n</td></tr><tr><td align=\"left\">C-section</td><td align=\"left\">83 (47.70)</td><td align=\"left\"><sc>101</sc> (58.05)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Normal</td><td align=\"left\"><sc>91 (52.</sc>30)</td><td align=\"left\">73 <sc>(41.9</sc>5)</td><td align=\"left\"><sc>1.</sc>5<sc>2</sc> (0.99, <sc>2.32)</sc></td><td align=\"left\">0.054</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Exclusive breastfeeding</bold>\n</td></tr><tr><td align=\"left\">No</td><td align=\"left\">86 (49.43)</td><td align=\"left\">58 (33.33)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Yes</td><td align=\"left\">83 (47.70)</td><td align=\"left\"><sc>11</sc>3 (64.94)</td><td align=\"left\">0.50 (0<sc>.32</sc>, 0.77)</td><td align=\"left\">\n<bold>0.00</bold>\n<bold><sc>2*</sc></bold>\n</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Nutritional Status</bold>\n</td></tr><tr><td align=\"left\">Malnourished</td><td align=\"left\">54 (3<sc>1.</sc>03)</td><td align=\"left\">34 <sc>(19.</sc>54)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">Healthy</td><td align=\"left\">80 (45.98)</td><td align=\"left\">59 (33.9<sc>1)</sc></td><td align=\"left\">0.85 (0.49, <sc>1.</sc>47)</td><td align=\"left\">0.570</td></tr><tr><td align=\"left\" colspan=\"5\">\n<bold>Vaccination</bold>\n</td></tr><tr><td align=\"left\">Complete for age</td><td align=\"left\"><sc>13</sc>8 <sc>(79.31</sc>)</td><td align=\"left\"><sc>161 (92</sc>.53)</td><td align=\"left\">Reference</td><td align=\"left\"/></tr><tr><td align=\"left\">No/Incomplete for age</td><td align=\"left\">36 <sc>(20</sc>.69)</td><td align=\"left\"><sc>12</sc> (6.90)</td><td align=\"left\">3.50 <sc>(1</sc>.80, <sc>7.2</sc>6)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Association of potential in-house environmental and maternal factors with childhood ARI: Adjusted Conditional logistic regression model</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Characteristics</th><th align=\"left\">Reference</th><th align=\"left\">Adjusted OR (95% CI)</th><th align=\"left\"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"4\">\n<bold>Mother’s education</bold>\n</td></tr><tr><td align=\"left\"><sc>6–12</sc> years of schooling</td><td align=\"left\" rowspan=\"2\"><sc>No/1–5</sc> years schooling</td><td align=\"left\">0.83 (0.43, <sc>1.</sc>63)</td><td align=\"left\">0.60</td></tr><tr><td align=\"left\"><sc>12</sc> + years of schooling</td><td align=\"left\"><sc>1.</sc>55 (0.59, <sc>4.17)</sc></td><td align=\"left\">0.38</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>In-house crowding</bold>\n</td></tr><tr><td align=\"left\">&gt; 3</td><td align=\"left\">&lt;=3</td><td align=\"left\"><sc>2.</sc>66 <sc>(1.</sc>5<sc>2</sc>, <sc>4.71)</sc></td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Source of water</bold>\n</td></tr><tr><td align=\"left\">Tube well/surface water</td><td align=\"left\">Tap/piped water</td><td align=\"left\"><sc>1.27</sc> (0.64, <sc>2.51)</sc></td><td align=\"left\">0.50</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Cooking fuel</bold>\n</td></tr><tr><td align=\"left\">Unclean</td><td align=\"left\">Clean</td><td align=\"left\"><sc>1.</sc>77 (0.9, 3.47)</td><td align=\"left\">0.<sc>10</sc></td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Toilet facilities</bold>\n</td></tr><tr><td align=\"left\">Unimproved</td><td align=\"left\">Improved</td><td align=\"left\">4.35 <sc>(2.14, 9.2</sc>6)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>In-house Smoking habit by family members</bold>\n</td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">No</td><td align=\"left\"><sc>1.</sc>74 <sc>(1.01</sc>, 3.05)</td><td align=\"left\">\n<bold>0.04*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Birth order</bold>\n</td></tr><tr><td align=\"left\">≥ 3 born</td><td align=\"left\" rowspan=\"2\">1st born</td><td align=\"left\">4.<sc>26 (2.</sc>07, 9.03)</td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\">2nd born</td><td align=\"left\"><sc>1.15</sc> (0.63, <sc>2.</sc>09)</td><td align=\"left\">0.64</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Gestational age</bold>\n</td></tr><tr><td align=\"left\">Preterm</td><td align=\"left\">Full term</td><td align=\"left\"><sc>2.</sc>44 <sc>(1.</sc>43, 4.<sc>23)</sc></td><td align=\"left\">\n<bold>&lt; 0.001*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Exclusive breastfeeding</bold>\n</td></tr><tr><td align=\"left\">Yes</td><td align=\"left\">No</td><td align=\"left\">0.48 (0<sc>.28, 0.82)</sc></td><td align=\"left\">\n<bold>0.01*</bold>\n</td></tr><tr><td align=\"left\" colspan=\"4\">\n<bold>Vaccination</bold>\n</td></tr><tr><td align=\"left\">No/Incomplete for age</td><td align=\"left\">Complete for age</td><td align=\"left\"><sc>1.</sc>76 (0.77, 4.<sc>18)</sc></td><td align=\"left\">0.<sc>19</sc></td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>*significant at a 5% significance level</p><p>OR: odds ratio; CI: confidence interval</p></table-wrap-foot>", "<table-wrap-foot><p>*significant at a 5% significance level</p><p>OR: odds ratio; CI: confidence interval</p></table-wrap-foot>", "<table-wrap-foot><p>*significant at a 5% significance level, C-section: cesarean section</p><p>OR: odds ratio; CI: confidence interval</p></table-wrap-foot>", "<table-wrap-foot><p>*significant at a 5% significance level</p><p>AOR: adjusted odds ratio; CI: confidence interval</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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{ "acronym": [ "ARI", "WHO", "UNICEF", "MDG", "GAPPD", "OR", "AOR", "CI", "MUAC", "EPI", "VIF", "LPG", "BDT", "C-section" ], "definition": [ "Acute Respiratory Infections", "World Health Organization", "United Nations Children’s Fund", "Millennium Development Goal", "Global Action Plan for the Prevention and Control of Pneumonia and Diarrhea", "Odds Ratio", "Adjusted Odds Ratio", "Confidence Interval", "Mid-Upper Arm Circumference", "Expanded Program on Immunization", "Variance Inflation Factor", "Liquefied Petroleum Gas", "Bangladeshi Taka", "Cesarean Section" ] }
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2024-01-14 23:43:47
BMC Pediatr. 2024 Jan 13; 24:38
oa_package/20/d7/PMC10787469.tar.gz
PMC10787470
0
[ "<title>Introduction</title>", "<p id=\"Par14\">The movement of torsos in both hemiplegic and non-hemiplegic stroke patients is obviously [##REF##29947957##1##]. Fuglmeyer proposed that respiratory dysfunction was common in stroke patients [##REF##6396267##2##], and further that deep core muscles play a vital role in maintaining trunk posture and respiration [##REF##29848898##3##].</p>", "<p id=\"Par15\">Abnormalities in trunk control, such as reduced abdominal muscle activity and loss of selective trunk activity, results in the loss of flexion, rotation, and lateral flexion movements of the torso, as well as a lack of synchronized activation between the trunk and limb muscles [##REF##36819714##4##]. Trunk dysfunction after stroke also produces impaired balance and physical activities essential for daily living [##REF##37639516##5##]. Hyperactive back extensor muscle activity in patients often leads to abnormal lifting of the ribs and chest, which reduces the range of motion of the diaphragm and affects the activity of abdominal and deep core muscles [##UREF##0##6##], ultimately having an impact on lung capacity [##REF##35884689##7##]. Research has shown that forced vital capacity and maximum expiratory and inspiratory pressures are increased in stroke patients with hemiplegia after specialized trunk control training [##REF##33979696##8##].</p>", "<p id=\"Par16\">In turn, weakened respiratory muscles made it difficult for those patients to maintain proper breathing pattern, lead to a deterioration in trunk function, balance, and daily activities [##REF##36408866##9##]. Early stroke patients often experience a marked reduction in respiratory muscle strength on both the hemiplegic and non-hemiplegic side [##REF##12714347##10##], which was be worsened by prolonged confinement to bed. This caused reduced cough ability, difficulty in sputum excretion, and eventually in the worst cases to pneumonia [##REF##27821939##11##]. Studies have shown that respiratory muscle training improves maximal inspiratory pressure, inspiratory muscle endurance and peak expiratory flow in the short term, thereby promoting coughing ability [##REF##34687960##12##] and improving indicators such as the Trunk Impairment Scale (TIS) and Barthel Index (BI) [##REF##32795561##13##]. Research has shown that 6 weeks of respiratory muscle training effectively increases the speed and distance of patients’ centre of pressure shift [##REF##30712955##14##] and 8 weeks of inspiratory training improves the patient’s reflexes and ability to perform dynamic tasks [##REF##31074198##15##], which are required for balance.</p>", "<p id=\"Par17\">Respiratory and motor function training are both important treatments for post-stroke rehabilitation [##REF##34454573##16##, ##REF##32004440##17##]. However, the relationships between trunk capacity, balance, and activities of daily living to the inspiratory, and expiratory muscles, as well as lung volume at different levels of impairment after stroke, remain unclear. Expiratory muscle rehabilitation for stroke patients has not received much attention that it deserves until relatively recently [##UREF##1##18##]. Indeed, the profession of respiratory therapists was not established in China until 2019, and still at present problems remain, such as insufficient attention to respiratory training and inconsistent operating standards [##REF##34496514##19##]. It is imperative to investigate the impact of routine rehabilitation training on the respiratory function of patients with hemiplegia, as it may contribute to the optimization of post-stroke rehabilitation programs. Therefore, a retrospective study was conducted to explore these aspects in patients with post-stroke hemiplegia. The findings of this study may have significant implications for enhancing the motor performance and respiratory capacity of post-stroke patients.</p>" ]
[ "<title>Methods</title>", "<title>Study design and patients</title>", "<p id=\"Par18\">This was a retrospective study that received approval from ShangHai Xuhui Central Hospital Ethics Committee (No.2022-043). Due to the nature of a retrospective study, the need for informed consent was waived by ShangHai Xuhui Central Hospital Ethics Committee. Data were de-identified prior to analysis.</p>", "<p id=\"Par19\">Ultimately the clinical history data of 134 patients at hospital admission, including gender, age, height, weight, disease type, duration of onset, motor function assessment results and pulmonary capacity results were collected and analyzed. In addition, 60 of 134 patients’ motor function assessment and pulmonary capacity results at discharge were obtained.</p>", "<p id=\"Par20\">Through electronic medical records, the data of stroke patients hospitalized in the Rehabilitation Department of Xuhui District Central Hospital between December 2018 and March 2022 were reviewed. Patients had to meet the following criteria to be included in the study: 1) a diagnosis of cerebral infarction or cerebral hemorrhage; 2) met the diagnostic criteria for stroke; 3) hemiplegia patients with a first episode of stroke; 4) aged ≥ 18 years; 5) sitting balance of ≥ grade 1; and 6) had a report of a pulmonary ventilatory function test. Exclusion criteria were: 1) had consciousness disorder and severe cognitive dysfunction; and 2) had acute diseases of the heart, brain, kidney and other organs. The research process is shown schematically in Fig. ##FIG##0##1##.</p>", "<title>Evaluation of motor functions</title>", "<p id=\"Par21\">Trunk function has been identified as an important early predictor of functional outcomes after stroke. The TIS is a valid tool for examining person with hemiplegia’ trunk control ability, allowing for both qualitative and quantitative assessment of trunk deficits [##UREF##2##20##]. TIS consists of 3 subscales: namely, static, dynamic sitting balance and trunk coordination in a sitting position, with a total maximum score of 23 [##REF##15137564##21##]. According to previous studies, non-ambulatory patients had a median TIS score of 8 and ambulatory patients had a median score of 14 (11–18) [##REF##16774097##22##]. Although it was not a direct reference basis, we believe it was a relatively appropriate method for our research. We took 8 points and 18 points as two nodes and divided patients into 3 groups based on their TIS scores and classified thus: a patient score of 0–7 points as a severe level, 8–17 points a moderate level and 18–23 points a slight level.</p>", "<p id=\"Par22\">The Berg Balance Scale (BBS) is a comprehensive balance function examination scale, which evaluates the patient’s ability to shift actively their centre of gravity through multiple functional activities, including dynamic and static balance tasks while sitting and standing. It had 14 item list with each item consisting of a 5-point ordinal scale ranging from 0 to 4. 0 indicated the lowest level of function and 4 was the highest level. Scores of 0 to 20 suggested that patients had poor balance and needed a wheelchair. Scores of 21–40 indicated that patients had a certain balance ability and could walk with assistance. Scores of 41–56 showed that patients can walk independently [##UREF##3##23##].</p>", "<p id=\"Par23\">The BI was used to measure the degree of assistance required for patients’ activities involved in daily living, which included 10 personal activities with a total score of 100 points. Guidelines for interpreting BI scores are: scores of 0–20 indicate “total” dependency; 21–60 indicate “severe” dependency; 61–90 indicate “moderate” dependency; and 91–99 indicate “slight” dependency [##REF##34299709##24##].</p>", "<title>Evaluation of spirometry</title>", "<p id=\"Par24\">Spirometric data were evaluated through a portable pulmonary function instrument (Xeek X1, China) with the patients in a sitting position. The measured value of the parameter was expressed as a percentage of the predicted value. The main collected parameters were as follows: 1) maximal inspiratory pressure (MIP), male normal value ≥ 75% (of predicted value), female normal value ≥ 50%; 2) maximal expiratory pressure (MEP), male normal value ≥ 100%, female normal value ≥ 80%; 3) forced vital capacity (FVC): the total volume of air exhaled with maximum strength and fastest speed; 4) forced expiratory volume in 1 s(FEV<sub>1</sub>), evaluated the volume of air exhaled by the patient using the maximum force and the fastest speed in 1 s, which reflected ventilation dysfunction and was dependent on the respiratory muscles and airway status [##REF##29785797##25##]. It is divided into 5 different levels: mild, FEV<sub>1</sub> over 70%; moderate, FEV<sub>1</sub> 60–70%; moderately severe, FEV<sub>1</sub> 50–60%; severe, FEV<sub>1</sub> 35–50%; very severe, FEV<sub>1</sub> &lt; 35% [##REF##16264058##26##]. 5) peak expiratory flow (PEF) reflecting the highest flow rate during forced expiration, which is an important index reflecting the strength of the expiratory muscles [##UREF##4##27##]; and 6) maximal mid-expiratory flow (MMEF) representing the mean expiratory flow rate at which 25%-75% of vital capacity is exhaled with force.</p>", "<title>Statistical analysis</title>", "<p id=\"Par25\">The data were analyzed using SPSS 23 (SPSS Inc., 233S. Wacker Dr., IL). Categorical data are presented as percentages and continuous data as means ± standard deviation (SD) and medians (interquartile ranges).</p>", "<p id=\"Par26\">Spearman’s correlation coefficient was employed to analyze the relationship between values in motor function scales and respiratory indicators. The Wilcoxon signed-rank test was utilized to analyze any differences in spirometric data among individuals with varying degrees of motor dysfunction, as well as the differences in motor function across different spirometric indexes. Additionally, we used the Minimal Clinically Important Difference (MCID) of TIS, BBS and BI to determine if genuine changes in a patient’s function had occurred [##REF##11552860##28##]. We also analyzed the changes in lung function indexes after 3 weeks of physical therapy intervention. Finally, the study investigated the differences in the change values of spirometric indexes among individuals with different levels of motor dysfunction following the 3-week physical therapy intervention. A significance level (<italic>p</italic>) of 0.05 was determined for the statistical comparisons.</p>" ]
[ "<title>Results</title>", "<p id=\"Par27\">The details of demographic and related indicators are presented in Table ##TAB##0##1##. The data of 100 males and 34 females were analyzed, the average age was 66.7 ± 10.1 years and the average post-stroke duration was 42.3 ± 34.8 days; 114 (85.1%) patients were diagnosed with ischemic stroke, and 20 (14.9%) with hemorrhagic stroke. Left hemiplegia was 57 with a proportion of 42.5%, while right hemiplegia was 77 with a proportion of 57.5%.</p>", "<title>Correlation between motor function and spirometric data</title>", "<p id=\"Par28\">The results of Spearman’s correlation coefficient analysis are presented in Fig. ##FIG##1##2##. TIS was shown to have slight positive correlations with MIP, MEP, FVC, FEV<sub>1</sub> and PEF.</p>", "<p id=\"Par29\">BBS showed moderate positive correlations with MIP (<italic>r</italic> = 0.37, <italic>P</italic> &lt; 0.001, PEF (<italic>r</italic> = 0.40, <italic>P</italic> &lt; 0.001), and slight positive correlations with MEP, FVC, FEV<sub>1</sub> and MMEF. BI indicated moderate positive correlations with MIP (<italic>r</italic> = 0.33, <italic>P</italic> &lt; 0.001), MEP (<italic>r</italic> = 0.32, <italic>P</italic> &lt; 0.001), FVC (<italic>r</italic> = 0.3, <italic>P</italic> &lt; 0.001), and slight positive correlations with MEP, FVC, FEV<sub>1</sub> and MMEF. FEV<sub>1</sub> and PEF and MMEF.</p>", "<title>Respiratory functions at multiple motor dysfunction levels</title>", "<p id=\"Par30\">TIS determined a patient’s trunk control ability at 3 levels, namely severe, moderate and slight. The MIP values were 29.0 (20.3–44.0), 33.7 (22.4–45.3) and 38.4 (28.1–59.4) for the 3 levels, respectively with statistical significance (<italic>P</italic> = 0.029). The MEP was 29.0 (19.4–38.0), 33.3 (23.1–46.8) and 45.8 (29.4–80.5) for the 3 levels, respectively with significant differences (<italic>P</italic> = 0.002). Significant effects were also found with FVC (<italic>P</italic> = 0.014) and FEV<sub>1</sub> (<italic>P</italic> = 0.011) for the 3 levels of TIS (Table ##TAB##1##2##, Fig. ##FIG##2##3##a). The findings indicated that different trunk control abilities showed differences in these respiratory indicators. Thus, increasing trunk control ability will clearly help in improving these respiratory indicators.</p>", "<p id=\"Par31\">BBS evaluates a patient’s balance ability at 3 levels, namely severe, moderate, and slight. Table ##TAB##1##2## and Fig. ##FIG##2##3##b illustrate the spirometric data at 3 different balance ability levels. MIP values were 29.1 (18.5–38.0), 36.2 (28.4–47.3) and 43.9 (33.2–64.6), respectively for the 3 levels with statistical significance reached (<italic>P</italic> &lt; 0.001). The MEP was 28.4 (19.2–39.2), 37.2 (28.9–59.6) and 54.6 (36.1–71.9), respectively for the 3 levels all with significant differences (<italic>P</italic> &lt; 0.001). Significant differences were also found in FVC (<italic>P</italic> = 0.002), FEV<sub>1</sub> (<italic>P</italic> &lt; 0.001), PEF (<italic>P</italic> &lt; 0.001), and MMEF (<italic>P</italic> = 0.01) at the 3 BBS levels. The results indicated that different balance abilities reflect differences in these respiratory indicators, thus increasing balance ability should help to improve respiratory indicators.</p>", "<p id=\"Par32\">BI assessed the patient’s dependency on daily living activities, which included 5 levels. This study included 3 levels, namely total, severe and moderate dependency due to the highest BI scores being ≤ 90 points. The results indicated that patients’ respiratory muscle strength decreased with increasing dependency on living activities. MIP values were 20.5 (17.2–28.5), 32.2 (22.3–44.7) and 46.8 (32.8–66.7) for 3 levels with significant differences (<italic>P</italic> &lt; 0.001). MEP values were 26 (22.6–29), 31.8 (23.6–43.8) and 56.3 (34.3–71.9), respectively for 3 levels with significant differences (<italic>P</italic> = 0.008). Significant differences were associated with FVC (<italic>P</italic> = 0.005) and PEF (<italic>P</italic> = 0.04) on three BI levels (Table ##TAB##1##2##, Fig. ##FIG##2##3##c). The results indicated that various daily living abilities exhibited differences in these respiratory indicators, thus increasing daily living abilities should help to facilitate these respiratory indicators.</p>", "<title>Motor dysfunction at 2 levels of respiratory muscle strength</title>", "<p id=\"Par33\">Between normal and abnormal MIP levels, TIS was 13 (10–15) and 15 (13–16) points, with no significant differences (<italic>P</italic> = 0.099), whereas BBS were 17 (3–32.5) and 33 (29–42), with significant differences (<italic>P</italic> = 0.02), and BI were 50 (35–55) and 62.5 (50–70), also with significant differences (<italic>p</italic> = 0.022) (Table ##TAB##2##3##).</p>", "<p id=\"Par34\">Between normal and abnormal MEP levels, TIS were 13 (10–15) and 13 (7.5–15) points, with no significant differences (<italic>P</italic> = 0.944), BBS were 20 (3–35) and 31 (17.5–3.5), with no significant differences (<italic>P</italic> = 0.597), and BI were 50 (35–60) and 55 (42.5–57.5), again with no significant differences (<italic>P</italic> = 0.876) (Table ##TAB##2##3##).</p>", "<title> Motor dysfunction at 5 pulmonary ventilation dysfunction levels (FEV<sub>1</sub>)\n</title>", "<p id=\"Par35\">The FEV<sub>1</sub> was divided into five different levels, including mild: FEV<sub>1</sub> over 70%; moderate: FEV<sub>1</sub> 60–70%; moderately severe: FEV<sub>1</sub> 50–60%; severe: FEV<sub>1</sub> 35–50%; very severe: FEV<sub>1</sub> &lt; 35%. Table ##TAB##2##3## shows no significant difference in TIS (<italic>P</italic> = 0.33), however, there were significant differences in BBS (<italic>P</italic> = 0.004) and BI (<italic>P</italic> = 0.044) in 5 different ventilatory dysfunction levels. The patients with higher FEV<sub>1</sub> values tended to have better balance ability and independence in daily activities.</p>", "<title>The progress of motor function brought changes in spirometric data after 3-weeks rehabilitation</title>", "<p id=\"Par36\">Regular rehabilitation training used the Bobath technique to inhibit abnormal posture and movement patterns, to induced postural reflex and balance reaction, and to promote the formation of normal movement patterns. It included joint movement training, supine turnover and bridge training, transfer of the torso while sitting and standing, and ball activities to build muscle strength and endurance, improve static and dynamic balance, and enhance walking ability. All patients did not receive specific breathing training.</p>", "<p id=\"Par37\">The correlation coefficients between the two assessment results of TIS, BBS and BI were 0.840, 0.947 and 0.956. MCID were 1.5, 3.4 and 4.3 points respectively (Table ##TAB##3##4##). MCID determined whether the change in two assessment results was real or caused by random testing errors. It was considered that changed scores were real when the change value was greater than MCID [##REF##17916763##29##]. The changed scores (T<sub>0</sub>-T<sub>1</sub>) of TIS, BBS and BI were 3.5, 4 and 10 points, respectively which all exceeded the MCID values, indicating that patients’ scores had really changed after 3-weeks treatment.</p>", "<p id=\"Par38\">Table ##TAB##4##5## shows the improvements in respiratory muscle strength and pulmonary volume. MIP at T<sub>1</sub> (38.1 ± 2.0) was significantly higher than at T<sub>0</sub> (31.0 ± 1.8) (<italic>P</italic> &lt; 0.001). MEP at T<sub>1</sub> (35.4 ± 1.9) was significantly greater than at T<sub>0</sub> (27.2 ± 1.6) (<italic>P</italic> &lt; 0.001). FVC significantly increased from 65.9 ± 2.5 (T<sub>0</sub>) to 71.9 ± 2.5 (T<sub>1</sub>) (<italic>P</italic> &lt; 0.001). FEV<sub>1</sub> significantly promoted from 59.7 ± 2.7 (T<sub>0</sub>) to 68.7 ± 2.6 (T<sub>1</sub>) (<italic>P</italic> &lt; 0.001). PEF significantly improved from 29.2 ± 1.8 (T<sub>0</sub>) to 36.8 ± 2.0 (T<sub>1</sub>) (<italic>P</italic> &lt; 0.001). MMEF were 46.5 ± 2.9 (T<sub>0</sub>) and 57.5 ± 3.5 (T<sub>1</sub>), significantly difference(<italic>P</italic> &lt; 0.001).</p>", "<p id=\"Par39\">The results of Spearman’s correlation coefficient analysis are in Fig. ##FIG##3##4##. △ was used to represent the variation of the parameters. △TIS had significant positive correlations with △MEP (<italic>r</italic> = 0.49, <italic>P</italic> &lt; 0.001), △FVC (<italic>r</italic> = 0.27,<italic> P</italic> = 0.034), △FEV<sub>1</sub> (<italic>r</italic> = 0.49, <italic>P</italic> &lt; 0.001), △PEF (<italic>r</italic> = 0.45, <italic>P</italic> &lt; 0.001) and MMEF (<italic>r</italic> = 0.42, <italic>P</italic> = 0.001). △BI showed significant positive correlations with △FEV<sub>1</sub> (<italic>r</italic> = 0.31,<italic> P</italic> = 0.016).</p>", "<p id=\"Par40\">The results demonstrated that △MIP were 2.6(0–4.7), 6.4(4.5–11.1) and 8.3, with significant differences (<italic>P</italic> = 0.026), at severe, moderate, and slight TIS levels, respectively (Table ##TAB##5##6##, Fig. ##FIG##4##5##a). Less improvement of inspiratory pressure was found in the severe level of a trunk control disorder. The △MIP were 5 (2.5–8.5), 9 (4.8–12.6) and 9.7 (7.3–14.6), with a significant difference (<italic>P</italic> = 0.044), for severe, moderate, and mild BBS levels, respectively (Table ##TAB##5##6##, Fig. ##FIG##4##5##b). Respiratory parameters showed no differences in 3 different BI levels (Table ##TAB##5##6##, Fig. ##FIG##4##5##c).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par41\">This study analyzed variations in respiratory functions in patients with different motor disabilities and motor functions, and differences in these indicators at baseline and after 3 weeks treatment. Abnormal inspiratory muscle strength resulted in lower balance skills and activities of daily living, but not in trunk control. Regular training enhanced the strength of both inspiratory and expiratory muscles in stroke patients. Those with mild motor impairment demonstrated greater improvement in their inspiratory muscles strength after therapy.</p>", "<title>Correlations between motor and pulmonary function and respiratory muscles</title>", "<p id=\"Par42\">TIS was used to evaluate the capacity of trunk muscles to maintain an upright posture and execute targeted movements during both static and dynamic postural modifications [##UREF##5##30##]. BBS assessed a patient’s ability actively to shift the center of gravity. BI was used to measure performance in activities of daily living. MIP and MEP revealed the strength of the maximum inspiratory and expiratory muscles. FVC and FEV<sub>1</sub> were indicators that directly reflect the respiratory capacity, which depends on muscular strength [##UREF##6##31##, ##REF##28588895##32##]. PEF and MMEF refer to the maximum expiratory flow rate and the average respiratory flow rate in the mid-section during forced exhalation, respectively. These parameters were primarily influenced by lung volume and expiratory muscle strength [##UREF##7##33##, ##UREF##8##34##].</p>", "<p id=\"Par43\">It was found that TIS, BBS, and BI were positively correlated with MIP, MEP, FVC, FEV<sub>1</sub>, PEF, and MMEF in the present study. The results showed consistency with Fuglmyer’s study, indicating that respiratory dysfunction is prevalent in stroke patients with hemiplegia [##REF##6396267##2##]. BBS and BI exhibited a moderate correlation with MIP in our study. The results also showed that FVC, FEV<sub>1</sub>, PEF and MMEF were correlated with respiratory muscle strength, especially the expiratory muscles. Further analysis of the variations in respiratory function among different levels of motor impairment were undertaken.</p>", "<title>Respiratory function analysis of different motor function levels</title>", "<p id=\"Par44\">The study found notable differences in MIP, MEP and pulmonary function indicators at three levels of TIS, as well as BBS and BI. In contrast, there were significant differences in BBS and BI at two levels of MIP and 5 levels of FEV<sub>1</sub>. These results are consistent with the previous findings that BBS and BI were moderately correlated with MIP.</p>", "<p id=\"Par45\">The decrease in TIS score after a stroke was primarily due to a reduction in selective trunk activities, which included the ability to perform unconstrained active movements of the trunk such as flexion, dorsiflexion, lateral flexion, and rotation [##UREF##9##35##]. Patients may exhibit abnormal trunk movement patterns, which require more energy for trunk activities [##REF##35962597##36##] and can lead to a solidification pattern of the trunk, back extensor spasms, limited thoracic movement and diaphragm activity. These factors further inhibit the activity of the deep and superficial core muscles. TIS reflects the ability to move the torso flexibly and does not directly result in changes in respiratory muscle strength or lung volume [##UREF##10##37##]. Restricted trunk mobility indirectly resulted in a restrictive respiratory syndrome [##REF##2254236##38##].</p>", "<p id=\"Par46\">The lower the BBS and BI scores, then lower pulmonary function parameter values were recorded. A pervious study had also indicated that balance was independently associated with individual activities and participation [##REF##22502804##39##]. This study found a strong correlation between BBS and BI. The analysis of the relationship between BI and respiratory function yielded a similar relationship between balance and respiratory function.</p>", "<p id=\"Par47\">The inspiratory and expiratory muscles are the deep core muscles that directly affected a patient’s the ability to maintain trunk stability, rather than the selective control ability of the trunk. Therefore, there was no difference in MIP or MEP whether TIS was normal or not. However, patients with normal inspiratory muscles had higher BBS scores than those with abnormal activity, but the BBS scores did not differ between those with normal and abnormal MEP as well as for BI. The results indicated that inspiratory muscles were more involved in balance functions or daily activities than expiratory muscles, implying that the inspiratory muscles were more important for maintaining body balance and daily activities [##REF##36017026##40##].</p>", "<p id=\"Par48\">In brief, various motor functions had direct or indirect effects on respiratory function. Conversely, the inspiratory muscles had a direct impact on a patient’s balance and daily activities.</p>", "<title>Changes in motor and pulmonary function and respiratory muscle after 3 weeks rehabilitation</title>", "<p id=\"Par49\">Bobath selective trunk postural control was an essential component of routine rehabilitation training, including turnover and bridge exercise training in the supine position, shifting the torso in the sitting and standing positions, and activating trunk muscles with ball activities. Our study found that after 3 weeks of routine rehabilitation without specific respiratory exercises, increased motor function also improved the strength of the respiratory muscles and pulmonary volume. Changes in TIS were moderately positively correlated with changes in MEP, FEV1, PEF, and FVC.</p>", "<p id=\"Par50\">The results suggest that routine rehabilitation focusing on facilitating active and flexible trunk movement will significantly improve TIS, and will reflect enhanced control of trunk. Deep core muscles, such as the abdominal muscles, which are also the main exhalation muscles, were activated [##REF##27408635##41##]. This activation explains the results, which found that changes in TIS were moderately correlated with changes in MEP. Of a correlation between TIS and MIP was not found, as also reported in the study by Jandt [##REF##21157882##42##]. Zheng’s study demonstrated that routine rehabilitation improved diaphragm mobility but not its thickness [##UREF##11##43##], implying that routine training did not improve inspiratory muscle strength. Therefore, based on routine rehabilitation, it was necessary to improve the inspiratory muscle strength of patients with hemiplegia through multiple means, including increasing the thoracic range of motion, diaphragmatic mobilization, and muscle strength training.</p>", "<p id=\"Par51\">Moreover, we also found that MIP improved in various ways in patients with different trunk control abilities. Patients with severe trunk control disorders showed less improvement. Possible reasons for this findings included: (1) in routine rehabilitation, patients received passive training supplemented by low-dose active training, which cannot effectively activate the diaphragm; (2) inspiratory training was often neglected due to poor patient cooperation; and (3) the therapist may neglect the active and passive training of the diaphragm in clinical treatment. Therefore, specific inspiratory muscle training should be included in the clinical rehabilitation process, especially for patients with severe trunk control disorders.</p>", "<p id=\"Par52\">After 3 weeks treatment, we observed differences in the improvement of MIP among individuals with varying levels of balance disorders. Patients with higher balance abilities achieved a better degree of improvement in their core muscle groups, which was beneficial for the original role of the respiratory muscles [##REF##29848898##3##].</p>", "<p id=\"Par53\">The present study had some limitations, such as the small number of patients studied with certain impairment levels, which made it difficult to explain certain issues. Additionally, the 3-week treatment period was relatively short for stroke patients due to hospitalization requirements. Future studies will increase the treatment time to observe its impact on the respiratory muscles and pulmonary function.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par54\">This research found that patients with hemiplegia exhibited suboptimal respiratory muscle strength and pulmonary function in the presence of more severe motor dysfunction. Impaired inspiratory muscle strength was found to be associated with a reduced balance ability and limitations in activities necessary for daily living, while trunk control remained unaffected. The functions of the inspiratory muscles, particularly the diaphragm, were crucial for both respiratory and motor functions. Routine rehabilitation enhanced exercise capacity and improved the activity of the expiratory muscles more than the inspiratory muscles. Therefore, in clinical settings, enhancing motor function may improve respiratory function. However, it is imperative for therapists to prioritize the activation of diaphragm function in critically ill patients.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The interaction between motor dysfunction and respiratory functions in stroke patients with hemiplegia are not fully understood, particularly with regard to the relationship between changes in trunk control, balance, and daily activities, and changes in respiratory muscle strength and pulmonary volume. Investigating this relationship will facilitate the optimization of stroke rehabilitation strategies.</p>", "<title>Methods</title>", "<p id=\"Par2\">Clinical history data were collected from 134 patients to analyze the relationship between motor function scales scores and spirometric data. The data from 60 patients’ data were used to evaluate the relationship between motor function scales scores and spirometric data at baseline and after 3-weeks rehabilitation.</p>", "<title>Results</title>", "<p id=\"Par3\">(1) Patients with lower scores on Trunk impairment Scale (TIS), Berg Balance Scale (BBS) and Barthel Index (BI) had weaker respiratory muscle strength and pulmonary function. (2) Stroke patients’ BBS and BI scores showed differences between normal and unnormal maximal inspiratory pressure (MIP), but not in TIS. (3) Improvements in motor function led to promotion of enhanced respiratory function. Patient exhibited less MIP improvement at the severe level of TIS and BBS.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Patients with hemiplegia exhibited diminished respiratory muscle strength and pulmonary function at a more severe motor dysfunction level. Impaired inspiratory muscle strength was associated with reduced balance ability and limitations in activities required for daily living. Enhanced motor function improved respiration and rehabilitation programs should prioritize the activation of diaphragm function to improve overall outcomes.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Authors’ contributions</title>", "<p>M Li sorted out the data and drafted the manuscript. Y Zhou made substantial contributions to study conception and design. Y Huang contributed to the analysis and interpretation of spirometric data. HY Chen completed patient’s pulmonary function test. SS Wang collected and organized patients’ medical histories. Y Zhang made important intellectual contributions by critically reviewing and approving the final version of the manuscript. All authors read and agreed to the final manuscript.</p>", "<title>Funding</title>", "<p>The work was supported by 2020 Shanghai Municipal Health Commission Chinese Medicine Research Project (No.2020LZ005) and 2020 Shanghai Xuhui district scientific research project (No. SHXH202032) and 2023 Xuhui District Health System Peak Discipline Construction Funding Project.</p>", "<title>Availability of data and materials</title>", "<p>The datasets are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par55\">This study has been approved by ShangHai Xuhui Central Hospital Ethics Committee (No.2022-043). Due to the nature of retrospective study, the need for informed consent was waived by ShangHai Xuhui Central Hospital Ethics Committee.</p>", "<title>Consent for publication</title>", "<p id=\"Par56\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par57\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Research flow chart</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Spearman’s correlation between motor function and spirometric data</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p><bold>a</bold> Spirometric data at three levels of TIS (<bold>a</bold>), BBS (<bold>b</bold>) and BI (<bold>c</bold>)</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Spearman’s correlation between variations of motor function and variations of spirometric data</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Variation of spirometric data at 3 levels of TIS (<bold>a</bold>), BBS (<bold>b</bold>) and BI (<bold>c</bold>) after 3 weeks rehabilitation</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>General characteristics of patients at admission</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"><bold>Value at T</bold><sub><bold>0</bold></sub></th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\">General, n (%)</td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">100 (74.6)</td></tr><tr><td align=\"left\"> Female</td><td align=\"left\">34 (25.3)</td></tr><tr><td align=\"left\">Age, years (Mean ± SD)</td><td align=\"left\">66.7 ± 10.1</td></tr><tr><td align=\"left\">Post-stroke duration, days (Mean ± SD)</td><td align=\"left\">42.3 ± 34.8</td></tr><tr><td align=\"left\" colspan=\"2\">Type, n (%)</td></tr><tr><td align=\"left\"> Ischemic</td><td align=\"left\">114 (85.1)</td></tr><tr><td align=\"left\"> Hemorrhagic</td><td align=\"left\">20 (14.9)</td></tr><tr><td align=\"left\" colspan=\"2\">Hemiplegic side, n (%)</td></tr><tr><td align=\"left\"> Left</td><td align=\"left\">57 (42.5)</td></tr><tr><td align=\"left\"> Right</td><td align=\"left\">77 (57.5)</td></tr><tr><td align=\"left\">TIS (Points, Mean ± SD)</td><td align=\"left\">12.0 ± 4.3</td></tr><tr><td align=\"left\">BBS (Points, Mean ± SD)</td><td align=\"left\">19.9 ± 16.4</td></tr><tr><td align=\"left\">BI (Points, Mean ± SD)</td><td align=\"left\">47.5 ± 15.5</td></tr><tr><td align=\"left\">MIP (%, Mean ± SD)</td><td align=\"left\">36.7 ± 18.8</td></tr><tr><td align=\"left\">MEP (%, Mean ± SD)</td><td align=\"left\">38.7 ± 22.5</td></tr><tr><td align=\"left\">FVC (%, Mean ± SD)</td><td align=\"left\">72.9 ± 24.9</td></tr><tr><td align=\"left\">FEV<sub>1</sub> (%, Mean ± SD)</td><td align=\"left\">70.2 ± 27.2</td></tr><tr><td align=\"left\">PEF (%, Mean ± SD)</td><td align=\"left\">38.3 ± 23.8</td></tr><tr><td align=\"left\">MMEF (%, Mean ± SD)</td><td align=\"left\">57.7 ± 31.8</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Spirometric data (Median (Q1-Q3)) at three levels of trunk Impairment, Berg Balance Scale and Barthel Index</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"4\"><bold>Trunk Impairment Scale (TIS)</bold></th><th align=\"left\" colspan=\"4\"><bold>Berg Balance Scale (BBS)</bold></th><th align=\"left\" colspan=\"4\"><bold>Barthel Index (BI)</bold></th></tr><tr><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 20)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 101)</bold></th><th align=\"left\"><bold>Slight (</bold><bold><italic>N</italic></bold><bold> = 13)</bold></th><th align=\"left\"><italic>P</italic></th><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 68)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 43)</bold></th><th align=\"left\"><bold>Slight (</bold><bold><italic>N</italic></bold><bold> = 23)</bold></th><th align=\"left\"><italic>P</italic></th><th align=\"left\"><bold>Total (</bold><bold><italic>N</italic></bold><bold> = 6)</bold></th><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 108)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 20)</bold></th><th align=\"left\"><italic>P</italic></th></tr></thead><tbody><tr><td align=\"left\"><bold>MIP (%)</bold></td><td align=\"left\">29.0 (20.3–44.0)</td><td align=\"left\">33.7 (22.4–45.3)</td><td align=\"left\">38.4 (28.1–59.4)</td><td align=\"left\">0.029</td><td align=\"left\">29.1 (18.5–38.0)</td><td align=\"left\">36.2 (28.4–47.3)</td><td align=\"left\">43.9 (33.2–64.6)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">20.5 (17.2–28.5)</td><td align=\"left\">32.2 (22.3–44.7)</td><td align=\"left\">46.8 (32.8–66.7)</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\"><bold>MEP (%)</bold></td><td align=\"left\">29.0 (19.4–38.0)</td><td align=\"left\">33.3 (23.1–46.8)</td><td align=\"left\">45.8 (29.4–80.5)</td><td align=\"left\">0.002</td><td align=\"left\">28.4 (19.2–39.2)</td><td align=\"left\">37.2 (28.9–59.6)</td><td align=\"left\">54.6 (36.1–71.9)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">26 (22.6–29)</td><td align=\"left\">31.8 (23.6–43.8)</td><td align=\"left\">56.3 (34.3–71.9)</td><td align=\"left\">0.008</td></tr><tr><td align=\"left\"><bold>FVC (%)</bold></td><td align=\"left\">63.3 (47.2–78.3)</td><td align=\"left\">71.1 (54.7–89.1)</td><td align=\"left\">94.7 (78.5–103.8)</td><td align=\"left\">0.014</td><td align=\"left\">65.8 (48.1–86.6)</td><td align=\"left\">71.1 (57.7–86.2)</td><td align=\"left\">94.6 (77.9–103.8)</td><td align=\"left\">0.002</td><td align=\"left\">55.3 (48.4–58.8)</td><td align=\"left\">70.6 (54.7–88.3)</td><td align=\"left\">85.3 (69.5–101.4)</td><td align=\"left\">0.005</td></tr><tr><td align=\"left\"><bold>FEV</bold><sub><bold>1</bold></sub><bold> (%)</bold></td><td align=\"left\">59.7 (48.9–77.9)</td><td align=\"left\">67.4 (49.2–85.2)</td><td align=\"left\">88.7 (71.7–100.4)</td><td align=\"left\">0.011</td><td align=\"left\">61.9 (43.9–79.2)</td><td align=\"left\">67.4 (57.3–84.4)</td><td align=\"left\">89.2 (76.5–99.1)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">57.3 (52.3–60.9)</td><td align=\"left\">69.7 (50.8–85)</td><td align=\"left\">83.8 (54–99.1)</td><td align=\"left\">0.051</td></tr><tr><td align=\"left\"><bold>PEF (%)</bold></td><td align=\"left\">31.9 (19.8–38.2)</td><td align=\"left\">33.6 (23.3–47.6)</td><td align=\"left\">45.9 (40.6–75.3)</td><td align=\"left\">0.154</td><td align=\"left\">30.2 (19.6–41.1)</td><td align=\"left\">37.7 (27.7–52.4)</td><td align=\"left\">48.9 (35.3–64.1)</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">27.1 (22.8–31.7)</td><td align=\"left\">33.6 (24.9–46)</td><td align=\"left\">48.2 (31.1–58)</td><td align=\"left\">0.04</td></tr><tr><td align=\"left\"><bold>MMEF (%)</bold></td><td align=\"left\">46.6 (33.1–70.6)</td><td align=\"left\">52.4 (35.8–71.0)</td><td align=\"left\">68.7 (53.6–84.3)</td><td align=\"left\">0.254</td><td align=\"left\">47 (34–67.1)</td><td align=\"left\">52.4 (35.3–73.5)</td><td align=\"left\">64.6 (54.6–82.4)</td><td align=\"left\">0.01</td><td align=\"left\">36.5 (34.7–46.5)</td><td align=\"left\">52.6 (36–71.8)</td><td align=\"left\">59.2 (43.3–88.3)</td><td align=\"left\">0.223</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>TIS, BBS and BI values (Median (Q1-Q3)) with normal and abnormal MIP and MEP level and five different FEV<sub>1</sub> levels</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"3\"><bold>Maximal inspiratory pressure (MIP)</bold></th><th align=\"left\" colspan=\"3\"><bold>Maximal expiratory pressure (MEP)</bold></th><th align=\"left\" colspan=\"6\"><bold>Forced expiratory volume in 1 s (FEV</bold><sub><bold>1</bold></sub><bold>)</bold></th></tr><tr><th align=\"left\"><bold>Abnormal (</bold><bold><italic>N</italic></bold><bold> = 124)</bold></th><th align=\"left\"><bold>Normal (</bold><bold><italic>N</italic></bold><bold> = 10)</bold></th><th align=\"left\"><bold><italic>p</italic></bold></th><th align=\"left\"><bold>Abnormal (</bold><bold><italic>N</italic></bold><bold> = 131)</bold></th><th align=\"left\"><bold>Normal (</bold><bold><italic>N</italic></bold><bold> = 3)</bold></th><th align=\"left\"><bold><italic>p</italic></bold></th><th align=\"left\"><bold>Mild (</bold><bold><italic>N</italic></bold><bold> = 67)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 19)</bold></th><th align=\"left\"><bold>Moderately Severe (</bold><bold><italic>N</italic></bold><bold> = 18)</bold></th><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 18)</bold></th><th align=\"left\"><bold>Very Severe (</bold><bold><italic>N</italic></bold><bold> = 12)</bold></th><th align=\"left\"><bold><italic>p</italic></bold></th></tr></thead><tbody><tr><td align=\"left\">TIS (Point)</td><td align=\"left\">13 (10–15)</td><td align=\"left\">15 (13–16)</td><td align=\"left\">0.099</td><td align=\"left\">13 (10–15)</td><td align=\"left\">13 (7.5–15)</td><td align=\"left\">0.944</td><td align=\"left\">13 (11–15)</td><td align=\"left\">14 (11–15)</td><td align=\"left\">14 (6–15)</td><td align=\"left\">11.5 (8–14)</td><td align=\"left\">11 (10–14)</td><td align=\"left\">0.330</td></tr><tr><td align=\"left\">BBS (Point)</td><td align=\"left\">17 (3–32.5)</td><td align=\"left\">33 (29–42)</td><td align=\"left\">0.02</td><td align=\"left\">20 (3–35)</td><td align=\"left\">31 (17.5–33.5)</td><td align=\"left\">0.597</td><td align=\"left\">25 (9–42)</td><td align=\"left\">21 (2.5–28)</td><td align=\"left\">22 (1–35)</td><td align=\"left\">3 (1–16)</td><td align=\"left\">15.5 (1–23)</td><td align=\"left\">0.004</td></tr><tr><td align=\"left\">BI (Point)</td><td align=\"left\">50 (35–55)</td><td align=\"left\">62.5 (50–70)</td><td align=\"left\">0.022</td><td align=\"left\">50 (35–60)</td><td align=\"left\">55 (42.5–57.5)</td><td align=\"left\">0.876</td><td align=\"left\">50 (40–60)</td><td align=\"left\">45 (35–55)</td><td align=\"left\">50 (30–60)</td><td align=\"left\">35 (30–55)</td><td align=\"left\">45 (35–60)</td><td align=\"left\">0.044</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Assessment results at T0 and T1 and MCID of TIS, BBS and BI. Data expressed as Median (Q1-Q3)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"><bold>TIS (</bold><bold><italic>n</italic></bold><bold> = 60)</bold></th><th align=\"left\"><bold>BBS (</bold><bold><italic>n</italic></bold><bold> = 60)</bold></th><th align=\"left\"><bold>BI (</bold><bold><italic>n</italic></bold><bold> = 60)</bold></th></tr></thead><tbody><tr><td align=\"left\">T<sub>0</sub></td><td align=\"left\">13 (9.3–14)</td><td align=\"left\">10 (1–23)</td><td align=\"left\">45 (35–55)</td></tr><tr><td align=\"left\">T<sub>1</sub></td><td align=\"left\">16 (14–19)</td><td align=\"left\">16.5 (4.3–32)</td><td align=\"left\">55 (45–65)</td></tr><tr><td align=\"left\">T<sub>0</sub>-T<sub>1</sub></td><td align=\"left\">3.5 (2–4.8)</td><td align=\"left\">4 (2–8)</td><td align=\"left\">10 (5–15)</td></tr><tr><td align=\"left\">MCID</td><td align=\"left\">1.5</td><td align=\"left\">3.4</td><td align=\"left\">4.3</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>TIS, BBS, BI, Pulmonary ventilatory function and respiratory muscle strength variation (Mean ± SD) after 3-week rehabilitation</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\"><bold>T</bold><sub><bold>0</bold></sub></th><th align=\"left\"><bold>T</bold><sub><bold>1</bold></sub></th><th align=\"left\"><bold><italic>P</italic></bold></th></tr></thead><tbody><tr><td align=\"left\">MIP (%)</td><td align=\"left\">31.0 ± 1.8</td><td align=\"left\">38.1 ± 2.0</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">MEP (%)</td><td align=\"left\">27.2 ± 1.6</td><td align=\"left\">35.4 ± 1.9</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">FVC (%)</td><td align=\"left\">65.9 ± 2.5</td><td align=\"left\">71.9 ± 2.5</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">FEV<sub>1</sub> (%)</td><td align=\"left\">59.7 ± 2.7</td><td align=\"left\">68.7 ± 2.6</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">PEF (%)</td><td align=\"left\">29.2 ± 1.8</td><td align=\"left\">36.8 ± 2.0</td><td align=\"left\">&lt; 0.001</td></tr><tr><td align=\"left\">MMEF (%)</td><td align=\"left\">46.5 ± 2.9</td><td align=\"left\">57.5 ± 3.5</td><td align=\"left\">&lt; 0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab6\"><label>Table 6</label><caption><p>Variation (△) of Spirometric data at three BBS and BI levels after 3-week rehabilitation. Data expressed as Median (Q1-Q3)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"4\"><bold>Trunk Impairment Scale (TIS)</bold></th><th align=\"left\" colspan=\"4\"><bold>Berg Balance Scale (BBS)</bold></th><th align=\"left\" colspan=\"4\"><bold>Barthel Index (BI)</bold></th></tr><tr><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 10)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 49)</bold></th><th align=\"left\"><bold>Slight (</bold><bold><italic>N</italic></bold><bold> = 1)</bold></th><th align=\"left\"><bold><italic>p</italic></bold></th><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 40)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 16)</bold></th><th align=\"left\"><bold>Slight (</bold><bold><italic>N</italic></bold><bold> = 4)</bold></th><th align=\"left\"><bold><italic>p</italic></bold></th><th align=\"left\"><bold>Total (</bold><bold><italic>N</italic></bold><bold> = 1)</bold></th><th align=\"left\"><bold>Severe (</bold><bold><italic>N</italic></bold><bold> = 54)</bold></th><th align=\"left\"><bold>Moderate (</bold><bold><italic>N</italic></bold><bold> = 5)</bold></th><th align=\"left\"><bold><italic>p</italic></bold></th></tr></thead><tbody><tr><td align=\"left\">△MIP (%)</td><td align=\"left\">2.6 (0–4.7)</td><td align=\"left\">6.4 (4.5–11.1)</td><td align=\"left\">8.3</td><td align=\"left\">0.026</td><td align=\"left\">5 (2.5–8.5)</td><td align=\"left\">9 (4.8–12.6)</td><td align=\"left\">9.7 (7.3–14.6)</td><td align=\"left\">0.044</td><td align=\"left\">0</td><td align=\"left\">6 (3.5–10.9)</td><td align=\"left\">11 (8.3–11)</td><td align=\"left\">0.204</td></tr><tr><td align=\"left\">△MEP (%)</td><td align=\"left\">5.8 (1.7–10.7)</td><td align=\"left\">6 (1.7–11.4)</td><td align=\"left\">0.5</td><td align=\"left\">0.392</td><td align=\"left\">5.2 (1.5–10.2)</td><td align=\"left\">10.6 (4.3–14.5)</td><td align=\"left\">3.6 (0.9–10.2)</td><td align=\"left\">0.065</td><td align=\"left\">18.1</td><td align=\"left\">5.5 (1.5–10.7)</td><td align=\"left\">10.9 (10.5–11)</td><td align=\"left\">0.234</td></tr><tr><td align=\"left\">△FVC (%)</td><td align=\"left\">9.7 (3.1–14.6)</td><td align=\"left\">6.9 (-0.5–12.6)</td><td align=\"left\">3.5</td><td align=\"left\">0.599</td><td align=\"left\">7.9 (1.8–13.2)</td><td align=\"left\">5.4 (-3.1–9.8)</td><td align=\"left\">6.1 (3.7–10.8)</td><td align=\"left\">0.475</td><td align=\"left\">10.3</td><td align=\"left\">7.6 (-0.5–13.1)</td><td align=\"left\">4.5 (3.5–6.3)</td><td align=\"left\">0.685</td></tr><tr><td align=\"left\">△FEV<sub>1</sub> (%)</td><td align=\"left\">8.3 (0.7–19.0)</td><td align=\"left\">7.8 (2.2–18.0)</td><td align=\"left\">3.2</td><td align=\"left\">0.825</td><td align=\"left\">8 (1.3–18.3)</td><td align=\"left\">9.3 (3.8–18.3)</td><td align=\"left\">5.5 (2.3–14)</td><td align=\"left\">0.044</td><td align=\"left\">17.5</td><td align=\"left\">7.6 (1.8–19)</td><td align=\"left\">11.5 (6.9–13)</td><td align=\"left\">0.709</td></tr><tr><td align=\"left\">△PEF (%)</td><td align=\"left\">3.9 (1.3–11.3)</td><td align=\"left\">7.2 (2.2–11.8)</td><td align=\"left\">0.4</td><td align=\"left\">0.389</td><td align=\"left\">4.6 (1.3–11.3)</td><td align=\"left\">9.5 (4.9–14.3)</td><td align=\"left\">4.8 (2.2–9.9)</td><td align=\"left\">0.056</td><td align=\"left\">20.7</td><td align=\"left\">5.7 (1.7–10.9)</td><td align=\"left\">11.8 (7.8–20.5)</td><td align=\"left\">0.135</td></tr><tr><td align=\"left\">△MMEF (%)</td><td align=\"left\">4.6 (0.2–20.3)</td><td align=\"left\">10.2 (1.9–20.8)</td><td align=\"left\">-2.6</td><td align=\"left\">0.382</td><td align=\"left\">7.3 (1.1–21)</td><td align=\"left\">10.3 (6.8–20.6)</td><td align=\"left\">2.6 (-0.7–14.9)</td><td align=\"left\">0.236</td><td align=\"left\">18.7</td><td align=\"left\">7.5 (1.3–21.6)</td><td align=\"left\">10.5 (6.9–19.7)</td><td align=\"left\">0.82</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>T</italic><sub><italic>0</italic></sub> The time of admission, <italic>TIS</italic> Trunk Impairment Scale, <italic>BBS</italic> Berg balance scale, <italic>BI</italic> Barthel index, <italic>MIP</italic> Maximal inspiratory pressure, <italic>MEP</italic> Maximal expiratory pressure, <italic>FVC</italic> Force vital capacity, <italic>FEV</italic><sub><italic>1</italic></sub> Forced expiratory volume in one second, <italic>PEF</italic> Peak expiratory flow, <italic>MMEF</italic> Maximal mid expiratory flow</p></table-wrap-foot>", "<table-wrap-foot><p><italic>TIS</italic> Trunk Impairment Scale, <italic>BBS</italic> Berg balance scale, <italic>BI</italic> Barthel index, <italic>T0</italic> Time to assessment at admission, <italic>T1</italic> Time to assessment at discharge, <italic>MCID</italic> Minimal clinically important difference</p></table-wrap-foot>", "<table-wrap-foot><p><italic>T</italic><sub><italic>0</italic></sub> The time of admission, <italic>T</italic><sub><italic>1</italic></sub> The time after 3 weeks of treatment</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Meng Li, Ying Huang and HaiYun Chen contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12877_2023_4647_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12877_2023_4647_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12877_2023_4647_Fig3_HTML\" id=\"MO3\"/>", "<graphic xlink:href=\"12877_2023_4647_Fig4_HTML\" id=\"MO4\"/>", "<graphic xlink:href=\"12877_2023_4647_Fig5_HTML\" id=\"MO5\"/>" ]
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[{"label": ["6."], "surname": ["Park"], "given-names": ["SJ"], "article-title": ["Effects of inspiratory muscles training plus rib cage mobilization on chest expansion, inspiratory accessory muscles activity and pulmonary function in stroke patients"], "source": ["Appl Sci"], "year": ["2020"], "volume": ["10"], "issue": ["15"], "fpage": ["5178"]}, {"label": ["18."], "surname": ["Liu", "Ren", "Yu", "Chen", "Xu"], "given-names": ["J", "H", "Y", "Z", "K"], "article-title": ["Pulmonary rehabilitation after stroke"], "source": ["Phys Med Rehab Kuror"], "year": ["2017"], "volume": ["27"], "issue": ["06"], "fpage": ["329"], "lpage": ["334"]}, {"label": ["20."], "surname": ["Sidaway", "Ujma", "Krawczyk"], "given-names": ["M", "R", "M"], "article-title": ["Trunk Impairment Scale -TIS precise tool for evaluating trunk motor deficit of stroke patients"], "source": ["Adv Rehabil"], "year": ["2015"], "volume": ["29"], "issue": ["4"], "fpage": ["33"], "lpage": ["40"]}, {"label": ["23."], "surname": ["Miranda-Cantellops", "Tiu"], "given-names": ["N", "TK"], "source": ["Berg balance testing"], "year": ["2022"], "publisher-loc": ["Treasure Island"], "publisher-name": ["StatPearls Publishing"]}, {"label": ["27."], "surname": ["Sly", "Collins", "Morgan", "Taussig", "Landau"], "given-names": ["PD", "RA", "WJ", "LM", "LI"], "article-title": ["Lung function in cooperative subjects"], "source": ["Pediatric respiratory medicine"], "year": ["2008"], "edition": ["2"], "publisher-loc": ["Philadelphia"], "publisher-name": ["Mosby/ Elsevier"], "fpage": ["171"], "lpage": ["178"]}, {"label": ["30."], "surname": ["Karthikbabu", "Rao", "Manikandan", "Solomon", "Chakrapani", "Nayak"], "given-names": ["S", "BK", "N", "JM", "M", "A"], "article-title": ["Role of trunk rehabilitation on trunk control, balance and gait in patients with chronic stroke: a pre-post design"], "source": ["Neurosci Med"], "year": ["2011"], "volume": ["2"], "issue": ["02"], "fpage": ["61"], "lpage": ["67"]}, {"label": ["31."], "surname": ["P\u00e9rez"], "given-names": ["LL"], "article-title": ["Office spirometry"], "source": ["Osteopath Fam Physician"], "year": ["2013"], "volume": ["5"], "issue": ["2"], "fpage": ["65"], "lpage": ["69"]}, {"label": ["33."], "surname": ["Quanjer", "Lebowitz", "Gregg", "Miller", "Pedersen"], "given-names": ["PH", "MD", "I", "MR", "OF"], "article-title": ["Peak expiratory flow: conclusions and recommendations of a Working Party of the European Respiratory Society"], "source": ["Eur Respir J"], "year": ["1997"], "volume": ["24"], "fpage": ["2s"], "lpage": ["8s"]}, {"label": ["34."], "mixed-citation": ["Douglas RB. Pulmonary function and assessment. In: Waldron HA, editor. Occupational health practice"], "italic": ["."]}, {"label": ["35."], "surname": ["Davies", "Davies"], "given-names": ["PM", "PM"], "article-title": ["Problems associated with the loss of selective trunk activity in hemiplegia"], "source": ["Right in the middle: selective trunk activity in the treatment of adult hemiplegia"], "year": ["1990"], "edition": ["2"], "publisher-loc": ["Berlin, Heidelberg"], "publisher-name": ["Springer"], "fpage": ["31"], "lpage": ["65"]}, {"label": ["37."], "surname": ["Santos", "Dall\u2019alba", "Forgiarini", "Rossato", "Dias", "Junior"], "given-names": ["RSAD", "SCF", "SGI", "D", "AS", "LAF"], "article-title": ["Relationship between pulmonary function, functional independence, and trunk control in patients with stroke"], "source": ["Arq Neuro-Psiquiatr"], "year": ["2019"], "volume": ["77"], "issue": ["6"], "fpage": ["387"], "lpage": ["392"]}, {"label": ["43."], "surname": ["Zhang", "Wang", "Yang", "Qiao", "Xu", "Yu", "Wang", "Ni", "Wang", "Yao"], "given-names": ["Y", "C", "J", "L", "Y", "L", "J", "W", "Y", "Y"], "article-title": ["Comparing the effects of short-term Liuzijue exercise and core stability training on balance function in patients recovering from stroke: a pilot randomized controlled trial"], "source": ["Front Neurol"], "year": ["2022"], "volume": ["13"], "fpage": ["748"], "lpage": ["751"]}]
{ "acronym": [ "TIS", "BBS", "BI", "MIP", "MEP", "FVC", "FEV1", "PEF", "MMEF" ], "definition": [ "Trunk Impairment Scale", "The Berg Balance Scale", "The Barthel Index", "Maximal inspiratory pressure", "Maximal expiratory pressure", "Forced vital capacity", "Forced expiratory volume in 1 s", "Peak expiratory flow", "Maximal mid-expiratory flow" ] }
43
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2024-01-14 23:43:47
BMC Geriatr. 2024 Jan 13; 24:59
oa_package/28/8d/PMC10787470.tar.gz
PMC10787471
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Osteoarthritis (OA) is the most prevalent degenerative joint disease. OA leads to chronic low-grade synovitis, joint pain, and even disability [##REF##33406330##1##, ##UREF##0##2##]. Synovial tissues include a thin membrane lining the inside of synovial joints, comprising immune cells (e.g., monocytes, macrophages, dendritic cells), fibroblasts, and a sub-lining vascularized connective tissue. Among multiple immune cell types in OA synovium, macrophages are the most common immune cells in inflammatory synovial tissues and are correlated with the disease’s clinical symptoms [##REF##36789002##3##–##REF##34539648##6##]. Notably, OA is always first diagnosed at an irreversible stage after bone damage has occurred [##REF##22682469##7##]. The diagnosis by testing early or pre-osteoarthritic changes before the onset of irreversible changes is crucial for understanding its underlying pathogenesis and designing treatment strategies. Metabolic changes in synovial tissues may represent the earliest measurable changes and are considered reversible [##REF##22682469##7##, ##REF##32958644##8##]. Sulfur-containing amino acids play an important role in health and some inflammatory diseases, such as ulcerative colitis [##REF##16694758##9##–##REF##31027194##11##]. Cysteine is a semi-essential proteinogenic amino acid given its synthesis from methionine and serine by trans-sulfuration. L-cysteine exerts an anti-inflammatory effect, including enhancing the inhibitory effect of vitamin D under oxidative stress [##REF##19520150##12##–##REF##34410507##15##]. To date, sulfur metabolism in OA has not been studied.</p>", "<p id=\"Par6\">In response to the low-grade inflammation stress in OA, multiple forms of cell death occur in OA synovial tissues, such as apoptosis and ferroptosis [##REF##35118075##16##, ##REF##36982438##17##]. Notably, SLC7A11, coding for the sodium-independent cystine-glutamate antiporter Xc- [##REF##15151999##18##], is involved in the clearance of apoptotic cells [##REF##35614212##19##] and inhibition of cellular ferroptosis [##REF##36063875##20##, ##REF##33000412##21##]. SLC7A11 inhibition can increase efferocytosis of dendritic cells blocking the cysteine transport into cells. Interestingly, a recent study found that SLC7A11 was involved in regulating a new form of cell death, disulfidptosis, by mediating cysteine intake and inhibiting ferroptosis under glucose starvation conditions [##REF##15151999##18##, ##REF##36747082##22##]. Disulfidptosis is induced by aberrant disulfide bonds in actin cytoskeleton proteins and F-actin collapse and can be promoted by activating cytoskeleton-associated WAVE regulatory complex and Rac. In addition to disulfidptosis, SLC7A11 is also involved in two other sulfur-associated functions as per the gene ontology (GO), namely, “regulation of sulfur metabolic process” and “cysteine metabolic process” [##UREF##2##23##, ##UREF##3##24##]. Among the top-ranked proteins that can inhibit disulfidptosis in SLC7A11<sup>high</sup> cells, GYS1, NDUFA11, NUBPL, and LRPPRC promote glycogen synthesis and mitochondrial oxidative phosphorylation, suggesting the close relationship between energy metabolism and disulfidptosis [##REF##36747082##22##]. Therefore, whether the expression of sulfur metabolism-related genes is enhanced or weakened in OA synovial tissues merits investigation.</p>", "<p id=\"Par7\">To explore the role of sulfur metabolism-associated genes in OA, including those involved in cysteine metabolism, sulfur metabolism, and disulfidptosis, differentially expressed genes among them were identified and a consensus cluster analysis was performed to compare the C1/C2 groups and OA/healthy groups. We constructed a gene signature using LASSO COX regression and validated their diagnostic efficiency using receiver operating characteristic curve (ROC) analysis, followed by external validation using the expressional data from GSE12021 and GSE1919. To gain a deeper understanding of the relevant underlying molecular mechanisms, immunological relevance, and cell specificity of the signature gene, <italic>TM9SF2</italic>, we conducted correlational, functional enrichment, and immune cell deconvolution analyses. After silencing the expression of <italic>TM9SF2</italic> in THP-1-derived macrophages, phagocytosis by macrophages M2 was weakened. Our findings can provide molecular clues for the role of sulfur metabolism in the pathogenesis of OA along with new therapeutic targets.</p>" ]
[ "<title>Methods and materials</title>", "<title>Data resource and processing</title>", "<p id=\"Par8\">Microarray and single-cell RNA sequencing (scRNA-seq) data were obtained from the gene expression omnibus (GEO) database (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc\">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc</ext-link>=) with accession IDs, GSE55235/GSE55457/GSE82107/GSE12021/GSE1919, using the ‘GEOquery’ R package [##REF##17496320##25##]. The platform annotation documents were downloaded from GEO and annotated for microarray probes by using the ‘merge’ R command after Log<sub>2</sub>(<italic>x</italic> + 1) normalization. Batch effects among datasets GSE55235 (10 healthy and 10 OA synovial tissues), GSE55457 (10 healthy and 10 OA synovial tissues), and GSE82107 (7 healthy and 10 OA synovial tissues) were removed by the command, ‘removeBatchEffect(data, batch = datasets, design = group)’ in ‘Limma’ R package [##REF##25605792##26##]. Nine healthy and 10 OA synovial tissues in the GSE12021 dataset and 5 healthy and 5 OA synovial tissues in the GSE1919 dataset were obtained.</p>", "<title>Single-sample gene set enrichment analysis (ssGSEA)</title>", "<p id=\"Par9\">ssGSEA was performed and the enrichment score of each sample was calculated for energy metabolism- and sulfur metabolism-associated gene sets using the ‘GSVA’ R package [##UREF##4##27##]. Boxplots and heatmaps were drawn using the ‘ggplot2’ R package [##UREF##5##28##].</p>", "<title>Differentially expressed gene (DEG) analysis</title>", "<p id=\"Par10\">Student’s <italic>t</italic>-test was used to assess the significance of DEGs between OA and healthy groups. The ‘Limma’ R package was used to identify DEGs between C1 and C2 classes. Briefly, the ‘lmFit’ function for multiple linear regression was used, followed by the ‘eBays’ function to calculate moderated t-statistics/F-statistics and log odds of differential expression by using empirical Bayes moderation of the standard errors toward a common value, and finally, statistically significant DEGs were obtained.</p>", "<title>Cluster analysis</title>", "<p id=\"Par11\">Consensus cluster analysis was performed using the ‘ConsensusClusterPlus’ R package [##REF##20427518##29##] for the 10 sulfur-related DEGs. The agglomerative partition around medoids (PAM) clustering with a 1-Pearson correlation distance and resampling of 80% of the samples in 10 repetitions was used in the analysis. Clustering by tSNE was performed for the merged dataset, GSE55235/GSE55457/GSE82107, using the ‘Rtsne’ R package [##UREF##6##30##]. Specifically, we first obtained the z-score of the expression profile and used the ‘Rtsne’ function for dimensionality reduction analysis to obtain the dimensionality-reduced matrix.</p>", "<title>Functional enrichment analysis</title>", "<p id=\"Par12\">GO and pathway analysis based on gene cluster GO terms [including biological process (BP), molecular functions (MF), and cellular components (CC)] and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations were obtained by using the ‘clusterProfiler’ R package [##REF##22455463##31##] and virtualized by the ‘ggplot2’ R package. GSEA was performed by pre-ranking genes based on their correlation with classes C1/C2. We subsequently performed GSEA by pre-ranking the c2.cp.kegg.v7.4.symbols.gmt gene set from MsigDB [##REF##26771021##32##, ##REF##16199517##33##] by using the ‘clusterProfiler’ R package.</p>", "<title>Immune cell deconvolution analysis</title>", "<p id=\"Par13\">Immune cell deconvolution analysis methods, CIBERSORT [##REF##29344893##34##] and xCell [##REF##29141660##35##] were used to calculate the proportion and score of immune cell infiltration, respectively, in the synovial microenvironment using the ‘IOBR’ R package [##REF##34276676##36##]. Boxplots of proportions and scores were drawn with the ‘ggplot2’ R package. Student’s t-test was performed to compare between groups.</p>", "<title>Least absolute shrinkage and selection operator (LASSO)-COX regression analysis</title>", "<p id=\"Par14\">LASSO-COX regression analysis was performed using the ‘glmnet’ R package to identify signature genes and their coefficients to predict the risk of OA [##REF##27065756##37##, ##REF##20808728##38##].</p>", "<title>ROC analysis</title>", "<p id=\"Par15\">We used the ‘pROC’ R package [##UREF##7##39##] to perform ROC analysis, and the results were visualized with the ‘ggplot2’ R package.</p>", "<title>Correlational analysis</title>", "<p id=\"Par16\">Correlational analysis was performed by computing Pearson correlation coefficients between the expression levels of two genes or between the expression level of gene A and the infiltrated level of immune cell B, using the function, ‘cor’, of the base R package.</p>", "<title>Phagocytosis analysis</title>", "<p id=\"Par17\">THP-1-derived macrophages M2 were induced with 20 ng/ml PMA for two days followed by polarization with 20 ng/ml IFN-r and 100 ng/ml LPS for another two days. The macrophages were co-cultured with IgG-PE labeled latex beads (Phagocytosis Assay Kit (Cat. 600540; Cayman Chemical, Ann Arbor, MI, USA)) or PKH26-labeled apoptotic Jurkat cells for phagocytosis or efferocytosis for 1 h, respectively. For efferocytosis, apoptosis was induced in PKH26-labeled Jurkat cells by UV irradiation for 15 min. After apoptosis induction in Jurkat cells, they were added to the macrophage culture in a ratio of 1:10 (macrophages to Jurkat cells). The efficiency of phagocytosis/efferocytosis was quantified by flow cytometry.</p>", "<title>Interaction among proteins</title>", "<p id=\"Par18\">The protein–protein interaction (PPI) network analysis was performed using the STRING database (<ext-link ext-link-type=\"uri\" xlink:href=\"https://cn.string-db.org\">https://cn.string-db.org</ext-link>), and the Analysis Tab on the website was used for conducting KEGG pathway analysis for the PPI network. Potential interactors of TM9SF2 were identified using BioGRID (<ext-link ext-link-type=\"uri\" xlink:href=\"https://thebiogrid.org\">https://thebiogrid.org</ext-link>) and HIPPIE (<ext-link ext-link-type=\"uri\" xlink:href=\"http://cbdm-01.zdv.uni-mainz.de/~mschaefer/hippie/index.php\">http://cbdm-01.zdv.uni-mainz.de/~mschaefer/hippie/index.php</ext-link>). TM9SF2 was knocked down by shRNA and its mRNA and protein levels were quantified by qPCR and western blotting (#PA-48517, ThermoFisher), respectively. PLC-γ1 (#2822, CST) activity was assessed based on Y783 phosphorylation (#2821, CST) by western blotting.</p>" ]
[ "<title>Results</title>", "<title>Scores of sulfur-related annotations are reduced in the osteoarthritic synovium</title>", "<p id=\"Par19\">We first merged the synovial tissue microarray datasets, GSE55235 (10 healthy/10 OA), GSE55457 (10 healthy/10 OA), and GSE82107 (7 healthy/10 OA). We downloaded gene sets (Additional file ##SUPPL##0##1##) related to energy and sulfur metabolism annotations from MSigDB along with the gene set regulating cell disulfidptosis, particularly SLC7A11, from the literature [##REF##36747082##22##]. Based on the expression matrix, by ssGSEA, we analyzed energy metabolism (i.e., glycolysis, oxidative phosphorylation) and sulfur metabolism (i.e., sulfur metabolism, cysteine metabolism, and disulfidptosis) in osteoarthritic synovial tissues compared with those in normal synovial tissues (Fig. ##FIG##0##1##A,B). The scores for sulfur metabolism, cysteine metabolism, and disulfidptosis were significantly reduced in OA tissues (Fig. ##FIG##0##1##A,B), suggesting their potential inhibitory effect on the pathogenesis of OA or reduction in sulfur metabolism with OA progression. The scores of glycolysis and oxidative phosphorylation (OXPHOS) were all unchanged in OA tissues, except for the “KEGG_OXIDATIVE_PHOSPHORYLATION” score in OA, which was increased (Fig. ##FIG##0##1##A,B), further indicating increased OXPHOS in osteoarthritic synovial tissues. Furthermore, between the healthy and OA groups, we obtained 91 DEGs by t-test (Fig. ##FIG##0##1##C).</p>", "<title>Classification of synovial tissues based on sulfur metabolism-associated DEGs and their potential molecular mechanisms of action</title>", "<p id=\"Par20\">To select characteristic genes in the OA synovium among the 91 DEGs, we overlapped the 91 DEGs with sulfur metabolism-associated genes (Fig. ##FIG##1##2##A). We obtained 10 DEGs from sulfur metabolism-associated annotations, including <italic>CTH</italic>, <italic>MTHFD1</italic>, <italic>SNCA</italic>, <italic>PDK4</italic>, <italic>TM9SF2</italic>, <italic>ELTD1</italic>, <italic>POU4F1</italic>, <italic>HOXA2</italic>, <italic>NCKAP1</italic>, and <italic>RPN1</italic> (Fig. ##FIG##1##2##B). To understand their ability to distinguish between OA and healthy groups, we performed a consensus cluster analysis according to the expressional level of the ten sulfur metabolism-associated genes (Fig. ##FIG##1##2##C,D). The ten-gene classified C1 and C2 groups were consistent for the OA and healthy groups (Fig. ##FIG##1##2##E,F).</p>", "<p id=\"Par21\">To explore the potential functions of the ten sulfur metabolism-associated genes, we performed a functional enrichment analysis by using all DEGs between C1 and C2. The upregulated genes in the OA-dominated C2 group were mainly enriched in the following KEGG pathways: “Hematopoietic cell lineage,” “Cell adhesion molecules (CAMs),” and “Antigen processing and presentation” (Fig. ##FIG##1##2##G), with GO annotations of “extracellular matrix,” “leukocyte migration,” and “vesicle” (Fig. ##FIG##1##2##H). The upregulated genes in the healthy samples-dominated C1 group were primarily enriched in the KEGG pathways of “Tyrosine metabolism” and “Fatty-acid degradation” (Fig. ##FIG##1##2##I), with GO annotations of “lipid transport”, “ethanol metabolic process”, “lipid localization”, and “regulation of glucose transmembrane transport” (Fig. ##FIG##1##2##J). These suggest the potential associations between sulfur metabolism and extracellular matrix, antigen processing/presentation, tyrosine metabolism, and lipid/glucose transport.</p>", "<title>Identifying a sulfur metabolism-associated gene signature for diagnosing OA</title>", "<p id=\"Par22\">We performed a LASSO COX regression analysis for the nine genes (since we planned to use the GSE12021 and GSE1919 datasets to verify the diagnostic efficacy of gene biomarkers, we removed <italic>ELTD1</italic>, which was absent in the two datasets) and identified the diagnostic gene signature comprising six genes (Fig. ##FIG##2##3##A). The risk score could be used for diagnosing OA. The following was the calculation: Risk Score =  − 0.1355 × <italic>MTHFD1</italic> (expression level) + (− 0.1114) × <italic>PDK4</italic> + 0.7726 × <italic>TM9SF2</italic> + (− 0.0031) × <italic>POU4F1</italic> + (− 0.0374) × <italic>HOXA2</italic> + (− 0.0047) × <italic>NCKAP1</italic>. The diagnostic ROC of the risk score showed excellent predictive power (area under the ROC curve (AUC) = 0.867, Fig. ##FIG##2##3##B). From the heatmap (Fig. ##FIG##2##3##C) and boxplot (Fig. ##FIG##2##3##D) of gene expression, we observed that most of the high-risk group samples were in the OA group with <italic>TM9SF2</italic> being significantly upregulated while the other five genes were significantly downregulated. Most of the high-risk group samples were of OA (Fig. ##FIG##2##3##C).</p>", "<p id=\"Par23\">To verify the diagnostic gene signature’s reliability, we calculated the risk score of the samples in GSE12021 and GSE1919 using the same coefficients and validated the diagnostic ability of the gene signature (Fig. ##FIG##3##4##A,B shows the ROC curve for assessing the overall diagnostic performance of the risk score and gene expression; Fig. ##FIG##3##4##E,F shows the risk score in the upper layer, the OA status in the middle layer, and gene expression in the lower layer). Although the expressional differences of some genes (i.e., <italic>MTHFD1</italic>, <italic>PDK4</italic>, <italic>POU4F1</italic>, and <italic>NCKAP1</italic>) were not statistically significant (Fig. ##FIG##3##4##C,D), the basic changing trends were consistent with those in the original data (Fig. ##FIG##2##3##D). Notably, <italic>TM9SF2</italic> was significantly upregulated in the OA group among all datasets (Figs. ##FIG##2##3##D, ##FIG##3##4##C,F).</p>", "<title>Functional enrichment and cell specificity analyses for the signature gene, <italic>TM9SF2</italic></title>", "<p id=\"Par24\">To further understand the function of TM9SF2 in OA synovial tissue, we performed a correlation analysis for <italic>TM9SF2</italic> and GO/KEGG pathway enrichment analysis results for <italic>TM9SF2</italic> positively correlated genes. TM9SF2 was associated with phagosome, lysosome, and antigen processing/presentation via MHCII (Fig. ##FIG##4##5##A).</p>", "<p id=\"Par25\">We performed a GSEA between <italic>TM9SF2</italic> high- and low-expression samples, classified based on the median expression of <italic>TM9SF2</italic>. The high-<italic>TM9SF2</italic> expression samples were enriched in the following KEGG pathways: “FC_GAMMA_MEDIATED_PHAGOCYTOSIS,” “LYSOSOME,” and “N/O_GLYCAN_BIOSYNTHESIS,” and the low <italic>TM9SF2</italic> samples were enriched in “TYROSINE_METABOLISM,” “INSULIN_SIGNALING_PATHWAY,” and “ADIPOCYTOKINE_SIGNALING_PATHWAY” (Fig. ##FIG##4##5##B). TM9SF2 was involved in the functions of phagocytosis, lysosome, and glycan biosynthesis, and could potentially inhibit tyrosine metabolism, insulin, and adipokine signaling pathways.</p>", "<p id=\"Par26\">Many immune cells infiltrate the OA synovium, and we further studied the correlation between this gene and immune cells. From CIBERSORT analysis, <italic>TM9SF2</italic> was found to be positively correlated with macrophages M2 and negatively with macrophages M1 (Fig. ##FIG##4##5##C). After xCell analysis, TM9SF2 was found to be positively correlated with both macrophages and M2 macrophages (Fig. ##FIG##4##5##D).</p>", "<title>TM9SF2 regulates the phagocytic function of macrophages M2</title>", "<p id=\"Par27\">According to the GESA and immune cell infiltration analyses described above, we speculated that upregulated <italic>TM9SF2</italic> expression potentially regulated the phagocytic function of macrophages M2 in OA. Therefore, we silenced <italic>TM9SF2</italic> by siRNA in THP-1-derived macrophage M2 (Fig. ##FIG##5##6##A,B) and cocultured them with IgG-coated beads to assess phagocytosis level. Knocking down <italic>TM9SF2</italic> reduced the proportion of phagocytic macrophages (Fig. ##FIG##5##6##C). Because apoptotic cells are accumulated in the synovium in OA, we tested efferocytosis efficiency by co-culturing macrophages M2 with PKH26-labeled apoptotic Jurkat cells. Knocking down <italic>TM9SF2</italic> reduced the efferocytosis of THP-1-derived macrophages M2 (Fig. ##FIG##5##6##D).</p>", "<p id=\"Par28\">To explore the mechanisms underlying the downregulation of phagocytosis by shTM9SF2, we performed a PPI network analysis in STRING. TM9SF2 was involved in functions of “Fc gamma R-mediated phagocytosis,” “Regulation of actin cytoskeleton,” and “Endocytosis” by potential interaction with ARPC5 or BCAR1 (Fig. ##FIG##6##7##A). To identify protein interactors of TM9SF2 and their associated functions, we combined the interacting proteins of TM9SF2 from BioGRID and HIPPIE databases and performed GO/KEGG enrichment analyses. TM9SF2 may promote phagocytosis by regulating phospholipase C activity by interacting with LPAR1/S1PR4/EGFR/NMUR1 (Fig. ##FIG##6##7##B). Given the connection between PLC-γ1 activation, calcium release, and phagocytosis, we tested the status of PLC-γ1 activation after knocking down TM9SF2 and found downregulation of PLC-γ1 activity (Fig. ##FIG##6##7##C), as evidenced by the phosphorylation of PLC-γ1 at Y783.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par29\">The pathogenesis and early diagnosis of OA are interesting and challenging issues. Metabolic changes often yield biomarkers for early diagnosis, however, sulfur metabolism has not been analyzed in synovial tissues in OA. In this study, by analyzing the scores of sulfur metabolism-related genes in OA, we found reduced sulfur metabolism in OA synovial tissues and increased OXPHOS. The results suggest that impaired sulfur metabolism may play a role in OA pathogenesis. We obtained 10 differentially expressed sulfur metabolism-related genes, which could distinguish between OA and healthy synovial tissues following consensus cluster analysis. Sulfur metabolism-associated mechanical changes in OA-dominated class C2 included the upregulation of hematopoietic cell lineage, CAM, extracellular matrix, and vesicles, along with the downregulation of tyrosine metabolism, fatty acid degradation, glycolysis/gluconeogenesis, and lipoprotein particles. LASSO COX regression identified six signature genes, which could well distinguish OA samples in both the training (merged from GSE55235/GSE55457/GSE82107) and the verification (GSE12021 and GSE1919) datasets. Among the six genes, <italic>TM9SF2</italic> was upregulated in OA synovial tissues, suggesting strengthened activity of “FC_GAMMA_MEDIATED_PHAGOCYTOSIS,” “LYSOSOME,” and “N/O_GLYCAN_BIOSYNTHESIS,” and attenuated activity of “TYROSINE_METABOLISM,” “INSULIN_SIGNALING_PATHWAY,” and “ADIPOCYTOKINE_SIGNALING_PATHWAY” in osteoarthritic synovial tissues. Correlation analysis among immune cells showed that <italic>TM9SF2</italic> was expressed in macrophages M2.</p>", "<p id=\"Par30\">MTHFD1 has trifunctional enzymatic activities and catalyzes one of three sequential reactions during the interconversion of 1-carbon derivatives of tetrahydrofolate, the substrates for methionine, thymidylate, and de novo purine syntheses [##REF##18767138##40##]. PDK4 is localized in the matrix of the mitochondria and regulates glucose and fatty acid metabolism [##REF##8798399##41##]. It inhibits the pyruvate dehydrogenase complex by phosphorylating one of its subunits, either PDHA1 and PDHA2, further downregulating aerobic respiration and inhibiting the formation of acetyl-coenzyme A from pyruvate. PDK4 can inhibit ferroptosis by blocking pyruvate dehydrogenase-dependent pyruvate oxidation in human pancreatic ductal carcinoma cells, indicating its ability of metabolic reprogramming [##REF##33626342##42##]. Furthermore, it is a sensitive marker of increased fatty acid oxidation in multiple tissue types and cell types [##REF##31351920##43##]. TM9SF2 plays a role in small molecule transport or can act as an ion channel [##REF##9729438##44##]. It can promote cell adhesion and phagocytosis of eukaryotic phagocytes [##REF##25139117##45##, ##REF##18796536##46##]. It has also been implicated as an oncogene in colorectal cancer owing to its promotive effect on the cell cycle and OXPHOS [##REF##30333512##47##]. In this study, we provide evidence of the potential link between TM9SF2 and antigen presentation/macrophage M2. Macrophage polarization is essential in the development of OA-associated synovitis [##UREF##1##5##, ##REF##37492583##48##]. Functionally, macrophages can be categorized into three types, namely, unstimulated macrophages M0, proinflammatory macrophages M1, and anti-inflammatory macrophages M2. In addition to its anti-inflammatory effect, macrophage M2 plays an important role in clearing synovial apoptotic cells, which can attenuate OA’s progression [##REF##36448607##49##]. POU4F1 belongs to the POU-IV class of neural transcription factors which regulate the expression of specific genes involved in differentiation and survival, including osteoclast/neuron differentiation and BCL2-promoted cell survival [##REF##24736625##50##–##REF##22326227##53##]. Recently, Pou4f1 was found to be expressed in kidney infiltrating macrophages in progressive renal fibrosis, with the proportion of Pou4f1<sup>+</sup> macrophages being correlated with the degree of macrophage–myofibroblast transition in human kidney tissues [##REF##32788346##54##]. TGF-β1 can promote the expression of neuronal differentiation marker, Tubb3, and neuron development transcription factor, Pou4f1, in bone marrow-derived macrophages [##REF##32788346##54##, ##REF##36206343##55##]. The link between POU4F1 and macrophages may partly explain the negative correlation between POU4F1 and lysosome in macrophages. HOXA2, as a transcription factor regulating gene expression during cell morphogenesis, cell differentiation, and embryonic development, may be involved in the placement of hindbrain segments in their proper locations along the anterior–posterior axis [##REF##25914765##56##]. Hoxa2 can regulate palate development by inhibiting osteogenic differentiation of palatal mesenchyme [##REF##29184513##57##]. NCKAP1 is part of the WAVE complex that regulates lamellipodia formation [##REF##9148763##58##, ##REF##32646006##59##] and has an important positive regulatory role on disulfidptosis [##REF##36747082##22##]. Interestingly, NCKAP1 disruptive variants lead to a neurodevelopmental disorder [##REF##33157009##60##]. HOXA2, POU4F1, and NCKAP1 are all associated with the development of the nervous system, suggesting their potential connection with pain in patients with OA.</p>", "<p id=\"Par31\">TM9SF2 is a member of the transmembrane 9 superfamily and localizes to early endosomes in human cells, which may play a role in small molecule transport or act as an ion channel [##REF##30333512##47##, ##UREF##8##61##, ##REF##31541081##62##]. In addition to its role in promoting tumorigenesis and facilitating cell adhesion and phagocytosis of eukaryotic phagocytes [##REF##25139117##45##–##REF##30333512##47##], studies on the function of TM9SF2 and its association with OA are scarce. We tested and confirmed the sustaining effect of TM9SF2 on macrophage phagocytosis. The phagocytosis-sustaining effect of TM9SF2 was potentially due to the interaction between TM9SF2 and molecules associated with cytoskeleton/focal adhesion, phospholipase C activity, and vesicle formation. Notably, one study showed that high accumulation of apoptotic cells in the synovium of OA with the impaired efferocytosis ability of synovial macrophages [##REF##36448607##49##]. Therefore, we hypothesized that TM9SF2 may attenuate the progression of OA. Why upregulated TM9SF2 expression in OA synovial tissues could not reverse impaired efferocytosis of synovial macrophages and the role of TM9SF2 in the phagocytosis/efferocytosis/antigen processing and presentation of synovial macrophages merit further exploration. Inhibiting PLC-γ1 exerts a protective effect on cartilage against OA [##REF##29435116##63##, ##REF##33372388##64##]. However, given the role of TM9SF2-activated PLC-γ1 in facilitating efferocytosis of macrophages, the inhibition of PLC-γ1 may promote the OA progression by impairing efferocytosis. The link between the TM9SF2/PLC-γ1 axis and OA progression merits further studies.</p>", "<p id=\"Par32\">Some limitations of our study warrant consideration. First, we identified synovial OA biomarkers by using a small number of samples (27 healthy and 30 OA samples) by integrating GSE55235, GSE55457, and GSE82107 datasets, all of which were obtained from synovial tissues and are reliable GEO resources. We validated the result in two other datasets, GSE12021 (9 healthy and 10 OA samples) and GSE1919 (5 healthy and 5 OA samples) but the results were inferred from a sample size, and more studies are needed to validate our findings. Second, this study was based on bioinformatics analysis of the transcriptome of clinical samples, and in vivo studies or cohort studies are needed to validate the real diagnostic performance of these biomarkers. Moreover, the specific connection between the upregulated TM9SF2 expression and PLC-γ1 activation remains unclear. We think that it may be a result of the interaction between TM9SF2 and LPAR1/S1PR4/EGFR/NMUR1 and deserves further investigation. Nevertheless, our study has many advantages. Since the progression of OA is irreversible, late-stage OA can only be treated by joint replacement. Synovial tissues are more accessible by biopsy than by obtaining cartilage tissues during surgery. Furthermore, synovial samples have a closer pathological correlation with OA than peripheral blood samples. Therefore, identifying biomarkers of OA from synovial tissues can facilitate the early diagnosis and intervention of patients with OA.</p>", "<p id=\"Par33\">In conclusion, we identified a six-gene signature for the diagnosis of OA and explored their correlated functions and immune cell infiltration state in OA synovial tissues. The availability of genomic biomarkers with diagnostic potential is invaluable for patients with OA for early detection and treatment.</p>" ]
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[ "<title>Background</title>", "<p id=\"Par1\">Osteoarthritis (OA) is a chronic and low-grade inflammatory disease associated with metabolism disorder and multiple cell death types in the synovial tissues. Sulfur metabolism has not been studied in OA.</p>", "<title>Methods</title>", "<p id=\"Par2\">First, we calculated the single sample gene set enrichment analysis score of sulfur metabolism-associated annotations (i.e., cysteine metabolism process, regulation of sulfur metabolism process, and disulfidptosis) between healthy and synovial samples from patients with OA. Sulfur metabolism-related differentially expressed genes (DEGs) were analyzed in OA. Least absolute shrinkage and selection operator COX regression were used to identify the sulfur metabolism-associated gene signature for diagnosing OA. Correlation and immune cell deconvolution analyses were used to explore the correlated functions and cell specificity of the signature gene, <italic>TM9SF2</italic>. TM9SF2’s effect on the phagocytosis of macrophages M2 was analyzed by coculturing macrophages with IgG-coated beads or apoptotic Jurkat cells.</p>", "<title>Results</title>", "<p id=\"Par3\">A diagnostic six gene signature (i.e., <italic>MTHFD1, PDK4</italic>, <italic>TM9SF2</italic>, <italic>POU4F1</italic>, <italic>HOXA2</italic>, <italic>NCKAP1</italic>) was identified based on the ten DEGs, validated using GSE12021 and GSE1919 datasets. <italic>TM9SF2</italic> was upregulated in the synovial tissues of OA at both mRNA and protein levels. The relationship between TM9SF2 and several functional annotations, such as antigen processing and presentation, lysosome, phagosome, Fcγ-mediated phagocytosis, and tyrosine metabolism, was identified. <italic>TM9SF2</italic> and macrophages M2 were significantly correlated. After silencing <italic>TM9SF2</italic> in THP-1-derived macrophages M2, a significantly reduced phagocytosis and attenuated activation of PLC-γ1 were observed.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">A sulfur metabolism-associated six-gene signature for OA diagnosis was constructed and upregulation of the phagocytosis-associated gene, <italic>TM9SF2</italic>, was identified. The findings are expected to deepen our understanding of the molecular mechanism underlying OA development and be used as potential therapeutic targets.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13018-023-04384-2.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>SZ and ML helped in conception of the project, designed the study, wrote the manuscript, and edited the manuscript. SZ, LY, and YL acquired data, analyzed data, and did experiments.</p>", "<title>Funding</title>", "<p>Key Natural Science Research Project of Higher Education of Anhui Province (KJ2021A0299 to M.L.), Scientific Research of BSKY from First Affiliated Hospital of Anhui Medical University (BSKY2022008 to M.L.), and National Natural Science Foundation of China (82202756 to S.Z.).</p>", "<title>Availability of data and materials</title>", "<p>All data were downloaded from GEO database with accession IDs (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc\">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc</ext-link>=): GSE55235, GSE55457, GSE82107, GSE12021, GSE1919, GSE152805.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par34\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par35\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par36\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>ssGSEA scores for different gene sets related to glycolysis, OXPHOS, cysteine metabolic process, sulfur metabolic process, and disulfidptosis in synovial samples. <bold>A</bold> Boxplot shows the ssGSEA score for each gene set in synovial samples. Only the scores of the cysteine metabolic process, regulation of the sulfur metabolic process, and disulfidptosis gene sets are significantly downregulated. The <italic>P</italic> value is shown at the top of the figure for each group. <bold>B</bold> The heatmap shows the normalized ssGSEA score for each gene set. <bold>C</bold> The heatmap shows the expression of DEGs between healthy (red samples) and OA (light blue samples) groups. DEGs: differentially expressed genes between OA and healthy groups</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Sulfur-associated DEGs distinguish classes C1 and C2, along with their differentially enriched functions. <bold>A</bold> The Venn diagram shows ten overlapping genes between DEGs and sulfur-associated gene sets (i.e., cysteine metabolic process, regulation of sulfur metabolic process, and disulfidptosis gene sets). DEGs: differentially expressed genes between OA and healthy groups. <bold>B</bold> The violin plot shows the expression of the ten 10 sulfur metabolism-associated DEGs. <bold>C</bold> The bar graph shows the consistency within each group following consensus cluster analysis. Different colors represent the K-value or the number of groups set in each round of the clustering algorithm. The clustering solution based on K = 2 groups shows a higher intra-group consistency compared to other K values. <bold>D</bold> The heatmap shows two classes distinguished by consensus cluster analysis based on the 10 sulfur-associated DEGs. <bold>E</bold>, <bold>F</bold> Clusters identified by tSNE analysis for the expression profile of all genes. These are labeled with colors for healthy/OA groups (<bold>E</bold>) or C1/C2 groups (<bold>F</bold>), and the results suggest a consistency between the two classifications <bold>G</bold>, <bold>H</bold>. KEGG (<bold>G</bold>) and GO (<bold>H</bold>) enriched functions for the upregulated genes in class C2 (OA-dominated); e.g., cell adhesion molecules, IL-17 signaling pathways, rheumatoid arthritis, extracellular matrix, and leukocyte migration. <bold>I</bold>, <bold>J</bold> KEGG (<bold>I</bold>) and GO (<bold>J</bold>) enriched functions for genes upregulated in class C1 (healthy-dominated); e.g., tyrosine metabolism, fatty acid degradation, and lipid transport.`</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Establishment of the diagnostic gene signature by LASSO COX regression analysis. <bold>A</bold> LASSO COX regression for 9 sulfur-associated genes. The coefficient profile plot was generated against the log (lambda) sequence (Upper). LASSO coefficient profiles of the nine genes in the merged dataset (Lower). <bold>B</bold> Accuracy of the diagnostic model for the six-gene signature to predict OA diagnosis, as evidenced by the receiver operating characteristic (ROC) curve analysis. When AUC (i.e., Area under the ROC curve) is 0.5, it means there is a 50% chance that the model can distinguish between positive and negative classes; 0.7 ≥ AUC &gt; 0.6: acceptable discrimination; AUC &gt; 0.7: excellent discrimination. <bold>C</bold> Detailed diagnostic information (healthy/OA) and expressional patterns of candidate genes differ between high-risk score and low-risk score groups. Upper layer: level of risk score for each sample; middle layer: OA status (red: OA, green: healthy); lower layer: heatmap shows the gene expression. <bold>D</bold> The boxplot shows differential expression levels of the six genes between healthy and OA groups</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Validation of the diagnostic six-gene signature in GSE12021 and GSE1919 datasets. <bold>A</bold>, <bold>B</bold> Accuracy of the diagnostic model for the six-gene signature in predicting osteoarthritis by ROC analysis in GSE12021 (<bold>A</bold>) and GSE1919 (<bold>B</bold>) datasets. <bold>C</bold>, <bold>D</bold> Boxplot shows the differential expression of the six genes between healthy and OA groups in the GSE12021 (<bold>C</bold>) and GSE1919 (<bold>D</bold>) datasets. <bold>E</bold>, <bold>F</bold> Detailed diagnostic information (healthy/OA) and expression patterns of candidate genes between high-risk score and low-risk score groups in the GSE12021 (<bold>E</bold>) and GSE1919 (<bold>F</bold>) datasets, thus validating the diagnostic performance of the six-gene signature. Upper layer: risk score for each sample; middle layer: OA status (red: OA, green: healthy); lower layer: heatmap shows the gene expression</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Functional enrichment analysis and cell-specificity analysis. <bold>A</bold> Functionally enriched annotations from GO and KEGG analyses for the positively correlated genes of TM9SF2, suggesting potential functions, including antigen processing and presentation, lysosome, and phagosome. <bold>B</bold> Enriched KEGG annotations in high- or low-<italic>TM9SF2</italic> expression samples after GSEA, suggesting potential functions, including lysosome, phagocytosis, and tyrosine metabolism. <bold>C</bold> The heatmap shows the correlation between the six genes and CIBERSORT-identified immune cells. There is a strong correlation between TM9SF1 and macrophages M1/M2. <bold>D</bold> The heatmap shows the correlation between the six genes and xCell-identified immune cells. There is a strong correlation between TM9SF1 and macrophage M2</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>The effect of TM9SF2 on phagocytosis of macrophages M2. <bold>A</bold>, <bold>B</bold> Knocking down <italic>TM9SF2</italic> in THP-1-derived macrophages M2 at mRNA (<bold>A</bold>) and protein (<bold>B</bold>) levels. <bold>C</bold> The downregulation of macrophage phagocytosis on PE-stained IgG-coated latex beads by knocking down <italic>TM9SF2</italic>. <bold>D</bold> Downregulation of macrophage phagocytosis on PKH26-stained apoptotic Jurkat cells following <italic>TM9SF2</italic> knockdown. Flow cytometry and immunofluorescence results with statistical values obtained from three biological replicates in one technical replicate. The data are representative of three independent experiments. *<italic>P</italic> &lt; 0.05, two-sided t-test. Red scale bar: 50 μm</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Proteins interacting with TM9SF2 and their enriched annotations. <bold>A</bold> The TM9SF2-centered STRING PPI network was enriched in functions “Fc gamma R-mediated phagocytosis,” “Regulation of actin cytoskeleton,” and “Endocytosis” as evidenced by the direct interaction with ARPC5 and BCAR1. <bold>B</bold> Proteins interacting with TM9SF2 (from BioGRID and HIPPIE databases) were enriched in functions of “activation of phospholipase C activity,” “endocytic vesicle,” and “phagocytic vesicles.” Enriched proteins are shown on the right side (pointed out by arrow), such as LPAR1 and RAB9A. <bold>C</bold> Knocking down TM9SF2 attenuates PLC-γ1 activation, as reflected by phosphorylation at its Y783 position. Data are representative of three independent experiments. *<italic>P</italic> &lt; 0.05, **<italic>P</italic> &lt; 0.01, two-sided <italic>t</italic> test</p></caption></fig>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Shuang Zheng and Yetian Li contributed equally to this study as first author.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"13018_2023_4384_MOESM1_ESM.xlsx\"><caption><p><bold>Additional file 1.</bold> Table 1. Gene lists for analysis.</p></caption></media>" ]
[{"label": ["2."], "surname": ["Allen", "Thoma", "Golightly"], "given-names": ["KD", "LM", "YM"], "article-title": ["Epidemiology of osteoarthritis"], "source": ["Osteoarthr Cartil"], "year": ["2022"], "volume": ["30"], "issue": ["2"], "fpage": ["184"], "lpage": ["195"], "pub-id": ["10.1016/j.joca.2021.04.020"]}, {"label": ["5."], "surname": ["Wu"], "given-names": ["CL"], "article-title": ["The role of macrophages in osteoarthritis and cartilage repair"], "source": ["Osteoarthr Cartil"], "year": ["2020"], "volume": ["28"], "issue": ["5"], "fpage": ["544"], "lpage": ["554"], "pub-id": ["10.1016/j.joca.2019.12.007"]}, {"label": ["23."], "surname": ["Ashburner"], "given-names": ["M"], "article-title": ["Gene ontology: tool for the unification of biology"], "source": ["Gene Ontol Consort Nat Genet"], "year": ["2000"], "volume": ["25"], "issue": ["1"], "fpage": ["25"], "lpage": ["29"], "pub-id": ["10.1038/75556"]}, {"label": ["24."], "mixed-citation": ["The Gene Ontology resource: enriching a GOld mine. Nucleic Acids Res. 2021;49(D1):D325-34."]}, {"label": ["27."], "surname": ["H\u00e4nzelmann", "Castelo", "Guinney"], "given-names": ["S", "R", "J"], "article-title": ["GSVA: gene set variation analysis for microarray and RNA-seq data"], "source": ["BMC Bioinform"], "year": ["2013"], "volume": ["14"], "fpage": ["7"], "pub-id": ["10.1186/1471-2105-14-7"]}, {"label": ["28."], "surname": ["Wickham", "Wickham"], "given-names": ["H", "H"], "article-title": ["Data analysis"], "source": ["ggplot2: elegant graphics for data analysis"], "year": ["2016"], "publisher-loc": ["Cham"], "publisher-name": ["Springer"], "fpage": ["189"], "lpage": ["201"]}, {"label": ["30."], "mixed-citation": ["Krijthe JH. Rtsne: T-distributed stochastic neighbor embedding using Barnes-Hut implementation. R package version 0.13. "], "ext-link": ["https://github.com/jkrijthe/Rtsne"]}, {"label": ["39."], "surname": ["Robin"], "given-names": ["X"], "article-title": ["pROC: an open-source package for R and S+ to analyze and compare ROC curves"], "source": ["BMC Bioinform"], "year": ["2011"], "volume": ["12"], "fpage": ["77"], "pub-id": ["10.1186/1471-2105-12-77"]}, {"label": ["61."], "surname": ["Tanaka"], "given-names": ["A"], "article-title": ["Genome-wide screening uncovers the significance of N-sulfation of heparan sulfate as a host cell factor for chikungunya virus infection"], "source": ["J Virol"], "year": ["2017"], "volume": ["91"], "issue": ["13"], "fpage": ["10"], "lpage": ["1128"], "pub-id": ["10.1128/JVI.00432-17"]}]
{ "acronym": [], "definition": [] }
64
CC BY
no
2024-01-14 23:43:47
J Orthop Surg Res. 2024 Jan 13; 19:62
oa_package/66/16/PMC10787471.tar.gz
PMC10787472
38216958
[ "<title>Background</title>", "<p id=\"Par9\">Neurofibromatosis type 1 (NF1), also known as von Recklinghausen disease, is a neurocutaneous genetic disorder with an estimated worldwide incidence of 1 in 4950 individuals [##REF##2511318##1##, ##REF##23931823##2##]. The disorder arises from mutations in the NF1 gene, which codes for the protein neurofibromin, a regulator of RAS-MAPK signalling and tumor suppressor. The loss of neurofibromin function leads to dysregulation of cell growth and proliferation, ultimately forming benign tumors known as neurofibromas, which can arise from any peripheral nerve [##REF##1971145##3##].</p>", "<p id=\"Par10\">Among the types of tumors seen in patients with NF1, neurofibromas are the most common and typically grow slowly and remain benign [##REF##30653135##4##]. A subtype of neurofibroma called a plexiform neurofibroma (PN) is particularly common in patients with NF1 and is characterized by diffuse involvement of multiple nerves, which can cause pain, functional impairment, and cosmetic disfigurement [##UREF##0##5##].</p>", "<p id=\"Par11\">We report the case of a patient with NF1 who developed a giant plexiform neurofibroma in the gluteal region, with accompanying infiltration of the urinary bladder wall causing bilateral hydronephrosis.</p>" ]
[]
[]
[ "<title>Discussion and conclusions</title>", "<p id=\"Par14\">PNs are pathognomonic for NF1 and can result in significant disfigurement and functional limitations. This type of neurofibroma typically arises in early childhood and becomes more apparent as a cutaneous lesion once it has fully developed [##UREF##1##6##]. PNs can vary greatly in size and location, with many developing along large nerve trunks or regions with increased adipose tissue deposition [##UREF##0##5##]. These tumors can cause the affected nerve to thicken and expand, leading to hypertrophy of surrounding tissues and possible compression of neighboring structures [##REF##10469434##7##].</p>", "<p id=\"Par15\">PNs can involve not only superficial tissues, but also deep tissues or internal organs, such as the gastrointestinal tract or urogenital area, without any apparent external extension [##UREF##0##5##]. A higher incidence in female patients during adolescence was noted for internal neurofibromas [##UREF##2##8##].</p>", "<p id=\"Par16\">Imaging studies are valuable for assessing the location and extent of lesions. Ultrasonography (US) is a valuable diagnostic tool in differentiating between benign and malignant lesions. However, its accuracy may be insufficient, and hence it is commonly used in combination with magnetic resonance imaging (MRI). MRI is the gold standard for preoperative assessment. T1-weighted images of neurofibromas (NFs) typically depict a low-to-intermediate signal, while T2-weighted images show a high signal [##REF##19864525##9##]. The “target sign,” which is a homogeneous hyperintense region, is a characteristic pattern commonly observed in NFs [##REF##11133542##10##, ##REF##31708092##11##].</p>", "<p id=\"Par17\">Computed tomography (CT) imaging is an effective diagnostic modality for identifying nodular, fusiform, or cluster-like lesions that have a lower density than muscle (20–30 UH). This lower density is attributed to lipid inclusions present in Schwann cells, adipocytes, cystic degeneration, and myxoid stroma. The enhancement pattern of these lesions after contrast injection varies, with some showing homogeneous or heterogeneous enhancement. In our case, the patient was found to have extensive involvement of the cervical, abdominal, and pelvic structures with the invasion of adjacent tissues, as identified on the CT scan.</p>", "<p id=\"Par18\">To reduce the risk of potential complications, such as malignant transformation into malignant peripheral nerve sheath tumors (MPNSTs), which pose a significant concern, with an estimated lifetime risk of 15.8% of PNs transforming into MPNSTs, it is essential to closely monitor PNs [##UREF##3##12##].</p>", "<p id=\"Par19\">The management of plexiform neurofibromas can be classified into three main approaches: conservative, surgical, and medical therapies. Conservative management involves regular monitoring, pain control, and psychological support. Various studies have suggested monitoring the cases of PN with CT or MRI every 6 months to 1 year [##REF##36792186##13##]. Surgical resection is effective for excluding malignancy and is usually only used in certain cases, such as large superficial lesions and craniofacial lesions [##UREF##0##5##]. However, surgery, especially for diffuse plexiform neurofibromas, is challenging because of the risk of massive bleeding due to tumor spread and tissue invasion. Medical therapy with mitogen-activated protein kinase kinase (MEK) inhibitors, especially selumetinib, is a promising option for inoperable and symptomatic PN, with positive results in pediatric trials [##UREF##0##5##]. Sawaragi <italic>et al</italic>. have shown that a carefully selected group of patients with extensive disfiguring plexiform neurofibromas with pain and/or threat to function may benefit from MEK inhibitors, either as monotherapy or in combination with surgery [##UREF##0##5##]. Other centers have demonstrated the use of MEK inhibitors to reduce tumor size to enable surgical excision [##REF##31141829##14##]. However, it is crucial to note that while selumetinib has been approved by the Food and Drug Administration (FDA) in the USA and has recently been authorized in the United Kingdom [##UREF##4##15##], access to MEK inhibitors is yet to be authorized in our country. Nevertheless, given the extensive and diffuse nature of the lesions, and the associated surgical challenges, we strongly believe that our patient would be an excellent candidate for selumetinib therapy.</p>", "<p id=\"Par20\">PNs can cause a variety of symptoms depending on their location, including visual problems, respiratory difficulties, motor impairments, etc. These symptoms are primarily due to the tumor’s direct pressure on surrounding tissues and can become life-threatening when vital organs are compressed. The most common symptoms are pain and motor deficits. The presence of infection and chronic disease can worsen the prognosis of this serious condition [##REF##34441638##16##]. In a pediatric cohort study assessing the mortality and morbidity profiles associated with NF1, it was observed that children afflicted with symptomatic neurofibromas and NF1 exhibited an elevated mortality rate of 3.2% [##REF##21996156##17##]. Notably, the size of the tumor plays a pivotal role in determining the severity of the clinical manifestations, with larger tumors correlating with more pronounced pathological effects. These functional impairments exert a detrimental influence on the overall quality of life [##REF##28193237##18##], underscoring the essential need for ongoing surveillance to assess the clinical impact of therapeutic interventions.</p>", "<p id=\"Par21\">In our clinical case, we are committed to the rigorous monitoring of our patient, vigilantly screening for signs of tumor growth, potential complications, or the ominous transformation into MPNST. This monitoring regimen involves the routine utilization of computed tomography (CT) or magnetic resonance imaging (MRI) scans at intervals ranging from 6 months to 1 year.</p>", "<p id=\"Par22\">NF1 is a rare genetic disorder that can present with a wide range of clinical manifestations. Giant plexiform neurofibromas are a rare but significant complication of NF1. Early detection and prompt surgical intervention can prevent complications and improve outcomes. It is crucial to closely monitor patients with NF1 to detect the development of neurofibromas as early as possible, including the use of imaging studies to identify the presence of tumors. The optimal management of these tumors remains unclear. Therefore, decisions regarding the management of NF1 should be made in specialized centers and be the subject of a multicenter study to ensure adequate patient care.</p>" ]
[ "<title>Discussion and conclusions</title>", "<p id=\"Par14\">PNs are pathognomonic for NF1 and can result in significant disfigurement and functional limitations. This type of neurofibroma typically arises in early childhood and becomes more apparent as a cutaneous lesion once it has fully developed [##UREF##1##6##]. PNs can vary greatly in size and location, with many developing along large nerve trunks or regions with increased adipose tissue deposition [##UREF##0##5##]. These tumors can cause the affected nerve to thicken and expand, leading to hypertrophy of surrounding tissues and possible compression of neighboring structures [##REF##10469434##7##].</p>", "<p id=\"Par15\">PNs can involve not only superficial tissues, but also deep tissues or internal organs, such as the gastrointestinal tract or urogenital area, without any apparent external extension [##UREF##0##5##]. A higher incidence in female patients during adolescence was noted for internal neurofibromas [##UREF##2##8##].</p>", "<p id=\"Par16\">Imaging studies are valuable for assessing the location and extent of lesions. Ultrasonography (US) is a valuable diagnostic tool in differentiating between benign and malignant lesions. However, its accuracy may be insufficient, and hence it is commonly used in combination with magnetic resonance imaging (MRI). MRI is the gold standard for preoperative assessment. T1-weighted images of neurofibromas (NFs) typically depict a low-to-intermediate signal, while T2-weighted images show a high signal [##REF##19864525##9##]. The “target sign,” which is a homogeneous hyperintense region, is a characteristic pattern commonly observed in NFs [##REF##11133542##10##, ##REF##31708092##11##].</p>", "<p id=\"Par17\">Computed tomography (CT) imaging is an effective diagnostic modality for identifying nodular, fusiform, or cluster-like lesions that have a lower density than muscle (20–30 UH). This lower density is attributed to lipid inclusions present in Schwann cells, adipocytes, cystic degeneration, and myxoid stroma. The enhancement pattern of these lesions after contrast injection varies, with some showing homogeneous or heterogeneous enhancement. In our case, the patient was found to have extensive involvement of the cervical, abdominal, and pelvic structures with the invasion of adjacent tissues, as identified on the CT scan.</p>", "<p id=\"Par18\">To reduce the risk of potential complications, such as malignant transformation into malignant peripheral nerve sheath tumors (MPNSTs), which pose a significant concern, with an estimated lifetime risk of 15.8% of PNs transforming into MPNSTs, it is essential to closely monitor PNs [##UREF##3##12##].</p>", "<p id=\"Par19\">The management of plexiform neurofibromas can be classified into three main approaches: conservative, surgical, and medical therapies. Conservative management involves regular monitoring, pain control, and psychological support. Various studies have suggested monitoring the cases of PN with CT or MRI every 6 months to 1 year [##REF##36792186##13##]. Surgical resection is effective for excluding malignancy and is usually only used in certain cases, such as large superficial lesions and craniofacial lesions [##UREF##0##5##]. However, surgery, especially for diffuse plexiform neurofibromas, is challenging because of the risk of massive bleeding due to tumor spread and tissue invasion. Medical therapy with mitogen-activated protein kinase kinase (MEK) inhibitors, especially selumetinib, is a promising option for inoperable and symptomatic PN, with positive results in pediatric trials [##UREF##0##5##]. Sawaragi <italic>et al</italic>. have shown that a carefully selected group of patients with extensive disfiguring plexiform neurofibromas with pain and/or threat to function may benefit from MEK inhibitors, either as monotherapy or in combination with surgery [##UREF##0##5##]. Other centers have demonstrated the use of MEK inhibitors to reduce tumor size to enable surgical excision [##REF##31141829##14##]. However, it is crucial to note that while selumetinib has been approved by the Food and Drug Administration (FDA) in the USA and has recently been authorized in the United Kingdom [##UREF##4##15##], access to MEK inhibitors is yet to be authorized in our country. Nevertheless, given the extensive and diffuse nature of the lesions, and the associated surgical challenges, we strongly believe that our patient would be an excellent candidate for selumetinib therapy.</p>", "<p id=\"Par20\">PNs can cause a variety of symptoms depending on their location, including visual problems, respiratory difficulties, motor impairments, etc. These symptoms are primarily due to the tumor’s direct pressure on surrounding tissues and can become life-threatening when vital organs are compressed. The most common symptoms are pain and motor deficits. The presence of infection and chronic disease can worsen the prognosis of this serious condition [##REF##34441638##16##]. In a pediatric cohort study assessing the mortality and morbidity profiles associated with NF1, it was observed that children afflicted with symptomatic neurofibromas and NF1 exhibited an elevated mortality rate of 3.2% [##REF##21996156##17##]. Notably, the size of the tumor plays a pivotal role in determining the severity of the clinical manifestations, with larger tumors correlating with more pronounced pathological effects. These functional impairments exert a detrimental influence on the overall quality of life [##REF##28193237##18##], underscoring the essential need for ongoing surveillance to assess the clinical impact of therapeutic interventions.</p>", "<p id=\"Par21\">In our clinical case, we are committed to the rigorous monitoring of our patient, vigilantly screening for signs of tumor growth, potential complications, or the ominous transformation into MPNST. This monitoring regimen involves the routine utilization of computed tomography (CT) or magnetic resonance imaging (MRI) scans at intervals ranging from 6 months to 1 year.</p>", "<p id=\"Par22\">NF1 is a rare genetic disorder that can present with a wide range of clinical manifestations. Giant plexiform neurofibromas are a rare but significant complication of NF1. Early detection and prompt surgical intervention can prevent complications and improve outcomes. It is crucial to closely monitor patients with NF1 to detect the development of neurofibromas as early as possible, including the use of imaging studies to identify the presence of tumors. The optimal management of these tumors remains unclear. Therefore, decisions regarding the management of NF1 should be made in specialized centers and be the subject of a multicenter study to ensure adequate patient care.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Neurofibromatosis type 1 is a neurocutaneous genetic disorder caused by mutations in the NF1 gene, resulting in the formation of benign tumors called neurofibromas. The most common type of tumor seen in patients with neurofibromatosis type 1 is the slow-growing and benign neurofibroma, with a subtype called plexiform neurofibroma being particularly common and causing pain, functional impairment, and cosmetic disfigurement.</p>", "<title>Case presentation</title>", "<p id=\"Par2\">We report the case of a 20-year-old North African female patient with a history of neurofibromatosis type 1 who presented with a growing mass in her right gluteal region, which was later diagnosed as a giant cutaneous neurofibroma. Imaging studies revealed infiltration in several regions, including the urinary bladder wall, resulting in significant bilateral hydronephrosis. The patient is currently being monitored, and no excisional procedures are planned.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">Neurofibromatosis type 1 can cause a variety of clinical symptoms, including the development of large plexiform neurofibromas. It is important to closely monitor patients with neurofibromatosis type 1 for the early detection of neurofibromas. Early detection and prompt surgical intervention are essential for preventing complications.</p>", "<title>Keywords</title>" ]
[ "<title>Case presentation</title>", "<p id=\"Par12\">A 20-year-old North African female patient, born to consanguineous parents, presented with a medical history of Hirschsprung’s disease and a concurrent diagnosis of NF1 with a growing mass in the left gluteal region that had been present since childhood but increased in size over the last few years. Physical examination revealed multiple café au lait spots and neurofibromas of different sizes on the limbs and trunk. A giant cutaneous neurofibroma measuring 30 × 25 cm of the sacral region was also observed (Fig. ##FIG##0##1##).</p>", "<p id=\"Par13\">Computed tomography (CT) scan revealed nodular infiltration of neurofibromatosis in the right and left gluteal regions with dermal–hypodermal invasion (Fig. ##FIG##1##2##d) and poorly defined infiltrating nodules in the pelvic region. The pelvic organs, including the uterus, ovaries, rectal wall, and bladder wall (Fig. ##FIG##1##2##b) were infiltrated. The thickened bladder wall caused the stenosis of the vesicoureteral junctions (Fig. ##FIG##1##2##a) and consequently significant bilateral hydronephrosis (Fig. ##FIG##1##2##c). The patient was referred to urology, but no endoscopic procedure could be performed due to massive infiltration. The patient is currently being followed up with stable radiological lesions and normal renal function. No excisional procedures are planned.</p>" ]
[ "<title>Acknowledgements</title>", "<p>We would like to acknowledge the Archive of the Salah Azaiez Institute of Oncology in Tunis for their assistance.</p>", "<title>Author contributions</title>", "<p>IS: drafting of the manuscript. MAB: data acquisition. AH: data analysis and interpretation and drafting of the manuscript. IZ: critical revision of the manuscript. TBD: approval of the version to be published.</p>", "<title>Funding</title>", "<p>This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.</p>", "<title>Availability of data and materials</title>", "<p>This work was created with the utmost respect for the code of ethics under the supervision of the Medical and Ethics Committee of the Salah Azaiez Institute of Oncology.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par23\">Manuscripts reporting studies involving human participants, human data, or human tissue must: include a statement on ethics approval and consent (even where the need for approval was waived) and include the name of the ethics committee that approved the study and the committee’s reference number if appropriate. Studies involving animals must include a statement on ethics approval, and for experimental studies involving client-owned animals, authors must also include a statement on informed consent from the client or owner.</p>", "<title>Consent for publication</title>", "<p id=\"Par24\">Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal on request.</p>", "<title>Competing interests</title>", "<p id=\"Par25\">The authors declare that they have no conflict of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Multiple café au lait spots with a plexiform neurofibroma of the sacral region appearing darker in color compared with the surrounding skin, measuring 30 × 25 cm</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p><bold>a</bold> Axial contrast-enhanced computed tomography (CT) image revealing the thickened wall of the urinary bladder with stenosis of the right ureter at the vesicoureteral junction (arrow) and the dilated left ureter (circle) just before joining the bladder <bold>b</bold> Sagittal CT image showing infiltration of the wall of the urinary bladder (53 mm thick) <bold>c</bold> Coronal CT image showing bilateral hydronephrosis <bold>d</bold> Axial CT image revealing the infiltration of neurofibromatosis in the right and left gluteal regions with dermal–hypodermal invasion (triangle)</p></caption></fig>" ]
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[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[]
[{"label": ["5."], "surname": ["Collins-Sawaragi", "Ferner", "Vassallo"], "given-names": ["YC", "R", "G"], "article-title": ["Location, symptoms, and management of plexiform neurofibromas in 127 children with neurofibromatosis 1, attending the National Complex Neurofibromatosis 1 service, 2018\u20132019"], "source": ["Am J Med Genet Pt A"], "year": ["2022"], "volume": ["188"], "fpage": ["1723"], "lpage": ["1727"], "pub-id": ["10.1002/ajmg.a.62691"]}, {"label": ["6."], "surname": ["Hoda"], "given-names": ["SA"], "article-title": ["Enzinger and Weiss\u2019s soft tissue tumors"], "source": ["Am J Clin Pathol"], "year": ["2020"], "volume": ["154"], "fpage": ["424"], "lpage": ["424"], "pub-id": ["10.1093/ajcp/aqaa078"]}, {"label": ["8."], "surname": ["Bayram", "Bayram", "Tireli"], "given-names": ["T", "D", "H"], "article-title": ["Neurofibromatosis type 1-related multiple plexiform neurofibromas: a case report"], "source": ["J Neurol"], "year": ["2020"], "volume": ["26"], "fpage": ["42"], "lpage": ["46"], "pub-id": ["10.4274/tnd.2019.44520"]}, {"label": ["12."], "surname": ["Uusitalo", "Rantanen", "Kallionp\u00e4\u00e4"], "given-names": ["E", "M", "RA"], "article-title": ["Distinctive cancer associations in patients with neurofibromatosis type 1"], "source": ["JCO"], "year": ["2016"], "volume": ["34"], "fpage": ["1978"], "lpage": ["1986"], "pub-id": ["10.1200/JCO.2015.65.3576"]}, {"label": ["15."], "mixed-citation": ["(2022) Overview | Selumetinib for treating symptomatic and inoperable plexiform neurofibromas associated with type 1 neurofibromatosis in children aged 3 and over | Guidance | NICE. "], "ext-link": ["https://www.nice.org.uk/guidance/hst20"]}]
{ "acronym": [ "NF1", "PN", "CT", "US", "MPNSTs" ], "definition": [ "Neurofibromatosis type 1", "Plexiform neurofibroma", "Computed tomography", "Ultrasonography", "Malignant peripheral nerve sheath tumors" ] }
18
CC BY
no
2024-01-14 23:43:47
J Med Case Rep. 2024 Jan 13; 18:15
oa_package/64/3b/PMC10787472.tar.gz
PMC10787473
38216944
[ "<title>Introduction</title>", "<p id=\"Par5\">Anterior Cruciate Ligament Reconstruction (ACLR) is a usual treatment for patients with anterior cruciate ligament rupture. Effective ACL reconstruction requires professional rehabilitation to help patients return to their previously active lifestyles [##REF##34903114##1##]. However, a few patients still have knee instability, decreased proprioceptive function, neuromuscular function, motor level difficult to restore and other problems. Therefore, clinical researchers must actively study new rehabilitation tools to help patients alleviate pain and restore neuromuscular function. Extracorporeal shock wave therapy (ESWT) is a kind of physical therapy, which generates mechanical waves and provides local therapeutic effects through the probe [##REF##28892648##2##]. There are two types of ESWT generators, focused ESWT (fESWT) and radial ESWT (rESWT) [##REF##23738271##3##]. Compared with fESWT, rESWT pressure increases slightly and much more slowly. When treated in the superficial area of interest, fESWT has more intensive energy exposure than rESWT. For this reason, the rESWT is considered less invasive than fESWT, so it might be more suitable for our study purposes [##REF##25019247##4##].</p>", "<p id=\"Par6\">Although rESWT is widely used for musculoskeletal disorders, the management of ACLR is unknown. Here, the purpose of this study was to explore whether rESWT contributed to the recovery of ACLR.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study design and participants</title>", "<p id=\"Par7\">We conducted the randomized, single-blind clinical trial in China, with subjects recruited from November 2021 to March 2023 in the Second Hospital of Shanxi Medical University. Patients were divided into two groups using the software program. The experimental group : standard rehabilitation plus rESWT; The control group: standard rehabilitation plus sham rESWT (Fig. ##FIG##0##1##). Sham shock wave therapy refers to the use of a simulated therapeutic head only to reduce interference brought on by vibration during shock wave therapy. It did not produce sound waves and had no therapeutic effect.</p>", "<p id=\"Par10\">\n\n</p>", "<title>Inclusion and exclusion criteria</title>", "<p id=\"Par8\">The inclusion criteria: (i) age ≥ 18years; (ii) unilateral ACL rupture without other ligament or meniscus injury; (iii) no other osteoarticular or soft tissue lesions in the lower extremities; (iv) no cognitive impairment or disturbance of consciousness. In addition,subjects should have no contraindications to shock waves to ensure the trial goes smoothly.</p>", "<p id=\"Par9\">The exclusion criteria: (i) patients with tumors or other serious diseases; (ii) history of deep vein thrombosis or vascular pathology in any lower limb; (iii) rheumatoid arthritis or other signifcant co-morbidities; (iv) intraarticular injections into the knee in the preceding 6 months.</p>", "<title>Interventions</title>", "<title>Preoperative rehabilitation</title>", "<p id=\"Par13\">To improve the outcome of postoperative conditions, patients undergoing ACL reconstruction should undergo rehabilitation before surgery [##REF##25351782##5##, ##REF##23845398##6##]. Patients who are better prepared, both psychologically and functionally, prior to ACLR also have better outcomes after ACLR. Preoperative care was personalized according to the subject’s situation, covering preoperative assessment, rehabilitation guidance and psychological counseling. Deficits in passive joint range of motion and quadriceps strength should be specifically targeted because these factors are associated with Postoperative results [##REF##27539507##7##]. A common belief is that preoperative rehabilitation has been associated with better postoperative function and activity level compared. To reduce the risk of knee re-injury, clinicians should provide education to patients, including the possible benefits of rehabilitation.</p>", "<title>Standard rehabilitation programs</title>", "<p id=\"Par16\">Phase 1: For the treatment of completely passive stretching, quadriceps femoris functional exercise should be started on the first day after ACL reconstruction. Cryotherapy can be used to treat the pain during training. Active and passive range-of-motion exercises (e.g., straight leg raise in the supine position and lateral leg raise, heel slides and continuous passive motion (CPM) was used to carry out joint movement), and it is advocated to manage effusion by adjusting the load in this phase. After surgery, both weight-bearing (closed kinetic chain) and non-weight-bearing (open kinetic chain) exercises were performed simultaneously.</p>", "<p id=\"Par17\">Phase 2: This phase will start neuromuscular training and muscle strength training. The purpose of neuromuscular training is to improve the dynamic stability of the knee joint by establishing more beneficial proprioception and motor control strategies [##REF##27539507##7##]. The goal of muscle strength training is to restore the muscle strength needed by patients to participate in sports and activities of daily living. Muscle strength exercises will gradually develop from a lighter load with a higher number of repetitions to a heavier load with fewer repetitions. If the patient can perform two additional repetitions according to the target repetition times, the load will be increased in the next training [##REF##20710097##8##]. The gradual increase in training load is also a key component of the transition to activity/movement [##REF##26701923##9##].</p>", "<p id=\"Par18\">Phase 3: Individualized training should be carried out in the late rehabilitation according to the specific goals and sports needs of patients. Generally, this stage includes specific damage of heavy strength training, strength and agility training, and specific exercise training. When patients gradually return to exercise, all kinds of pivoting sports are effective injury prevention plans, including lower limb strength exercises and low-risk exercise mode training. Knee joint effusion and knee joint pain rules are commonly used clinical indicators to evaluate response to load [##REF##22402434##10##].</p>", "<title>rESWT programs</title>", "<p id=\"Par21\">The experimental group received rESWT and standard rehabilitation, while the control group received sham rESWT and standard rehabilitation. Patients in the experimental group started receiving rESWT on the second postoperative day, and the standard rehabilitation training program was the same in both groups. The source of shockwave was from Swiss Dolor Clast (EMS, Switzerland). The shockwave was focused at the area around the patella and the rectangular area 10 cm above the upper edge of the patella, avoiding the operation area (Fig. ##FIG##1##2##). Application of 2500 impulses of ESWT at a frequency of 6–8 Hz (0.298 mJ/mm2) was administered to the treatment area. The treatment schedule was 6 consecutive weeks, once a week. If the patient cannot tolerate rESWT due to pain during treatment, the intensity is appropriately reduced to a low energy flux density range (0.08–0.28 mJ/mm2) and the shock is reduced to 1200–1500. Sham rESWT was performed with a simulated head (consistent with the appearance of real head but inneffective) to the control group.</p>", "<p id=\"Par22\">\n\n</p>", "<title>Outcome measures</title>", "<p id=\"Par23\">The baseline data were recorded before treatment and followed up at the 3rd, 6th and 24th weeks. The Visual Analogue Scale (VAS), Lysholm Knee Score (LKS), Range of movement (ROM)and the International Knee Documentation Committee (IKDC) were adopted to evaluate the changes in pain and function of patients in both groups. These four scales are internationally recognized to evaluate knee function and frequently used in clinical studies.</p>", "<title>Statistical analysis and plotting</title>", "<p id=\"Par24\">The patients’ baseline demographics and knee-related characteristics among the designated groups were expressed as mean ± standard deviation (SD), and baseline characteristics were tested by independent t-test and chi-square test, the Mann-Whitney U test was used for group comparisons of functional outcomes. All data analyses were carried out using the SPSS statistical software version 26.0, and the statistical significance of all tests was evaluated at a predetermined significance level of 0.05. In addition, plots were made with Originpro8.1.</p>" ]
[ "<title>Results</title>", "<title>Baseline characteristics</title>", "<p id=\"Par25\">Nine participants were lost before completing the study protocol due to being unable to contact them, leaving 63 completed participants. There were no statistically significant differences between groups in age, sex,side of injury, or cause of injury (Table ##TAB##0##1##). Therefore, two groups are comparable. Meanwhile, there were no adverse events reported.</p>", "<p id=\"Par26\">\n\n</p>", "<title>Lysholm knee score</title>", "<p id=\"Par27\">At pre-treatment, there were no statistically significant differences between the experimental and control groups in terms of LKS. Interestingly, the LKS was significantly different in the two groups at 3 and 6 weeks after treatment. The LKS of the two groups continued to increase from pre-treatment to 24 weeks after treatment, but there was no significant difference between the two groups at 24 weeks after treatment (<italic>P</italic> &gt; 0.05)(Table ##TAB##1##2##; Fig. ##FIG##2##3##).</p>", "<p id=\"Par28\">\n\n</p>", "<p id=\"Par29\">\n\n</p>", "<title>Range of movement</title>", "<p id=\"Par30\">There were no statistically significant differences between groups in terms of ROM at pre-treatment. Interestingly, the ROM was significantly different in the experimental and control groups at 3 and 6 weeks after treatment. Conservely, there was no significant difference in ROM between groups at 24 weeks after treatment (<italic>P</italic> &gt; 0.05)(Table ##TAB##2##3##; Fig. ##FIG##3##4##).</p>", "<p id=\"Par31\">\n\n</p>", "<p id=\"Par32\">\n\n</p>", "<title>International knee documentation committee</title>", "<p id=\"Par33\">At pre-treatment, there were no significant differences between the experimental and control groups in terms of IKDC. At 3 and 6 weeks after treatment, both groups experienced significant increases in IKDC with group differences. Of note, there was no significant difference in IKDC between groups at 24 weeks after treatment (<italic>P</italic> &gt; 0.05)(Table ##TAB##3##4##; Fig. ##FIG##4##5##).</p>", "<p id=\"Par34\">\n\n</p>", "<p id=\"Par35\">\n\n</p>", "<title>Visual analogue scale</title>", "<p id=\"Par36\">There were no significant differences in VAS at pre-treatment. Importantly, we found that, compared with the control group, the VAS in the experimental group was significantly lower at 3 weeks and 6 weeks after treatment. At the same time, no significant changes were found between the two groups at 24 weeks after treatment (<italic>P</italic> &gt; 0.05)(Table ##TAB##4##5##; Fig. ##FIG##5##6##).</p>", "<p id=\"Par37\">\n\n</p>", "<p id=\"Par38\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par39\">This study was to examine the effect of rESWT on muscle strength, physical function, knee pain and range of motion during an ACLR rehabilitation program. The results of this randomized, controlled trial involving ACL reconstruction indicate that a strategy of rESWT plus standard rehabilitation was superior to a strategy of standard rehabilitation.</p>", "<p id=\"Par40\">After ACL reconstruction, there may be changes in knee joint control and motor perception, decreased spinal reflex and excitability of corticospinal pathway, and persistent defects in quadriceps function [##REF##27695905##11##, ##REF##30326547##12##]. Therefore, early intervention in rehabilitation therapy is very important to improve the postoperative effect. The traditional initial treatment of choice is standard rehabilitation, comprehending modalities such as cryotherapy, continuous passive motion(CPM) [##REF##33204500##13##], high-intensity neuromuscular electrical stimulation (NMES) [##REF##20592480##14##], neuromuscular training and muscle strength training [##REF##27539507##7##]. However, this method has not produced encouraging results over the past years.</p>", "<p id=\"Par41\">To our knowledge, there is limited evidence on functional outcomes of the ACLR by using rESWT. This is a study to compare the rESWT program and standard rehabilitation program for patients with ACLR. rESWT acts at the tendon-bone interface by physical impact, triggering cell regeneration and stimulating the release of growth factors [##REF##26834326##15##–##UREF##0##17##]. The effect of physical energy on biological tissues is similar to a cascade process, in which the energy of shock wave sequentially activates the cytoskeletal system and organelles, releasing proteins for the healing process [##UREF##1##18##]. Among these, the growth factor stimulates cell surface to express the protein, activating the intercellular interactions. In addition, rESWT promoted extracellular matrix metabolism, neovascularization [##REF##21915315##19##], bone mineralization, and formation. Reductions in adhesions and improvements in joint mobility allow patients to recover better, including reductions in pain and improvements in function and microcirculation.</p>", "<p id=\"Par42\">In the present study, we sought to preliminarily determine the efficacy of rESWT in reducing pain and improving function and mobility in ACL reconstruction patients. Additionally, VAS, IKDC, LKS and ROM were assessed. In the course of rehabilitation, pain, inflammatory irritation and limited mobility [##REF##25693627##20##]all have an adverse impact on patients’ mood and training, as well as the overall rehabilitation outcome. Pain mainly originates from inflammation, swelling and muscle adhesions in rehabilitation [##REF##28498226##21##]. The VAS score is mainly used to score the patients’ pain and quantify subjective perception. In our study, there was a more pronounced improvement in VAS of experimental group at 3 and 6 weeks (<italic>P</italic> &lt; 0.05). The reasons for the outcome were that standard rehabilitation stimulates knee mechanoreceptors by joint mobilization and traction, which achieve the effect of assisted movement, only in a movable range. In contrast, rESWT can modulate local inflammatory factors and nociceptive transmission, exert anti-inflammatory, anti-swelling, and analgesic effects, and make the pain-relieving effects more pronounced [##REF##21139662##22##].</p>", "<p id=\"Par43\">The IKDC primarily assesses activities of daily living following knee injury, and provides a comprehensive assessment of stability and pain [##REF##8536037##23##]. The higher the score, the lower the subjective discomfort and the stronger the function. The improvement in IKDC of experimental group (<italic>P</italic> &lt; 0.05) at 3 and 6 weeks might be attributed to a decrease of postoperative discomfort. Even though rESWT point had the highest mean IKDC score improvement after 24 weeks the differences between the groups were statistically insignificant. However, due to the considerable disparity in the patients’ tolerance, the questionnaire ratings may be influenced.</p>", "<p id=\"Par44\">Lysholm score emphasizes patients’ subjective feelings about symptoms, and combined with digital score and patients’ daily activity level, the degree of patients’ dysfunction can be graded. The research shows that the scale is the most reliable for patients with anterior cruciate ligament reconstruction, and the score difference is more significant when evaluating patients with self-limiting activities. Wang et al [##REF##24560350##24##]reported an rESWT treatment to ACL reconstruction patients in the bone tunnel area, and the rESWT group showed higher LKS and superior knee stability at a follow-up of 2 years after surgery, similar to our results of LKS in the experimental group, all dramatically higher than the control group (<italic>P</italic> &lt; 0.05). In addition, ROM can determine the degree of joint limitation as an evaluation method for treatment and training. Notably, the results of ROM were significantly higher in the experimental group at 3 and 6 weeks (<italic>P</italic> &lt; 0.05), indicating a pronounced improvement in knee function. After ACL reconstruction, the injured site secretes growth factors and cytokines, which guide cells to migrate from the periphery of the graft to the injured site, further proliferate and produce extracellular matrix, and tendinous differentiation is performed under growth factor stimulation to promote ligament healing. In this study, rESWT combined with standard rehabilitation methods had better recovery effect, which was consistent with Lu et al. [##REF##32832074##25##] who found that rESWT could enhance the residual cell activity of anterior cruciate ligament and the activity and differentiation of surrounding cells, induce ACL cells to secrete transforming growth factor TGF-βand vascular endothelial growth factor VEGF, and promote vascular and tissue regeneration. Experimental group had a larger range of ROM, and the LKS was higher than that of the control group. The reason may be that standard rehabilitation methods can release adhesion, improve physiological axial movement, whereas rESWT enhances ACL residual cell activity, strengthen tendon-bone connection, significantly improve ligament recovery, stimulate muscles around the knee joint, improve local lymphatic circulation, and promote inflammatory absorption [##UREF##2##26##].</p>", "<p id=\"Par45\">In the present research, we have demonstrated that all participants showed significant improvement in knee function after 24 weeks of treatment. Experimental design in this study focused on the effects of rESWT on pain relief, knee function and mobility in the short-term postoperative period, with follow-up and data recorded at 3, 6 and 24 weeks. Some measures about subjective perception and knee joint function have been improved in different degrees, which is consistent with the research results of Aldajah et al. [##UREF##3##27##]. This study found that rESWT can significantly relieve the pain, upper limb function and grip strength in volunteers with humeral epicondylitis. According to Lie et al [##REF##35365190##28##], the application of rESWT triggered nerve tissue regeneration, stimulated cell differentiation, and reduced neuronal loss, all of these might aid to repair acute traumatic spinal cord damage. Because early postoperative rehabilitation training is particularly important for the recovery of knee joint function after ACL reconstruction, it is more vital to study the improvement of knee joint function and rehabilitation effect by rESWT in the short term after surgery for early rehabilitation training.</p>", "<title>Strengths and limitations</title>", "<p id=\"Par47\">rESWT, as a positive factor affecting the rapid recovery of patients, has the advantages of non-invasive, low cost and energy regulation, and can strengthen the training and auxiliary effect in the postoperative rehabilitation stage. The results of this study suggest that rESWT is promising in the rehabilitation of ACL reconstruction and musculoskeletal system diseases, therefore, it is worthy of further study in this direction. However, this study is not without its limitations. Our study did not provide a more objective evaluation of healing, such as MRI, X-ray, KT1000, etc. Furthermore, it remains unclear whether patients with higher pain levels and severe knee impairment would benefit from rESWT and whether multiple applications of rESWT would lead to different outcomes. Due to the limitations of this study, it is necessary to include more comprehensive evaluation criteria in subsequent studies. For patients after ACL reconstruction, the optimal treatment protocol has not yet been established, and a higher level of evidence is needed to demonstrate and determine the efficacy of rESWT in future clinical trials.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par48\">The randomized controlled trial demonstrated that the individuals showed varying degrees of improvement in pain relief and knee function after 24 weeks of rehabilitation training. rESWT can regulate local inflammatory factors and nociceptive transmission, acting as an anti-inflammatory, anti-swelling and analgesic, it can also promotes ACL residual cell activity, strengthens tendon-bone connections, improves ligament repair, stimulates peri-knee muscles and local lymphatic circulation around the knee, to achieve the recovery of improving knee function and mobility. Taken together, the application of rESWT in the early rehabilitation period after ACL reconstruction is an effective and positive method, and this method can reduce the pain level of subjects and improve their knee joint function.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">The aim of this study was to explore the effects of radial extracorporeal shock wave therapy (rESWT) in patients with anterior cruciate ligament(ACL) reconstruction(ACLR).</p>", "<title>Methods</title>", "<p id=\"Par2\">We conducted a randomized, controlled trial involving 72 eligible patients with ACL reconstruction in which we compared two strategies: the experimental group was standard rehabilitation plus rESWT and the control group was standard rehabilitation plus sham rESWT. The outcome was the change from baseline to 24 weeks in the average score on Lysholm knee joint score (LKS), range of motion (ROM), visual analogue scale (VAS) and International Knee Literature Committee (IKDC).</p>", "<title>Results</title>", "<p id=\"Par3\">Of 36 subjects assigned to rehabilitation plus rESWT, 4 lost to follow up. Of 36 assigned to rehabilitation plus sham rESWT, 5 lost to follow up. The LKS, ROM and IKDC scores of the experimental group were markedly increased at 3 and 6 weeks after treatment (<italic>P</italic> &lt; 0.001), and the VAS was notably decreased (<italic>P</italic> &lt; 0.001). However, there were no significant differences in the LKS, ROM, IKDC and VAS between the groups at 24 weeks after treatment (<italic>P</italic> &gt; 0.05).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The strategy of rehabilitation plus rESWT had better functional outcomes after ACL reconstruction. As such, our study demonstrates that rESWT is essential for patients with ACL reconstruction. Early use of rESWT can improve joint function, pain relief and ability of daily living. rESWT has a positive effect on the overall rehabilitation of patients.</p>", "<title>Keywords</title>" ]
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[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>Yufeng Song and Xinle Che wrote the main manuscript text. Zheyun Wang and Mengshi Li prepared figures and tables. Runjie Zhang and Qiongfang Shi were responsible for data curation. Dongming Wang supervised the study. All authors reviewed the manuscript.</p>", "<title>Funding</title>", "<p>The study was supported by Science and Technology Department of Shanxi Province natural science research program (202203021211034).</p>", "<title>Data availability</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participat</title>", "<p id=\"Par51\">The protocol was approved by the Second Hospital of Shanxi Medical University ethics committee. The study was performed in accordance with the protocol, and all subjects provided written informed consent. Clinical registration was completed in the “China Clinical Experiment Registration Center”, and the approved clinical registration number was ChiCTR2100053320(18/11/2021). The study adhered to the Declaration of Helsinki. In addition, minors and illiterates were not involved in this study.</p>", "<title>Consent for publication</title>", "<p id=\"Par52\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par49\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flowchart of the study design</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Treatment area of radial extracorporeal shock wave therapy (rESWT)</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Change in LKS over the duration of the study</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Change in ROM over the duration of the study</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Change in IKDC over the duration of the study. Data are presented as mean ± SD</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Change in VAS over the duration of the study</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Comparison of baseline characteristics between the two groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Demographics</th><th align=\"left\">experimental group (<italic>n</italic> = 32)</th><th align=\"left\">control group<break/>(<italic>n</italic> = 31)</th><th align=\"left\">P-values</th></tr></thead><tbody><tr><td align=\"left\">Age(y)</td><td align=\"left\">27.94 ± 6.38</td><td align=\"left\">27.00 ± 6.11</td><td char=\".\" align=\"char\">0.628</td></tr><tr><td align=\"left\">Male sex, n(%)</td><td align=\"left\">21(65.63)</td><td align=\"left\">18(58.06)</td><td char=\".\" align=\"char\">0.537</td></tr><tr><td align=\"left\">Side of injury (left/right)</td><td align=\"left\">15/17</td><td align=\"left\">16/15</td><td char=\".\" align=\"char\">0.707</td></tr><tr><td align=\"left\">exercise</td><td align=\"left\">15</td><td align=\"left\">14</td><td char=\".\" align=\"char\" rowspan=\"4\">0.870</td></tr><tr><td align=\"left\">Car accidents</td><td align=\"left\">9</td><td align=\"left\">10</td></tr><tr><td align=\"left\">Fall</td><td align=\"left\">5</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Other</td><td align=\"left\">3</td><td align=\"left\">4</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Change in LKS over the duration of the study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Group</th><th align=\"left\">Cases</th><th align=\"left\">pre-treatment</th><th align=\"left\">3 week after treatment</th><th align=\"left\">6 week after treatment</th><th align=\"left\">24 week after treatment</th><th align=\"left\">P-values</th></tr></thead><tbody><tr><td align=\"left\">experimental group</td><td char=\".\" align=\"char\">32</td><td align=\"left\">11.19 ± 2.023</td><td align=\"left\">66.91 ± 2.607</td><td align=\"left\">75.69 ± 3.814</td><td align=\"left\">90.87 ± 1.792</td><td char=\".\" align=\"char\" rowspan=\"2\">0.038</td></tr><tr><td align=\"left\">control group</td><td char=\".\" align=\"char\">31</td><td align=\"left\">11.00 ± 1.751</td><td align=\"left\">61.35 ± 3.179</td><td align=\"left\">69.29 ± 3.268</td><td align=\"left\">90.19 ± 2.040</td></tr><tr><td align=\"left\"><italic>P</italic>-values</td><td align=\"left\"/><td align=\"left\">0.646</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.224</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Change in ROM over the duration of the study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Group</th><th align=\"left\">Cases</th><th align=\"left\">pre-treatment</th><th align=\"left\">3 week after treatment</th><th align=\"left\">6 week after treatment</th><th align=\"left\">24 week after treatment</th><th align=\"left\">P-values</th></tr></thead><tbody><tr><td align=\"left\">experimental group</td><td char=\".\" align=\"char\">32</td><td align=\"left\">80.41 ± 13.423</td><td align=\"left\">104.22 ± 8.091</td><td align=\"left\">125.16 ± 5.941</td><td align=\"left\">130.34 ± 2.509</td><td char=\".\" align=\"char\" rowspan=\"2\">0.050</td></tr><tr><td align=\"left\">control group</td><td char=\".\" align=\"char\">31</td><td align=\"left\">81.19 ± 11.071</td><td align=\"left\">94.97 ± 6.631</td><td align=\"left\">118.48 ± 5.464</td><td align=\"left\">129.55 ± 2.514</td></tr><tr><td align=\"left\">P-values</td><td align=\"left\"/><td align=\"left\">0.794</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.348</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Change in IKDC over the duration of the study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Group</th><th align=\"left\">Cases</th><th align=\"left\">pre-treatment</th><th align=\"left\">3 week after treatment</th><th align=\"left\">6 week after treatment</th><th align=\"left\">24 week after treatment</th><th align=\"left\">P-values</th></tr></thead><tbody><tr><td align=\"left\">experimental group</td><td char=\".\" align=\"char\">32</td><td align=\"left\">29.78 ± 3.170</td><td align=\"left\">42.25 ± 3.111</td><td align=\"left\">49.69 ± 2.596</td><td align=\"left\">71.94 ± 2.940</td><td char=\".\" align=\"char\" rowspan=\"2\">0.008</td></tr><tr><td align=\"left\">control group</td><td char=\".\" align=\"char\">31</td><td align=\"left\">29.77 ± 3.939</td><td align=\"left\">37.61 ± 2.895</td><td align=\"left\">41.71 ± 3.079</td><td align=\"left\">70.55 ± 2.593</td></tr><tr><td align=\"left\">P-values</td><td align=\"left\"/><td align=\"left\">0.879</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.055</td><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Change in VAS over the duration of the study</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Group</th><th align=\"left\">Cases</th><th align=\"left\">pre-treatment</th><th align=\"left\">3 week after treatment</th><th align=\"left\">6 week after treatment</th><th align=\"left\">24 week after treatment</th><th align=\"left\">P-values</th></tr></thead><tbody><tr><td align=\"left\">experimental group</td><td char=\".\" align=\"char\">32</td><td align=\"left\">6.84 ± 0.884</td><td align=\"left\">1.69 ± 0.821</td><td align=\"left\">0.41 ± 0.499</td><td align=\"left\">0.31 ± 0.471</td><td char=\".\" align=\"char\" rowspan=\"2\">0.033</td></tr><tr><td align=\"left\">control group</td><td char=\".\" align=\"char\">31</td><td align=\"left\">6.71 ± 1.006</td><td align=\"left\">2.68 ± 1.166</td><td align=\"left\">1.29 ± 0.824</td><td align=\"left\">0.35 ± 0.486</td></tr><tr><td align=\"left\">P-values</td><td align=\"left\"/><td align=\"left\">0.560</td><td align=\"left\">0.001</td><td align=\"left\">&lt; 0.001</td><td align=\"left\">0.724</td><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
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[{"label": ["17."], "surname": ["Xu", "Wu", "Liu"], "given-names": ["Y", "K", "Y"], "article-title": ["The effect of extracorporeal shock wave therapy on the treatment of moderate to severe knee osteoarthritis and cartilage lesion[J]"], "source": ["Med (Baltim)"], "year": ["2019"], "volume": ["98"], "issue": ["20"], "fpage": ["e15523"], "pub-id": ["10.1097/MD.0000000000015523"]}, {"label": ["18."], "mixed-citation": ["Mittermayr R, Haffner N, Feichtinger X et al. The role of shockwaves in the enhancement of bone repair - from basic principles to clinical application[J]. Injury, 2021;52(Suppl 2):S84\u2013S90."]}, {"label": ["26."], "surname": ["Murray", "Magarian", "Zurakowski"], "given-names": ["MM", "E", "D"], "article-title": ["Bone-to-bone fixation enhances functional healing of the porcine anterior cruciate ligament using a collagen-platelet composite[J]"], "source": ["Arthroscopy"], "year": ["2010"], "volume": ["26"], "issue": ["9 Suppl"], "fpage": ["49"], "lpage": ["S57"], "pub-id": ["10.1016/j.arthro.2009.12.017"]}, {"label": ["27."], "mixed-citation": ["Aldajah S, Alashram AR, Annino G et al. Analgesic effect of extracorporeal shock-Wave Therapy in individuals with lateral epicondylitis: a randomized controlled Trial[J]. J Funct Morphol Kinesiol, 2022;7(1)."]}]
{ "acronym": [ "rESWT", "ACL", "LKS", "ROM", "VAS", "IKDC" ], "definition": [ "Radial Extracorporeal shock wave therapy", "Anterior Cruciate Ligament", "Lysholm knee score", "Range of movement", "Visual Analogue Scale", "International Knee Documentation Committee" ] }
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2024-01-14 23:43:47
BMC Musculoskelet Disord. 2024 Jan 13; 25:57
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PMC10787474
0
[ "<title>Background</title>", "<p id=\"Par30\">Bronchial asthma is a chronic inflammatory lung disease that affects more than 300 million people worldwide and is increasing in prevalence [##UREF##0##1##]. First described as an allergic disorder of the lower airways driven by mast cells and eosinophils, asthma is now understood to be a heterogeneous syndrome with different clinical phenotypes, pathogenesis and underlying immunological endotypes. These range from type 2 inflammatory endotypes that are dominated by interleukin (IL)-4, IL-5 and IL-13, to other types where no eosinophilic inflammation is detected in the airways or mixed inflammation with type 1 and type 17 cytokines.</p>", "<p id=\"Par31\">The complexity of the different pathophysiological mechanisms underlying asthma is also mirrored by the therapeutic success of different therapies in the varying phenotypes. Individuals with milder forms asthma benefit from treatment with inhaled corticosteroids and beta-2 agonists, while those with more severe disease often show poor or no response to these conventional therapies. In recent years, novel antibody-based approaches have been developed for certain phenotypes of asthma. The main application for these treatments to date has been severe allergic asthma and severe asthma and type 2 high inflammation or eosinophilic inflammation. In individuals with the relevant asthma phenotype and severe disease, these novel therapeutics help to reduce exacerbation rates and improve quality of life. In 2022, an anti-thymic stromal lymphopoietin (TSLP) antibody was approved for use in Europe for the treatment of severe asthma in patients with no phenotype or biomarker limitations [##UREF##1##2##] This agent, tezepelumab, has shown some effectiveness in individuals with type 2-low asthma, however, the observed effects are less convincing compared to the effectiveness in type 2-high patients. There is still a therapeutic gap for patients with severe type 2-low asthma.</p>", "<p id=\"Par32\">Based on available data, there is a need for novel treatment strategies that provide better control of the pathology driving inflammatory processes to prevent asthma development or disease exacerbations. In particular, it would be interesting to determine the long-lasting effects of therapeutic interventions that stimulate endogenous anti-inflammatory responses by inducing and activating regulatory T cells (Tregs). Together with T helper cells Tregs belong to the fraction of CD4<sup>+</sup> T cells. They can differentiate in the thymus or only in the periphery, so that one commonly differentiates between naturally occurring thymus-derived tTregs and induced pTregs. Unlike effector T cells, Tregs are responsible for maintaining immune homeostasis, preventing autoimmunity, and eliminating/preventing excessive inflammatory responses after contact with pathogens or pollutants [##REF##31993063##3##]. In murine models, Treg cells can control type 2-high and type 2-low inflammation [##REF##21242522##4##], and dampen human cell-dependent allergic airway inflammation in the lung [##REF##22078574##5##]. This suppression is mediated via the release of anti-inflammatory cytokines (such as IL-10, transforming growth factor [TGF]-β, and IL-35) or via cell–cell contacts. In addition, Tregs can also indirectly throttle immune cell activity via interaction with dendritic cells (DC) and degradation of metabolically essential products (e.g., adenosine triphosphate or tryptophan).</p>", "<p id=\"Par33\">Surprisingly, although normally associated with the development, progression or exacerbation of diseases, microbes have emerged as potential beneficial tools that have immune dampening properties. Both commensal bacteria forming the microbiome and microbes normally seen as pathogens have shown bacterial-host interactions with potential therapeutic suitability. This review will highlight several microbe-associated approaches representing current or future potential therapeutics for the treatment of inflammatory diseases.</p>" ]
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[ "<title>Conclusions</title>", "<p id=\"Par105\">Over time, humans have co-evolved with a large number of microbes that live on or in us. In this process, a community of life has evolved consisting of the microbiome, which includes bacteria, viruses and fungi, with humans as the host as seen in Fig. ##FIG##4##5##. The communication between the host and the microbiome has a significant impact on immunological and metabolic processes. Therefore, it is not surprising that disturbances in the microbiome can have an impact on the development and progression of diseases. In recent years, research into the interaction of the environment with the microbiome and the host has helped to identify processes that can have both positive and negative effects on our health. Targeting microbiome-associated health-promoting effects and avoiding the effects associated with disease development has the potential to contribute to the development of new therapeutic options in the coming years. These could function via direct manipulation of an existing microbiome using pre- or probiotics, or via the targeted use of specific beneficial microbial strains, their metabolites or individual components.</p>" ]
[ "<p id=\"Par1\">Bronchial asthma is a prevalent and increasingly chronic inflammatory lung disease affecting over 300 million people globally. Initially considered an allergic disorder driven by mast cells and eosinophils, asthma is now recognized as a complex syndrome with various clinical phenotypes and immunological endotypes. These encompass type 2 inflammatory endotypes characterized by interleukin (IL)-4, IL-5, and IL-13 dominance, alongside others featuring mixed or non-eosinophilic inflammation. Therapeutic success varies significantly based on asthma phenotypes, with inhaled corticosteroids and beta-2 agonists effective for milder forms, but limited in severe cases. Novel antibody-based therapies have shown promise, primarily for severe allergic and type 2-high asthma. To address this gap, novel treatment strategies are essential for better control of asthma pathology, prevention, and exacerbation reduction. One promising approach involves stimulating endogenous anti-inflammatory responses through regulatory T cells (Tregs). Tregs play a vital role in maintaining immune homeostasis, preventing autoimmunity, and mitigating excessive inflammation after pathogenic encounters. Tregs have demonstrated their ability to control both type 2-high and type 2-low inflammation in murine models and dampen human cell-dependent allergic airway inflammation. Furthermore, microbes, typically associated with disease development, have shown immune-dampening properties that could be harnessed for therapeutic benefits. Both commensal microbiota and pathogenic microbes have demonstrated potential in bacterial-host interactions for therapeutic purposes. This review explores microbe-associated approaches as potential treatments for inflammatory diseases, shedding light on current and future therapeutics.</p>", "<title>Keywords</title>", "<p>Open Access funding enabled and organized by Projekt DEAL.</p>" ]
[ "<title>The other face of bacteria: symbiotic or commensal roommates</title>", "<p id=\"Par34\">The role of microbes as hostile intruders that are responsible for the development of infectious diseases that could have life-threatening consequences is well known. Infections are associated with asthma and, in particular, exposure to certain viruses is associated with the development of asthma and acute disease exacerbations [##REF##31989228##6##]. The interactions between microbes and humans are complex, ranging from pathological destructiveness to indifferent coexistence and symbiotic cohabitation. Based on these different forms of interaction, several hypotheses have been developed stating that beneficial interactions between microbes and host can prevent diseases, while the absence of microbial species, due to changes in lifestyle (e.g. excessive hygiene or use of antibiotics) can be responsible for disease development.</p>", "<p id=\"Par35\">In his “hygiene hypothesis”, Strachan was one of the first to postulate that infections in early childhood and improved hygiene standards in developed countries are responsible for an increased risk of developing allergies [##REF##2513902##7##]. Further studies and developments in gnotobiotic animal research showed a protective role of various environmental bacteria and commensal bacteria, forming the indigenous microbiota, on the development of atopy.</p>", "<p id=\"Par36\">Culturing of anaerobes and new high-throughput methodology such as matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF), 16S RNA sequencing, phylogenetic microarrays or taxon targeted qPCR, have shown the diversity of bacterial species colonizing environmental-exposed organs including the gut and skin, but also the lung. Furthermore, methods like metabolomics, proteomics, transcriptomics, metagenomics or single cell sequencing have provided additional insights into the physiological function of our body mates.</p>", "<p id=\"Par37\">Based on data obtained using these techniques, it was found that the microbiota in one healthy human subject consists of approximately 30 trillion microbes, with the largest proportion being bacteria, followed by viruses (bacteriophages and human viruses), and yeasts [##REF##27541692##8##]. In healthy individuals, the composition of the microbiome is quite stable but differs between organs or even within sections of the same organ. In the gastrointestinal tract, the functions of the microbiome are already quite well described. Several studies have shown an impact of the microbiome on the development of immunity [##REF##24679531##9##], host defense [##REF##30761120##10##], metabolic supply [##REF##33432175##11##], fat storage [##REF##15505215##12##], synthesis of vitamins [##REF##28393285##13##] and even an association with behavior [##REF##33093662##14##]. Microbial products have many functions: defense systems can protect from pathogens, while ligands and nutrients can perform intra-microbial communication, and inter-kingdom communication between microbe and host. Signals can act as short-distance messengers but are also able communicate with distant organs [##REF##27711063##15##]. Pathogen-associated molecular patterns (PAMPS), and metabolic products like indole-3-aldehyde (a ligand to the aryl hydrocarbon receptor [AHR]) or short fatty acids modulate host immune responses and therefore mediate both pro- and anti-inflammatory responses. These are associated with the development and maintenance of healthy immune homeostasis. Interestingly, changes in the microbiome-host relationship are associated with several diseases in different organs, such as autism, stress or stroke (brain), asthma (lung), atopic dermatitis (skin), inflammation and obesity (adipose tissue), and others such as type 3 diabetes, systemic lupus erythematosus or atherosclerosis.</p>", "<p id=\"Par38\">There are different reasons for these associations. Pathophysiological changes due to disease, exogenous stressors, medication [e.g. antibiotics] and changes in diet can all affect the composition of the microbiome and drive host interaction malfunction. The identification of beneficial microbial strains and their restoration to regain health-promoting function could be a therapeutic approach for various diseases. Different strategies helping to restore, complement or replace ineffective microbiomes are in development. Targeted treatments with antibiotics or bacteriophages are thought to destroy pathogenic bacterial species. Mills et al. showed that phages naturally shape host-associated bacterial populations [##REF##23022738##16##]. With new gene editing methods, it will be possible to design specific phages to target specific unsuitable bacterial species at an individual patient level [##REF##25240928##17##]. This will terminate pathogenic processes and create space for the expansion of beneficial species. To further support repopulation with desirable species, targeted transfer of single beneficial or genetically modified species (probiotics), designed communities, or multispecies or whole microbiome applications by fecal transplantations (FMT) can be performed. For example, Sheng et al. showed that FMT is a beneficial treatment option in children with infantile allergic colitis refractory to standard therapeutics [##REF##29358865##18##].</p>", "<p id=\"Par39\">However, it should not go unmentioned that these methods still present us with a number of challenges. With FMT in particular, it is clear that rigorous screening of donors and recipients is important to ensure the success of a healthy microbiome transfer and to avoid potential side effects such as the transfer of antibiotic-resistant bacteria or the induction of sepsis.</p>", "<p id=\"Par40\">Due to the increasing simplicity of methods for genetic modification of microorganisms, bacteria of the microbiota themselves are being considered as therapeutic tools. This is especially the case for bacteria such as <italic>Escherichia coli Nissle</italic> [##REF##28398304##19##], <italic>Lactobacillus</italic> or <italic>Lactococcus</italic> [##REF##30561594##20##], which tend to induce anti-inflammatory immune responses in the host and are not capable of long-term colonization. Designed bacteria are capable of supporting the formation of a healthy microbiota and producing compounds that support beneficial metabolic pathways, or destroy or prevent pathogenic processes [##REF##28398304##19##]. In addition to the supplementation of bacteria, diets with selected nutrients and the use of prebiotics or synbiotics can enhance the development of metabolites with beneficial effects.</p>", "<p id=\"Par41\">Taken together, maintenance of a healthy microbiota and support for the development of desirable metabolites provide a “natural” therapeutic tool to prevent, treat or at least support the treatment of a wide range of diseases. New methods allowing personalized examinations to provide detailed characterization of the host microbiota will help to optimize individual treatment strategies.</p>", "<title>The lung and the microbiome</title>", "<p id=\"Par42\">The long-held dogma that the lungs are a sterile organ meant that it was not considered to be an area that contained a microbiome. However, almost a decade after initiation of the human microbiome project in 2007 [##REF##17943116##21##], the first studies revealed a microbial microcosm in the healthy lung [##REF##24450871##22##, ##REF##21680950##23##]. Still, limited access to sample material from healthy lungs and concerns about contaminations during the sample collection process slowed the research. Today, with the emergency of methods like 16S rRNA analysis, this view has changed. A healthy lung microbiota, which is formed from different bacteria including members of the <italic>Protobacteria</italic>, <italic>Firmicutes</italic>, <italic>Actionbacteria</italic> and Bacteroidetes phyla, has been identified and is now accepted [##REF##27606957##24##]. In healthy people, the lung microbiome shares many similarities with the upper airway microbiome; probably caused by aspirations of oropharyngeal fluids [##REF##28196961##25##]. Furthermore, shifts in the composition of the bacterial communities of the lung microbiota is associated with different lung diseases. Specific changes in the lung microbiome have been found in individuals with asthma [##REF##20052417##26##–##REF##37163754##31##], while different changes have been associated with chronic obstructive pulmonary disease (COPD) [##REF##20052417##26##, ##REF##25253795##32##] or cystic fibrosis [##REF##25629612##33##].</p>", "<p id=\"Par43\">An important role for the microbiome has been identified for susceptibility to asthma. Data from germ-free or antibiotic-treated murine models have shown a strong relationship between the microbiome and the development of asthma [##REF##21471101##34##–##REF##23333861##36##]. In this setting there appears to be a “time window of opportunity” during pregnancy and especially in the first years of life that seems to be important for the development of a healthy protective microbiome.</p>", "<p id=\"Par44\">The antibiotic animal models served to emphasize the role of the microbiome as a beneficial early childhood factor that can reduce the risk of developing diseases later in life. Under no circumstances should they cast doubt on the usefulness of antibiotics for the treatment of potentially life-threatening infectious diseases, but they should encourage the sensible use of these drugs. In this context, it is also worth mentioning that that the timing of antibiotic treatment, such as azithromycin, plays an important role. While mouse model confirm that early life treatment with azithromycin increased the susceptility to develop allergic asthma in later life, epidemiological studies on the effect of antibiotics on the course of lung disease in older children are controversial [##REF##35842561##37##]. On the one hand, no positive effects on recurrent wheezing after RSV bronchiolitis could be observed with parallel treatment with the antibiotic [##REF##37621674##38##, ##UREF##2##39##]; on the other hand, early treatment in children who frequently suffer from severe episodes of lower respiratory tract illness (LRTI) led to a milder course of the disease [##REF##26575060##40##]. The exact role of the microbiome in asthma is not yet fully understood. What is clear is that there are differences between healthy people and those with asthma. Whether there are also differences in the microbiome depending on asthma severity remains controversial. Some think that the microbiome does not differ between asthma phenotypes [##REF##23265859##41##, ##REF##21194740##42##], while other studies show that the microbiome of individuals with severe asthma is associated with corticosteroid insensitivity and eosinophils [##REF##24024497##43##, ##REF##27078029##44##]. Nevertheless, there are several disease-driving functions that are likely to be affected by the composition of the lung microbiome. For example, interactions with the immune system can affect the inflammatory profile or corticosteroid responsiveness and so dramatically influence the course of the disease.</p>", "<p id=\"Par45\">Positive manipulation of the lung microbiome could have beneficial therapeutic effects. Although data concerning a direct therapeutic manipulation of the human lung microbiome are scarce, we can expect that every environmental manipulation supporting the development of a “healthy” microbiome will reduce susceptibility to the development of atopy. It has already been shown for other organs, especially the gastrointestinal tract, that different exogenous factors such as supplementation of omega-3 fatty acids or vitamin D during pregnancy [##REF##31078013##45##], natural delivery [##REF##25452656##46##, ##REF##18352976##47##] breastfeeding [##REF##28755494##48##], and the avoidance of maternal antibiotics have been associated with a reduction in the risk of asthma development by shaping a healthy microbiome (Fig. ##FIG##0##1##).</p>", "<title>Microbiome-immune system interaction: a relationship with an educational mission</title>", "<p id=\"Par46\">The innate and adaptive immune systems represent an endogenous task force responsible for defense against exogenous, potentially harmful, intruders and the maintenance of homeostasis, respectively. Forming a complex network, immune cells are present in, or can be recruited within minutes to, all tissues. A sophisticated control and balancing of immune cells and their mediators is essential to provide appropriate and effective responses against pathogens and harmful substances while preventing overwhelming potentially destructive inflammatory reactions or misguided responses against innocuous stimuli. Malfunction in this finely-tuned control of immunity is responsible for the development, progression and exacerbation of various diseases.</p>", "<p id=\"Par47\">Co-evolved towards mutualism, interactions between the immune system and the microbiome play a central role in the development and induction of proper immune functions. In the first years of life, the microbiome plays a central role in the maturation of a variable, unorganized infantile immune system to an effective, organized adult set-up. Studies in germ-free animals showed that an abundant microbiota led to defects in gastrointestinal tract lymphoid cells, monocytes, and the production of and sensitivity to antibodies [##REF##19343057##49##]. This shaping of immunity in the early life “window of opportunity” seems to mediate long-lasting beneficial effects on homeostasis and adequate host defense. In particular, interplay between structural cells (such as epithelial cells), dendritic cells and the microbes is thought to play a key role in microbiome-mediated immune regulation. Pattern recognition receptors on both endogenous cell types are able to sense bacterial structures and mediate both pro- and anti-inflammatory signals. Epithelial cells of the intestine can express Toll-like receptors (TLR; -1,-2,-3,-5,-9) and nucleotide oligomerization domain 2 (NOD2). They can interact directly with immune cells by the expression of chemokines, cytokines and major histocompatibility complex (MHC) I and MHCII. Moreover, they are also able to directly modulate the composition of the gut microbiota via expression of anti-microbial peptides [##REF##24329495##50##].</p>", "<p id=\"Par48\">Epithelial cells are in close proximity to intraepithelial lymphocytes, which can mediate both structural protection and inflammation. Right beside these first-line defenders lays the lamina propria, which is populated with T and B lymphocytes and DC. These cells are able to exert both pro- and anti-inflammatory responses. Anti-inflammatory responses are mediated by Tregs induced especially by CD103<sup>+</sup> DC, whereas CD103<sup>−</sup> DC are associated with inflammation and the activation of IL-4, interferon (IFN)-γ, IL-22 or IL-17 secreting effector T cells. While it is most likely that immune regulation is mediated by the entire microbiome, most of the findings relating to microbiome-host interactions come from single bacteria species studies. Here, impact on induction of anti-inflammatory Tregs, activation of NK cells and Th17/22 cells, or development of IgA-producing B cells could be observed.</p>", "<p id=\"Par49\">Their ability to sense a plurality of endo- and exogeneous danger signals, to uptake, process and present antigens via MHCI and MHCII, and to produce chemokines and cytokines make DC a professional antigen-presenting cell and a central element in the regulation of adaptive immunity. The type and strength of activation signal regulates the maturation state and determines the nature of the immune response; tolerance or sensitization. DC play an essential role in the induction of T cell and B cell responses. They are able to directly or indirectly modulate T cell subtypes and class-switch of B cells via expression of immune activating but also inhibitory motifs and the release of different mediators.</p>", "<p id=\"Par50\">As a result, it is not surprisingly that DC play a central role in mediating the communication between microbiome and adaptive immunity. DC activation and subsequently induced T cell response seem to be differentially regulated depending on type of commensal bacteria [##REF##16390334##51##]. Interestingly, application of the mixture IRT5 containing microbiome-associated bacterial species is able to induce DC with a tolerogenic phenotype. These DC are able to induce regulatory T cells and have beneficial effects in different diseases like inflammatory bowel disease [##REF##30574151##52##], atopic dermatitis [##REF##26217343##53##], rheumatoid arthritis [##REF##20080669##54##] or myasthenia gravis [##REF##35458209##55##].</p>", "<p id=\"Par51\">One approach to enhancing immune-suppressing properties is to eliminate pro-inflammatory bacterial compounds. For example, lipoteichoic acid (LTA) is major membrane component of gram-positive bacteria and a well-known antagonist of TLR-2. Several studies showed that Lactobacillus species deficient in LTA can mediate anti-inflammatory responses and induce regulatory DC [##REF##22689992##56##, ##REF##21282652##57##]. The effects of bacterial compounds seem to differ between bacterial species, reports on the functional role of LTA are controversial, and this seems to depend on both strain and immunological milieu [##REF##18458151##58##–##REF##21835472##60##]. Both pro- and anti-inflammatory effects are also described for other compounds like peptidoglycan (PGN). Fernandez et al. reported that PGN derived from <italic>Lactobacillus salivarius Ls33</italic> was capable to induce anti-inflammatory DC, while <italic>L. acidophilus</italic> failed to mediate protection [##REF##21471573##61##].</p>", "<p id=\"Par52\">This is also the case for <italic>Bifidobacterium adolescentis</italic> strains. Depending on the strain, differences in DC-specific IL-6, TNF-α, IL-10 induction have been seen, with consequences for the ratio of developing Th17 cells and Tregs. Jeon et al. further analyzed the effectiveness of different intestinal bacteria capable of promoting the induction of regulatory T cells. In their studies <italic>Bifidobacteria breve</italic> but not <italic>Lactobacillus casei</italic> were able to induce Tregs by a DC IL-10- and IL-27-dependent mechanism [##REF##22693446##62##].</p>", "<p id=\"Par53\">Taken together, these data demonstrate that the interaction between the microbiome and DC is complex. Depending on the type of bacteria, differences between species of the same genus and differences in comparable molecules between species, both inflammatory and tolerogenic DC phenotypes can be induced. These promote antigen-specific responses, but also modulate “bystander” immune responses, and therefore influence the pathology of diseases. For example, in a murine tumor model, the elimination of gram-positive bacteria led to a more effective DC-dependent anti-tumor response following radiotherapy [##REF##31815742##63##].</p>", "<p id=\"Par54\">Originating from DC, activation and differentiation of T cells is another important step that determines adaptive immunity. Activation of naïve CD8<sup>+</sup> cytotoxic T cells and differentiation of CD4<sup>+</sup> T helper cells is important for the type and strength, and the abrogation, of immunological responses. Effector T helper cells can differentiate in a variety of subclasses with specific cytokine profiles and are so capable in modulate B cell and innate immune responses. However, in addition to these pro-inflammatory T cells, Treg can also be activated by DC, which can exert immunosuppressive effects by means of cytokines or by direct cell contact.</p>", "<p id=\"Par55\">Commensal bacteria of the gastrointestinal tract control T cell homeostasis by regulating balance between inflammation-inducing Th17 cells and inflammation-suppressing IL-10-producing Tregs.</p>", "<p id=\"Par56\">Bacterial strains belonging to the microbiome, like <italic>Bacteroides fragilis</italic> or several <italic>Clostridium</italic> strains, have been positively associated with the induction of Tregs. Interestingly, <italic>Clostridium</italic> strains, devoid of toxins or virulence factors, are strong inducers of Tregs. The generation of Tregs seems to be dependent on microbial products. Metabolites like Bacteroides-derived polysaccharide A [##REF##30787928##64##] and short chain fatty acids (SCFA) [##REF##23828891##65##, ##REF##25550694##66##] were identified as major drivers for immune protection. In particular, SCFA metabolites butyrate and propionate, but not acetate, have Treg inducing properties [##REF##24226773##67##]. SCFA exert their immune regulatory function by inhibiting histone deacetylases and are able to induce both pro- and anti-inflammatory effects [##REF##24917457##68##].</p>", "<p id=\"Par57\">These modulations are thought to protect degradation of FoxP3 proteins and to induce their expression, thereby mediating both the induction and stability of Tregs [##REF##24226773##67##]. Moreover, SCFA appear to be capable of inducing CD103 + tolerogenic DC [##REF##24412617##69##] and IL-10-producing B cells (Bregs) [##REF##30770822##70##]. The immune dampening effects are thought to mediate tolerance against microbial antigens, thus supporting the cohabitation between host and microbial guest. As a positive side effect, SCFA also mediate immune suppression to food allergens. Modulation SCFA metabolism, for example by special SCFA-containing diets, is thought to be a therapeutic approach for food allergy [##REF##32612610##71##, ##REF##27332875##72##]. Interestingly, SCFA did not only protect from food but also from other not gut related allergies (see next section).</p>", "<p id=\"Par58\">Similar to SCFA, the zwitterionic capsular polysaccharide A (PSA), derived from <italic>B. fragilis,</italic> demonstrated T cell-dependent regulatory properties. Oral application of PSA induced IL-10 producing CD4<sup>+</sup>FoxP3<sup>−</sup> T cells that attenuated inflammatory responses in a murine asthma model [##REF##25347992##73##].</p>", "<p id=\"Par59\">Treg and IL-10-positive B cell inducing capacities have also been described as necessary to protect against inflammatory bowel disease [##REF##30787928##64##, ##REF##25347992##73##]. In humans, PSA support Treg stability [##REF##26230152##74##]. Interestingly, PSA-induced Tregs suppressed Th17 cells, supporting the idea that <italic>B. fragilis</italic> induces host Tregs to prevent counter measure and promote its colonization. Detailed analysis of T cells showed that PSA is able to modulate both inflammatory cytokine profiles with induction of regulatory surface marker profiles on T cells [##REF##33488624##75##]. Again, these observations demonstrate the ability of a microbial compound to induce context-dependent both pro- and anti-inflammatory responses.</p>", "<p id=\"Par60\">While induction of Tregs and IL-10 is associated with immune suppression, IL-17 is associated with anti-bacterial inflammatory responses and often accompanied by neutrophilia. Several bacterial strains of the microbiota demonstrate IL-17-inducing properties. IL-17 seems to be necessary to maintain immune homeostasis and promote appropriate communication with commensal bacteria, thereby preventing induction of inflammatory responses. Altered composition or dysbiosis of gut microbiota and infectious contact with pathogens can change the role of IL-17 towards a pro-inflammatory disease-driving molecule [##UREF##3##76##].</p>", "<p id=\"Par61\">Microbiota-associated bacteria like cytophaga-flavobacter-bacter-oidetes (CFB) [##REF##18854238##77##] or segmented filamentous bacteria (SFB) [##REF##24684957##78##] seem to be two central IL-17 triggers. Changes in the composition of these bacteria affect the Tregs/Th17 ratio [##REF##18854238##77##]. Imbalances in this complicated relationship are responsible for the induction and severity of several diseases, including COPD [##REF##25329073##79##], systemic sclerosis [##REF##30219674##80##, ##REF##30760822##81##]; thrombocytopenia, GVHD [##REF##20484086##82##, ##REF##23226546##83##], and asthma [##REF##28672989##84##]. Shifting the equilibrium to immune suppression by supporting the induction of Tregs or preventing the development of IL-17-producing cells will have beneficial effects for numerous diseases.</p>", "<title>The far-reaching arm of the gut</title>", "<p id=\"Par62\">Microbes of the gastrointestinal tract microbiota exist in close proximity to the host but fail to cross epithelial barriers and reach the inside of the body. Breach of this compartmentalization can induce massive inflammatory responses that often have drastic consequences for the host. A reduction of the epithelial integrity can result in a “leaky gut”. Bacteria can now reach sterile tissues and body regions, and activate innate and adaptive immunity. Depending on the extent of the leakage, this change in host and microbiome communication could also contribute to the development of chronic systemic diseases (e.g. stress-related psychiatric disorders like depression [##REF##26528128##85##], heart failure [##REF##30410105##86##]) or acute life-threatening conditions like sepsis.</p>", "<p id=\"Par63\">Transfer of microbial compounds or metabolic products across the epithelial border affects local organs and systemic processes in a beneficial way. One of the main pathways of long-reaching immune modulation within the gut–lung axis is the mesenteric lymphatic system. Through this system, metabolites can translocate across the intestinal barrier and modulate immune responses [##REF##29075294##87##]. While immune system-triggering factors like LPS, flagellin, peptidoglycan and other PAMPS are generally not translocated across the epithelial barrier, bacterial metabolites are capable of entering the body. Here, they are mainly associated with beneficial, but also sometimes negative, effects. SCFA, for example, is involved in energy metabolism [##REF##2181501##88##], to modulate pancreatic function and insulin release, and regulate appetite [##REF##27279214##89##] and glucogenesis [##REF##24412651##90##]. Lactobacilli-derived indole-3-aldehyde or bile-acids are involved in mucosal homeostasis [##REF##23973224##91##]. Bile acids produced by the liver and modified by the microbiota can act as secondary hormones and modulate responses in adipose tissue, kidneys, heart or the enterohepatic circulation [##REF##24625896##92##].</p>", "<p id=\"Par64\">Precise information concerning the mechanisms describing the interplay between the microbiome and other organs have been reviewed elsewhere (e.g. cardiovascular system [##REF##30264354##93##], liver [##REF##29843959##94##], adipose tissue [##UREF##4##95##] and the brain [##REF##34335190##96##]. Communication between several different tissues, such as the cardiovascular system, liver, adipose tissue, brain and lung have been described. These observations led to the development of terms like the “gut-brain” or “gut–lung axis” to refer to the complex relationship between the gut microbiome and its impact on disease-promoting or preventing processes in peripheral organs.</p>", "<p id=\"Par65\">Next we will focus on cross-talk between the lung and the gut microbiome. Observations that gut dysbiosis is associated with asthma development in children [##UREF##5##97##, ##REF##26424567##98##] contributed to the hypothesis that bacteria in the gut have a beneficial effect in preventing inappropriate immune responses towards harmless antigens in later life. Children with a reduced abundance of bacterial genera like <italic>Lachnospira, Veillonella, Faecalibacterium</italic>, and <italic>Rothia</italic> had an increased susceptibility to develop asthma in later life [##REF##32072252##99##]. A humanized microbiota mouse model confirmed these observations and showed that the early time window after birth is critical for the development of an atopy preventing microbiota [##REF##27115049##100##]. In addition, early-life colonization with species like <italic>Clostridium difficile</italic> [##UREF##6##101##] or <italic>Lactobacillus rhamnosus</italic> [##REF##29453431##102##] are associated with protection from developing asthma in later life.</p>", "<p id=\"Par66\">Similar to other organs, SCFA produced in the gastrointestinal tract that enter the bloodstream and therefore the systemic circulation are thought to be a central regulator in lung immunology. High fiber diets increase SCFA levels and protect against the development of allergic disease. Data from an epidemiological study showed that higher stool concentrations of SCFA in early life were associated with reduced susceptibility to the development of atopic diseases in later life [##REF##30390309##103##]. In an animal model of asthma, oral application of SCFA reduced the developing asthma phenotype by increasing the percentage of Tregs [##REF##30390309##103##]. Moreover, SCFA reduce the survival and mobility of human eosinophils. SCFA-dependent reduction of eosinophils contributed to amelioration of the asthmatic phenotype in mice [##REF##31082458##104##]. SCFA also appear to affect monocyte and subsequent DC macrophage development towards increased phagocytosis but reduced T cell activation ability [##REF##24390308##105##]. Cait et al. reported that dysbiosis of SCFA-producing gut bacteria can affect systemic DC and T cell responses and thereby modulate allergic lung inflammation. Treatment with SCFA reduced the ability to mount enhanced antigen-specific adaptive immune responses and ameliorated lung disease [##REF##29067994##107##] (Fig. ##FIG##1##2##). The SCFA butyrate is also able to reduce activation of murine and human innate lymphoid cells type 2 [ILC2] [##REF##32541842##108##]. These cells are involved in innate immunity and can produce IL-5 and IL-13, similar to Th2 cells. However, in contrast to their T cell counterparts, they seem to be resistant to treatment with corticosteroids, and are therefore associated with severe eosinophilic asthma. Interestingly, diet-mediated induction of SCFA reduced the capability of murine ILC2 cells to induce lung inflammation [##REF##32038630##109##]. Initial clinical trials show that supplementation with soluble fiber, to increase SCFA levels, improved asthma control and inflammation. Even if currently available data are limited by small sample sizes and short follow-up, it does provide and initial indication that diets inducing SCFA could be potential add-on treatment for asthma [##REF##31375426##110##]. PSA has also had beneficial effects on asthma development. In a mouse model, gastrointestinal exposure to PSA derived from the commensal bacterium <italic>Bacteroides fragilis</italic> reduced susceptibility to develop asthma [##REF##25347992##73##].</p>", "<p id=\"Par67\">Gut-lung axis communication has also been reported to have negative consequences. Antibiotic-induced dysbiosis in the gut can lead to an overgrowth of microbiota-associated fungi. These fungi, mainly belonging to <italic>Candida</italic> species, induce inflammatory responses. Release of mediators like prostaglandin E2 can shape circulating monocytes towards M2 macrophages and these are able to exacerbate lung inflammation [##REF##24439901##111##]. Likewise, expansion of the commensal fungus <italic>Wallemia mellicola</italic> has been linked to the severity of asthma. Mice colonized with the fungus demonstrated increased signs of asthma, like airway hyperresponsiveness, BAL eosinophilia or goblet cell metaplasia upon allergen challenge. The signs were associated with an increased secretion of allergen positive immunoglobulins and IL-13 producing T cells [##REF##30235351##112##].</p>", "<p id=\"Par68\">Administration of probiotics, prebiotics or synbiotics can help to maintain, restore or support a healthy gut microbiome and so strengthen the beneficial arm of the gut–lung axis. Especially when done in early life, this is thought to reduce susceptibility to asthma development. Based on observations that low abundances of <italic>Lactobacilli</italic> was associated with asthma risk, bacilli from this species were considered as potential probiotics and are still one of the most common probiotics [##REF##21829685##113##]. Unfortunately, the effectiveness of such treatments to attenuate or prevent asthma in humans are so far not convincing. However, animal data regarding the usage of probiotics as therapeutic intervention for allergic airway disease is promising.</p>", "<p id=\"Par69\">Application of probiotics like <italic>Lactobacillus rhamnosus</italic> [##REF##22548208##114##, ##REF##25440975##115##], <italic>Lactobacillus reuteri</italic> [##REF##32315360##116##], <italic>Lactobacillus gasseri</italic>, [##REF##21996276##117##], and <italic>Bifidobacterium infantis</italic> [##UREF##7##118##] all reduced the development of allergic airway diseases in mice. Treatment was associated with induction of Tregs and modulation of the ratio T helper cell subtypes. The effectiveness of <italic>Lactobacillus Rhamnosus</italic> was shown in both chronic prophylactic and therapeutic models of allergic airway disease in mice [##REF##30952512##119##].</p>", "<p id=\"Par70\">Prebiotics have also been investigated as potential add-on treatment for asthma. Administration of the prebiotic mannose receptor blocker “mannan”, derived from <italic>Saccharomyces cerevisiae,</italic> had beneficial effects on airway inflammation and remodeling in a murine asthma model [##REF##28835901##120##]. Interestingly, mannan seems to be also involved in human epithelial repair processes [##REF##28835901##120##]. Prophylactic immune dampening effectiveness of probiotic <italic>Lactobacillus Rhamnosus</italic> and of a prebiotic crude turmeric extract were also observed in a house dust mite-specific murine asthma model, and symbiotic application of bacterium and extract improved therapeutic effectiveness [##REF##32582180##121##]. Similar results have been obtained after application of long-chain fructooligosaccharide (lcFOS) combined with <italic>Bifidobaterium breve</italic> M-16 V [##REF##17920536##122##, ##UREF##8##123##].</p>", "<p id=\"Par71\">Meta-analysis of clinical data showed beneficial effects of probiotics to reduce susceptibility to develop eczema in later life, there was no indication of their effectiveness for the treatment for wheezing or preventing asthma development in children [##REF##26198702##124##–##REF##30051941##126##]. However, there are some positive studies. Van der Aa reported a reduction in respiratory symptoms in children receiving a symbiotic formula consisting of a hydrolyzed <italic>Bifidobacterium breve M-16 V</italic> altogether galacto/fructooligosaccharide mixture [##UREF##9##127##].</p>", "<p id=\"Par72\">Clinical trials in adults are scarce. One small, short-term trial reported improvements in airway inflammation and asthma control after the application of prebiotics, but the authors recommended the need for larger-scale trials to confirm the potential of fiber diets an addition to asthma management [##REF##31375426##110##]. In a review summarizing the effectiveness of <italic>Lactobacillus</italic> species in allergic rhinitis, Steiner and Lorentz presented therapeutic effectiveness from murine experiments and human trials [##REF##33882482##128##]. They highlighted an interaction between <italic>Lactobacillus</italic> and the immune system, and noted that the majority of clinical trials showed beneficial effects. Nevertheless, they also noted that further studies are needed to provide precise information concerning appropriate species, dosage and timing of treatment, and to facilitate understanding of the underlying mechanism(s) of any benefit.</p>", "<title>Environmental factors derived from exogenous microbiota offer protection from atopy</title>", "<p id=\"Par73\">Exogeneous stressors like allergens, pollutants (e.g. cigarette smoke) or pathogens altered microbiome composition and thus contribute to the development of lung diseases [##REF##32072252##99##]. Today we also know that exogeneous “relaxators” exist, and that these can be beneficial microbes, microbial-derived components or proteins exerting protective effects. Differences in microbial communities, their components and metabolites between urban and rural and rural farming sides have been discussed as significantly contributing to protection against asthma [##REF##11597666##129##–##REF##28939248##135##]. Contact with exogenous factors derived from countryside microbes in early life supports the development of a “healthy immune system”, whereas insufficient signals provided in urban sites leads to an inadequately trained immune system that can induce inappropriate responses and therefore increase susceptibility to develop allergies. Communication between microbes and host, and the shaping of a protective immune system, starts even before birth. For example, maternal exposure to a farm microbiota was associated with decreased asthma risk in offspring [##REF##21112617##136##–##REF##18678343##139##]. Comparing dust from rural and suburban areas in Germany, Ege et al. found a negative association between both gram-positive (staphylococci, corynebacteria, lactic acid fermenters) and gram-negative bacteria (neisseriae, Acinetobacter) and the development of asthma [##REF##22994424##140##]. Beneficial effects of <italic>Staphylococcus sciuri W620</italic> (<italic>S. sciuri W620</italic>) could be confirmed in murine models of asthma [##REF##23369007##141##].</p>", "<p id=\"Par74\">The importance of microbial composition in protective effects was highlighted in another study, where children living in non-farm homes were protected from asthma development when their home dust microbiota was similar to a farm microbiota [##REF##31209334##142##]. Likewise, living in close proximity to farms and access to raw cow’s milk reduced asthma susceptibility in later life in another study [##REF##29314275##143##]. Components in farm dust [##REF##21345099##130##] and cow’s milk [##REF##16751000##133##] have been identified as mediators of immune protective functions. The Pasteur study followed 1133 children from rural areas from age 0 to 6 and identified that continuous consumption of unprocessed cow’s milk was associated with increased Treg numbers and a reduced susceptibility to develop asthma in later life [##REF##23265859##41##]. This finding could be partly explained by a higher uptake of omega-3 polyunsaturated fatty acids in unprocessed cow’s milk [##REF##26792208##144##].</p>", "<p id=\"Par75\">These findings are not intended as a recommendation to consume raw cow's milk directly, as this is associated with a number of foodborne illnesses. Rather, it is important to identify beneficial components of milk and make them available to humans in a safe form as a medicine or dietary supplement.</p>", "<p id=\"Par76\">Deciphering underlying components, LPS concentrations in dust were associated with a reduced susceptibility to develop asthma in children growing up on a farm [##REF##12239255##145##]. Mouse models confirmed that farm dust is a strong immune modulator and can prevent the development of asthma in mice [##REF##16244088##146##]. Interestingly, not all farms seem to have protective properties. Further epidemiological studies revealed that the type of farm is an important modulator for the mediation of ignorance towards “harmless” environmental antigens [##REF##17349684##147##]. Especially cattle and pig farms, but not farms keeping animals like hares, rabbits or sheep, had a protective effect. A study analyzed asthma development of Amish and Hutterite children, both with similar genetic ancestries and farming lifestyle, and found that Hutterite children were particularly prone to develop atopy and asthma in later life [##REF##27518660##148##]. The main differences between the two communities is the technological level of farming, with the Amish using more traditional methods and the Hutterite using more advanced methods. This results in differences in the composition of stable and household dusts. Higher endotoxin levels in Amish dust were associated with differences in the modulation of innate immune cell activation towards tolerance induction. Moreover, animals receiving Amish, but not Hutterite, dust demonstrated a reduced capability to develop an asthma phenotype.</p>", "<p id=\"Par77\">It is important to note that the time of contact, the formulation and the dose of the endotoxin have an important influence on its mode of action. Various studies have also shown that LPS plays an important role in the development [##UREF##11##149##, ##REF##16461458##150##] and exacerbation of lung diseases [##UREF##12##151##–##UREF##15##155##].</p>", "<p id=\"Par78\">Interactions between the dust, structural epithelial cells and immune cells contribute to protective effects. Hammad et al. found that environmental factors like farm dust or chronic exposure to low concentrations of LPS can affect the threshold of allergen recognition by suppressing activation of epithelial cells and DC [##REF##18301423##156##]. Epithelial cells seemed to mediate asthma protection via a mechanism that depends on the ubiquitin-modifying enzyme A20 [##REF##26339029##157##]. Clinical trials confirmed the immune regulatory association of TNF-α-induced protein 3 (TNFAIP3; A20) and asthma in humans. Treatment of PBMC derived from rural asthmatics with farm dust restored TNFAIP3 to levels comparable to those in healthy individuals and induced an anti-inflammatory state [##REF##31381928##158##]. Farm dust also increased barrier function of epithelial cells, and this was associated with a reduction in viral uptake [##REF##29425849##159##]. Since viral infections are associated with induction and exacerbation of asthma, this dust-mediated strengthening of barrier integrity might also have beneficial effects on asthma development and progression. Non-microbial substances in farm dust, such as N-glycolylneuraminic acid (Neu5Gc) [##REF##28629745##160##], a glycoprotein expressed by non-human/non-bacterial cells, or Beta-lactoglobulin (a bovine-lipocalin), or plant-associated arabinogalactans [##REF##20621350##161##], are also able to mediate immune protection [##REF##32485264##162##].</p>", "<title>Old companions—new foes or still friends?</title>", "<p id=\"Par79\">Growing knowledge about the interaction between the environment, microbiota and immune system has resulted in a revision of the hygiene hypothesis.</p>", "<p id=\"Par80\">Industrialization and accompanying improvements in hygiene standards changed the make-up of our microbiota. Environmental stressors including pollutants/toxins, drugs (especially antibiotics), increased indoor and water hygiene standards, along with new approaches in childbirth and early childcare (Caesarean section; bottle-feeding) have had a large impact on the composition and ratios of microbes that have co-evolved with and in us. There has been a progressive loss of microbial species over several decades, which has had unforeseen consequences [##REF##19898491##163##].</p>", "<p id=\"Par81\">Today, many ancestral indigenous microbes like various bacteria (e.g. <italic>Helicobacter pylori</italic>), helminths and protozoa have been lost and are even been seen as pathogens. Based on available information, it can be assumed that this disappearance of microbes previously belonging to the host microbiome (and their compounds and metabolites) has an important impact on immunity and, subsequently, disease susceptibility. Having coevolved over thousands of years, microbes have developed inter-kingdom communication with the host that often has beneficial effects for both partners.</p>", "<p id=\"Par82\">Next, we will review data relating to bacteria and helminths that were once associated with the human microbiome but have now largely been eliminated, especially in the industrialized world. Both beneficial and pathologic effects will be discussed.</p>", "<title><italic>Helicobacter pylori</italic></title>", "<p id=\"Par83\">A textbook example of how the disappearance of ancestral bacteria can affect immunity and disease development is the gram-negative flagellated bacteria <italic>Helicobacter pylori</italic>. <italic>H. pylori</italic> can be regarded as one of the microbial companions of humans [##REF##17287725##164##]. Colonizing as a dominant species in large numbers in a specific organ (the stomach) [##UREF##16##165##] over 58,000 years, <italic>H. pylori</italic> was once omnipresent in all humans. <italic>H. pylori</italic> colonizes the human stomach in youth and if not eradicated, persist through lifetime [##UREF##17##166##]. Today, approximately 50% of the world population is infected with the bacterium, but colonization rates are lowest in industrialized countries and highest in developing countries [##UREF##18##167##].</p>", "<p id=\"Par84\"><italic>H. pylori</italic> developed several tactics to evade the immune system and protect itself against gastric acid [##REF##12471160##168##]. Using its flagella [##REF##1629897##169##] and following chemotactic signals [##REF##9143884##170##, ##REF##15272070##171##], the bacterium colonizes the mucus layer in the stomach. Moreover, <italic>H. pylori</italic> seemed to be masked against detection by pathogen recognition receptors because infections lead to an attenuated activation of adaptive immunity [##REF##12599057##172##, ##REF##14670447##173##]. Such interactions between <italic>H. pylori</italic> and adaptive immunity are of central importance for the development of immunological tolerance towards the bacterium.</p>", "<p id=\"Par85\">Infection with <italic>H. pylori</italic> can lead to both pro- and anti-inflammatory immune reactions. It induces Tregs as well as Th1 and Th17 cells, along with the cytokines IFN-γ, IL-17 and TNF-α [##REF##30483500##174##]. Neutrophils and monocytes support the development of these T cell responses, while Th17 cells induce the release of IL-8 and thus promote the neutrophil-mediated clearance of <italic>H. pylori</italic> [##REF##9647250##175##]. In particular, exuberant and chronic inflammatory responses enhanced by environmental factors are responsible for a <italic>H. pylori</italic> gastric pathology resulting in peptic ulcer, primary gastric B cell lymphoma and gastric carcinoma. Details concerning the role of <italic>H. pylori</italic> in the development of these diseases are beyond the scope of this review and can be found elsewhere [##REF##20938460##176##, ##REF##20930071##177##].</p>", "<p id=\"Par86\">The induction of Tregs is more likely to be associated with anti-inflammatory processes. Infections with <italic>H. pylori</italic> are associated with an induction of Tregs [##REF##15618192##178##]. Naturally occurring Tregs and TGF-β seem to be particularly important for <italic>H. pylori</italic> colonization [##REF##18665940##179##]. Interestingly, the depletion of Tregs not only led to decreased colonization with <italic>H. pylori</italic> but also to an increased inflammatory reaction [##REF##16890606##180##]. Owyang et al. reported that TGF-β-producing DC play a central role in colonization and in <italic>H. pylori</italic>-mediated Treg immunology [##REF##33025641##181##]. Interestingly, the induction of Tregs and the associated increased H. pylori colonization also seems to be also involved in the progression of gastric tumors [##REF##26657504##182##].</p>", "<p id=\"Par87\">Virulence factors, like cytotoxin-associated gene A (CagA), vacuolating cytotoxin A (VacA), γ-glutamyl transferase (GGT), neutrophil-activating protein (HP-NAP) and adhesins are interaction factors that help the bacterium to attach and communicate with the host. The functionality of these factors depends on the strain and can therefore differentially contribute to pro-, but also anti-inflammatory, <italic>H. pylori</italic>-driven host responses. Amedia et al. showed that neutrophils and monocytes produce IL-12 in response to HP-NAP and are thus able to induce IFN-γ-driven Th1 gastric inflammation [##REF##16543949##183##]. Arginin [##REF##23937242##184##], VacA and GGT dampen T cell responses and therefore support the survival of the bacteria. VacA is able to directly suppress bacterial proliferation [##REF##28522905##185##] and modulate activation. Effects seem to be mediated by VacA binding to CD18 [##REF##18191791##186##]. Likewise, GGT mediates T cell suppression by the induction of cell cycle arrest [##REF##25278676##187##]. Both, GGT and VacA induced DC-dependent Tregs and suppressed the activity of CD4<sup>+</sup> T cells [##UREF##19##188##] (Fig. ##FIG##2##3##).</p>", "<p id=\"Par88\">Overall, <italic>H. pylori</italic> infections modulate host immunity, resulting in both pro-inflammatory and anti-inflammatory responses that on the one hand affect bacterial colonization and development of gastric diseases but on the other hand have the potential to orchestrate protective immunity that is capable of suppressing misguided immune responses that otherwise result in diseases like allergy.</p>", "<p id=\"Par89\">Several epidemiological studies support the hypothesis for the beneficial role of this, once commensal, bacteria. These show that colonization with <italic>H. pylori</italic> in early childhood is negatively associated with the development asthma [##UREF##20##189##]. Further cross-sectional studies and meta-analyses confirmed this observation and reported an inverse association between <italic>H. pylori</italic> infections and the development of asthma in children and adults [##REF##17452546##190##–##REF##28787771##198##]. In particular, CagA positive strains [##REF##28634020##196##, ##REF##28787771##198##, ##UREF##22##199##] and maternal <italic>H. pylori</italic> status [##REF##26932510##200##] seem to influence the susceptibility to asthma development. However, several studies failed to find an inverse relationship between <italic>H. pylori</italic> infection and asthma development, or had inconclusive results [##REF##23028243##201##–##REF##19109248##205##].This highlighted the need for additional studies to investigate <italic>H. pylori</italic>-host interactions.</p>", "<p id=\"Par90\">A decade ago, the first studies using a murine model began to examine the role of <italic>H. pylori</italic> infections in the development of asthma in more detail. Isabelle Arnold showed that neonatal animals infected with <italic>H. pylori</italic> had an attenuated asthma phenotype in later life [##REF##21737881##206##]. Transfer experiments found that Tregs played an important role in the <italic>H. pylori</italic>-mediated immune protection [##REF##21737881##206##]. Further work by the same research group showed that <italic>H. pylori</italic> modulates DC and that these are involved in the development of immunoprotective Tregs via the release of IL-18 [##UREF##23##207##]. DC infected with <italic>H. pylori</italic> mutants devoid of virulence factors VacA or GGT failed to generate tolerogenic DC and immune protection, indicating a central role for both of these factors in <italic>H. pylori</italic>-mediated protection from asthma development [##UREF##19##188##]. The above data confirmed the epidemiological studies and showed that postnatal infection with <italic>H. pylori</italic> protected against the development of asthma in later life.</p>", "<p id=\"Par91\">The data also suggest that the administration of <italic>H. pylori</italic> could be suitable as a therapeutic strategy for the treatment of allergic diseases such as asthma. To avoid side effects of a live infection, experiments were carried out with bacterial extract. Comparable to live infections, prophylactic application of <italic>H. pylori</italic>-derived bacterial extracts modulated DC and Treg responses in a IL-10 dependent manner and attenuated the development of allergic airway disease in later life [##UREF##24##208##]. Similar to the clinical studies from den Hollander [##REF##26932510##200##], trans maternal-induced asthma protection was also seen in mice. The offspring of mothers receiving bacterial extract during pregnancy plus during lactation showed fewer asthma signs in later life [##REF##30240703##209##]. Interestingly, studies of therapeutic approaches also found that adult mice developed fewer signs of asthma like allergen induced airway inflammation and mucus secretion after treatment with <italic>H. pylori</italic> extract [##UREF##25##210##, ##UREF##26##211##].</p>", "<p id=\"Par92\">Studies that applying purified VacA prophylactically after birth or by means of trans maternal transfer showed a protective effect [##UREF##24##208##, ##REF##30240703##209##]. Moreover, recently published studies have shown that VacA is also therapeutically effective. In acute or therapeutic murine models of allergic airway disease [##UREF##27##212##], including a chronic disease model [##REF##37415170##213##], treatment with VacA attenuated airway disease. Similar to the prophylactic models, induction of Tregs was observed. In addition, repeated treatment with VacA in the chronic model appeared to suppress the development of the local lung-specific adaptive immunological memory. VacA affects myeloid cells in the gastric mucosa creating a Treg-inducing tolerogenic milieu [##UREF##28##214##]. These cells are capable of migrating within the body and thereby mediating immune suppression. This in turn could reduce the capability of mounting excessive immune responses and thus reduce susceptibility to develop allergies.</p>", "<p id=\"Par93\">In addition to VacA, other <italic>H. pylori</italic>-derived molecules have been reported to mediate immune suppression. Zhou et al. showed that recombinant <italic>H. pylori</italic> NAP (rNAP) suppressed ovalbumin-induced allergic airway disease in mice in a prophylactic manner [##REF##28087613##215##].</p>", "<p id=\"Par94\">Currently available data indicate that <italic>H. pylori</italic> is an indigenous commensal microbe that co-evolved with humans. During a cohabitation period of approximately 60,000 years, the development of communication between host and bacteria has resulted in immune dampening effects in the host, which allow colonization and survival of the bacteria. Improved hygiene standards led to the disappearance of the bacteria and thus presumably also to a change in immune responsiveness that has contributed to the development of allergic diseases. Deciphering the protective mechanisms could provide the tools needed to help avoid and treat allergic disease such as asthma. It is important to note that potential side effects of H. pylori already discussed are excluded and only the beneficial properties of the bacterium are identified.</p>", "<title>Helminths</title>", "<p id=\"Par95\">Like bacteria such as <italic>H. pylori,</italic> intestinal parasites also co-evolved with humans and parasitic infections still affect 2 million people worldwide, especially in developing countries [##REF##26932510##200##]. Of these, protozoa and helminths are of central importance for human health [##REF##20109051##216##]. Co-evolutionary acquired mechanisms allow helminths suppress host defense mechanisms and these organisms remain in the host for up to 20 years [##REF##33193405##217##]. The naturally occurring immune response against helminths is a pronounced type 2 response, phenotypically similar to an allergic immune reaction.</p>", "<p id=\"Par96\">The observations led to the concept that both, anti-inflammatory endogenous processes to restore homeostasis after strong Th2 responses to worm infections, but also escape mechanisms developed by the parasite contribute to asthma protection. In particular, chronic (but not acute) helminth infections seem able to create regulatory environments capable of suppressing immune responses to harmless antigens/allergens [##REF##20425508##218##].</p>", "<p id=\"Par97\">One of the first clinical studies analyzing the relationship between helminth infection and the development of allergy made two key observations. It found that children infected with <italic>Schistosoma haematobium</italic> had a lower prevalence of HDM allergies, and that there was a correlation between the reduction of HDM-specific antibodies and helminth-specific induction of the anti-inflammatory cytokine IL-10 [##REF##11095260##219##]. Subsequently, numerous other studies also showed an inverse correlation between helminth infections and the development of allergies [##REF##11060486##220##–##REF##12743556##224##]. Again, however, published data are not consistent, with other studies finding a positive correlation or no correlation at all [##REF##20047687##225##–##REF##25403350##228##].</p>", "<p id=\"Par98\">Epidemiological studies suggest that the influence of helminths on asthma is strongly dependent on the helminth species and the time, duration and strength of infection [##REF##17689595##229##, ##REF##28402840##230##]. Smits and colleagues summarized these relationships very well [##REF##20425508##218##]. They emphasized that early childhood and chronic infections in particular have protective effects. Infections with high numbers of parasites seem to have an immune-protective effect, whereas weak infection processes are more likely to be associated with the development of allergies. Regarding the helminth species, infections with trichuris, hookworm, or schistosome protect from the development of allergies, while infections with <italic>Ascaris lumbricoides</italic> [##REF##25237284##231##–##REF##12045121##233##] and especially worms for which humans are not normally the host (<italic>Toxocara spp</italic>) [##REF##29573999##234##], are positively associated with the development of atopy. Clear identification of protective species and immune-dampening molecules could provide new therapeutic approaches for the treatment of allergic diseases.</p>", "<p id=\"Par99\">Animal models helped to clarify the immune regulatory role of helminth infection and allergic diseases. Moreover, they provided the first data about the therapeutic effectiveness of immune-suppressive helminth-derived molecules [##REF##25174866##235##]. Worms belonging to the species Schistosoma in particular showed promising effects. Chronic infection with <italic>Schistosoma mansoni</italic> resulted in an immune regulatory milieu capable of suppressing the development of allergic airway diseases [##REF##17689595##229##, ##REF##16365404##236##]. Transfer experiments found that T cells and B cells are important in the mediation of this immune suppression [##REF##17689595##229##]. Comparable results were observed in mice infected with <italic>Schistosoma japonicum</italic> [##REF##18654798##237##], and DC also appear to play an important role in the protective effects of helminth infection [##REF##20042008##238##]. Transfer of DC isolated from helminth-infected mice enhanced Treg responses in airway allergic inflammation [##REF##21711363##239##]. Interestingly, in worm infections, regulatory B cells also appear to have an important function in mediating the immune suppressive effects [##REF##22347409##240##] (Fig. ##FIG##3##4##).</p>", "<p id=\"Par100\">Other studies suggest that worm eggs play a central role for Treg induction and are therefore beneficial for the suppression of allergies [##REF##23967364##241##, ##REF##28753651##242##]. Prophylactic treatment of mice with eggs derived from <italic>Schistosoma mansoni</italic> attenuated allergic airway disease; the effects were independent of B cells and Tregs but were associated with a strong systemic helminth egg-specific Th2 response [##REF##30107039##243##]. Application of eggs can also result in strong lung inflammation accompanied by granuloma formation [##REF##22710310##244##]. Because of these side effects, efforts have been made to identify components of worms and their eggs that induce protective but not inflammatory processes and thus could be suitable as potential therapeutic agents [##REF##17042799##245##]. Initial studies showed that crude mixtures prepared from worms and eggs can attenuate the development of diseases, including type 1 diabetes [##REF##19291704##246##, ##REF##12731071##247##]. The mixture of antigens modulates both arms of immunity [##REF##20204176##248##]. DCs and monocytes are differentially activated, and show a cytokine and costimulatory cytokine pattern that indicates the induction of both effector and regulatory T cell responses [##REF##20204176##248##]. Ongoing projects identified different worm- or egg-derived molecules that were capable of suppressing the immune response and thereby attenuating the development of allergic airway diseases [##REF##27454771##249##–##REF##31496071##251##]. As previously mentioned with H. pylori, it is imperative to keep the safety aspect in mind when developing new therapeutic strategies based on the use of pathogen-associated molecules.</p>", "<p id=\"Par101\">Worm colonization can lead to severe medical problems, especially in the chronic course. When researching new worm-based drugs, it is therefore important to exclude negative mechanisms of action and to identify and isolate as many positive aspects as possible and formulate them into an effective drug.</p>", "<p id=\"Par102\">As well as plathelminthes like <italic>Schistosoma,</italic> nematodes have also shown beneficial effects for prevention of asthma. Live infections [##REF##31397879##252##] and treatment with molecules derived from animals in this phylum [##REF##18322239##253##] induced anti-inflammatory responses.</p>", "<p id=\"Par103\">Taken together, currently available data suggests that worms, especially those that have humans as a natural host, have immune dampening effects. The induction of Tregs and B cells, and the release of the anti-inflammatory cytokine IL10 play a central role. Active proteins can be found in the worms themselves and their eggs. Targeted characterization of these proteins could provide new therapeutic options for the treatment of allergic diseases. Evans and Mitre have summarized the mouse models for different allergic diseases in which helminths show prophylactic or therapeutic benefit [##REF##25174866##235##]. In addition, their review highlighted that infections are effective in mice, but that initial clinical studies in humans were largely unable to show any positive effects of treatment with worm components [##REF##25174866##235##]. In 2020, Ryan et al. provided an update on the efficacy of helminth infection in clinical trials [##REF##32407385##254##]. The article summarized data on the effectiveness of treatments with the pig whipworm <italic>Trichuris suis</italic> or the human hookworm <italic>Necator americanus</italic> in different inflammatory human diseases, including Crohn’s disease, ulcerative colitis, rheumatoid arthritis, multiple sclerosis, allergic rhinitis and asthma [##REF##32407385##254##].</p>", "<p id=\"Par104\">As with other microbes, data in this area are not consistent. Some studies have failed to find any effect of helminth infection, and results vary depending on the worm species and the clinical setting. Just like bacteria, worms have evolved with humans and have developed mechanisms that ensure the survival of both the host and the microorganism. The decoding of these mechanisms and the creation of target structures that are therapeutically effective are needed if worm-based therapeutics are to be developed and applied in the future.</p>" ]
[ "<title>Acknowledgements</title>", "<p>English language editing and styling assistance was provided by Nicola Ryan, independent medical writer, funded by University Hospital Essen-Ruhrlandklinik. We acknowledge support by the Open Access Publication Fund of the University of Duisburg-Essen</p>", "<title>Author contributions</title>", "<p>All authors wrote and reviewed the manuscript. S.R. prepared all figures.</p>", "<title>Funding</title>", "<p>Open Access funding enabled and organized by Projekt DEAL. The authors were funded by the Deutsche Forschungsgemeinschaft (DFG) (RE3652/4-1; TA275/7-1 and TA275/8-1.</p>", "<title>Availability of data and materials</title>", "<p>Not applicable.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par106\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par107\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par108\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Factors influencing the composition of the microbiome. These factors include host characteristics, such as genetic factors or age, the use of drugs (antibiotics) or pre- and probiotics, environmental factors, nutrition or early childhood factors (birth and feeding mode). Changes often have consequences on the interaction of the microbiome with the immune system and can affect the development and progression of diseases</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Intestinal/lung microbial axis. In the intestine, the microbiome communicates with structural and immune cells of the host via the release of microbial antigens, TLR ligands or metabolites such as SCFA or deaminotyrosine (DAT). In this process, a kind of immune system fine-tuning occurs, supporting the symbiotic community between bacteria and host. Anti-inflammatory metabolites can also enter the circulation and influence immune responses in distal parts of the body. In addition to the systemic release of metabolites, the migration of cells from the intestine to the periphery and their immunoregulatory function are also shown. This can be anti-inflammatory, but also support processes that are needed to defend against infections. Picture adapted from: Wypych TP et al. [##REF##31501577##106##]</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p><italic>Helicobacter pylori</italic> can act as an immunoregulator via VacA and GGT. Both proteins induce a tolerogenic DC phenotype that can induce Tregs or Th1 cells. Among other things, the T cells have an anti-inflammatory effect via the release of IL-10 and can thus suppress the development of an allergic respiratory disease</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Comparable to allergy, strong Th2 immune responses are induced to eliminate worms. Especially for human-associated worms, infection also leads to the development of an anti-inflammatory immune response in which both anti-inflammatory T and B cells are induced. It is believed that both cell types, which can be induced by the worm itself and by components from its eggs, can prevent the development of allergies</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Humans have evolved together with a wide range of bacteria, viruses, worms and fungi. In this process, favorable communities have developed that have a positive effect on metabolism and the immune system, and a negative effect on the development of diseases. Alternations in this coexistence, such as changes in lifestyle (industrialization, hygiene status, pollutants) mean that modern man is more susceptible to the development of diseases such as allergies or asthma</p></caption></fig>" ]
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[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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{ "acronym": [ "IL", "TSLP", "Treg", "TGF", "DC", "MALDI-TOF", "PAMPS", "AHR", "FMT", "COPD", "TLR", "NOD2", "MHC", "IFN", "LTA", "PGN", "SCFA", "Breg", "CFB", "SFB", "DAT", "ILC2", "lcFOS", "TNFAIP3", "Neu5Gc", "CagA", "VacA", "GGT" ], "definition": [ "Interleukin", "Thymic stromal lymphopoietin", "Regulatory T cell", "Transforming growth factor", "Dendritic cell", "Matrix-assisted laser desorption/ionization-time of flight", "Pathogen-associated molecular patterns", "Aryl hydrocarbon receptor", "Fecal microbiome transplantations", "Chronic obstructive pulmonary disease", "Toll like receptor", "Nucleotide oligomerization domain 2", "Major histocompatibility complex", "Interferon", "Lipoteichoic acid", "Peptidoglycan", "Short chain fatty acid", "Regulatory B cell", "Cytophaga-flavobacter-bacter-oidetes", "Segmented filamentous bacteria", "Deaminotyrosine", "Lymphoid cells type 2", "Long-chain fructooligosaccharide", "TNF-α-induced protein 3", "N-glycolylneuraminic acid", "Cytotoxin-associated gene A", "Vacuolating cytotoxin A", "γ-Glutamyl transferase" ] }
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oa_package/79/55/PMC10787474.tar.gz
PMC10787475
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[ "<title>Introduction</title>", "<p id=\"Par11\">Human Immunodeficiency Virus (HIV) deteriorates the human immune system and makes the body vulnerable to secondary and opportunistic infections [##REF##18382737##1##]. The progression of HIV infection in children is especially rapid in the absence of HIV care antiretroviral therapy [##UREF##0##2##]. Antiretroviral therapy (ART) determined impact and outcome could be achieved when the children on ART had good adherence to regular follow-ups [##UREF##1##3##].</p>", "<p id=\"Par12\">Globally, it has been estimated that out of 1.7 million children living with HIV, 65% of them received Anti-retroviral Therapy (ART), and 57% of them had viral suppression at the end of 2021 [##UREF##2##4##]. As ART coverage grows, a rise in LTFU has been observed in many African ART programs, with children faring the worst. Loss to follow-up (LTFU) of ART is defined as failing to engage in the continuum of care for 90 days (3 months) after the last scheduled appointment due to their wishes or beliefs or barriers to continued access to care [##UREF##3##5##]. Here we can understand that, LTFU is a major obstacle to the success of HIV treatment in meeting the UNAIDS 95–95-95 goals in 2025 &amp; and ending the HIV epidemic by 2030 [##REF##35925943##6##]with an estimated 20–40% of patients experiencing loss to follow-up in Sub-Saharan Africa countries [##REF##17941716##7##] and 14 -28% globally [##REF##31312327##8##]. Children who have failed antiretroviral medication have an increased number of side effects like expansion of drug-resistant viral strains and mortality [##REF##16388496##9##]. The emergence of drug-resistant strains, which results in the transmission of drug-resistant strains to the population, has devastating consequences, rendering future therapeutic interventions ineffective [##REF##24855332##10##] and narrowing the subsequent possible alternatives, as well as affecting the success of HIV treatment in meeting the Joint United Nations Program on HIV/AIDS (UNAIDS) 95–95-95 goals in 2025 ending HIV epidemic by 2030 [##UREF##4##11##].</p>", "<p id=\"Par13\">ART failure may be secondary to LTFU, and it is a growing issue (such as increasing ART accessibility) that threatens to undermine much of the work that has been prioritized for patients, the community, and the country at large.</p>", "<p id=\"Par14\">Despite the fact that several primary studies on the incidence and predictors of LTFU among Ethiopian children on ART have been conducted, this study was conducted to estimate the pooled incidence and predictors of LTFU among Ethiopian children on ART due to the presence of conflicting (inconsistent) findings, which makes programmers, policymakers, and healthcare professionals difficult.</p>", "<p id=\"Par15\">The findings of this study will be important for designing mechanisms for interventions like prevention to improve the quality of life of children.</p>", "<title>Research question</title>", "<p id=\"Par16\">What are the incidence and predictors of loss to follow-up among Ethiopian children on ART?</p>", "<title>Condition</title>", "<p id=\"Par17\">Loss to follow-up of ART.</p>", "<title>Context</title>", "<p id=\"Par18\">Ethiopia.</p>", "<title>Population</title>", "<p id=\"Par19\">Ethiopian children on ART.</p>" ]
[ "<title>Methods</title>", "<title>Study design</title>", "<p id=\"Par20\">Systematic review and Meta-analysis.</p>", "<title>Study setting</title>", "<p id=\"Par21\">Ethiopia is a Federal Democratic Republic with nine regional states (Afar, Amhara, Benishangul-Gumuz, Gambella, Harari, Oromia, Somali, Southern Nations Nationalities and People's Region, and Tigray) and two city administrations (Addis Ababa and Dire Dawa). It has a total area of 1,100,000 km2 and is divided into zones, which are further subdivided into districts, which are further subdivided into kebeles, the lowest administrative divisions [##UREF##5##12##]. Ethiopia, with a population of approximately 112 million people, is Africa's second most populous country (56,010, 000 females and 56, 069, 000 males in 2019) [##UREF##6##13##].</p>", "<title>Participants</title>", "<p id=\"Par22\">All cohort research articles conducted on incidence and predictors of loss to follow-up among Ethiopian children and published in English.</p>", "<title>Data source and searching strategy</title>", "<p id=\"Par23\">This review was reported using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline [##REF##25046131##14##], (Additional file ##SUPPL##0##1##). We conducted a systematic search of electronic databases (PubMed/MEDLINE, CINAHL, EMBASE, Google Scholar, and Science Direct) for previous research related with our topic of interest. In addition to the databases, articles were also found by searching the reference lists of eligible studies. Two authors worked independently on the search (MYB and SSJ). Endnote X9 was used to retrieve and manage studies found after conducting a systematic search. Of the search engine, the following is the example used in PubMed database searches: (((((((HIV infected children[Text Word]) OR (Children living with HIV[Text Word])) OR (children on ART[Text Word])) OR (HIV infected Adolesecent[Text Word])) OR (Adolescents living with HIV[Text Word])) OR (HIV infected children[MeSH Terms])) AND (((Ethiopia[Text Word]) OR (Federal Democratic Republic of Ethiopia[Text Word])) OR (Ethiopia[MeSH Terms]))) AND (((((((Loss to follow up[Text Word]) OR (withdraw[Text Word]))) OR (New occurrence[Text Word])) OR (incidence[Text Word])) OR (predictor*s[Text Word])) OR (Loss to follow up[MeSH Terms])).\" The search strategy began on December 25, 2022, and ended on January 12, 2023.</p>", "<title>Eligibility criteria</title>", "<title>Included criteria</title>", "<p id=\"Par24\">All cohort studies conducted on incidence and predictors of loss to follow-up among Ethiopian children on ART and Published in English were eligible.</p>", "<title>Excluded</title>", "<p id=\"Par25\">Articles were excluded when they did not have the outcome variable and those articles having the same title but different study designs.</p>", "<title>Screening procedure/ study size</title>", "<p id=\"Par26\">Two authors (MYB and SA) independently screened all titles/abstracts found in electronic databases. Two authors (MYB and SSJ) independently screened the full text of screened and included articles for title and abstract. Disagreements during the screening of the title and full length were resolved through discussion in the presence of the third author (GMB).</p>", "<title>Quality assessment (risk of bias)</title>", "<p id=\"Par27\">The Newcastle–Ottawa Quality Assessment Scale for cohort study (NOQAS) [##REF##19053169##15##] was used to evaluate the quality of the included primary studies based on selection (Representativeness of the exposed cohort, Selection of the non-exposed cohort, Ascertainment of exposure, and Demonstration that outcome of interest was not present at start of study), Comparability(based on the design or analysis controlled for confounders), and outcome (Assessment of outcome, Was follow-up long enough for outcomes to occur, Adequacy of follow-up of cohorts). During the quality assessment of articles, all included articles were declared as having good quality because the articles scored 3 stars in the selection domain AND 2 stars in the comparability domain AND 2 stars in the outcome/exposure domain.</p>", "<title>Data extraction</title>", "<p id=\"Par28\">The data were extracted using the data extraction Checklist prepared from a Microsoft Excel spreadsheet. To ensure consistency, three authors (MYB, SSJ, and BE) extracted data independently using a predefined extraction checklist. After the source of the disagreements was identified, disagreements between or among authors were resolved through discussion. The incidence of LTFU of ART among children, the study region, year of publication, sample size, follow-up period, and the first author's name were all the extracted data from the primary article during extraction.</p>", "<title>Outcome variable and measures</title>", "<p id=\"Par29\">The primary outcome of interest was the pooled incidence of LTFU from ART. It was calculated by considering the incidence of primary studies and its standard error using the random effects model through the DerSmonian-laired method and I<sup>2</sup> tests. The second outcome of interest was the pooled predictors of LTFU which was identified using a binary meta-regression model with a 95% confidence level and the strength of association has been presented using relative risk. It was again calculated after the log transformation of the primary studies' effect size had been further computed. First, the RR of the primary studies was transformed into logRR to get the actual effect size and its standard error was computed using lnlogRR. Hereafter, the binary meta-regression model was fitted considering the logRR and lnlogRR to identify the predictors of first-line ART failure among Ethiopian school children. Finally, the association between variables was presented using RR with a 95% CI.</p>", "<title>Data management and analysis</title>", "<p id=\"Par30\">For further analysis, the extracted data were exported to Stata™ Version 17.0 software. The pooled incidence of loss to follow-up from ART was estimated using the random effects model with the DerSimonian laired method. The standard errors were calculated from the reported estimates and population denominators using a binomial distribution assumption. The presence of heterogeneity between studies was determined using the Cochran-Q test and quantified using I-square statistics. The level of heterogeneity was classified as low (I<sup>2</sup>:0—25), moderate(I<sup>2</sup>: 25—50), or high (I<sup>2</sup>: ≥ 50) [19. For the first time, the presence of heterogeneity was checked using a forest plot test through a fixed effects model with inverse variance method and revealed the presence of heterogeneity. Thereafter, a forest plot test through the random-effect model with the DerSimonian and Laird method was computed [##REF##3802833##16##]. After getting heterogeneity, subgroup analysis, publication bias, sensitivity analysis, and meta-regression were performed to identify the source of heterogeneity but not explained. The study regions, publication year (before 2021 vs. after 2021), sample size (above mean vs. below mean), and follow-up period (&lt; 8 vs. &gt; 8 years) were used to conduct a subgroup analysis. To determine the presence of publication bias after the funnel plot, Egger's linear regression test and trim and fill analysis were used to declare the effect of small studies [##UREF##7##17##]. Finally, the findings depending on the objectives of the study were presented in the form of tables and figures.</p>" ]
[ "<title>Results</title>", "<title>Search results</title>", "<p id=\"Par31\">A total of 1304 studies were discovered through electronic database searches on PubMed/ MEDLINE, CINAHL, EMBASE, Google Scholar, and Science Direct, as well as organizational records and websites. Approximately 872 articles were excluded due to duplication, 245 articles were excluded due to differences in study setting/context [##UREF##7##17##–##REF##30024494##22##], 133 articles were excluded due to differences in study population [##REF##36407380##23##–##UREF##12##29##], 45 articles were excluded due to the study conducted on the general population [##REF##35457498##18##, ##UREF##13##30##–##REF##33505567##32##]. Finally, 9 cohort studies were identified for inclusion and followed for the current Systematic Review and Meta-analysis (Fig. ##FIG##0##1##).</p>", "<title>Characteristics of the included articles</title>", "<p id=\"Par32\">In Ethiopia, about nine studies qualified for inclusion and analysis, involving a total of 3336 children on ART which were published up to 2022. These studies were conducted in three regions and one city administration. Among the included studies, about 5 [##UREF##15##33##–##REF##32931502##37##] of them were in the Amhara region, 1 [##UREF##19##38##] in the Oromia region, 1 [##REF##34514177##39##] in SNNPR, and 2 [##REF##29408897##40##] in Addis Ababa. The studies with the smallest and largest sample sizes, 254 and 533, were conducted in SNNPR and Addis Abeba respectively, followed by a study conducted at Amhara region with a sample size of 448. The included studies' follow-up periods ranged from 2 to 14 years, with 287.7 to 1555.56 child-years of ART failure-free observation (Table ##TAB##0##1##).\n</p>", "<title>The pooled incidence of loss to follow-up</title>", "<p id=\"Par33\">The incidence of LTFU from ART among Ethiopian children was 5.83 (95% CI: 3.94, 7.72) per 100 children-years of observation with I<sup>2</sup>: 83.7% &amp; <italic>P</italic>-value &lt; 0.001. When we looked at it by region, Addis Ababa city administration had 8.59 (95% CI: -2.88, 20.05) incidence of LTFU among children, SNNPR had 5.20 (95% CI: 2.47, 7.93), and Oromia region had 3.30 (95% CI: 1.17, 5.43) per 100 children-years of ART failure free observation (Fig. ##FIG##1##2##).</p>", "<title>Subgroup meta-analysis</title>", "<p id=\"Par34\">Despite the presence of strong evidence supporting the existence of heterogeneity (using sample size for those whose sample size was less than the mean (&lt; 371) I<sup>2</sup> = 35.19 with <italic>P</italic>-value &lt; 0.19 &amp; &gt; 371 I<sup>2</sup> = 90.40 with <italic>P</italic>-value &lt; 0.001 (Fig. ##FIG##2##3##), publication year (those published before 2021 I<sup>2</sup> = 88.00 with <italic>P</italic>-value &lt; 0.00 &amp; after 2021 I<sup>2</sup> = 44.17 with <italic>P</italic>-value &lt; 0.001) (Fig. ##FIG##3##4##), and length of follow-up period ( those conducted less than the mean follow-up years (&lt; 8 years) I<sup>2</sup> = 91.40 with <italic>P</italic>-value &lt; 0.001, &amp; those conducted greater than the mean follow-up years (&gt; 8 years) I<sup>2</sup> = 0.00 with <italic>P</italic>-value &lt; 0.56) (Fig. ##FIG##4##5##), no sources of heterogeneity were identified using subgroup Meta-analysis.</p>", "<title>Meta-regression</title>", "<p id=\"Par35\">The meta-regression is the extension of subgroup analysis conducted to identify the source of heterogeneity using continuous variables. Thus, the publication year and sample size were used as covariates in random-effects meta-regression. The analysis revealed that sample size (<italic>P</italic>-value = 0.43) and publication year (<italic>P</italic>-value = 0.88) did not affect heterogeneity (Table ##TAB##1##2##).\n</p>", "<title>Publication bias (Bias detection)</title>", "<p id=\"Par36\">The presence or absence of publication bias was initially determined using a funnel plot, and the distribution of the studies in the funnel plot was asymmetrical, indicating that the small studies did not affect the heterogeneity (Fig. ##FIG##5##6##). As well known, the funnel plot is a subjective measure for assessing publication bias; so, the Egger linear regression test was used to confirm the presence of publication bias objectively, and it demonstrated that small studies had an effect on the existence of heterogeneity. Hence, Trim and fill analysis was performed as a tiebreaker to obtain a definitive conclusion on the presence of publication bias, and it yielded 5.85, which is consistent with the funnel plots estimate. Finally, we declared that small studies did not affect the existence of heterogeneity among studies (Table ##TAB##2##3##).</p>", "<title>Predictors of LTFU among Ethiopian children</title>", "<p id=\"Par37\">Baseline WHO stage (including six studies), adherence (including three studies), disclosure status (including two studies), parents' educational status, baseline CD4 count, and parental status were used to predict the new occurrence of LTFU of ART in Ethiopian children. As a result, being a rural resident and having poor ART adherence were identified as significant predictors for the incidence of LTFU from ART among Ethiopian Children.</p>", "<p id=\"Par38\">Those study participants who were from rural residences had a 1.65 (95% CI: 1.06, 2.52) times higher chance of getting LTFU when compared with those children living in urban (Fig. ##FIG##6##7##). Children who had poor ART adherence had a 2.03 (95% CI: 1.23, 3.34) times higher chance of experiencing LTFU of ART than children having good ART adherence (Fig. ##FIG##7##8##).</p>" ]
[ "<title>Discussions</title>", "<p id=\"Par39\">This systematic review and meta-analysis included nine articles that were published up to 2022 and had 3336 children. The sample size for each study ranged from 254 to 533 children on ART in Ethiopia. The included studies were conducted either in prospective or retrospective cohort study design and all have the same LTFU operational definition “LTFU is failing to engage in the continuum of care for 90 days (3 months) after the last scheduled appointment due to their wishes or beliefs or barriers to continued ART access for care”.</p>", "<p id=\"Par40\">Among Ethiopian children, the pooled incidence of LTFU from ART was 5.83 (95% CI: 3.94, 7.72) per 100 children- years of observation with I<sup>2</sup>: 83.7% &amp; <italic>p</italic>-value &lt; 0.001. This finding is too high and requires immediate attention to accomplish the predetermined goals and targets, such as meeting the Joint United Nations Program on HIV/AIDS (UNAIDS) 95–95-95 by 2025 and ending the HIV epidemic by 2030. The high incidence of LTFU could be because most of the HIV-infected children who were experiencing LTFU were from rural and their families had low incomes, and were uneducated in their educational background. Because of the children's aforementioned circumstances, they did not receive regular ART follow-ups from the ART institution they founded. In addition to the above, due to the fear of social stigma, families may be unwilling to have regular ART follow-ups from which their children had tested and initiated ART in their locality, and those children having ART initiation and follow-up far from their locality may experience LTFU from their ART appointment schedule due to their family's economic scarcity. Further more, the children may also experience LTFU because their families had poor knowledge about the drawbacks of LTFU and regular ART follow-up practice due to their educational background plus the minister of health did not implement close follow-up and monitoring. Finally, due to the inadequate setup of ART centers for diagnosing opportunistic infections like tuberculosis, children are exposed to a double disease burden, which leads to more immunocompromization and disease progression. This ultimately results in LTFU from ART due to the development of hopelessness secondary to the disease progression. These all might be the factors associated with HIV-infected children experiencing LTFU from their ART. Here, the minister of health should be applied close follow-up like using phone message text as a reminder of children's appointment schedule, and daily pill intake for their families. Additionally, healthcare professionals should pay more attention to educating families about the importance of regular ART follow-up and the disadvantages of LTFU for children and their families.</p>", "<p id=\"Par41\">Those children who were rural dwellers had a 1.65 (95% CI: 1.06, 2.52) times higher chance of experiencing LTFU when compared with those children who came from urban. This finding was supported by the study conducted in South Africa [##UREF##19##38##]. This could be because children from rural areas are more likely to experience loss to follow-up (LTFU) in ART centers due to several reasons. Firstly, they may be uneducated and lack economic management skills, which limits their family’s access to information and leads to low-income status. This, in turn, affects their practice on regular ART follow-up and health-seeking behavior due to the scarcity of money for transportation costs as well as the absence of nearby ART treatment centers. Secondly, the absence of integrated services for chronic diseases may also contribute to LTFU among rural dweller children. This is because it takes extra time devoted to waiting for different diagnoses and treatment services, which may lead them to have nights where money for bed and food is requested, leaving the clients unsatisfied. Therefore, it is recommended that the minister of health collaborates with governmental and non-governmental sectors to strengthen the scale-up of ART centers and initiate HIV services integrated with chronic diseases [##REF##29373574##42##].</p>", "<p id=\"Par42\">Children who have poor ART adherence had a 2.03 (95% CI: 1.23, 3.34) times higher chance of experiencing LTFU of ART than children having good ART adherence. This finding is sustained by the study conducted in Nigeria [##REF##28261274##43##]. Studies conducted in Uganda have shown that rural dwelling is the primary predictor of LTFU among children on ART. This is due to several reasons. Firstly, even with regular follow-ups, children may not take their daily pills dose due to low follow-up by their families. Secondly, in rural areas, there is no matured peer support and counseling but more pronounced stigma and discrimination which leads to children developing depression and hopelessness. Thirdly, poor ART adherence leads to the progression of diseases (AIDS) called ART failure, and the development of ART-resistant viral strain narrowing the treatment option which lead to LTFU and end up with death. Therefore, it is recommended that ART centers should provide targeted adherence support for children from rural areas [##UREF##20##44##, ##REF##25567701##45##]. The study’s strength lies in providing the pooled incidence and predictors of LTFU among children on ART in Ethiopia. However, it is important to note that the study only included studies that were published in English, which may be taken as the limitation of the study.</p>" ]
[ "<title>Conclusions and recommendation</title>", "<p id=\"Par43\">Among Ethiopian children on ART, one out of 167 children on ART had a risk of experiencing LTFU. The identified predictors of LTFU were being rural dwellers and having poor ART adherence. The authors recommend that the minister of health should strengthen the scale-up of ART centers, initiate HIV service integrated with chronic diseases, and have close follow-up and monitoring to address the high incidence of LTFU. To focus on rural dwellers, the minister of health should scale-up ART centers in collaboration with governmental and non-governmental sectors and use phone message texts as reminders of their appointment schedule. Healthcare professionals should also pay more attention to rural dwellers by providing education on the importance of having regular ART follow-ups and the drawbacks of LTFU. Children’s nearby families should control and remind the children to take their daily pill dose intake at the appropriate time and frequency. Considering poor ART adherence, healthcare professionals must ensure that children take their daily pill at the correct dose and frequency when they come for their next appointment follow-up. The minister of health should set daily reminders using phone text messages and scale-up ART centers more. Future researchers should conduct a study on the fate of children after LTFU from ART.</p>" ]
[ "<title>Introduction</title>", "<p id=\"Par1\">Loss of follow-up (LTFU) from ART regular follow-up is one of the key acknowledged causes for the development of ART-resistant virus strains currently. It becomes a major weakness for the successful implementation of HIV care and treatment programs mainly in Sub-Saharan Africa but also globally. About 20—40% of children on ART loss their regular ART follow-up annually. Because of the inconsistency of the prior publications' findings, policymakers, programmers, and healthcare providers find it difficult to intervene. Hence, this study was conducted to provide a pooled incidence and identify the predictors of LTFU among children on ART in Ethiopia.</p>", "<title>Methods</title>", "<p id=\"Par2\">Articles were searched from PubMed/ MEDLINE, CINAHL, EMBASE, Google Scholar, and Science Direct, as well as organizational records and websites. This review included both retrospective and prospective follow-up studies published in English. The data were extracted using Microsoft Excel and exported into Stata™ Version 17.0 for further processing and analysis. The presence of heterogeneity was assessed using forest plots with the I<sup>2</sup> test. To identify the source of heterogeneity subgroup analysis, meta-regression, publication bias, and sensitivity analysis were computed. The pooled incidence of LTFU was estimated using a random effects meta-analysis model with the DerSimonian-laired method. To identify the predictors, a 95% confidence interval with relative risk was used to declare the presence or absence of an association.</p>", "<title>Results</title>", "<p id=\"Par3\">In this systematic review and Meta-analysis, nine studies with a total of 3336 children were included. The pooled incidence of LTFU from ART was 5.83 (95% CI: 3.94, 7.72) per 100 children-years of observation with I<sup>2</sup>: 83% &amp; <italic>p</italic>-value &lt; 0.001. Those children who were from rural were had a 1.65 (95% CI: 1.06, 2.52) times higher chance of getting LTFU when compared with their counterparts. Children who had poor ART adherence had a 2.03 (95% CI: 1.23, 3.34) times higher chance of experiencing LTFU of ART than children having good ART adherence.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Among Ethiopian children on ART, one out of 167 had the risk of experiencing LTFU. Being rural dwellers and having poor ART adherence were the identified predictors of LTFU. Close follow-up and phone message text should be used to have good ART adherence among rural dwellers to meet the predetermined goal of ART.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12889-023-17333-9.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>I would like to thank the authors of this manuscript for their unwavering commitment and collaboration in providing accurate information to scientific society.</p>", "<title>Authors’ contributions</title>", "<p>Conceptualization: Molla Yigzaw Birhan, Selamawit Shita Jemberie: Data curation: Molla Yigzaw Birhanu, Getamesay Molla Bekele, Getasew Yirdaw, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie. Formal analysis: Molla Yigzaw Birhanu, Getasew Yirdaw, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie. Investigation: Molla Yigzaw Birhanu, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie. Methodology: Molla Yigzaw Birhanu, Getamesay Molla Bekele, Selamawit Shita Jemberie. Project administration: Molla Yigzaw Birhanu, Getasew Yirdaw, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie. Resources: Molla Yigzaw Birhanu, Getasew Yirdaw, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie. Software: Molla Yigzaw Birhanu, Getasew Yirdaw, Getamesay Molla Bekele, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie. Supervision: Molla Yigzaw Birhanu, Getasew Yirdaw, Getamesay Molla Bekele, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit. Shita Jemberie. Validation: Molla Yigzaw Birhanu, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie, Getamesay Molla Bekele. Visualization: Molla Yigzaw Birhanu, Bekele Simegn Demissie, Genanaw Kassie Getahun, Selamawit Shita Jemberie.  Writing – original draft: Molla Yigzaw Birhanu, Bekele Simegn Demissie, Genanaw Kassie Getahun, Getamesay Molla Bekele, Selamawit Shita Jemberie. Writing – review &amp; editing: Molla Yigzaw Birhanu, Getamesay Molla Bekele, Getasew Yirdaw, Selamawit Shita Jemberie.</p>", "<title>Funding</title>", "<p>Not applicable to this section.</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and analyzed during the current study are available upon reasonable request from the corresponding author.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par44\">Not applicable to this section because it was conducted using secondary data.</p>", "<title>Consent for publication</title>", "<p id=\"Par45\">Not applicable” in this section.</p>", "<title>Competing interests</title>", "<p id=\"Par46\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>STROBE flow diagram of the included studies for LTFU from ART among Ethiopian children</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The pooled new occurrences of loss to follow-up among Ethiopian children on ART</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Subgroup analysis using mean sample size for LTF</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Subgroup analysis using publication years for LTFU</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Subgroup analysis using mean follow-up period for LTFU</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Funnel plot to check publication bias of LTFU among Ethiopian children on ART</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Association of LTFU and rural residency of Ethiopian children on ART</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>Association of LTFU and poor ART adherence among Ethiopian Children on ART</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>The characteristics of the included studies among Ethiopian children on ART</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Sn</th><th align=\"left\">Authors</th><th align=\"left\">Publication year</th><th align=\"left\">Region</th><th align=\"left\">cases</th><th align=\"left\">Sample size</th><th align=\"left\">PYO</th><th align=\"left\">Incidence</th><th align=\"left\">Follow-up period</th><th align=\"left\">Quality assessment</th></tr></thead><tbody><tr><td align=\"left\">1</td><td align=\"left\">Tiruye Menshw et al. [##UREF##15##33##]</td><td align=\"left\">2021</td><td align=\"left\">Amhara</td><td align=\"left\">101</td><td align=\"left\">448</td><td align=\"left\">1603.17</td><td align=\"left\">6.3</td><td align=\"left\">10</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">2</td><td align=\"left\">TAMENE FETENE etal [##UREF##16##34##]</td><td align=\"left\">2018</td><td align=\"left\">Addis Ababa</td><td align=\"left\">46</td><td align=\"left\">533</td><td align=\"left\">317.6</td><td align=\"left\">14.5</td><td align=\"left\">5</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">3</td><td align=\"left\">Chalachew Adugna Wubneh et al. [##UREF##17##35##]</td><td align=\"left\">2020</td><td align=\"left\">Amhara</td><td align=\"left\">24</td><td align=\"left\">402</td><td align=\"left\">800</td><td align=\"left\">6</td><td align=\"left\">5</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">4</td><td align=\"left\">Yitbarek Tenaw Hibstie et al. [##REF##32931502##37##]</td><td align=\"left\">2019</td><td align=\"left\">Amhara</td><td align=\"left\">70</td><td align=\"left\">408</td><td align=\"left\">1555.56</td><td align=\"left\">4.5</td><td align=\"left\">14</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">5</td><td align=\"left\">Kirubel Biweta Bimer et al. [##REF##34514177##39##]</td><td align=\"left\">2020</td><td align=\"left\">SNNPR</td><td align=\"left\">70</td><td align=\"left\">254</td><td align=\"left\">1357.6</td><td align=\"left\">5.2</td><td align=\"left\">6</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">6</td><td align=\"left\">Mulatu Biru et al. [##REF##29408897##40##]</td><td align=\"left\">2018</td><td align=\"left\">Addis Ababa</td><td align=\"left\">8</td><td align=\"left\">304</td><td align=\"left\">287.7</td><td align=\"left\">2.8</td><td align=\"left\">2</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">7</td><td align=\"left\">Ermias Sisay Chanie et al. [##REF##35173969##41##]</td><td align=\"left\">2022</td><td align=\"left\">Amhara</td><td align=\"left\">76</td><td align=\"left\">357</td><td align=\"left\">1590.1</td><td align=\"left\">4.8</td><td align=\"left\">13</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">8</td><td align=\"left\">Assefa Washo Bankere et al. [##UREF##19##38##]</td><td align=\"left\">2022</td><td align=\"left\">Oromia</td><td align=\"left\">43</td><td align=\"left\">269</td><td align=\"left\">1,299</td><td align=\"left\">3.3</td><td align=\"left\">5</td><td align=\"left\">Good</td></tr><tr><td align=\"left\">9</td><td align=\"left\">Selam Fisiha Kassa et al. [##UREF##18##36##]</td><td align=\"left\">2020</td><td align=\"left\">Amhara</td><td align=\"left\">79</td><td align=\"left\">361</td><td align=\"left\">1280.8</td><td align=\"left\">6.2</td><td align=\"left\">11</td><td align=\"left\">Good</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Meta-regression using publication year and sample size for LTFU in Ethiopian children</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Logrr</th><th align=\"left\">Coefficient</th><th align=\"left\">Std. err</th><th align=\"left\">t</th><th align=\"left\">P &gt;|t|</th><th align=\"left\">[95% conf. interval]</th></tr></thead><tbody><tr><td align=\"left\">Sample size</td><td align=\"left\">0.01</td><td align=\"left\">0.01</td><td align=\"left\">0.84</td><td align=\"left\">0.43</td><td align=\"left\">-0.01 0.02</td></tr><tr><td align=\"left\">Publication year</td><td align=\"left\">0.04</td><td align=\"left\">0.27</td><td align=\"left\">0.15</td><td align=\"left\">0.88</td><td align=\"left\">-0.62 0.70</td></tr><tr><td align=\"left\">Constant</td><td align=\"left\">-83.52</td><td align=\"left\">545.71</td><td align=\"left\">-0.15</td><td align=\"left\">0.88</td><td align=\"left\">-1418.83 1251.78</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Heterogeneity check through conducting publication bias check</p></caption></table-wrap>" ]
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[ "<media xlink:href=\"12889_2023_17333_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1.</bold></p></caption></media>" ]
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KnE Life Sciences 2021:312\u201321."]}, {"label": ["20."], "surname": ["Mohammed", "Abdi", "Palani", "Joseph"], "given-names": ["A", "S", "S", "NM"], "article-title": ["Moderate incidence of lost follow-up and risk factors among adult HIV patients on second-line ART regimens in Amhara region hospitals, Ethiopia"], "source": ["J Drug Delivery Ther"], "year": ["2019"], "volume": ["9"], "issue": ["1\u2013s"], "fpage": ["52"], "lpage": ["59"], "pub-id": ["10.22270/jddt.v9i1-s.2253"]}, {"label": ["24."], "mixed-citation": ["Bantie B, Seid A, Kerebeh G, Alebel A, Dessie G. Loss to follow-up in test and treat era and its predictors among HIV-positive adults receiving ART in Northwest Ethiopia: Institution-based cohort study. Front Public Health 2022."]}, {"label": ["26."], "surname": ["Dessu", "Mesele", "Habte", "Dawit"], "given-names": ["S", "M", "A", "Z"], "article-title": ["Time until loss to follow-up, incidence, and predictors among adults taking ART at public hospitals in Southern Ethiopia"], "source": ["HIV/AIDS (Auckland NZ)"], "year": ["2021"], "volume": ["13"], "fpage": ["205"]}, {"label": ["29."], "surname": ["Wagner", "Furin", "Gripshover", "Jeenah", "Jonsson"], "given-names": ["T", "J", "B", "Y", "G"], "article-title": ["Loss to follow-up among a group of patients with HIV and severe mental illness in South Africa"], "source": ["World J AIDS"], "year": ["2014"], "volume": ["4"], "fpage": ["74"], "lpage": ["80"], "pub-id": ["10.4236/wja.2014.41009"]}, {"label": ["30."], "surname": ["Berheto", "Haile", "Mohammed"], "given-names": ["TM", "DB", "S"], "article-title": ["Predictors of loss to follow-up in patients living with HIV/AIDS after initiation of antiretroviral therapy"], "source": ["North Am J Med Sci"], "year": ["2014"], "volume": ["6"], "issue": ["9"], "fpage": ["453"], "pub-id": ["10.4103/1947-2714.141636"]}, {"label": ["31."], "mixed-citation": ["Nshimirimana C, Ndayizeye A, Smekens T, Vuylsteke B. Loss to follow-up of patients in HIV care in Burundi: a retrospective cohort study. Tropical Medicine and International Health; 2022."]}, {"label": ["33."], "surname": ["Menshw", "Birhanu", "Gebremaryam", "Yismaw", "Endalamaw"], "given-names": ["T", "S", "T", "W", "A"], "article-title": ["Incidence and predictors of loss to follow-up among children attending ART clinics in Northeast Ethiopia: a retrospective cohort study"], "source": ["HIV/AIDS-Res Palliative Care"], "year": ["2021"], "volume": ["13"], "fpage": ["801"], "lpage": ["812"], "pub-id": ["10.2147/HIV.S320601"]}, {"label": ["34."], "surname": ["Menshaw", "Birhanu", "Endalamaw", "G\u00e9bermaryam"], "given-names": ["T", "S", "A", "T"], "source": ["Incidence and predictors of lost to follow up among children attending ART clinic at Dessie Referral Hospital"], "year": ["2020"], "publisher-loc": ["Northeast Ethiopia"], "publisher-name": ["A Retrospective Cohort Study"]}, {"label": ["35."], "surname": ["Wubneh", "Belay", "Yehualashet", "Tebeje", "Mekonnen", "Endalamaw"], "given-names": ["CA", "GM", "FA", "NB", "BD", "A"], "article-title": ["Lost to follow-up and predictors among HIV-Exposed infants in Northwest Ethiopia"], "source": ["Infect Dis Therapy"], "year": ["2021"], "volume": ["10"], "issue": ["1"], "fpage": ["229"], "lpage": ["239"], "pub-id": ["10.1007/s40121-020-00360-z"]}, {"label": ["36."], "surname": ["Fisiha Kassa", "Zemene Worku", "Atalell", "Agegnehu"], "given-names": ["S", "W", "KA", "CD"], "article-title": ["Incidence of loss to follow-up and its predictors among children with HIV on antiretroviral therapy at the University of Gondar comprehensive specialized referral hospital: a retrospective data analysis"], "source": ["HIV/AIDS-Rese Palliative Care"], "year": ["2020"], "volume": ["12"], "fpage": ["525"], "lpage": ["533"], "pub-id": ["10.2147/HIV.S269580"]}, {"label": ["38."], "mixed-citation": ["Bankere AW, Gemechu BL, Ami B, Kebebe L, Gabisa S. 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{ "acronym": [ "AIDS", "HIV", "UNAIDS", "CLHIV", "LTFU", "ART" ], "definition": [ "Acquired immunodeficiency syndrome", "Human Immunodeficiency Virus", "United Nations Program on HIV/AIDS", "Children Living with Human Immunodeficiency Virus", "Loss to Follow-up", "Antiretroviral Therapy" ] }
45
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2024-01-14 23:43:47
BMC Public Health. 2024 Jan 13; 24:169
oa_package/e6/16/PMC10787475.tar.gz
PMC10787476
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Lumbar disc herniation (LDH) is a common and prevalent spinal disease with an increasing incidence, affecting 1–5% of the global population annually [##REF##34267943##1##]. Approximately 80% of Americans have been reported to experience at least one episode of LDH and subsequent low back pain in their lifetime [##REF##28980275##2##]. Conservative treatment is the first-choice approach for patients with LDH, but some patients need surgical intervention after conservative treatment to alleviate pain [##REF##36615124##3##]. With the popularization of the minimally invasive concept and the innovation in the design of surgical instruments, minimally invasive spine endoscopy has become the mainstream surgical technique for treating LDH due to its advantages, such as minimal trauma, rapid recovery, and shorter hospitalization [##REF##32013278##4##, ##REF##32683107##5##]. Currently, percutaneous endoscopic lumbar discectomy (PELD) is widely used in the clinical treatment of LDH and has achieved favourable clinical outcomes [##REF##32013278##4##]. PELD includes two different surgical approaches, namely percutaneous endoscopic transforaminal discectomy (PETD) and percutaneous endoscopic interlaminar discectomy (PEID), each with its own advantages in treating LDH [##REF##27454540##6##].</p>", "<p id=\"Par6\">Compared with PEID, PETD removes the herniated disc through the \"safety triangle\" of the intervertebral foramina without laminectomy and dural retraction, causing less damage to the spinal canal and the soft tissues of the lumbar spine [##REF##32190653##7##, ##UREF##0##8##]. Some researchers believe that PETD can more effectively relieve postoperative pain and reduce blood loss and hospital stay [##UREF##0##8##]. However, for L5–S1 disc herniation, PETD still faces significant technical challenges due to its challenging anatomical characteristics such as a high position of iliac crest, narrow intervertebral foramen, and facet hypertrophy [##REF##27454540##6##, ##REF##30710722##9##]. On the other hand, PEID benefits from a wider interlaminar space and easier localization; thus, some scholars believe that it is a better choice for treating L5–S1 disc herniation and may facilitate surgery and shorten operative time [##REF##33274579##10##]. Nevertheless, Yeung et al. [##REF##11923665##11##] demonstrated that PETD can be successfully used in treating disc herniation at all lumbar levels, including L5–S1. Therefore, it is still controversial which surgical approach yields better outcomes in the treatment of L5–S1 disc herniation. In this study, we retrospectively analysed the clinical outcomes of patients with L5–S1 disc herniation who underwent two different surgical approaches. Our findings illuminate their comparative clinical safety and efficacy and provide some clinical rationale for selecting surgical methods.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study design and patients</title>", "<p id=\"Par7\">This study was a single-centre retrospective cohort study approved by the Ethics Committee of the Sixth Medical Center of the PLA General Hospital (No. HZKY-PJ-2023–34). All patients provided written informed consent before treatment. From February 2016 to May 2020, 120 patients with L5–S1 disc herniation who underwent PEID or PETD were included in this study according to inclusion and exclusion criteria (Table ##TAB##0##1##). Among them, 63 patients underwent PEID, and 57 patients underwent PETD. Due to the inherent imbalances in covariates between the two groups, we adopted propensity score matching (PSM) (matching tolerance set at 0.02) to balance the influence of confounding factors when comparing clinical outcomes. The propensity score for each patient was calculated as the probability of accepting different surgical treatments, including all covariates considered clinically relevant and possibly affecting clinical outcomes. The following variables were used for PSM: (1) age; (2) body mass index (BMI); (3) gender; (4) disease duration; (5) smoking history; (6) medical history; (7) pathological classification; and (8) follow-up time.</p>", "<title>Surgical methods</title>", "<title>PEID approach</title>", "<p id=\"Par8\">Patients in the PEID group were placed in a prone position under basic combined local anaesthesia. The puncture point of the body surface projection of the responsible segment was identified under C-arm X-ray fluoroscopy, which was located 1–2 cm lateral to the midline. Then, a puncture needle was inserted and the tip landing point was confirmed to be positioned within the interlaminar space and adjacent to the medial margin of the facet joint. A 7–10 mm surgical incision was made, and a soft tissue dilator was used to expand the surgical access. Next, the working cannula was placed and the endoscopic system was installed. After the endoscopic resection of part of the superior lamina, inferior lamina, and ligamentum flavum, epidural fat, nerve roots, and dural sac were clearly exposed. The herniated disc was excised at the lateral shoulder or medial axilla of the nerve root according to the location of the herniated disc or the patient's reaction to the radicular pain during the operation. The nerve root was gently retracted using a nerve dissector to expose the herniated disc. Thereafter, the herniated disc was removed using disc forceps under endoscopic visualization, and the endoscope angle was adjusted to explore the nerve root and confirm complete removal. Decompression was considered successful if the nerve root tension decreased, no compressive tissue remained around the nerve, and the nerve root and dura sac showed autonomous pulsation. After completing decompression, the operative area was confirmed to have no active bleeding, and the endoscope and working cannula were removed. Representative cases are shown in Fig. ##FIG##0##1##.</p>", "<title>PETD approach</title>", "<p id=\"Par9\">Similar to PEID, patients in the PETD group were also placed in the prone position under the same protocol of anaesthesia. The responsible segment was identified using C-arm fluoroscopy, and the puncture point was located 12–15 cm lateral to the midline. The puncture needle was inserted at an angle of 15–25° to the horizontal plane. Its correct position was confirmed under fluoroscopy if: (1) the anteroposterior view showed that the needle tip intersected the inner margin of the vertebral pedicle and (2) the lateral view showed that the needle tip was located above the posterior margin of the intervertebral disc. Then, a 7–10 mm surgical incision was made, and a soft tissue dilator was used to expand the surgical access. If necessary, intraoperative foraminal enlargement with a ring saw was performed to remove part of the hypertrophic bone and facet joints. A working cannula was inserted, and the endoscopic system was installed. Under endoscopic visualization, the herniated disc was completely exposed, and the protruded material was removed using disc forceps. Thereafter, the endoscope was adjusted to explore and release the nerve root. After completing decompression, the operative area was observed to confirm the absence of active bleeding. Finally, the endoscope and working cannula were removed, followed by the closure of the working channel and skin suture. Representative cases are shown in Fig. ##FIG##1##2##.</p>", "<title>Data collection and measurements</title>", "<p id=\"Par10\">Baseline data and perioperative data of all successfully matched patients with L5–S1 disc herniation were collected. Perioperative data included operation time, frequency of fluoroscopy, intraoperative blood loss, hospital stay, and total incision length. Regular follow-up was conducted at 3 months, 6 months, 12 months postoperatively, and the last follow-up through phone calls and/or emails to record patients' clinical functional scores, imaging data, and incidence of complications.</p>", "<title>Clinical assessment</title>", "<p id=\"Par11\">Clinical functional scores were determined using self-assessment questionnaires, including visual analogue scale (VAS) for back and leg pain, Oswestry disability index (ODI), and modified MacNab criteria. Furthermore, we used minimal clinically important difference (MCID) to assess the clinical significance of changes in VAS and ODI. An MCID value of a change of 2 or greater for VAS and 13 or greater for ODI was considered clinically significant [##REF##18201937##12##, ##REF##34559749##13##]. At the last follow-up, patients’ satisfaction was assessed using the modified MacNab criteria as follows: excellent: complete disappearance of symptoms with the ability to resume original work and daily activities; good: mild symptoms with slight restriction of activities but no impact on work and daily life; fair: symptom relief with moderate restriction of activities and impact on normal work and daily life; poor: no improvement or even worsening of symptoms [##REF##32583556##14##]. The excellent and good rates were calculated as (excellent + good) / total number of cases *100%.</p>", "<title>Imaging measurements</title>", "<p id=\"Par12\">Patients in both groups underwent X-ray imaging of the lumbar spine in the lateral, flexion, and extension positions. In addition, magnetic resonance imaging (MRI) was performed. Imaging data were collected using Image Viewer or AnyPacs software installed on workstations in DICOM or JPG format. All imaging data were measured three times by three independent evaluators, and the average values were collected.<list list-type=\"order\"><list-item><p id=\"Par13\">Disc height index (DHI) was used to assess changes in disc height at different follow-up time points, as previously described [##REF##35427416##15##]. The anterior, middle, and posterior heights of the upper and lower vertebral bodies and discs were measured on lateral lumbar spine X-ray. DHI was calculated as the ratio of the sum of intervertebral disc heights to the sum of upper and lower vertebral body heights: DHI = 2(b1 + b2 + b3) / (a1 + a2 + a3 + c1 + c2 + c3) * 100% (Fig. ##FIG##2##3##A).</p></list-item><list-item><p id=\"Par14\">The ratio value of the greyscale (RVG) was measured based on the modified Schneiderman method to evaluate disc hydration [##REF##2954224##16##]. The MRI midsagittal T2-weighted images were imported into Photoshop software (Adobe Photoshop 2023 version), and the average grayscale value of the intervertebral disc and cerebrospinal fluid were measured at the same segment. RVG was calculated as the ratio of the average grayscale value of the intervertebral disc to the average grayscale value of cerebrospinal fluid: RVG = (average grayscale value of the intervertebral disc / average grayscale value of cerebrospinal fluid) * 100% (Fig. ##FIG##2##3##B).</p></list-item><list-item><p id=\"Par15\"> Range of motion (ROM) was measured on lumbar spine X-ray in hyperextension and flexion positions. The line connecting the inferior endplate of the superior vertebra to the superior endplate of the inferior vertebra formed an angle that was positive when measured posterior to the vertebra and negative when measured anterior to the vertebra. The difference between the angles in hyperextension and flexion was considered a segmental range of motion (ROM = angle in hyperextension position—angle in hyperflexion position) (Fig. ##FIG##2##3##C and D). Based on the theory proposed by Frymoyer et al. [##REF##3992349##17##], we concluded that lumbar instability exists in the L5–S1 segment at ROM &gt; 20°.</p></list-item></list></p>", "<title>Statistical analysis</title>", "<p id=\"Par16\">All statistical analyses were performed using SPSS version 25 (IBM SPSS Statistics for Windows, version 25.0. Armonk, NY: IBM Corp.). Student's <italic>t</italic>-test was used for continuous data that followed a normal distribution, and the results are expressed as mean ± SD. Within-group comparisons at different time points were analysed using repeated measures analysis of variance (ANOVA). The nonparametric test was used for data without normal distribution. To assess the balance between the two groups, we calculated standardized mean differences (SMD) [##REF##34559749##13##] to represent the intergroup balance of a given covariate. The SMD is not affected by sample size and compares the relative balance between variables [##REF##34559749##13##]. According to the Cohen's criteria, an SMD ≤ 0.2 for a covariate indicates a small difference [##REF##33264818##18##]. Categorical data were compared using the Chi-square test and are presented as frequency and percentage. A <italic>p </italic>value &lt; 0.05 showed statistically significant intergroup differences.</p>" ]
[ "<title>Results</title>", "<title>Baseline characteristics before and after PSM</title>", "<p id=\"Par17\">In total, 120 patients with L5–S1 disc herniation were included in this study, with 63 cases in the PEID group and 57 cases in the PETD group, based on the inclusion and exclusion criteria. The baseline characteristics of the two groups before PSM are shown in Table ##TAB##1##2##. Covariates with SMD ≤ 0.2 and <italic>P</italic> &gt; 0.05 were considered balanced and comparable between the two groups. However, we observed three covariates unbalanced between the two groups in Table ##TAB##1##2##, including age (SMD = 0.285, <italic>P</italic> = 0.120), disease duration (SMD = 0.542, <italic>P</italic> = 0.003), and follow-up time (SMD = 0.239, <italic>P</italic> = 0.212). After PSM, 78 patients with L5–S1 disc herniation were included in this study., The baseline characteristics of the two groups are shown in Table ##TAB##2##3##, indicating that all covariates between the two groups were balanced and comparable.</p>", "<title>Perioperative data</title>", "<p id=\"Par18\">All patients underwent surgery by the same team of surgeons. In the PEID group, the average operation time was 65.23 ± 4.95 min, frequency of fluoroscopy was 2.97 ± 0.63, intraoperative blood loss was 35.13 ± 5.42 mL, hospital stay was 6.33 ± 0.96 days, and total incision length was 8.60 ± 0.79 mm. In the PETD group, the average operation time was 85.31 ± 6.30 min, frequency of fluoroscopy was 11.38 ± 1.09, intraoperative blood loss was 36.10 ± 4.52 mL, hospital stay was 6.23 ± 0.87 days, and total incision length was 8.64 ± 0.81 mm. The PEID group had significantly shorter operation time and frequency of fluoroscopy compared with the PETD group (<italic>P</italic> &lt; 0.001). However, there were no statistically significant differences between the two groups in terms of intraoperative blood loss, postoperative hospital stay, and total incision length (<italic>P</italic> &gt; 0.05) (Table ##TAB##3##4##).</p>", "<title>Clinical assessment</title>", "<p id=\"Par19\">The mean VAS scores for low back pain in the PEID and PETD groups decreased from 4.21 ± 0.89 and 4.28 ± 0.86 before the operation (<italic>P</italic> = 0.820) to 2.79 ± 0.98 and 2.62 ± 1.04 at 3 months postoperatively (<italic>P</italic> = 0.524), 1.90 ± 1.07 and 1.74 ± 0.99 at 6 months postoperatively (<italic>P</italic> = 0.644), 1.07 ± 1.01 and 0.92 ± 0.90 at 12 months postoperatively (<italic>P</italic> = 0.555), and 0.79 ± 0.92 and 0.67 ± 0.81 at the last follow-up (<italic>P</italic> = 0.610), respectively. Additionally, the mean VAS scores for lower limb pain in the PEID and PETD groups decreased from 6.44 ± 0.99 and 6.67 ± 0.93 before the operation (<italic>P</italic> = 0.315) to 3.59 ± 0.81 and 3.74 ± 0.88 at 3 months postoperatively (<italic>P</italic> = 0.402), 2.59 ± 0.85 and 2.72 ± 0.89 at 6 months postoperatively (<italic>P</italic> = 0.578), 1.87 ± 1.13 and 1.77 ± 0.84 at 12 months postoperatively (<italic>P</italic> = 0.854), and 1.41 ± 1.02 and 1.28 ± 0.89 at the last follow-up (<italic>P</italic> = 0.570), respectively. There were no statistically significant differences in VAS scores for low back pain and lower limbs pain between the two groups. Compared with before the surgery, both groups demonstrated significant improvement in VAS scores after the surgery (<italic>P</italic> &lt; 0.001), and the improvement met the clinical significance criteria for MCID (Fig. ##FIG##3##4##A, B).</p>", "<p id=\"Par20\">The mean ODI scores in the PEID and PETD groups decreased from 49.28 ± 9.36 and 51.33 ± 9.31 before the operation (<italic>P</italic> = 0.335) to 28.92 ± 7.41 and 30.26 ± 6.87 at 3 months postoperatively (<italic>P</italic> = 0.413), 20.36 ± 5.21 and 20.97 ± 5.71 at 6 months postoperatively (<italic>P</italic> = 0.620), 15.79 ± 5.44 and 14.15 ± 5.81 at 12 months postoperatively (<italic>P</italic> = 0.202), and 10.36 ± 6.49 and 8.87 ± 6.01 at the last follow-up (<italic>P</italic> = 0.297), respectively. The difference in ODI between the two groups was not statistically significant. Compared with those before the operation, the postoperative ODI significantly improved (<italic>P</italic> &lt; 0.001) in both groups, which also met the clinical significance criteria for MCID (Fig. ##FIG##3##4##C).</p>", "<p id=\"Par21\">At the last follow-up, according to the modified MacNab criteria, 25 cases were rated as excellent, 11 cases as good, 3 cases as fair, and 0 cases as poor in the PEID group, with an excellent and good rate of 92.30%. In the PETD group, 23 cases were rated as excellent, 12 cases as good, 3 cases as fair, and 1 case as poor, with an excellent and good rate of 89.74%. There was no significant difference in the excellent and good rates between the two groups (<italic>P</italic> = 0.771) (Table ##TAB##4##5##).</p>", "<p id=\"Par22\">During the follow-up period, 4 patients experienced complications with a complication rate of 5.13%. Two patients in the PEID group and one patient in the PETD group experienced worsening of lower limb neurological symptoms postoperatively. In the PETD group, one patient experienced the recurrence of LDH after surgery. However, there was no significant difference in the complication rates between the two groups (<italic>P</italic> = 1.000) (Table ##TAB##4##5##). No serious complications such as dural tear or disc space infection, were detected among all patients.</p>", "<title>Image measurement</title>", "<p id=\"Par23\">In both groups, the average DHI of the responsible segments showed a decreasing trend (Fig. ##FIG##4##5##A). The mean DHI in the PEID and PETD groups decreased from (35.08 ± 2.74)% and (34.79 ± 2.77)% before the operation (<italic>P</italic> = 0.646) to (35.01 ± 2.67)% and (34.73 ± 2.75)% 3 months postoperatively (<italic>P</italic> = 0.642), (34.90 ± 2.55)% and (34.60 ± 2.69)% 6 months postoperatively (<italic>P</italic> = 0.619), (33.85 ± 2.44)% and (33.66 ± 2.56)% 12 months postoperatively (<italic>P</italic> = 0.741), and (32.24 ± 2.31)% and (32.40 ± 2.51)% at last follow-up (<italic>P</italic> = 0.770), respectively. There was no statistically significant difference in DHI between the two groups. However, the difference in DHI at 12 months postoperatively and at the last follow-up was statistically significant when compared with the preoperative period (<italic>P</italic> &lt; 0.001) (Fig. ##FIG##4##5##A).</p>", "<p id=\"Par24\">The mean RVG values in the PEID and PETD groups decreased from (32.81 ± 2.78)% and (33.15 ± 2.72)% before the operation (<italic>P</italic> = 0.590) to (32.73 ± 2.76)% and (33.07 ± 2.64)% 3 months postoperatively (<italic>P</italic> = 0.579), (32.65 ± 2.70)% and (32.99 ± 2.59)% 6 months postoperatively (<italic>P</italic> = 0.565), (32.00 ± 2.55)% and (32.41 ± 2.46)% 12 months postoperatively (<italic>P</italic> = 0.477), and (30.23 ± 2.51)% and (30.67 ± 2.41)% at last follow-up (<italic>P</italic> = 0.432), respectively. The trends in RVG values were similar between the two groups, with no statistically significant difference. Compared with baseline, RVG values showed a statistically significant difference at 12 months postoperatively and at the last follow-up (<italic>P</italic> &lt; 0.001) (Fig. ##FIG##4##5##B).</p>", "<p id=\"Par25\">The mean ROM values in the PEID and PETD groups were (8.07 ± 0.46)° and (8.17 ± 0.49)° before the operation (<italic>P</italic> = 0.347), (8.32 ± 0.45)° and (8.47 ± 0.48)° at 3 months postoperatively (<italic>P</italic> = 0.150), (8.28 ± 0.44)° and (8.42 ± 0.45)° at 6 months postoperatively (<italic>P</italic> = 0.174), (8.17 ± 0.40)° and (8.31 ± 0.42)° at 12 months postoperatively (<italic>P</italic> = 0.155), and (8.04 ± 0.36)° and (8.15 ± 0.38)° at the last follow-up (<italic>P</italic> = 0.186), respectively. There was no statistically significant difference in ROM values between the two groups. The ROM values increased after surgery in both groups, but the ROM values were all less than 20°, indicating no cases of lumbar instability in either group (Fig. ##FIG##4##5##C).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par26\">LDH is a chronic progressive disease that clinically presents with low back pain, radicular symptoms in the lower limbs, and sensory disturbances in the corresponding dermatomes [##UREF##1##19##]. Surgical intervention is required for patients with LDH who do not respond to conservative treatment. [##REF##36615124##3##, ##REF##30543041##20##]. Traditional open surgery is a classic approach for treating LDH but necessitates it involves extensive dissection of the paraspinal muscles and wide removal of the lamina, and facet joints, which can lead to postoperative complications such as refractory low back pain, muscle denervation, and lumbar instability [##REF##32190653##7##, ##REF##35279101##21##]. With the advancement of endoscopy techniques, several studies have shown that endoscopic treatment of LDH can achieve similar clinical outcomes as open surgery, with advantages such as less trauma, faster recovery, and fewer complications [##REF##32013278##4##, ##REF##32683107##5##]. Currently, PEID and PETD are widely used in the treatment of patients with LDH, with specific clinical characteristics [##REF##29783008##22##]. However, for L5–S1 disc herniation, the specific advantages and disadvantages of these two different surgical approaches are still unclear due to their unique anatomical characteristics.</p>", "<p id=\"Par27\">During the endoscopic treatment of L5–S1 disc herniation, the presence of the high iliac crest and a narrow intervertebral foramen can hinder the entry of the working cannula, and the hyperplastic facet joints can also obstruct the protruding disc [##REF##27454540##6##]. The lateral approach has a limited perforation angle, necessitating excessive intraoperative removal of facet joints that compromise the biomechanical stability of the spine. These limitations increase the difficulty of intraoperative accurate puncture positioning and adequate surgical decompression for PETD, necessitate repeated fluoroscopy, and increase radiation exposure for both patients and spine surgeons [##REF##30710722##9##]. Excessive X-ray exposure is a serious concern and can have significant health implications for medical personnel in the long term [##REF##23026867##23##]. In addition, due to the obstruction caused by the superior margin of the iliac crest and the narrow intervertebral foramen, the operating space during PETD is insufficient, which may lead to incomplete removal of the protruding disc in the far region. The residual disc tissue increases the risk of recurrent disc herniation, which can seriously affect the treatment outcome [##REF##27454540##6##]. Therefore, it is usually recommended to remove the L5–S1 disc through a wide interlaminar space during PEID. In the L5–S1 segment, the sacral one nerve root originating from the dural sac is positioned high in the plane of the intervertebral spaces, The herniated disc tissue can be removed intraoperatively from the shoulder or axilla of the nerve root according to the actual situation, which is easier and safer in this segment than in other segments. However, PEID necessitates the removal of the ligamentum flavum and a part of the lamina, which may interfere with the dural sac and increase the risk of injury to the dural sac or cauda equina [##REF##33821557##24##]. Therefore, caution is needed during PEID to reduce the incidence of postoperative complications.</p>", "<p id=\"Par28\">In our study, we observed that both PEID and PETD for L5–S1 disc herniation showed no significant difference in clinical functional scores and imaging. VAS scores for back and leg pain and ODI index of all patients significantly improved after the surgery, meeting the criteria for MCID. Therefore, both minimally invasive surgical techniques are safe and effective treatments for L5–S1 disc herniation, leading to favourable clinical outcomes. However, despite similar clinical outcomes of the two surgical approaches, they still have distinct characteristics in treating L5–S1 herniated discs. We found that the PEID group had significantly shorter operation time and lower frequency of fluoroscopy than the PETD group, suggesting the superiority of PEID over PETD in reducing surgical time and radiation exposure. The advantages of PEID may be related to several factors: (i) PEID uses an interlaminar approach, which is familiar to most spine surgeons and easier compared with PETD; (ii) PEID is not technically limited by the obstruction of the high iliac crest and narrow intervertebral foramen, allowing rapid and precise puncture positioning, and easy targeting of the L5–S1 herniated disc within a wide interlaminar space; (iii) PEID provides a spacious operating space, allowing better mobility of the working cannula for complete removal of the protruding disc; and (iv) PEID directly visualizes the protruded or extruded disc under endoscopy, enabling full decompression of central and paracentral disc herniation [##REF##27454540##6##].</p>", "<p id=\"Par29\">Although PETD for L5–S1 disc herniation is more challenging and requires higher proficiency of spine surgeons, it has its advantages and indications. PETD demands entering the spinal canal through a physiologically formed safe triangle of the intervertebral foramen, avoiding the blockade of the dural sac and nerve root traction during the surgery. Thus, PETD can reduce the incidence of complications, such as dural tear and nerve root injury. Besides, PETD is a better choice for patients with recurrent LDH as it can effectively avoid the influence of scar tissue from previous surgeries through the intervertebral foramen approach [##REF##33274579##10##]. PETD can treat almost all types of L5–S1 disc herniations, including central, paracentral, foraminal, and far lateral types. However, giant herniated discs are relative contraindications for PETD, primarily due to limited surgical space caused by the obstruction of the superior margin of the iliac crest and the narrow intervertebral foramen, which can lead to inadequate decompression of the herniated disc. On the other hand, PEID has advantages for central, paracentral, and freely isolated types of disc herniations since it is not limited by the iliac crest blockade and offers advantages such as rapid puncture positioning, shorter operation time, and lower frequency of fluoroscopy.</p>", "<p id=\"Par30\">In our study, all patients were successfully operated under endoscopy without any severe complications, such as dural tears or disc space infections. Four patients experienced postoperative complications. Two patients in the PEID group and one patient in the PETD group suffered from aggravating radicular symptoms within three days after surgery. The symptoms of patients improved by nerve nutrition, hormone therapy, and rehabilitation. One patient in the PETD group experienced LDH recurrence at 12 months postoperatively, and the symptoms improved after conservative treatment. There was no statistically significant difference in the incidence of complications between the two groups (<italic>P</italic> &gt; 0.05). In addition, the results of imaging revealed that the mobility of the responsible segment increased postoperatively compared with before surgery, implying that we should attempt to damage as little as possible of the original lumbar spine when decompressing the disc. Previous studies have shown that loss of structures such as facet joints, and intervertebral discs, can all affect lumbar spine biomechanics [##REF##32643308##25##, ##REF##35124438##26##]. In our study, both PETD and PEID were performed without intraoperative resection of the high-weight-bearing area of facet joints, which had less impact on segmental stability. After recovery from surgical trauma and lumbar functional exercises, the mobility of the responsible segment was restored, and no patient experienced segmental instability during follow-up. However, whether postoperative disc degeneration and decreased disc height affect patients' surgical prognosis needs further studies.</p>", "<p id=\"Par31\">In summary, both PEID and PETD for L5–S1 disc herniation can achieve favourable clinical outcomes. However, PEID has advantages over PETD, with reduced operation time and fluoroscopy exposure. There are some limitations to the current study. First, it was a retrospective study, and we could not completely eliminate subjective factors in case selection during the study period. We also could not achieve random grouping. Although we used PSM to minimize confounding factors, some biases might still exist. Second, although the results of imaging were averaged after 3 measurements by 3 independent reviewers, measurement error might still exist. Thirdly, the sample size was relatively small, the follow-up period was short, and it was a single-centre study, which might influence the results.</p>" ]
[]
[ "<title>Objective</title>", "<p id=\"Par1\">Percutaneous endoscopic lumbar discectomy (PELD) is a safe and effective minimally invasive surgery for treating lumbar disc herniation (LDH); however, the comparative clinical efficacy of percutaneous endoscopic transforaminal discectomy (PETD) and percutaneous endoscopic interlaminar discectomy (PEID) in treating L5–S1 LDH remains unclear. This study compared the clinical advantages of PEID and PETD for treating L5–S1 LDH.</p>", "<title>Methods</title>", "<p id=\"Par2\">This was a single-centre retrospective study analysing clinical data from 120 patients with L5–S1 LDH between February 2016 and May 2020. Propensity score matching (PSM) was used to adjust for imbalanced confounding variables between the two groups. Perioperative data were recorded, and clinical outcomes, including functional scores and imaging data, were compared between groups. Functional scores included visual analogue scale (VAS) for back and leg pain, Oswestry disability index (ODI), and modified MacNab criteria. Imaging data included disc height index (DHI), ratio of greyscale (RVG), and range of motion (ROM) of the responsible segment.</p>", "<title>Results</title>", "<p id=\"Par3\">After PSM, 78 patients were included in the study, and all covariates were well balanced between the two groups. In the matched patients, the PEID group showed significantly shorter surgical time (65.41 ± 5.05 vs. 84.08 ± 5.12 min) and lower frequency of fluoroscopy (2.93 ± 0.63 vs. 11.56 ± 1.54) compared with the PETD group (<italic>P</italic> &lt; 0.001). There were no statistically significant differences in intraoperative blood loss, postoperative hospital stay, total incision length, and incidence of complications between the two groups (<italic>P</italic> &gt; 0.05). After surgery, both groups showed significant improvement in back and leg pain based on VAS and ODI scores (<italic>P</italic> &lt; 0.05). There were no statistically significant differences in clinical functional scores and imaging data between the two groups at various time points after surgery (<italic>P</italic> &gt; 0.05). According to the modified MacNab criteria, the excellent and good rates in the PEID group and PETD group were 91.89% and 89.19%, respectively, with no statistically significant difference (<italic>P</italic> &gt; 0.05).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">PEID and PETD have similar clinical efficacy in treating L5–S1 disc herniation. However, PEID is superior to PETD in reducing operation time and frequency of fluoroscopy.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>The authors acknowledge the Imaging Department and Operation Department of the Sixth Medical Center of PLA General Hospital, for their technical support and expertise in the radiological assessments. Meanwhile, the authors would like to express their gratitude to EditSprings (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.editsprings.cn\">https://www.editsprings.cn</ext-link> ) for the expert linguistic services provided.</p>", "<title>Author contributions</title>", "<p>T.L. and Y.D., principal investigator, contributed to the study design, data collection, and manuscript writing; G.N. was involved in the data collection and manuscript review; W.Z. contributed to the data analysis; J.L. and Z.D. assisted in the manuscript review. All authors have read, revised, and approved the submitted manuscript.</p>", "<title>Funding</title>", "<p>This project is supported by Research and Demonstration application of Clinical Diagnosis and Treatment Technology in Beijing (Z191100006619028).</p>", "<title>Availability of data and materials</title>", "<p>The datasets used during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par32\">Ethics committee approval was given by the Committee of the Sixth Medical Center of the PLA General Hospital (HZKY-PJ-2023–34).</p>", "<title>Competing interests</title>", "<p id=\"Par33\">The authors declared no conflicts of interest.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Images from a patient treated with PEID. <bold>A</bold> and <bold>B</bold> Preoperative MRI showed L5–S1 disc herniation. <bold>C</bold> and <bold>D</bold> The position of the working cannula through the inter lamina approach during the operation. <bold>E</bold> Intraoperative grinding drill for laminoplasty. <bold>F</bold> Endoscopic demonstration of disc herniation with nerve root compression. <bold>G</bold> Nerve root decompression. <bold>H</bold> and <bold>I</bold> Postoperative MRI showed that the L5–S1 herniated intervertebral disc has been removed</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Images from a patient treated with PETD. <bold>A</bold> and <bold>B</bold> Preoperative MRI showed L5–S1 disc herniation. <bold>C</bold> and <bold>D</bold> The position of the working cannula through the inter lamina approach during the operation. <bold>E</bold> Intraoperative ring sawing to remove part of facet joints.<bold> F</bold> Removal of herniated disc tissue. <bold>G</bold> to <bold>I</bold> Postoperative MRI and CT showed that the L5–S1 herniated intervertebral disc has been removed</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Schematic of imaging measurements. <bold>A</bold> Disc height index (DHI), DHI = [2(b1 + b2 + b3)] / [(a1 + a2 + a2) + (c1 + c2 + c3)] *100%. <bold>B</bold> Ratio value of the greyscale (RVG). Midsagittal T2-weighted images were chosen, and RVG was the greyscale of discs a normalized against the greyscale of cerebrospinal fluid at the same level b. <bold>C</bold> and <bold>D</bold> Schematic diagram of the range of motion (ROM). <bold>C</bold> the segmental angle in hyperextension position (14.16°). <bold>D</bold> the segmental angle in hyperflexion position (6.31°); the range of motion of the segment (ROM = 14.16 − 6.31° = 7.85°)</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Results of clinical efficacy of functional scores. <bold>A</bold> Changes in VAS scores for low back pain over time. <bold>B</bold> Changes in VAS scores for lower limbs pain over time. <bold>C</bold> Changes in ODI over time. <italic>VAS</italic> visual analogue scale, <italic>ODI</italic> Oswestry disability index. a<bold>–</bold>e indicate the letter labelling of the time point difference (comparison within the group), if 2 time points have the same letter, there is no significant difference between the 2 time points (<italic>P</italic> &gt; 0.05); otherwise, different letters at 2-time points mean the difference is significant (<italic>P</italic> ≤ 0.05)</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Results of imaging measurement. <bold>A</bold> Changes in DHI during the follow-up.<bold> B</bold> Changes in RVG during the follow-up. <bold>C</bold> Changes in ROM during the follow-up. DHI, Disc Height Index; RVG, the ratio value of the greyscale; ROM, the range of motion; a-d indicate the letter labelling of the time point difference (comparison within the group); if two time points have the same letter, there is no significant difference between the two time points (<italic>P</italic> &gt; 0.05); otherwise, different letters at 2-time points mean the difference is significant (<italic>P</italic> ≤ 0.05)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Inclusion and exclusion criteria</p></caption><table frame=\"hsides\" rules=\"groups\"><tbody><tr><td align=\"left\">Inclusion criteria</td><td align=\"left\"><p>Central, paracentral, or prolapsed L5–S1 disc herniation</p><p>Symptoms of low back pain and leg pain</p><p>Failure of formal conservative treatment</p></td></tr><tr><td align=\"left\">Exclusion criteria</td><td align=\"left\"><p>Lumbar instability, such as lumbar spondylolisthesis</p><p>Intervertebral disc inflammation or tuberculosis</p><p>Severe lumbar stenosis, and far lateral disc herniation</p><p>Previous surgery at the lumbar spine</p><p>Multiple segments of disc herniation</p><p>Recurrent disc herniation</p><p>Pregnant or syndrome of cauda equina</p><p>Severe cardiac disease, active neoplasm, anaemia, or any other surgical contraindications</p></td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Baseline characteristics before propensity score matching</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Demographics</th><th align=\"left\">PEID group<break/>(<italic>n</italic> = 63)</th><th align=\"left\">PETD group (<italic>n</italic> = 57)</th><th align=\"left\">SMD</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"left\">41.76 ± 11.00</td><td align=\"left\">44.84 ± 10.47</td><td char=\".\" align=\"char\"><bold>0.285</bold></td><td char=\".\" align=\"char\">0.120</td></tr><tr><td align=\"left\">BMI (kg/m<sup>2</sup>)</td><td align=\"left\">24.84 ± 3.10</td><td align=\"left\">24.81 ± 3.03</td><td char=\".\" align=\"char\">0.010</td><td char=\".\" align=\"char\">0.959</td></tr><tr><td align=\"left\">Gender, <italic>n</italic> (%)</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.007</td><td char=\".\" align=\"char\">0.970</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">40 (63.49)</td><td align=\"left\">36 (63.16)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Female</td><td align=\"left\">23 (36.51)</td><td align=\"left\">21 (36.84)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Medical history, <italic>n</italic> (%)</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Hypertension</td><td align=\"left\">32 (50.79)</td><td align=\"left\">30 (52.63)</td><td char=\".\" align=\"char\">0.037</td><td char=\".\" align=\"char\">0.841</td></tr><tr><td align=\"left\">Diabetes</td><td align=\"left\">27 (42.86)</td><td align=\"left\">25 (43.86)</td><td char=\".\" align=\"char\">0.020</td><td char=\".\" align=\"char\">0.912</td></tr><tr><td align=\"left\">Pathological classification, <italic>n</italic> (%)</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.038</td><td char=\".\" align=\"char\">0.823</td></tr><tr><td align=\"left\">Central</td><td align=\"left\">9 (14.29)</td><td align=\"left\">6 (10.53)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Paracentral</td><td align=\"left\">31 (49.21)</td><td align=\"left\">29 (50.88)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Prolapsus</td><td align=\"left\">23 (36.51)</td><td align=\"left\">22 (38.60)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Disease duration (months)</td><td align=\"left\">23.22 ± 5.00</td><td align=\"left\">26.12 ± 5.35</td><td char=\".\" align=\"char\"><bold>0.542</bold></td><td char=\".\" align=\"char\"><bold>0.003</bold></td></tr><tr><td align=\"left\">Smoking, <italic>n</italic> (%)</td><td align=\"left\">29 (46.03)</td><td align=\"left\">26 (45.61)</td><td char=\".\" align=\"char\">0.008</td><td char=\".\" align=\"char\">0.963</td></tr><tr><td align=\"left\">Follow-up time</td><td align=\"left\">25.57 ± 1.50</td><td align=\"left\">25.93 ± 1.51</td><td char=\".\" align=\"char\"><bold>0.239</bold></td><td char=\".\" align=\"char\">0.212</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Baseline characteristics after propensity score matching</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Demographics</th><th align=\"left\">PEID group (<italic>n</italic> = 39)</th><th align=\"left\">PETD group (<italic>n</italic> = 39)</th><th align=\"left\">SMD</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"left\">45.05 ± 10.07</td><td align=\"left\">44.51 ± 10.69</td><td char=\".\" align=\"char\">0.052</td><td char=\".\" align=\"char\">0.819</td></tr><tr><td align=\"left\">BMI (kg/m<sup>2</sup>)</td><td align=\"left\">24.69 ± 2.99</td><td align=\"left\">24.81 ± 2.90</td><td char=\".\" align=\"char\">0.041</td><td char=\".\" align=\"char\">0.867</td></tr><tr><td align=\"left\">Gender, <italic>n</italic> (%)</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.055</td><td char=\".\" align=\"char\">0.808</td></tr><tr><td align=\"left\">Male</td><td align=\"left\">27 (69.23)</td><td align=\"left\">26 (66.67)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Female</td><td align=\"left\">12 (30.77)</td><td align=\"left\">13 (33.33)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Medical history, <italic>n</italic> (%)</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Hypertension</td><td align=\"left\">19 (48.72)</td><td align=\"left\">20 (51.28)</td><td char=\".\" align=\"char\">0.051</td><td char=\".\" align=\"char\">0.829</td></tr><tr><td align=\"left\">Diabetes</td><td align=\"left\">19 (48.72)</td><td align=\"left\">19 (48.72)</td><td char=\".\" align=\"char\">0.000</td><td char=\".\" align=\"char\">1.000</td></tr><tr><td align=\"left\">Pathological classification, <italic>n</italic> (%)</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.114</td><td char=\".\" align=\"char\">0.624</td></tr><tr><td align=\"left\">Central</td><td align=\"left\">5 (12.82)</td><td align=\"left\">5 (12.82)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Paracentral</td><td align=\"left\">16 (41.03)</td><td align=\"left\">20 (51.28)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Prolapsus</td><td align=\"left\">18 (46.15)</td><td align=\"left\">14 (35.90)</td><td char=\".\" align=\"char\"/><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Disease duration (months)</td><td align=\"left\">24.97 ± 4.15</td><td align=\"left\">25.36 ± 5.78</td><td char=\".\" align=\"char\">0.078</td><td char=\".\" align=\"char\">0.629</td></tr><tr><td align=\"left\">Smoking, <italic>n</italic> (%)</td><td align=\"left\">21 (53.85)</td><td align=\"left\">21 (53.85)</td><td char=\".\" align=\"char\">0.000</td><td char=\".\" align=\"char\">1.000</td></tr><tr><td align=\"left\">Follow-up time</td><td align=\"left\">25.59 ± 1.48</td><td align=\"left\">25.67 ± 1.51</td><td char=\".\" align=\"char\">0.054</td><td char=\".\" align=\"char\">0.848</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Comparison of perioperative data between the two groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">PEID group (<italic>n</italic> = 39)</th><th align=\"left\">PETD group (<italic>n</italic> = 39)</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\">Operative time (min)</td><td char=\".\" align=\"char\">65.23 ± 4.95</td><td char=\".\" align=\"char\">85.31 ± 6.30</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Fluoroscopy times</td><td char=\".\" align=\"char\">2.97 ± 0.63</td><td char=\".\" align=\"char\">11.38 ± 1.09</td><td char=\".\" align=\"char\"> &lt; 0.001</td></tr><tr><td align=\"left\">Intraoperative blood loss (ml)</td><td char=\".\" align=\"char\">35.13 ± 5.42</td><td char=\".\" align=\"char\">34.10 ± 4.52</td><td char=\".\" align=\"char\">0.367</td></tr><tr><td align=\"left\">Hospital stay (<italic>d</italic>)</td><td char=\".\" align=\"char\">6.33 ± 0.96</td><td char=\".\" align=\"char\">6.10 ± 0.75</td><td char=\".\" align=\"char\">0.255</td></tr><tr><td align=\"left\">Total length of incision (cm)</td><td char=\".\" align=\"char\">8.60 ± 0.79</td><td char=\".\" align=\"char\">8.46 ± 0.88</td><td char=\".\" align=\"char\">0.539</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Comparison of MacNab evaluation and complications between the two groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">PEID group (<italic>n</italic> = 39)</th><th align=\"left\">PETD group (<italic>n</italic> = 39)</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\">MacNab evaluation</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.771</td></tr><tr><td align=\"left\">Excellence</td><td align=\"left\">25</td><td align=\"left\">23</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Good</td><td align=\"left\">11</td><td align=\"left\">12</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Fair</td><td align=\"left\">3</td><td align=\"left\">3</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Poor</td><td align=\"left\">0</td><td align=\"left\">1</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Excellence/good rate</td><td align=\"left\">92.30%</td><td align=\"left\">89.74%</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Complications</td><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">1.000</td></tr><tr><td align=\"left\">Low back pain or lower limbs pain</td><td align=\"left\">2</td><td align=\"left\">1</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Recurrent disc herniation</td><td align=\"left\">0</td><td align=\"left\">1</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Dural sac tear</td><td align=\"left\">0</td><td align=\"left\">0</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">Disc space infection</td><td align=\"left\">0</td><td align=\"left\">0</td><td char=\".\" align=\"char\"/></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>Bolding is to indicate SMD &gt; 0.2 or P ≤ 0.05, which means that the corresponding confounders are not balanced between the two groups</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["8."], "surname": ["Chen", "Hu", "Li"], "given-names": ["P", "Y", "Z"], "article-title": ["Percutaneous endoscopic transforaminal discectomy precedes interlaminar discectomy in the efficacy and safety for lumbar disc herniation"], "source": ["Bioscience Rep"], "year": ["2019"], "volume": ["39"], "fpage": ["1"], "pub-id": ["10.1042/BSR20181866"]}, {"label": ["19."], "surname": ["Hasvik", "Haugen", "Grovle"], "given-names": ["E", "AJ", "L"], "article-title": ["Symptom descriptors and patterns in lumbar radicular pain caused by disc herniation: a 1-year longitudinal cohort study"], "source": ["BMJ Open"], "year": ["2022"], "volume": ["12"], "fpage": ["e65500"], "pub-id": ["10.1136/bmjopen-2022-065500"]}]
{ "acronym": [], "definition": [] }
26
CC BY
no
2024-01-14 23:43:47
J Orthop Surg Res. 2024 Jan 13; 19:64
oa_package/f8/d8/PMC10787476.tar.gz
PMC10787477
0
[ "<title>Introduction</title>", "<p id=\"Par4\">Cytochrome P450 monooxygenases (CYP450s), named after the absorption band at 450 nm exhibited by their carbon-monoxide-bound form [##UREF##0##1##], are a ubiquitous class of enzymes found in various organisms, including bacteria, plants, and humans [##UREF##1##2##]. The discovery of the first <italic>CYP450</italic> gene occurred in rat liver microsomes [##REF##12464237##3##, ##UREF##2##4##]. Subsequently, the X-ray crystal structure of CYP450 was obtained from bacterial CYP450cam [##REF##4066706##5##]. As more <italic>CYP450</italic> genes were identified, the subfamily of <italic>CYP450</italic> genes expanded [##UREF##3##6##–##UREF##4##8##]. The <italic>CYP450</italic> family is present in a wide range of organisms, including plants, insects, animals, fungi, bacteria, and viruses [##REF##19951895##9##]. Numerous <italic>CYP450</italic> genes, including approximately 16,000 in plants, have been identified across different organisms [##UREF##5##10##]. Gene structure analysis shows that members of this family all contain a conserved heme-binding domain with a sequence of FxxGxRxCxG [##UREF##6##11##]. Additional conserved domains are also present in CYP450 proteins. One such domain is the I-helix, which plays a role in both oxygen binding and catalysis on the distal side of the heme group. The sequence of the I-helix is characterized by the presence of A/G-X-E/D-T-T/S residues [##UREF##7##12##]. Furthermore, the PERF domain contains an arginine residue, while the K-helix consists of glutamate and arginine residues, forming the E-R-R triad. This triad is responsible for stabilizing the core structure of CYP450 enzymes [##UREF##8##13##]. Based on evolutionary relationships, plant CYP450s are divided into 11 families, with the smallest family number within each clan serving as its name [##REF##21443632##14##]. The <italic>CYP450</italic> genes in plants can generally be divided into A-type and non-A-type. Among them, <italic>CYP71</italic> is A type, and other families are non-A type [##UREF##9##15##]. A considerable number of CYP450 proteins are involved in the biosynthesis and breakdown of diverse substances, encompassing plant hormones, secondary metabolites, and defense compounds [##UREF##7##12##]. Within this context, several <italic>CYP450</italic> families, including <italic>CYP71</italic>, <italic>CYP85</italic>, and <italic>CYP72</italic>, are responsible for conducting oxidation and rearrangement reactions that contribute to the biosynthesis of diterpenes. These diterpenes serve as essential components in the production of hormones, pharmaceuticals, aroma compounds, and food ingredients [##REF##30733060##16##].</p>", "<p id=\"Par5\">In <italic>Arabidopsis</italic>, the <italic>CYP450</italic> family ranks as the third-largest gene family and plays crucial roles in the synthesis of antioxidants, phytohormones, structural polymers, and defense-related compounds [##UREF##10##17##–##UREF##13##25##]. <italic>AtCYP88A3</italic> and <italic>AtCYP88A4</italic> play a role in gibberellin biosynthesis, and mutations in <italic>CYP88</italic> lead to a dwarf phenotype in barley and maize [##UREF##7##12##]. Recent studies have focused on <italic>CYP450</italic> genes involved in stress resistance and secondary metabolism, such as the gossypol biosynthesis pathway in cotton [##REF##31932723##26##–##REF##32671865##29##]. Additionally, <italic>CYP450</italic> genes have been implicated in drought tolerance, exemplified by <italic>CYP86A2</italic> in Arabidopsis and <italic>CsCYP75B1</italic> in citrus [##UREF##16##30##, ##REF##15241470##31##]. Cold stress can also induce the expression of <italic>CYP450</italic> genes in perennial ryegrass, tall fescue, and roses [##REF##31765955##32##, ##UREF##17##33##]. Furthermore, <italic>CYP450</italic> genes participate in the biosynthesis of jasmonic acid (JA), as demonstrated by <italic>GmCYP82A3</italic> in soybean and <italic>DzCYP72As</italic> in Dioscorea zingiberensis [##REF##27588421##34##]. Multiple investigations have provided evidence supporting the involvement of <italic>CYP716A</italic> subfamily genes in regulating the biosynthetic pathway of triterpenoids. In the case of <italic>Artemisia annua</italic>, the genes <italic>CYP716A14v2</italic> and OSC2 (a multifunctional oxidosqualene cyclase) are responsible for the production of triterpenoids, which serve as constituents of the wax layer of the cuticle that covers the aboveground parts of the plants. Researchers suggest that specialized triterpenoids may serve a protective function against both biotic and abiotic stresses in <italic>A. annua</italic> [##REF##25576188##35##]. Similarly, in sweet basil, <italic>CYP716A52</italic> and <italic>CYP716A53</italic> catalyze C-28 oxidation to yield oleanolic acid and unsolid acid. These compounds aid in the plant’s defense mechanism against stress [##REF##28967669##36##]. These investigations propose that <italic>CYP450</italic> genes play a critical role in both plant growth and stress response. Previous investigations have successfully identified and carried out functional analysis on individual genes in the <italic>CYP450</italic> family of sweet potatoes. For example, <italic>IbCYP73A1(IbC4H)</italic> enhances the ability of plants to scavenge reactive oxygen species under stress. <italic>IbCYP82D47</italic> interacts with the carotenoid biosynthesis-related protein <italic>IbGGPPS12</italic>, increasing the content of carotenoids in transgenic sweet potatoes [##UREF##18##37##, ##REF##35351305##38##]. However, a systematic identification and analysis of <italic>CYP450</italic> family members in sweet potatoes has not yet been conducted.</p>", "<p id=\"Par6\">Sweet potato [<italic>Ipomoea batatas</italic> (L.)] is a vine plant belonging to the Convolvulaceae family. It is an important crop for food, feed, industrial raw materials, and new energy sources. Its edible enlarged storage root is a valuable source of nutrients and phytochemicals, making it widely cultivated [##UREF##19##39##]. These unique characteristics make it a staple food for humans, a feed source for animals, and a raw material source for the food and nonfood industries [##UREF##20##40##]. It is also used for the production of biofuels and alcohol [##UREF##21##41##]. With the development of sequencing technology, an increasing number of plant genomes and transcriptomes are being revealed, leading to a broader scope of research in this area. The sweet potato is one of the plants that has been extensively studied. In recent years, an increasing number of <italic>CYP450</italic> family genes have been discovered in crops, such as rice, soybean, and chili pepper [##REF##21062474##7##, ##UREF##22##42##, ##UREF##23##43##]. However, there have been few reports on this gene family in sweet potatoes. In this study, the whole genome, evolutionary relationships, chromosomal localization, collinearity relationships, and expression patterns of the sweet potato <italic>CYP450</italic> gene family were identified and comprehensively analyzed using bioinformatics methods. The results provide a theoretical basis for understanding the functions of <italic>CYP450</italic> genes in sweet potatoes and for molecular breeding of sweet potatoes.</p>" ]
[ "<title>Materials and methods</title>", "<title>Identification and physicochemical properties of <italic>IbCYP</italic> gene family members</title>", "<p id=\"Par7\">The genomic data of sweet potatoes were obtained from the Ipomoea Genome Hub website (<ext-link ext-link-type=\"uri\" xlink:href=\"https://ipomoea-genome.org/\">https://ipomoea-genome.org/</ext-link>) [##REF##33639840##44##]. For the downloaded protein sequences, BLAST was used to construct a local database. In contrast, the gene and protein sequences of the Arabidopsis <italic>CYP450</italic> gene family were obtained from the Cytochrome P450 Homepage website (<ext-link ext-link-type=\"uri\" xlink:href=\"http://drnelson.uthsc.edu/CytochromeP450.html\">http://drnelson.uthsc.edu/CytochromeP450.html</ext-link>). A BLAST comparison of <italic>CYP450</italic> gene family protein sequences between sweet potato and Arabidopsis was conducted. At the same time, a hidden Markov model of the typical CYP450 family protein structure was downloaded from the Pfam database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://pfam.sanger.ac.uk\">http://pfam.sanger.ac.uk</ext-link>) [##REF##30357350##45##], and HMMER software was used to search for the protein sequences [##REF##26342231##46##] containing the characteristic domains (PF00067). The candidate proteins identified through the previously mentioned methods were further analyzed using Snapgene software. Incomplete reading frame sequences and redundant sequences were manually eliminated. The remaining candidate protein domains were validated using Pfam and the Conserved Domain Database (CDD) online analysis tools [##REF##31777944##47##]. Gene sequences that did not contain the <italic>CYP450</italic> gene family domain or had incomplete CYP450 domains were removed from the analysis. Finally, 95 <italic>IbCYP</italic> genes were obtained and all the genes contained the FxxGxRxCxG characteristic domain. The coding sequence (CDS) and amino acid sequences of 95 <italic>IbCYP</italic> genes were corrected using the existing transcriptome sequencing results of sweet potato in our laboratory. The ExPASy ProtParam tool (<ext-link ext-link-type=\"uri\" xlink:href=\"http://web.ExPASy.org/protparam/\">http://web.ExPASy.org/protparam/</ext-link>) was used to predict protein physicochemical parameters [##UREF##24##48##]. Subcellular localization predictions were generated with BUSCA (<ext-link ext-link-type=\"uri\" xlink:href=\"http://busca.biocomp.unibo.it/\">http://busca.biocomp.unibo.it/</ext-link>) [##REF##29718411##49##].</p>", "<title>Gene structure and conserved motif analysis</title>", "<p id=\"Par8\">The exon–intron structure information of the candidate <italic>IbCYP</italic> was predicted by the online website GSDS2.0 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://gsds.gao-lab.org/\">http://gsds.gao-lab.org/</ext-link>) [##UREF##25##50##]. The MEME online website (<ext-link ext-link-type=\"uri\" xlink:href=\"http://meme-suite.org/tools/meme\">http://meme-suite.org/tools/meme</ext-link>) was used to predict the conserved domains in IbCYP450 protein sequences [##UREF##26##51##]. For this analysis, the number of motifs to be identified was set to 10, while default settings were adopted for other parameters and the results were visualized using TBtools. MEGA11 software [##UREF##27##52##] was used to perform multiple sequence alignment of 95 IbCYP proteins, and visualization was achieved with GeneDoc software.</p>", "<title>Phylogenetic analysis of IbCYP proteins</title>", "<p id=\"Par9\">One representative member of each plant <italic>CYP450</italic> family was used for alignment and phylogenetic analysis. Members with identified functions in a family were preferentially selected for phylogenetic analysis. ClustalW was employed for multiple sequence alignment of CYP450 protein sequences between sweet potato, <italic>Salvia miltiorrhiza</italic>, pepper, tobacco, and <italic>Arabidopsis</italic>. The phylogenetic tree was constructed using MEGA11 neighbor-joining (NJ) with 1000 bootstrap replicates [##UREF##27##52##].</p>", "<title>Chromosomal localization, gene duplication, and synteny analysis</title>", "<p id=\"Par10\">The locations of 95 <italic>IbCYP</italic> genes on chromosomes were obtained based on the information annotated for the sweet potato genome and analyzed through the Gene Location Visualization of TBtools [##UREF##28##53##]. <italic>Arabidopsis</italic>, tomato, pepper, maize, and rice downloaded from NCBI. Analysis of genome collinearity between sweet potatoes and these species was performed using MCScanX software [##UREF##29##54##]. Circos and Dual Synteny Plot in TBtools were used for visualized mapping of the collinear gene pairs [##UREF##28##53##].</p>", "<title>Cis-acting element analysis of <italic>IbCYP</italic> genes</title>", "<p id=\"Par11\">The upstream promoter region (2,000 bp) of the <italic>IbCYP</italic> genes was extracted using TBtools software and submitted to the PlantCARE website (<ext-link ext-link-type=\"uri\" xlink:href=\"https://bioinformatics.psb.ugent.be/webtools/plantcare/html/\">https://bioinformatics.psb.ugent.be/webtools/plantcare/html/</ext-link>) [##UREF##30##55##], which identified the cis-regulatory elements in the <italic>IbCYP</italic> genes. Then, the TBtools software was used to visualize the cis-regulatory element Fig. [##UREF##28##53##].</p>", "<title>Plant material and treatments</title>", "<p id=\"Par12\">The sweet potato materials used in the experiment were obtained from the experimental field of the College of Coastal Agriculture, Guangdong Ocean University (21°15′N, 110°30′E).</p>", "<p id=\"Par13\">After sweet potato seedlings were taken from the experimental field, the tuberous, pencil root, primary root, flower, fruit, and stem were covered with dry ice after being quickly frozen with liquid nitrogen. The tissues were then sent to Biomarker Technologies for total RNA extraction, library construction, and full-length transcriptome sequencing. Several strong branches grown consistently were selected and cultured with clean water for 10 days before being subjected to abiotic stress. During the development of adventitious roots in sweet potato shoots, the control group (CK) was maintained by continuing the culture with clean water. For salt stress treatment, the culture was continued with 200 mmol/L NaCl solution, and for drought stress treatment, 300 mmol/L mannitol solution was used. Each group was treated in triplicate with 3 branches per replicate. After 24 h of stress treatment, the primary roots, young stems, and leaves were taken and cooled by liquid nitrogen, covered with dry ice, and sent to Biomarker Technologies for transcriptomic sequencing.</p>", "<title>Protein-protein interaction (PPI) network construction</title>", "<p id=\"Par14\">Using the default parameters, the online STRING database (<ext-link ext-link-type=\"uri\" xlink:href=\"https://string-db.org/\">https://string-db.org/</ext-link>) [##UREF##31##56##] was utilized to predict and execute potential protein-protein interaction networks using IbCYP proteins based on known Arabidopsis homologs. Cytoscape (V3.10.0) was used to visualize the resulting network [##UREF##32##57##].</p>", "<title>Transcriptome analysis</title>", "<p id=\"Par15\">Five transcriptome bio project datasets were chosen for the <italic>IbCYP450</italic> gene expression profile analysis. Two bio project datasets (PRJNA511028 for hormone, and PRJNA987163 for cold) were downloaded from the NCBI database. Another three were our in-house (unpublished) sweet potato heat treatment, salt treatment, and drought treatment. Among them, “Xushu 18” was for hormonal treatment, clod-tolerant “Liaohanshu 21” and clod-sensitive “Shenshu 28” for cold treatment, heat-tolerant “Guangshu 87” and heat-sensitive “Ziluolan” for heat treatment and salt-tolerant and drought-tolerant “Guangshu 87” for salt and drought treatment. The <italic>CYP450</italic> expression was measured in fragments per kilobase of exon per million fragments mapped (FPKM). The heat maps of expression were constructed by TBtools software.</p>", "<title>Quantitative analysis of candidate <italic>IbCYP</italic> genes</title>", "<p id=\"Par16\">The sweet potato (<italic>I. batatas</italic>) cultivar “Jishu 26” was used for qRT-PCR analysis in this study. Sweet potato plants were cultivated in a field at the experimental field of Guangdong Ocean University, Guangdong, China. For tissue expression, the flower, leaf, stem, primary root, firewood root, and tuberous root tissues were sampled from 3-month-old “Jishu 26” planted in the field. For the abiotic stress treatments, the twigs about 30 cm in length from 3-month-old filed-grown “Jishu 26” were cultured in the Hoagland solution for 14 days to treat: for salt stress treatment, the twigs were cultured in the Hoagland solution with 0 and 200 mM NaCl. For drought stress treatments, the twigs were cultured in Hoagland solution with 0 and 300 mM mannitol. The primary root, stem, and leaf samples were collected at 0, 8, 16, and 24 h after the treatments.</p>", "<p id=\"Par17\">For qRT-PCR analysis, the 10 µL total reaction quantity of each sample contained 1 µL cDNA template, 0.5 µL (10µmol L-1) forward and reverse gene-specific primers, 5 µL 2×SYBR Green qPCR mix and 3 µL ddH2O. The qRT‒PCR reaction was conducted using the Bio-Rad system with the following thermal cycle conditions: 3 min of pre-degeneration at 95 °C, followed by 40 cycles of denaturation at 95 °C for 10 s and annealing at 60 °C for 30 s. The reaction was completed with a 5-second step at 65 °C and a cooling rate of 0.5 °C to reach 95 °C. Each sample was replicated 3 times, referring to Dingfa’s method [##UREF##33##58##] using the IbARF gene as an internal reference. We calculated relative transcript levels using the 2<sup>−ΔΔCT</sup> method.</p>" ]
[ "<title>Results</title>", "<title>Identification of cytochrome <italic>CYP450</italic> family genes in sweet potato\n</title>", "<p id=\"Par18\">The 95 <italic>IbCYP</italic> genes are given new names according to the classification and naming principles of <italic>CYP450</italic>. The proteins produced by these genes have different lengths, with amino acids ranging from 381 (<italic>IbCYP712A1</italic>) to 873 (<italic>IbCYP82D47</italic>). Their weights also vary, from 42.39 kD (<italic>IbCYP712A1</italic>) to 98.35 kD (<italic>IbCYP82D47</italic>). The predicted isoelectric points of the proteins range from 5.52 (<italic>IbCYP712A1</italic>) to 9.45 (<italic>IbCYP76G3</italic>). Of these, 75 proteins have isoelectric points higher than 7, making them positively charged in acidic solutions. The proteins have different levels of hydrophilicity, ranging from − 0.384 (<italic>IbCYP704A1</italic>) to 0.075 (<italic>IbCYP78A2</italic>). Furthermore, according to BUSCA subcellular localization predictions, all IbCYP proteins are found in the endomembrane system (Table ##TAB##0##1##).</p>", "<p id=\"Par19\">\n</p>", "<title>Motif compositions and gene structure of the <italic>IbCYP</italic> genes</title>", "<p id=\"Par20\">According to the classification principles of the <italic>CYP450</italic> family, we have divided the identified 95 IbCYP proteins into 5 families (Fig. ##FIG##0##1##A). After analyzing the CYP450 protein sequence of sweet potato using the MEME online tool, ten conserved motifs were predicted (Fig. ##FIG##0##1##B). Different IbCYP proteins showed variations in the number and distribution of these motifs. Each gene had between six and ten motifs, and all IbCYP proteins had a conserved heme-binding domain Motif 1. The C-terminal region of the IbCYP protein was highly conserved, with Motif 2 and Motif 3 commonly found in most proteins, while the N-terminal region was less conserved. The majority (86.7%) of A-type CYP450 proteins contained all ten motifs, while non-A-type CYP450 proteins typically had between six and nine motifs. Motif 10 was not found in the <italic>CYP97</italic> or <italic>CYP72</italic> families, and motif 5 was absent in the CYP86 family. This suggests that the <italic>IbCYP</italic> gene family shows both a high level of conservation and some differences. Different subfamilies have distinct types of motifs, which may be related to the various biological functions of genes within each subfamily.</p>", "<p id=\"Par21\">We studied the structure of the coding sequences of all 95 <italic>IbCYP</italic> genes and found that the <italic>CYP450</italic> gene family members of sweet potato had 1 to 15 coding sequences. The number of introns varied from 1 to 3, indicating that there was significant variation in the gene structure of <italic>IbCYP</italic> genes (Fig. ##FIG##0##1##C), the yellow box represents the coding sequence (CDS) of the <italic>CYP450</italic> gene family members.</p>", "<title>Conserved sequence alignment of the <italic>IbCYPs</italic></title>", "<p id=\"Par22\"> Multiple sequence alignment was performed for 95 IbCYP proteins using ClustalW. The results showed that all the IbCYP proteins have a highly conserved heme-binding region at the C-terminal end. The vast majority of IbCYP proteins (95.7%) exhibit the presence of all three conserved domains (Fig. ##FIG##1##2##), namely the K-helix region (ExxR), the PERF motif (PERF), and the heme-binding region (FxxGxRxCxG).</p>", "<title>Phylogenetic analysis of IbCYP proteins</title>", "<p id=\"Par23\">We constructed a phylogenetic tree containing 201 <italic>CYP450</italic> genes from five species (<italic>I. batatas</italic>, <italic>A. thaliana</italic>, <italic>C. annuum</italic>, <italic>N. tabacum</italic>, and <italic>S. miltiorrhiza</italic>) using MEGA software. We divided all of the <italic>CYP450</italic> genes into one of two major clades: A type, which contained the <italic>CYP71</italic> family, and non-A type, which contained 4 clans (Fig. ##FIG##2##3##).</p>", "<title>Chromosomal locations and gene duplication analysis</title>", "<p id=\"Par24\">Gene duplication is recognized as a prominent driver in the evolutionary process of genomes and genetic systems [##UREF##34##59##]. Two main types of gene duplication, namely tandem and segmental duplication, can give rise to numerous gene families [##REF##30791939##60##]. Tandem duplication occurs when multiple members of a gene family are found within the same intergenic region or neighboring intergenic regions [##REF##15208399##61##, ##REF##22849513##62##]. On the other hand, segmental duplication involves the duplication of multiple genes through polyploidy events, often followed by chromosomal rearrangements [##UREF##35##63##].</p>", "<p id=\"Par25\">After analyzing the chromosomal localization, we found that the 95 <italic>IbCYP</italic> genes were spread across 15 chromosomes (Fig. ##FIG##3##4##). Chromosomes 1 (LG1), 6 (LG6), and 13 (LG13) had the highest number of genes, with nine <italic>IbCYP</italic> genes each. Chromosomes 5 (LG5), 7 (LG7), and 8 (LG8) followed closely with eight <italic>IbCYP</italic> genes each. Chromosomes 2 (LG2) and 3 (LG3) contained seven <italic>IbCYP</italic> genes. In contrast, chromosomes 10 (LG10) and 12 (LG12) had the fewest genes, with only two and three genes, respectively. Additionally, we identified 15 pairs of tandemly duplicated genes among the <italic>IbCYP</italic> genes. These genes were located close to each other on the chromosomes and formed clusters on the phylogenetic tree, indicating similar functions. The expansion of the gene family was mainly attributed to tandem duplication and segment duplication, as shown by the presence of 13 duplicate gene pairs distributed on different chromosomes through MCScanX collinearity analysis (Fig. ##FIG##4##5##). This suggests that tandem duplication and segment duplication played a role in the expansion of <italic>CYP450</italic> genes.</p>", "<title>Synteny analysis of <italic>IbCYP</italic> genes in sweet potato, pepper, tomato, rice, maize, and <italic>Arabidopsis</italic></title>", "<p id=\"Par26\"> To better understand how the <italic>CYP450</italic> family evolved in sweet potatoes compared to other species, we conducted an evolutionary relationship analysis of <italic>CYP450</italic> genes. Specifically, we compared sweet potatoes with three dicotyledonous plants (<italic>Arabidopsis</italic>, tomato, and pepper) and two monocotyledonous plants (maize and rice) (Fig. ##FIG##5##6##). The analysis revealed that sweet potatoes shared 27 collinear genes with Arabidopsis, and 31, 26, 7, and 6 collinear genes with tomato, pepper, rice, and maize, respectively. These findings suggest that the <italic>IbCYPs</italic> in sweet potatoes have a close evolutionary relationship with the <italic>CYP450</italic> genes in dicotyledonous plants, particularly with tomatoes and peppers from the Solanaceae family.</p>", "<title>Analysis of cis‑regulatory element distribution in <italic>IbCYP</italic> promoters</title>", "<p id=\"Par27\">We extracted the genomic sequence of the <italic>IbCYP</italic> genes upstream region, specifically 2000 base pairs, to study their potential biological functions. This sequence was considered a hypothetical promoter sequence for cis-acting element analysis (Fig. ##FIG##6##7##). Our analysis revealed the presence of different types of cis-acting elements in the <italic>IbCYP</italic> gene family, which are associated with plant growth and development, hormone responses, and responses to abiotic stress. When examining the genes, it was found that 91 genes contained one to ten light response elements, 39 genes contained one to four auxin response elements, and 30 genes contained one to three gibberellin response elements.</p>", "<p id=\"Par28\">Moreover, some genes contained cis-acting elements related to plant hormones and abiotic stress, such as MeJA-responsive elements, salicylic acid response elements, abscisic acid response elements, and elements responding to drought, hypoxia, and low temperature. Additionally, a few genes had cis-acting elements linked to plant secondary metabolism and growth development, involving zein metabolism regulation, flavonoid biosynthesis, endosperm and meristem expression, and phytochrome downregulation response elements. Two genes also contained wound-responsive elements. Overall, the promoter regions of these <italic>IbCYPs</italic> contained various types of cis-elements, indicating their potential involvement in diverse biological processes and regulatory pathways.</p>", "<title>Transcript factors networks of <italic>IbCYP</italic> genes</title>", "<p id=\"Par29\">Through analysis of potential transcription factors (TFs), it was found that a total of 687 TFs were identified in the <italic>IbCYP</italic> genes under salt stress, distributed among 56 different TF families, such as AP2/ERF-ERF, MYB, bHLH, NAC, WRKY, C2H2, bZIP, GRAS, and others (Fig. ##FIG##7##8##A). In the <italic>IbCYP</italic> genes under drought stress, a total of 478 TFs were identified, distributed among 48 different TF families, including AP2/ERF-ERF, MYB, NAC, bHLH, WRKY, C2H2, bZIP, HB-HD-ZIP, GRAS, LOB, and others (Fig. ##FIG##7##8##B). The analysis of TF quantity revealed that there are 346 common TFs shared between salt stress and drought stress (Fig. ##FIG##7##8##C).</p>", "<title>Regulatory network in sweet potato</title>", "<p id=\"Par30\">We used the STRING database to predict potential interactions among the IbCYP proteins (Fig. ##FIG##8##9##). There were 20 nodes in the IbCYP protein interaction network, each of which interacted with other nodes. Some proteins exhibited direct interactions, such as <italic>IbCYP706A2</italic> and <italic>IbCYP94A2</italic>, whereas others exhibited more complex multigene interactions, such as <italic>IbCYP714E1 (Gas)</italic> and <italic>Ib</italic>CYP79A1. Notably, <italic>IbCYP72A8</italic> was predicted to be central nodes, radiating six connections to other genes.</p>", "<title>Expression patterns of <italic>IbCYP</italic> genes in sweet potato</title>", "<p id=\"Par31\">We analyzed the expression patterns of the <italic>IbCYP</italic> genes in various plant tissues using transcriptome data. The expression levels were measured as fragments per kilobase of exon model per million mapped fragments (FPKM). Our findings indicate that 95 <italic>IbCYP</italic> genes showed significant differences in expression patterns across different tissues (Fig. ##FIG##9##10##). Specifically, three genes exhibited high expression levels in tuber roots, 13 genes in leaves, 14 genes in flowers, and 9 genes in fruits.</p>", "<p id=\"Par32\">We also examined the expression of <italic>IbCYP</italic> genes under salt and drought stress conditions in sweet potato tissues (Fig. ##FIG##10##11##). In tissues exposed to salt and drought stress, the expression levels of all 95 <italic>IbCYP</italic> genes showed significant differences. Specifically, under salt stress, 21 genes were upregulated and 28 genes were downregulated in root tissues. In stem tissues, 15 genes were upregulated and 11 genes were downregulated, while in leaf tissues, 5 genes were upregulated and 10 genes were downregulated. Under drought stress, 9 genes were upregulated 22 genes were downregulated in root tissues, 20 genes were upregulated and 4 genes were downregulated in stem tissues, 13 genes were upregulated and 11 genes were downregulated in leaf tissues (Table ##TAB##1##2##). These findings suggest that <italic>IbCYP</italic> genes have distinct expression patterns under salt and drought stress conditions. Overall, most of the genes responded to different stress conditions.</p>", "<p id=\"Par33\">\n</p>", "<p id=\"Par34\">The expression of 95 <italic>IbCYP</italic> genes was detected under high-temperature stress, and we focused on two specifically highly expressed genes, including <italic>IbCYP82G1</italic> in “Ziluolan” fibrous roots and <italic>IbCYP78A1</italic> in “Guangshu 87” roots (Fig. ##FIG##11##12##A). These two genes may be related to the heat tolerance of sweet potatoes. Similarly, the expression of 95 <italic>IbCYP</italic> genes was detected under cold stress (Fig. ##FIG##11##12##B). In “Shenshu 28”, after 3 h of cold stress, <italic>IbCYP82G1</italic> and <italic>IbCYP82G3</italic> were highly expressed, but after 24 h of cold stress, the expression levels of these two genes decreased, while <italic>IbCYP707A1</italic> showed specific high expression. In “Liaohanshu 21”, after 3 h of cold stress, seven genes including <italic>IbCYP82G7</italic> were highly expressed, but after 24 h of cold stress, the expression levels of these seven genes decreased, while <italic>IbCYP82D47</italic> and <italic>IbCYP82G4</italic> were highly expressed.</p>", "<p id=\"Par35\">The expression profiles of 95 <italic>IbCYP</italic> genes were identified in three distinct tissues using the “Xushu 18” RNA-seq data obtained from the NCBI database (PRJNA511028) (Fig. ##FIG##12##13##). In fibrous roots, <italic>IbCYP736A3</italic>, <italic>IbCYP736A2</italic>, and <italic>IbCYP72A4</italic> were highly expressed after ABA treatment, while <italic>IbCYP76G3</italic> and <italic>IbCYP712A1</italic> were highly expressed after MeJA treatment. In stems, <italic>IbCYP82G1</italic> showed specific high expression after ABA treatment, <italic>IbCYP76C1</italic> was highly expressed after SA treatment, and <italic>IbCYP82F1</italic> showed specific high expression after MeJA treatment.</p>", "<title>Quantitative analysis of <italic>IbCYP</italic> genes in different tissues</title>", "<p id=\"Par36\">To confirm the accuracy of the transcriptome data, we selected 11 genes that showed significant expression differences and performed qRT-PCR analysis (Fig. ##FIG##13##14##). The results of the expression analysis of <italic>IbCYP</italic> genes in different parts of sweet potato were consistent with the transcriptome data. In general, the expression of these <italic>IbCYP</italic> genes was primarily detected in the pencil roots and leaves of sweet potatoes. Additionally, there were noticeable differences in the expression of these <italic>IbCYP</italic> genes among different parts. Notably, <italic>IbCYP82G2</italic> exhibited the highest expression level in the tuber, while <italic>IbCYP82G7</italic> showed the highest expression level in the primary root. This suggests that genes belonging to the same subfamily in the <italic>CYP450</italic> family may have diverse functions.</p>", "<title>Quantitative analysis of <italic>IbCYP</italic> genes under abiotic stresses</title>", "<p id=\"Par37\">To evaluate the expression of <italic>IbCYP</italic> genes in different tissues of sweet potato under various stress conditions, we utilized a technique called quantitative real-time polymerase chain reaction (qRT-PCR). The expression levels of sweet potato were examined after subjecting them to different durations of stress (Fig. ##FIG##14##15##). The results showed that exposure to salt and drought stress caused an increase in <italic>IbCYP</italic> gene expression in different parts of sweet potato. Specifically, under both stress conditions, most <italic>IbCYP</italic> genes in the primary root initially showed an increase in expression followed by a decrease, indicating a consistent pattern of expression. However, the expression of these <italic>IbCYP</italic> genes in stems showed the opposite trend. In the case of sweet potato leaves, a more complex pattern of expression was observed. For instance, <italic>IbCYP736A2</italic> displayed a gradual decrease in expression under salt stress but showed an initial increase followed by a decrease under drought stress. Additionally, it is important to note that the highest expression level of <italic>IbCYP76C2</italic> in roots was 3230 times higher than that in the control group after 16 h of salt stress, and 2844 times higher after 8 h of drought stress. Similarly, the highest expression level of <italic>IbCYP82G7</italic> in roots was 242 times higher than that in the control group after 16 h of salt stress and 177 times higher after 8 h of drought stress.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par38\">Plant <italic>CYP450</italic> genes are involved in the catalysis of multiple reactions, including growth, development, and secondary metabolite biosynthesis pathways [##UREF##36##64##–##UREF##39##67##]. With the development of gene sequencing technology, an increasing number of plant genomes have been deciphered, and the identification of the <italic>CYP450</italic> family is expanding to more plants, such as tea tree, foxtail millet, citrus, and peanut, etc. [##UREF##40##68##–##UREF##44##72##]. Due to gene duplication and divergence events, higher plants possess a large number of <italic>CYP450</italic> genes. In this study, we employed more rigorous criteria to identify <italic>CYP450</italic> genes in sweet potatoes. Our methodology included local BLAST, HMMER, CDD, and conserved motif analysis. To enhance accuracy, we refined the coding sequence (CDS) and amino acid sequences of 95 <italic>IbCYP</italic> genes using existing transcriptome sequencing data from our laboratory. In terms of gene structure, sweet potato genes show a wide range of gene lengths and significant differences in the number of exons. This may be related to the abundant biological functions carried out by the <italic>CYP450</italic> superfamily. The sweet potato genome encompasses a total of 95 <italic>CYP450</italic> genes, providing a valuable genetic foundation for further investigations into their functions.</p>", "<p id=\"Par39\">In sweet potatoes, the predicted 95 <italic>CYP450</italic> genes are classified into 5 gene families, namely, the <italic>CYP71</italic> family, <italic>CYP72</italic> family, <italic>CYP85</italic> family, <italic>CYP86</italic> family, and <italic>CYP97</italic> family, totaling 31 subfamilies. Among them, 60 (63.1%) genes belonging to the <italic>CYP71</italic> clan were classified as type A, while the rest were classified as nontype A. In contrast, more members of the <italic>CYP450</italic> gene family have been identified in other crops. For example, 326 <italic>CYP450</italic> family members were identified in rice, 332 <italic>CYP450</italic> genes in soybean, and 478 <italic>CYP450</italic> genes in pepper [##REF##21062474##7##, ##UREF##22##42##, ##UREF##23##43##]. This could be attributed to the fact that sweet potato’s two genomes are too similar. In the future, there may be additional discoveries of <italic>CYP450</italic> family members in sweet potatoes. Conducting a collinearity analysis within a specific species provides insights into the homology of genes across different chromosomes. Through chromosome localization and collinearity analysis, it was confirmed that <italic>IbCYP</italic>, a specific gene, consists of 28 duplicated gene pairs. Among these pairs, 15 were classified as tandem duplications, while the remaining 13 were classified as segmental duplications. Thus, it is speculated that the expansion of the <italic>CYP450</italic> gene family in the evolutionary process was primarily driven by segmental duplications, with tandem duplications playing a supplementary role. In addition, a collinearity analysis was performed among different species to explore gene evolution and genetic relationships. The evolutionary relationship between sweet potato and other species was examined based on family genes using a collinear analysis. The results revealed that the <italic>CYP450</italic> family genes of sweet potato were more closely related to other Solanales plants, such as tomato and pepper. Specifically, 31 and 26 collinear gene pairs were identified in tomato and pepper, respectively. However, the genetic relationship between sweet potato and gramineous plants, such as maize and rice, was found to be less significant, as only a few collinear gene pairs were observed. These findings align with the results obtained from the genetic relationship analysis.</p>", "<p id=\"Par40\">The cis-acting elements of promoters play a vital role in the regulation of gene expression. In this study, we verified that the <italic>IbCYP</italic> promoter region of sweet potato contained several elements related to the hormone regulation pathway. Among them, light responsiveness, auxin responsiveness, and gibberellin responsiveness were detected in most genes. Therefore, we inferred that light, gibberellin, and auxin may influence <italic>IbCYP</italic> gene expression, thereby affecting the growth and development of sweet potatoes. In <italic>Arabidopsis</italic>, <italic>CYP714A1</italic> and <italic>CYP714A2</italic> may function in the early stages of the GA biosynthetic pathway [##UREF##45##73##]. These drought-inducing elements were detected in 10 sweet potato genes. The results from the heatmap analysis revealed that <italic>IbCYP701A1</italic> and <italic>IbCYP96A3</italic> were highly expressed under drought stress. These findings indicated that <italic>IbCYP</italic> gene expression was regulated by cis-elements related to plant development and abiotic stress tolerance.</p>", "<p id=\"Par41\">The expression pattern of genes reflects their functions to a certain extent. Therefore, in this study, we analyzed the expression patterns of the <italic>IbCYP</italic> genes. In sweet potatoes, the <italic>CYP71</italic> clan exhibits specific expression in multiple tissues. For example, <italic>IbCYP71D5</italic> is specifically expressed in primary roots; <italic>IbCYP71D8</italic> is specifically expressed in stems; and <italic>CYP76C2</italic> in Arabidopsis has been found to respond to leaf senescence and aging in cell cultures, which are related to cellular deterioration and eventual cell death [##REF##9827554##74##]. Similarly, <italic>IbCYP76C2</italic> was detected to exhibit leaf-specific expression in sweet potato. It is speculated that it may also play a similar role in sweet potato leaves; <italic>IbCYP77B1</italic> is specifically expressed in the flowers, and <italic>IbCYP71D7</italic> is specifically expressed in the fruits. The monogenic family <italic>CYP97</italic> clan consists of two genes, namely <italic>IbCYP97A1</italic> and <italic>IbCYP97B1</italic>. This is similar to the case of pepper (3 genes) [##UREF##22##42##]. These two genes are specifically expressed in the leaves and stems of sweet potato, indicating a potential relationship with the growth and development of sweet potato stems and leaves. <italic>IbCYP77A1</italic> shows high expression in both flowers and fruits of sweet potatoes, which is similar to the role of <italic>CYP77A4</italic> in <italic>Arabidopsis thaliana</italic> [##UREF##46##75##], where it is involved in the development of cotyledons. This suggests that <italic>IbCYP77A1</italic> may play a role in the reproductive development of sweet potatoes. Under environmental stress, <italic>IbCYP</italic> genes also play a regulatory role. Usually, the root system is the first part to be affected by environmental stress. As the heatmap shows, the <italic>IbCYP</italic> genes were generally highly expressed in the primary root under different stresses. In sweet potatoes, a total of 34 <italic>IbCYP</italic> genes are upregulated in response to salt and drought stress. In response to cold and heat stress, <italic>IbCYP450</italic> genes also show a response. <italic>IbCYP82G1</italic>, <italic>IbCYP82G3</italic>, and <italic>IbCYP707A1</italic> exhibit different levels of response under cold stress. Under heat stress, both <italic>IbCYP82G1</italic> and <italic>IbCYP78A1</italic> are highly expressed, but the expression patterns of these two genes may vary among different varieties, possibly due to intervarietal differences. The <italic>IbCYP450</italic> genes also show varying degrees of response to plant hormones, which corresponds to the presence of multiple plant hormone response elements in the promoter cis-acting elements of <italic>IbCYP450</italic> genes. These findings have also been corroborated in foxtail millet. However, the response of <italic>CYP450</italic> genes to low temperature, salt stress, and plant hormones differs between foxtail millet and sweet potato, which is likely due to genetic differences between the two species [##UREF##40##68##]. It has been reported that the <italic>CYP86</italic> clan has a positive regulatory effect on the plant immune system [##REF##31207065##76##]. <italic>CYP86</italic> clan genes were expressed in the roots and leaves and were related to drought and salt tolerance.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par42\">We identified 95 <italic>IbCYP</italic> genes in the sweet potato genome, which were classified into 5 families and 31 subfamilies. Our evolutionary analysis of the <italic>CYP450</italic> superfamily in sweet potato showed that the <italic>IbCYP</italic> genes have undergone frequent duplication and functional diversification. This will help us understand the complex agronomic traits and evolutionary processes of sweet potatoes. Additionally, we observed species- or family-specific expansions of the <italic>CYP450</italic> superfamily, which may explain species divergence events. Expression analysis revealed the diversified expression patterns of <italic>CYP450</italic> genes in sweet potatoes, which were expressed in different tissues, under various abiotic stress conditions, and in response to plant hormones. This indicates the functional diversity and regulation of <italic>CYP450</italic> genes in sweet potatoes. The results of this study provide a solid foundation for further exploring the molecular evolution mechanisms and potential functions of the <italic>CYP450</italic> gene family in sweet potatoes.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Cytochrome P450 monooxygenases (CYP450s) play a crucial role in various biochemical reactions involved in the synthesis of antioxidants, pigments, structural polymers, and defense-related compounds in plants. As sweet potato (<italic>Ipomoea batatas</italic> L.) holds significant economic importance, a comprehensive analysis of <italic>CYP450</italic> genes in this plant species can offer valuable insights into the evolutionary relationships and functional characteristics of these genes.\n</p>", "<title>Results</title>", "<p id=\"Par2\">In this study, we successfully identified and categorized 95 <italic>CYP450</italic> genes from the sweet potato genome into 5 families and 31 subfamilies. The predicted subcellular localization results indicate that CYP450s are distributed in the cell membrane system. The promoter region of the <italic>IbCYP450</italic> genes contains various cis-acting elements related to plant hormones and stress responses. In addition, ten conserved motifs (Motif1-Motif10) have been identified in the <italic>IbCYP450</italic> family proteins, with 5 genes lacking introns and only one exon. We observed extensive duplication events within the <italic>CYP450</italic> gene family, which may account for its expansion. The gene duplication analysis results showed the presence of 15 pairs of genes with tandem repeats. Interaction network analysis reveals that <italic>IbCYP450</italic> families can interact with multiple target genes and there are protein-protein interactions within the family. Transcription factor interaction analysis suggests that <italic>IbCYP450</italic> families interact with multiple transcription factors. Furthermore, gene expression analysis revealed tissue-specific expression patterns of <italic>CYP450</italic> genes in sweet potatoes, as well as their response to abiotic stress and plant hormones. Notably, quantitative real-time polymerase chain reaction (qRT‒PCR) analysis indicated the involvement of <italic>CYP450</italic> genes in the defense response against nonbiological stresses in sweet potatoes.\n</p>", "<title>Conclusions</title>", "<p id=\"Par3\">These findings provide a foundation for further investigations aiming to elucidate the biological functions of <italic>CYP450</italic> genes in sweet potatoes.\n</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12864-024-09965-x.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank the Ipomoea Genome Hub project team for sharing the Ipomoea batatas genome annotation data (<ext-link ext-link-type=\"uri\" xlink:href=\"https://ipomoea-genome.org/\">https://ipomoea-genome.org/</ext-link>).</p>", "<title>Authors' contributions</title>", "<p>XL designed and performed the experiments and wrote the paper. BT and ZL performed some experiments and analyzed the data, and XL, BT, and LS analyzed the data. XL, BT, and LS revised the paper. XL and ZL conceived the experiment. All authors have read and approved the manuscript.</p>", "<title>Funding</title>", "<p>This research was funded by the Natural Science Foundation of China-Guangdong Joint Fund, China, and Studies on Resistance Resources and Molecular Mechanisms of Sweet Potato Weevil in South China (Grant number, U1701234).</p>", "<title>Availability of data and materials</title>", "<p>All datasets supporting the results of this study are included in this article and its ##SUPPL##0##Supplementary data files##.</p>", "<p>The transcriptomic data used in this study can be accessed through the NCBI accession numbers PRJNA511028, PRJNA987163, and PRJNA744414.</p>", "<p>The Ipomoea Genome Hub website (<ext-link ext-link-type=\"uri\" xlink:href=\"https://ipomoea-genome.org/\">https://ipomoea-genome.org/</ext-link>).</p>", "<p>The Cytochrome P450 Homepage website (<ext-link ext-link-type=\"uri\" xlink:href=\"http://drnelson.uthsc.edu/CytochromeP450.html\">http://drnelson.uthsc.edu/CytochromeP450.html</ext-link>).</p>", "<p>The Pfam database (<ext-link ext-link-type=\"uri\" xlink:href=\"http://pfam.sanger.ac.uk\">http://pfam.sanger.ac.uk</ext-link>).</p>", "<p>The ExPASy ProtParam tool (<ext-link ext-link-type=\"uri\" xlink:href=\"http://web.ExPASy.org/protparam/\">http://web.ExPASy.org/protparam/</ext-link>).</p>", "<p>The BUSCA (<ext-link ext-link-type=\"uri\" xlink:href=\"http://busca.biocomp.unibo.it/\">http://busca.biocomp.unibo.it/</ext-link>).</p>", "<p>The online website GSDS2.0 (<ext-link ext-link-type=\"uri\" xlink:href=\"http://gsds.gao-lab.org/\">http://gsds.gao-lab.org/</ext-link>).</p>", "<p>The MEME online website (<ext-link ext-link-type=\"uri\" xlink:href=\"http://meme-suite.org/tools/meme\">http://meme-suite.org/tools/meme</ext-link>).</p>", "<p>The PlantCARE website (<ext-link ext-link-type=\"uri\" xlink:href=\"https://bioinformatics.psb.ugent.be/webtools/plantcare/html/\">https://bioinformatics.psb.ugent.be/webtools/plantcare/html/</ext-link>).</p>", "<p>The online STRING database (<ext-link ext-link-type=\"uri\" xlink:href=\"https://string-db.org/\">https://string-db.org/</ext-link>).</p>", "<title>Declarations</title>", "<title>Ethical approval and consent to Participate</title>", "<p id=\"Par43\">The sweet potato materials used in this study were obtained from the College of Coastal Agriculture, Guangdong Ocean University, Guangdong Province, China. The collection and utilization of sweet potato materials, as well as the methods employed in this study, adhere to the guidelines and regulations set forth by relevant institutions, and national, and international standards.</p>", "<title>Consent for publication</title>", "<p id=\"Par44\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par45\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Phylogenetic tree, conserved motif, and gene structure of the <italic>IbCYP</italic> family in sweet potato. <bold>A</bold> A neighbor-joining (NJ) phylogenetic tree of sweet potato protein with 1000 bootstrap replicates was constructed based on the full-length sequence in MEGA11. <bold>B</bold> Distribution of conservative motifs in IbCYP proteins with colored boxes representing motifs 1-10 and scale representing 50 amino acids. <bold>C</bold> The genetic structure of the <italic>IbCYP</italic> gene, including introns (black line), exons (yellow rectangle), and untranslated regions (UTRs, green rectangle), with the scale representing 1 kb</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Conserved domains of sweet potato IbCYP proteins. Alignment of conservative motifs generated by the MEME online website for the 3 protein domains</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Phylogenetic Trees of CYP450 Proteins for Sweet Potato, Capsicum, Salvia miltiorrhiza, tobacco, and Arabidopsis. Arabidopsis CYP450 protein sequences were downloaded from the Cytochrome P450 Homepage website. A phylogenetic tree was constructed by the neighbor-joining method based on MEGA11 with 1000 bootstrap replicates. The tree was divided into 5 families represented by outer rings with different colors, black circles, white circles, black triangles, gray triangles, and white triangles representing the Arabidopsis, sweet potato, tobacco, capsicum, and Salvia miltiorrhiza CYP450 proteins</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Locations of <italic>IbCYP</italic> genes on chromosomes. The basic unit indicated a chromosome length of 5.0 Mb. For each chromosome, the number is labeled on the upper side with red indicating a gene pair with tandem duplication</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Distribution and collinearity of the <italic>IbCYP</italic> gene family in the sweet potato genome. <italic>IbCYPs</italic> labeled with red had collinearity, while those labeled with black had no collinearity. The two rings in the middle represent the gene density of each chromosome. The gray background lines represent a collinear background and the red lines indicate a collinear relationship between <italic>IbCYP</italic> members</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Collinearity analysis of CYP450 proteins in sweet potato among species. The species were Arabidopsis, tomato, pepper, maize, and rice. The red line represents the homologous <italic>CYP450 </italic>gene pair of the plant genome, and the gray line represents the collinear block of the plant genome</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>Distribution of cis-acting elements of the <italic>IbCYP</italic> gene family in sweet potato. Distribution of cis-acting elements identified in the 2000 bp upstream promoter region of the sweet potato <italic>IbCYP</italic> gene</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>The putative transcription factor regulatory network analysis of <italic>IbCYP</italic> genes. <bold>A</bold> Distribution of putative transcription factor regulatory networks of the <italic>IbCYP</italic> gene under salt stress. <bold>B</bold> Distribution of putative transcription factor regulatory networks of the <italic>IbCYP</italic> gene under drought stress. <bold>C</bold> Statistical analysis of the differences in putative transcription factor regulatory networks of the <italic>IbCYP</italic> gene under salt and drought stress</p></caption></fig>", "<fig id=\"Fig9\"><label>Fig. 9</label><caption><p>rotein–protein interaction (PPI) network of significant genes in sweet potato. Nodes represent proteins, central nodes are indicated in red, and black lines indicate interactions between nodes. The darker the color, the more important the protein in the interaction network</p></caption></fig>", "<fig id=\"Fig10\"><label>Fig. 10</label><caption><p>Expression heatmap of the <italic>IbCYP</italic> gene in different tissues of sweet potato. Red and blue indicate the intensity of genes in the heatmap: the more intense the red color is, the higher the gene expression level, while the more intense the blue color is, the lower the gene expression level</p></caption></fig>", "<fig id=\"Fig11\"><label>Fig. 11</label><caption><p>Expression heatmap of\n<italic>IbCYP</italic> in root, stem, and leaf tissues of sweet potato under salt and drought stress. Red and blue indicate the intensity of genes in the heatmap: the more intense the red color is, the higher the gene expression level, while the more intense the blue color is, the lower the gene expression level</p></caption></fig>", "<fig id=\"Fig12\"><label>Fig. 12</label><caption><p>\n<bold>A</bold> Gene expression patterns of <italic>IbCYP</italic> genes under heat stress as determined by RNA-seq. F: fibrous roots; T: tuberous roots; Z: heat-sensitive “Ziluolan”; G: heat-tolerant “Guangshu 87”. <bold>B</bold> Gene expression patterns of <italic>IbCYP</italic> genes under cold stress as determined by RNA-seq. ss: clod-sensitive “Shenshu 28”, lhs: cold-tolerant “Liaohanshu 21”</p></caption></fig>", "<fig id=\"Fig13\"><label>Fig. 13</label><caption><p>Expression analysis of <italic>IbCYP</italic> genes in fibrous roots (FR), stems and leaves of sweet potato under hormones treatment as determined by RNA-seq</p></caption></fig>", "<fig id=\"Fig14\"><label>Fig. 14</label><caption><p>Expression patterns of 11 <italic>IbCYP</italic> genes in different tissues. The x-axes represent different tissues including primary root, pencil root, tuber root, stem, leaf, and flower; the y-axes indicate the relative expression of <italic>IbCYP</italic> genes. The different letters of a, b, c, d, and e indicate significant differences at p\n&lt; 0.05, as determined by one-way ANOVA with SPSS single-factor tests</p></caption></fig>", "<fig id=\"Fig15\"><label>Fig. 15</label><caption><p>Changes in the expression levels of 11 IbCYP genes in different tissues under salt and drought treatments. The different letters of a, b, c, and d indicate significant differences at p &lt; 0.05, as determined by one-way ANOVA with SPSS single-factor tests. <bold>A</bold> Expression of 11 genes in primary roots under salt and drought stress. <bold>B</bold> Expression of 11 genes in stems under salt and drought stress. <bold>C</bold> Expression of 11 genes in leaves under salt and drought stress</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Identification of <italic>IbCYP</italic> genes and analysis of physicochemical properties of proteins in sweet potato</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Gene name</th><th align=\"left\">Accession Number</th><th align=\"left\">Chr</th><th align=\"left\">Size (aa)</th><th align=\"left\">Mv (kD)</th><th align=\"left\">pI</th><th align=\"left\">GRAVY</th><th align=\"left\">Predicted Location</th></tr></thead><tbody><tr><td align=\"left\">IbCYP704A1</td><td align=\"left\">OR359876</td><td align=\"left\">LG14</td><td align=\"left\">534</td><td align=\"left\">61.35</td><td align=\"left\">7.88</td><td align=\"left\">-0.384</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP716D2</td><td align=\"left\">OR359873</td><td align=\"left\">LG9</td><td align=\"left\">471</td><td align=\"left\">53.89</td><td align=\"left\">9.32</td><td align=\"left\">-0.377</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP75B4</td><td align=\"left\">OR359797</td><td align=\"left\">LG12</td><td align=\"left\">634</td><td align=\"left\">71.89</td><td align=\"left\">6.17</td><td align=\"left\">-0.357</td><td align=\"left\">plasma membrane</td></tr><tr><td align=\"left\">IbCYP82D47</td><td align=\"left\">OR359867</td><td align=\"left\">LG11</td><td align=\"left\">873</td><td align=\"left\">98.35</td><td align=\"left\">8.8</td><td align=\"left\">-0.351</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP76G3</td><td align=\"left\">OR359864</td><td align=\"left\">LG9</td><td align=\"left\">563</td><td align=\"left\">64.38</td><td align=\"left\">9.45</td><td align=\"left\">-0.325</td><td align=\"left\">organelle membrane</td></tr><tr><td align=\"left\">IbCYP96A4</td><td align=\"left\">OR359841</td><td align=\"left\">LG1</td><td align=\"left\">509</td><td align=\"left\">59.05</td><td align=\"left\">9.12</td><td align=\"left\">-0.294</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G4</td><td align=\"left\">OR359849</td><td align=\"left\">LG2</td><td align=\"left\">483</td><td align=\"left\">55.42</td><td align=\"left\">8.59</td><td align=\"left\">-0.277</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP76G4</td><td align=\"left\">OR359865</td><td align=\"left\">LG9</td><td align=\"left\">439</td><td align=\"left\">50.33</td><td align=\"left\">9.21</td><td align=\"left\">-0.277</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G1</td><td align=\"left\">OR359848</td><td align=\"left\">LG6</td><td align=\"left\">523</td><td align=\"left\">60.30</td><td align=\"left\">8.55</td><td align=\"left\">-0.272</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP736A2</td><td align=\"left\">OR359869</td><td align=\"left\">LG9</td><td align=\"left\">469</td><td align=\"left\">54.11</td><td align=\"left\">8.77</td><td align=\"left\">-0.254</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G7</td><td align=\"left\">OR359850</td><td align=\"left\">LG3</td><td align=\"left\">468</td><td align=\"left\">53.82</td><td align=\"left\">7.15</td><td align=\"left\">-0.253</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP81Q3</td><td align=\"left\">OR359847</td><td align=\"left\">LG11</td><td align=\"left\">511</td><td align=\"left\">58.19</td><td align=\"left\">7.28</td><td align=\"left\">-0.253</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A1</td><td align=\"left\">OR359826</td><td align=\"left\">LG13</td><td align=\"left\">515</td><td align=\"left\">59.31</td><td align=\"left\">9.26</td><td align=\"left\">-0.247</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP736A4</td><td align=\"left\">OR359823</td><td align=\"left\">LG5</td><td align=\"left\">495</td><td align=\"left\">56.63</td><td align=\"left\">6.66</td><td align=\"left\">-0.245</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP73A1(IbC4H)</td><td align=\"left\">ADB65927.1</td><td align=\"left\">LG12</td><td align=\"left\">505</td><td align=\"left\">58.14</td><td align=\"left\">9.21</td><td align=\"left\">-0.233</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP81Q2</td><td align=\"left\">OR359846</td><td align=\"left\">LG11</td><td align=\"left\">512</td><td align=\"left\">58.19</td><td align=\"left\">8.82</td><td align=\"left\">-0.232</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP84A1</td><td align=\"left\">OR359851</td><td align=\"left\">LG7</td><td align=\"left\">516</td><td align=\"left\">58.52</td><td align=\"left\">6.38</td><td align=\"left\">-0.217</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP89A1</td><td align=\"left\">OR359852</td><td align=\"left\">LG7</td><td align=\"left\">522</td><td align=\"left\">59.43</td><td align=\"left\">8.9</td><td align=\"left\">-0.215</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP734A1</td><td align=\"left\">OR359832</td><td align=\"left\">LG11</td><td align=\"left\">513</td><td align=\"left\">58.66</td><td align=\"left\">7.7</td><td align=\"left\">-0.209</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP85A1</td><td align=\"left\">OR359858</td><td align=\"left\">LG7</td><td align=\"left\">465</td><td align=\"left\">53.16</td><td align=\"left\">9.13</td><td align=\"left\">-0.206</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP88A1</td><td align=\"left\">OR359834</td><td align=\"left\">LG14</td><td align=\"left\">493</td><td align=\"left\">56.84</td><td align=\"left\">8.53</td><td align=\"left\">-0.203</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP90C1</td><td align=\"left\">OR359835</td><td align=\"left\">LG5</td><td align=\"left\">510</td><td align=\"left\">57.59</td><td align=\"left\">9</td><td align=\"left\">-0.203</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A4</td><td align=\"left\">OR359828</td><td align=\"left\">LG13</td><td align=\"left\">520</td><td align=\"left\">59.71</td><td align=\"left\">8.4</td><td align=\"left\">-0.201</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP736A3</td><td align=\"left\">OR359822</td><td align=\"left\">LG5</td><td align=\"left\">503</td><td align=\"left\">57.47</td><td align=\"left\">8.39</td><td align=\"left\">-0.197</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP81Q1</td><td align=\"left\">OR359807</td><td align=\"left\">LG13</td><td align=\"left\">520</td><td align=\"left\">59.26</td><td align=\"left\">8.22</td><td align=\"left\">-0.186</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A7</td><td align=\"left\">OR359857</td><td align=\"left\">LG13</td><td align=\"left\">512</td><td align=\"left\">59.11</td><td align=\"left\">8.86</td><td align=\"left\">-0.185</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP701A1</td><td align=\"left\">OR359820</td><td align=\"left\">LG15</td><td align=\"left\">511</td><td align=\"left\">57.88</td><td align=\"left\">6.31</td><td align=\"left\">-0.184</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP97B1</td><td align=\"left\">OR359843</td><td align=\"left\">LG8</td><td align=\"left\">584</td><td align=\"left\">65.30</td><td align=\"left\">7.53</td><td align=\"left\">-0.184</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D8</td><td align=\"left\">OR359794</td><td align=\"left\">LG13</td><td align=\"left\">498</td><td align=\"left\">56.74</td><td align=\"left\">6.42</td><td align=\"left\">-0.183</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP716D3</td><td align=\"left\">OR359874</td><td align=\"left\">LG1</td><td align=\"left\">455</td><td align=\"left\">51.9</td><td align=\"left\">9.13</td><td align=\"left\">-0.177</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP96A3</td><td align=\"left\">OR359840</td><td align=\"left\">LG1</td><td align=\"left\">519</td><td align=\"left\">60.15</td><td align=\"left\">6.68</td><td align=\"left\">-0.175</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP87A1</td><td align=\"left\">OR359833</td><td align=\"left\">LG8</td><td align=\"left\">479</td><td align=\"left\">54.88</td><td align=\"left\">8.96</td><td align=\"left\">-0.174</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP76C2</td><td align=\"left\">OR359799</td><td align=\"left\">LG1</td><td align=\"left\">499</td><td align=\"left\">56.15</td><td align=\"left\">9.11</td><td align=\"left\">-0.171</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP81Q4</td><td align=\"left\">OR359808</td><td align=\"left\">LG10</td><td align=\"left\">511</td><td align=\"left\">58.41</td><td align=\"left\">8.56</td><td align=\"left\">-0.17</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82F1</td><td align=\"left\">OR359810</td><td align=\"left\">LG4</td><td align=\"left\">514</td><td align=\"left\">58.61</td><td align=\"left\">6.64</td><td align=\"left\">-0.167</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G5</td><td align=\"left\">OR359814</td><td align=\"left\">LG2</td><td align=\"left\">541</td><td align=\"left\">60.85</td><td align=\"left\">6.02</td><td align=\"left\">-0.162</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP97A1</td><td align=\"left\">OR359842</td><td align=\"left\">LG8</td><td align=\"left\">625</td><td align=\"left\">69.92</td><td align=\"left\">6.23</td><td align=\"left\">-0.161</td><td align=\"left\">chloroplast outer membrane</td></tr><tr><td align=\"left\">IbCYP81H1</td><td align=\"left\">OR359805</td><td align=\"left\">LG7</td><td align=\"left\">454</td><td align=\"left\">51.84</td><td align=\"left\">8.85</td><td align=\"left\">-0.161</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A3</td><td align=\"left\">OR359827</td><td align=\"left\">LG8</td><td align=\"left\">524</td><td align=\"left\">59.75</td><td align=\"left\">8.9</td><td align=\"left\">-0.16</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G6</td><td align=\"left\">OR359815</td><td align=\"left\">LG3</td><td align=\"left\">519</td><td align=\"left\">58.68</td><td align=\"left\">8.46</td><td align=\"left\">-0.159</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D4</td><td align=\"left\">OR359790</td><td align=\"left\">LG6</td><td align=\"left\">509</td><td align=\"left\">57.53</td><td align=\"left\">8.77</td><td align=\"left\">-0.159</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP716A1</td><td align=\"left\">OR359860</td><td align=\"left\">LG7</td><td align=\"left\">481</td><td align=\"left\">54.22</td><td align=\"left\">9.17</td><td align=\"left\">-0.156</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP736A1</td><td align=\"left\">OR359855</td><td align=\"left\">LG14</td><td align=\"left\">496</td><td align=\"left\">56.78</td><td align=\"left\">8.06</td><td align=\"left\">-0.148</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP76G1</td><td align=\"left\">OR359844</td><td align=\"left\">LG6</td><td align=\"left\">506</td><td align=\"left\">57.68</td><td align=\"left\">8.14</td><td align=\"left\">-0.148</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D5</td><td align=\"left\">OR359791</td><td align=\"left\">LG6</td><td align=\"left\">505</td><td align=\"left\">56.42</td><td align=\"left\">8.28</td><td align=\"left\">-0.145</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP716D1</td><td align=\"left\">OR359836</td><td align=\"left\">LG2</td><td align=\"left\">483</td><td align=\"left\">55.16</td><td align=\"left\">9.09</td><td align=\"left\">-0.145</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP75B2</td><td align=\"left\">OR359795</td><td align=\"left\">LG8</td><td align=\"left\">514</td><td align=\"left\">58.25</td><td align=\"left\">8.79</td><td align=\"left\">-0.142</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP736A6</td><td align=\"left\">OR359825</td><td align=\"left\">LG15</td><td align=\"left\">502</td><td align=\"left\">56.53</td><td align=\"left\">9.13</td><td align=\"left\">-0.142</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A2</td><td align=\"left\">OR359856</td><td align=\"left\">LG13</td><td align=\"left\">516</td><td align=\"left\">58.91</td><td align=\"left\">7.21</td><td align=\"left\">-0.14</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP83A1</td><td align=\"left\">OR359817</td><td align=\"left\">LG15</td><td align=\"left\">432</td><td align=\"left\">49.44</td><td align=\"left\">6.78</td><td align=\"left\">-0.137</td><td align=\"left\">organelle membrane</td></tr><tr><td align=\"left\">IbCYP714A1</td><td align=\"left\">OR359831</td><td align=\"left\">LG5</td><td align=\"left\">537</td><td align=\"left\">60.82</td><td align=\"left\">9.45</td><td align=\"left\">-0.134</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G3</td><td align=\"left\">OR359813</td><td align=\"left\">LG2</td><td align=\"left\">521</td><td align=\"left\">59.36</td><td align=\"left\">8.31</td><td align=\"left\">-0.132</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP735A1</td><td align=\"left\">OR359871</td><td align=\"left\">LG5</td><td align=\"left\">503</td><td align=\"left\">57.58</td><td align=\"left\">8.46</td><td align=\"left\">-0.129</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP706A1</td><td align=\"left\">OR359853</td><td align=\"left\">LG4</td><td align=\"left\">511</td><td align=\"left\">57.96</td><td align=\"left\">6.52</td><td align=\"left\">-0.128</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP712A1</td><td align=\"left\">OR359821</td><td align=\"left\">LG6</td><td align=\"left\">381</td><td align=\"left\">42.39</td><td align=\"left\">5.52</td><td align=\"left\">-0.124</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP86A1</td><td align=\"left\">OR359861</td><td align=\"left\">LG2</td><td align=\"left\">543</td><td align=\"left\">61.14</td><td align=\"left\">6.77</td><td align=\"left\">-0.124</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A6</td><td align=\"left\">OR359830</td><td align=\"left\">LG13</td><td align=\"left\">514</td><td align=\"left\">58.89</td><td align=\"left\">8.27</td><td align=\"left\">-0.123</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82F2</td><td align=\"left\">OR359811</td><td align=\"left\">LG4</td><td align=\"left\">522</td><td align=\"left\">59.37</td><td align=\"left\">8.22</td><td align=\"left\">-0.122</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP89A2</td><td align=\"left\">OR359819</td><td align=\"left\">LG7</td><td align=\"left\">516</td><td align=\"left\">58.66</td><td align=\"left\">8.4</td><td align=\"left\">-0.121</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82C1</td><td align=\"left\">OR359809</td><td align=\"left\">LG7</td><td align=\"left\">529</td><td align=\"left\">59.99</td><td align=\"left\">7.99</td><td align=\"left\">-0.119</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP79A1</td><td align=\"left\">OR359845</td><td align=\"left\">LG6</td><td align=\"left\">531</td><td align=\"left\">60.16</td><td align=\"left\">8.34</td><td align=\"left\">-0.116</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP75B3</td><td align=\"left\">OR359796</td><td align=\"left\">LG8</td><td align=\"left\">518</td><td align=\"left\">58.98</td><td align=\"left\">9.21</td><td align=\"left\">-0.116</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP81K1</td><td align=\"left\">OR359806</td><td align=\"left\">LG15</td><td align=\"left\">505</td><td align=\"left\">57.80</td><td align=\"left\">5.85</td><td align=\"left\">-0.108</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G8</td><td align=\"left\">OR359816</td><td align=\"left\">LG2</td><td align=\"left\">536</td><td align=\"left\">60.92</td><td align=\"left\">6.9</td><td align=\"left\">-0.105</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP714E1(GAs)</td><td align=\"left\">OQ184947.1</td><td align=\"left\">LG3</td><td align=\"left\">518</td><td align=\"left\">58.04</td><td align=\"left\">7.18</td><td align=\"left\">-0.104</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP716A2</td><td align=\"left\">OR359872</td><td align=\"left\">LG1</td><td align=\"left\">445</td><td align=\"left\">50.23</td><td align=\"left\">8.72</td><td align=\"left\">-0.103</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP736A5</td><td align=\"left\">OR359824</td><td align=\"left\">LG1</td><td align=\"left\">518</td><td align=\"left\">58.41</td><td align=\"left\">7.68</td><td align=\"left\">-0.101</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP96A2</td><td align=\"left\">OR359839</td><td align=\"left\">LG1</td><td align=\"left\">534</td><td align=\"left\">60.43</td><td align=\"left\">8.26</td><td align=\"left\">-0.099</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP76G2</td><td align=\"left\">OR359800</td><td align=\"left\">LG6</td><td align=\"left\">506</td><td align=\"left\">57.01</td><td align=\"left\">8.41</td><td align=\"left\">-0.096</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP706A2</td><td align=\"left\">OR359854</td><td align=\"left\">LG10</td><td align=\"left\">513</td><td align=\"left\">57.63</td><td align=\"left\">7.19</td><td align=\"left\">-0.093</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A8</td><td align=\"left\">OR359870</td><td align=\"left\">LG11</td><td align=\"left\">516</td><td align=\"left\">58.90</td><td align=\"left\">8.73</td><td align=\"left\">-0.09</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP76C1</td><td align=\"left\">OR359798</td><td align=\"left\">LG1</td><td align=\"left\">533</td><td align=\"left\">60.39</td><td align=\"left\">8.73</td><td align=\"left\">-0.087</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP77A1</td><td align=\"left\">OR359801</td><td align=\"left\">LG7</td><td align=\"left\">518</td><td align=\"left\">57.78</td><td align=\"left\">8.84</td><td align=\"left\">-0.082</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP78A1</td><td align=\"left\">OR359866</td><td align=\"left\">LG1</td><td align=\"left\">484</td><td align=\"left\">54.66</td><td align=\"left\">8.65</td><td align=\"left\">-0.079</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G2</td><td align=\"left\">OR359812</td><td align=\"left\">LG5</td><td align=\"left\">537</td><td align=\"left\">60.53</td><td align=\"left\">7.7</td><td align=\"left\">-0.078</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP72A5</td><td align=\"left\">OR359829</td><td align=\"left\">LG13</td><td align=\"left\">519</td><td align=\"left\">59.64</td><td align=\"left\">9.26</td><td align=\"left\">-0.068</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP75B1(IbF3’H)</td><td align=\"left\">MT557577.1</td><td align=\"left\">LG14</td><td align=\"left\">453</td><td align=\"left\">50.27</td><td align=\"left\">8.98</td><td align=\"left\">-0.066</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP707A1</td><td align=\"left\">OR359859</td><td align=\"left\">LG15</td><td align=\"left\">474</td><td align=\"left\">53.71</td><td align=\"left\">9.27</td><td align=\"left\">-0.062</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP83A2</td><td align=\"left\">OR359818</td><td align=\"left\">LG15</td><td align=\"left\">503</td><td align=\"left\">57.80</td><td align=\"left\">8.01</td><td align=\"left\">-0.058</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D3</td><td align=\"left\">OR359789</td><td align=\"left\">LG6</td><td align=\"left\">494</td><td align=\"left\">55.52</td><td align=\"left\">6</td><td align=\"left\">-0.054</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D7</td><td align=\"left\">OR359793</td><td align=\"left\">LG3</td><td align=\"left\">435</td><td align=\"left\">49.05</td><td align=\"left\">5.66</td><td align=\"left\">-0.05</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP94A2</td><td align=\"left\">OR359863</td><td align=\"left\">LG3</td><td align=\"left\">489</td><td align=\"left\">56.3</td><td align=\"left\">8.99</td><td align=\"left\">-0.049</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71A1</td><td align=\"left\">OR359786</td><td align=\"left\">LG8</td><td align=\"left\">458</td><td align=\"left\">52.28</td><td align=\"left\">6.05</td><td align=\"left\">-0.048</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP86A2</td><td align=\"left\">OR359862</td><td align=\"left\">LG5</td><td align=\"left\">542</td><td align=\"left\">61.45</td><td align=\"left\">8.81</td><td align=\"left\">-0.041</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP77B1</td><td align=\"left\">OR359802</td><td align=\"left\">LG14</td><td align=\"left\">508</td><td align=\"left\">57.26</td><td align=\"left\">9.08</td><td align=\"left\">-0.041</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP714E2(GAs)</td><td align=\"left\">OQ184948.1</td><td align=\"left\">LG12</td><td align=\"left\">521</td><td align=\"left\">57.88</td><td align=\"left\">8.77</td><td align=\"left\">-0.039</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP96A1</td><td align=\"left\">OR359838</td><td align=\"left\">LG13</td><td align=\"left\">516</td><td align=\"left\">58.93</td><td align=\"left\">7.61</td><td align=\"left\">-0.037</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D1</td><td align=\"left\">OR359787</td><td align=\"left\">LG6</td><td align=\"left\">512</td><td align=\"left\">57.56</td><td align=\"left\">7.01</td><td align=\"left\">-0.031</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP94C1</td><td align=\"left\">OR359875</td><td align=\"left\">LG11</td><td align=\"left\">507</td><td align=\"left\">57.65</td><td align=\"left\">8.28</td><td align=\"left\">-0.03</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D6</td><td align=\"left\">OR359792</td><td align=\"left\">LG4</td><td align=\"left\">503</td><td align=\"left\">57.09</td><td align=\"left\">8.82</td><td align=\"left\">-0.029</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP71D2</td><td align=\"left\">OR359788</td><td align=\"left\">LG2</td><td align=\"left\">514</td><td align=\"left\">57.72</td><td align=\"left\">6.72</td><td align=\"left\">-0.028</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP94A1</td><td align=\"left\">OR359837</td><td align=\"left\">LG3</td><td align=\"left\">541</td><td align=\"left\">61.01</td><td align=\"left\">8.3</td><td align=\"left\">-0.027</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP82G9</td><td align=\"left\">OR359868</td><td align=\"left\">LG3</td><td align=\"left\">505</td><td align=\"left\">56.55</td><td align=\"left\">6.98</td><td align=\"left\">-0.007</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP78A3</td><td align=\"left\">OR359804</td><td align=\"left\">LG5</td><td align=\"left\">567</td><td align=\"left\">63.88</td><td align=\"left\">8.92</td><td align=\"left\">0.052</td><td align=\"left\">endomembrane system</td></tr><tr><td align=\"left\">IbCYP78A2</td><td align=\"left\">OR359803</td><td align=\"left\">LG8</td><td align=\"left\">536</td><td align=\"left\">59.43</td><td align=\"left\">9.18</td><td align=\"left\">0.075</td><td align=\"left\">endomembrane system</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>The regulation of the <italic>IbCYP</italic> gene under salt and drought stresses</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">down</th><th align=\"left\">up</th><th align=\"left\"/><th align=\"left\">down</th><th align=\"left\">up</th></tr></thead><tbody><tr><td align=\"left\">Under salt stress</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">Under drought stress</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Root</td><td align=\"left\">28</td><td align=\"left\">21</td><td align=\"left\">Root</td><td align=\"left\">22</td><td align=\"left\">9</td></tr><tr><td align=\"left\">Stem</td><td align=\"left\">11</td><td align=\"left\">15</td><td align=\"left\">Stem</td><td align=\"left\">4</td><td align=\"left\">20</td></tr><tr><td align=\"left\">Leaf</td><td align=\"left\">10</td><td align=\"left\">5</td><td align=\"left\">Leaf</td><td align=\"left\">11</td><td align=\"left\">13</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p>\n<italic>MW </italic>Molecular weight, <italic>pI </italic>isoelectric point, <italic>GRAVY </italic>Grand average of hydropathicity score\n</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"12864_2024_9965_MOESM1_ESM.zip\"><caption><p><bold>Additional file 1.</bold></p></caption></media>" ]
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{ "acronym": [], "definition": [] }
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PMC10787478
0
[ "<title>Introduction</title>", "<p id=\"Par5\">With development of the economy and arousal of the attention paid to body stature, there is an increasing sought for early medical treatment of children with short stature. Normally, short stature is defined as a height more than two standard deviations (SD) below the mean height of the reference population matched for age, sex, and pubertal stage [##UREF##0##1##]. This meant that about 2.3% of the population would be diagnosed as short stature. Growth hormone deficiency is a common reason for the short stature of these children with an estimated prevalence of 1 patient per about 4000-10,000 children [##REF##34417587##2##]. To confirm whether growth hormone is lacking in a timely and precise is of great importance, which highly depends on stimulation tests [##REF##27974188##3##].</p>", "<p id=\"Par6\">Clonidine stimulation test (CST) has been seen as a common way to evaluate the ability of children to secrete growth hormone [##REF##11095419##4##]. However, the side effect of this test may be a reduction of blood pressure of the tested children to a dangerous range, which has always been a disturbing problem, leading to headaches, dizziness, bradycardia, and even syncope [##REF##7046065##5##].</p>", "<p id=\"Par7\">Body posture has been confirmed to have effects on blood pressure [##REF##17181675##6##]. Passive leg raising (PLR) used to be recommended as the initial treatment of shock and hypotension [##UREF##1##7##]. This posture refers to raising the legs above cardiac level, with the patient in a supine position, and has been thought to help increase the volume of the returned blood, which may therefore raise the blood pressure as well as the pulse pressure [##REF##11948060##8##]. Due to the possible effect of PLR, some treatment groups in our hospital tried PLR in clinical practice and found that raising half of the bed when a child is taking CST and keeping a child lying on the bed until 4 h after the test began was just the same as PLR. This seemed to be an effective way to deal with hypotension caused by CST. Typically, PLR was thought to be a transient effect, which may only last for a few minutes. However, a meta-analysis indicated that PLR seemed to have long-term effects of increasing cardiac output, which may last for at least 10 min [##REF##23228872##9##]. Also, a study made in Iran indicated that PLR performed 2 min before anesthesia induction and continued for 20 min after tracheal intubation can help decrease the incidence of anesthesia-induced hypotension 20 min after intubation [##REF##29922085##10##]. Although these studies are not relevant to the current study population, they all indicated the potential long-term effects of PLR.</p>", "<p id=\"Par8\">Whether PLR can help reduce the problems of hypotension caused by clonidine has not yet been proven and the best angle to raise the body still needs to be confirmed. Therefore, in this retrospective cross-sectional study, we aimed to find whether postural characteristics, such as PLR, can be used to help relieve the side effects of CST and to find the best angle raised in these tests, which can better relieve the hypotension of the tested children.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par9\">From September 2020 to March 2022, children from several treatment groups who were hospitalized at the Children’s Hospital of Nanjing Medical University to participate in the clonidine stimulation tests were collected in this retrospective cross-sectional study. Only children with a height of two SD below the mean height of the reference population matched for age, sex, and pubertal stage were included in the study. Subjects with SBP higher than 140 mmHg or lower than 65 mmHg and with DBP higher than 100 mmHg or lower than 35 mmHg were excluded. All participants provided written informed consent to have their clinical information analyzed in a clinical study. All in all, we included 1200 children in this study.</p>", "<p id=\"Par10\">Basic systolic and diastolic blood pressure (SBP, DBP) in the supine position were measured by trained nurses. Changes in blood pressure at 1,2,3 and 4 h of the CST were recorded. Pulse pressure (PP) was calculated by using the formula: PP = SBP- DBP. ΔSBP, ΔDBP, and ΔPP were calculated by using the values of blood pressure at each time to minus the values of their baseline blood pressure. The dosage of the clonidine used in the stimulation test was 4 g/kg (no more than 150 g). Blood was drawn every 30 min for four times. The total time of the test was 90 min but the children would be kept lying on beds for at least 4 h for safety.</p>", "<p id=\"Par11\">During the whole test, children were kept lying on their elevated beds and the angles of these beds were set by nurses. Different treatment groups tended to use different angles. According to the angle of the beds they lay on, the tested children were divided into three groups namely the 0° group (N = 346), 20° group (N = 354), and 40° group (N = 500).</p>", "<p id=\"Par12\">Four covariates including age, gender, weight, and the dosage of clonidine were considered in this analysis. One-way ANOVA was used to compare differences in age, weight, the dosage of clonidine, and blood pressure changes one hour after CST began between the three groups. LSD was used as a post hoc test for results with statistically significant differences after One-way ANOVA. The chi-square test was used to compare the difference in gender between the three groups. The t-test was used to compare the differences in blood pressure at two, three, and four hours after CST began between the 20° and 40° groups. All analyses were performed with SPSS statistical software (Version 26.0. Armonk, NY: IBM Corp).</p>" ]
[ "<title>Results</title>", "<p id=\"Par13\">This study included 1200 children from Nanjing, China who were divided into three groups namely 0°, 20°, and 40° groups. The distributions of blood pressure of these three groups at different periods are presented by mean ± SD, percentile, and range in Table ##TAB##0##1##. Generally, drops in blood pressure levels were observed during the first 2 h after CST began, and then from 3 to 4 h after the commencement of CST, blood pressure levels gradually recovered.</p>", "<p id=\"Par14\">\n\n</p>", "<p id=\"Par15\">Age, gender, weight, doses of clonidine, basic SBP, basic DBP, and basic PP at admission were collected to compare the baseline of these three groups. During admission, no statistical differences were found in the distributions of age (P = 0.737), gender (P = 0.658), weight (P = 0.788), doses of clonidine used (P = 0.948), basic SBP (P = 0.293), basic DBP (P = 0.380) and basic PP (P = 0.195) between these three groups (Table ##TAB##1##2##).</p>", "<p id=\"Par16\">\n\n</p>", "<p id=\"Par17\">One hour after the CST began, a decrease in SBP and DBP was observed in all three groups compared with their basic ones while the PP witnessed slight increases (Table ##TAB##2##3##). The results showed that both ΔSBP (P = 0.165) and ΔDBP (P = 0.322) revealed no statistical differences between these three groups. However, ΔPP values (P = 0.001) showed a statistically significant difference. By post hoc comparison, we found that the difference in ΔPP between the 0° and 20° groups (P = 0.001) as well as the difference between the 0° group and 40° group (P = 0.005) were statistically significant. The difference between 20° group and 40° group was statistically insignificant (P = 0.369). This indicated that PLR can affect the patient’s blood pressure during the tests.</p>", "<p id=\"Par18\">\n\n</p>", "<p id=\"Par21\">Table ##TAB##3##4## shows that, two hours after CST began, no statistical differences were found in ΔSBP (P = 0.415), ΔDBP (P = 0.692), and ΔPP (P = 0.209) between the 20° and 40° groups. Then, three hours after CST began, there were also no statistical differences found in ΔSBP (P = 0.579), ΔDBP (P = 0.860), and ΔPP (P = 0.425). When it came to four hours after the commencement of CST, we found statistical differences in ΔPP (P = 0.042) while no statistical differences were found in ΔSBP (P = 0.888) and ΔDBP (P = 0.069). It showed that the ΔPP of the 20° group (1.46 ± 10.05 mmHg) was significantly higher than that of the 40° group (-0.05 ± 11.00 mmHg).</p>", "<p id=\"Par22\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par23\">In this retrospective cross-sectional study, we assessed the change in blood pressure at 1, 2, 3, and 4 h after the commencement of the stimulation tests separately. The result showed that PLR, which meant raising children’s legs above cardiac level can raise the change of their pulse pressure while keeping them in a supine position did not reach this outcome. Compared with elevated children’s legs at an angle of 40°, those who elevated their legs at an angle of 20° can better raise the change of their pulse pressure.</p>", "<p id=\"Par24\">Several research evidence indicate that the decrease in PP may be a risk factor for the death caused by shocks with hypotension. One research on trauma patients indicated that a PP of less than 45 appears to be positively correlated with death in patients with hemorrhagic shock [##UREF##2##11##]. Another study showed a positive association between 30-day mortality and initial PP &lt; 40mmHg in septic shock patients [##REF##37626302##12##]. Low PP seemed to be dangerous for patients in shock with hypotension. This may suggest that raising the change in their pulse pressure might be a good choice to alleviate the possible consequences of the hypotension caused by CST in clinical practice.</p>", "<p id=\"Par25\">The increase in the change of pulse pressure indicates that PLR can prompt the increase of stroke volume, which can be a great help for children with hypotension caused by clonidine. The effect of PLR has already been seen as autotransfusion [##REF##8814487##13##]. Morgan et al. estimated that raising a single leg at an angle of 30° may transfuse approximately 150 mL of blood to the central circulation [##REF##14102941##14##], which may increase the preload of the heart. So, the increase in stroke volume may be explained by the Frank-Starling relationship in normovolemic coronary artery disease patients which meant that the increase of the preload would strengthen cardiac contractility. This effect did not raise diverse attention to relieving hypotension, which may be attributed to its inefficiency in hypovolemic hypotension [##REF##23228872##9##]. However, in normovolemic patients, raising preload can help deal with hypotension [##REF##20517674##15##].</p>", "<p id=\"Par26\">Compared with PLR, another posture called the Trendelenburg position was more widely used in relieving hypotension. PLR and Trendelenburg’s position shared the same theory in increasing stroke volume. They can both increase preload and therefore increase cardiac outcome. Bart et al. reported that PLR seemed to have long-term effects while Trendelenburg’s position only lasted for 1 min. They explained this result by lower baroreceptors and more blood accumulating in the veins, atria, and pulmonary circulation [##REF##23228872##9##]. This gave us theoretical support for choosing PLR as the better posture to deal with the hypotension caused by CST. Another reason for recommending PLR as the better choice was that the Trendelenburg position would be more uncomfortable, which made it quite a challenge for children to keep this posture for 4 h.</p>", "<p id=\"Par27\">However, we are still unable to clearly explain the difference in outcomes between the 20° and 40° groups. The 20° group had a higher change in pulse pressure 4 h after CST began compared with the 40° group. We speculated that this might involve baroreceptors. Raising legs higher, from 20° to 40°, may incur extra gravitational force and hydrostatic pressure on baroreceptors, which may cause a decrease in cardiac activity to offset the effect of autotransfusion caused by PLR [##REF##533742##16##, ##REF##13630839##17##]. In addition, raising children’s legs at an angle of 40° may cause discomfort, which makes it difficult for children to keep this gesture cooperatively. Since we did not monitor children closely, they may change their posture due to discomfort.</p>", "<p id=\"Par28\">Previous studies proposed PLR exert a transient effect on blood pressure and cardiac outcome which commonly lasted less than 45 min [##REF##8814487##13##, ##REF##7069801##18##, ##REF##23117908##19##]. PLR has always been seen as a short-term method used for first aid or as a test for predicting fluid responsiveness. This may explain why few researchers have paid attention to its long-term effects on pulse pressure [##REF##26825952##20##–##REF##32353418##22##]. Our research results indicate the potential of PLR in long-term treatment for strengthening cardiac contractility to alleviate clonidine-induced hypotension. This was consistent with some research, but the quantity of these studies is low and the population sizes involved are small [##REF##23228872##9##, ##REF##29922085##10##]. Our study may be a good supplement for researchers who study the effect of postural characteristics on blood pressure.</p>", "<p id=\"Par29\">Our research has several strengths. Firstly, to the best of our knowledge, this is the first study to use body position in alleviating the hypotension caused by CST. As a treatment, it is easy to implement with few side effects and little cost, which means that it can be easily popularized. Secondly, besides only paying attention to demonstrating the effects of PLR, we further explored the best angle raised for this treatment, which makes this method more practical. Thirdly, we tried to study the long-term effect of this body position which was mostly seen to be only with transient ones.</p>", "<p id=\"Par30\">There are still limitations and deficiencies that need to be improved. Firstly, the participants only stayed in the hospital for about 3 days, which meant that they were not so familiar with the environment. This indicated that the white coat effect might not be excluded. Secondly, when the children were kept lying on their beds, we did not record whether the participants fell asleep and their sleeping time during CST was not recorded either. As sleeping may affect the patient’s blood pressure, these effects cannot be excluded. Thirdly, our study was only a single-center study which meant that this can only reflect the effects on children around Nanjing. This meant that our results may not be generalizable enough. Thus, more evidence is needed to determine whether PLR can alleviate the adverse effects of clonidine-induced hypotension.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par31\">Our result indicates that elevating the foot of the beds of the patients who are undergoing clonidine stimulation tests at an angle of 20° seemed to be a good choice to alleviate the hypotension caused by the tests. Our research may give theoretical support for those who try to utilize passive leg raising or other postural characteristics to deal with the adverse effects of this test.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Clonidine stimulation test has been widely used in the diagnosis of growth hormone deficiency in children with short stature with a high level of reliability. However, it may cause hypotension, which usually appears as headache, dizziness, bradycardia, and even syncope. It is well known that elevating the beds to make patients’ feet above their cardiac level might relieve this discomfort. However, the real efficiency of this method remains to be proved while the best angle for the elevated bed is still unclear.</p>", "<title>Methods</title>", "<p id=\"Par2\">A total of 1200 children with short stature were enrolled in this retrospective cross-sectional study. Age, gender, weight, and basic systolic and diastolic blood pressure were collected. Blood pressure at 1, 2, 3, and 4 h after stimulation tests were recorded. The participants were divided into 3 groups based on the angles of the elevated foot of their beds named 0°, 20°, and 40° groups.</p>", "<title>Results</title>", "<p id=\"Par3\">At one hour after the commencement of the tests, participants lying on the elevated beds showed a higher mean increase on the change of pulse pressure. The difference in the angles of the elevated beds did not show statistical significance compared with those who did not elevate their beds (0.13 vs. 2.83, <italic>P</italic> = 0.001; 0.13 vs. 2.18, <italic>P</italic> = 0.005; 2.83 vs. 2.18, <italic>P</italic> = 0.369). When it came to 4 h after the tests began, participants whose beds were elevated at an angle around 20° had a significantly higher mean increase in the change of pulse pressure values compared with those whose beds were elevated at an angle around 40° (1.46 vs. -0.05, <italic>P</italic> = 0.042).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">Elevating the foot of the beds of the patients who are undergoing clonidine stimulation tests at an angle of 20°might be a good choice to alleviate the hypotension caused by the tests.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We thank all the participants of the study and health staff who provided support for this study.</p>", "<title>Author contributions</title>", "<p>Y. W. and X. W. contributied to the study conception and design. W. Y., S. W., F. M. B. and W. G. contributied to data collection, analysis and interpretation of the data. W. Y. contributied to manuscript drafting. S. W., Wei G., F. M. B., Y. W. and X. W. contributed to the revising of the manuscript. All authors read and approved the manuscript before submission.</p>", "<title>Funding</title>", "<p>No funding was received to assist with the preparation of this manuscript.</p>", "<title>Data availability</title>", "<p>The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par33\">All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was reviewed and approved by the Human Research Ethics Committee of the Children’s Hospital of Nanjing Medical University (ID: 202101014-1). All participants provided written informed consent to have their clinical information analyzed in a clinical study.</p>", "<title>Consent for publication</title>", "<p id=\"Par34\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par32\">The authors declare no competing interests.</p>" ]
[]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Distribution of blood pressure in different positions at different time periods</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">Mean ± SD</th><th align=\"left\">25th</th><th align=\"left\">50th</th><th align=\"left\">75th</th><th align=\"left\">95th</th><th align=\"left\">Range</th></tr></thead><tbody><tr><td align=\"left\">0° (<italic>N</italic> = 346)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> <italic>0 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">104.14 ± 10.15</td><td char=\".\" align=\"char\">97.00</td><td char=\".\" align=\"char\">104.00</td><td char=\".\" align=\"char\">110.00</td><td char=\".\" align=\"char\">121.00</td><td align=\"left\">71–133</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">63.58 ± 9.45</td><td char=\".\" align=\"char\">58.00</td><td char=\".\" align=\"char\">64.00</td><td char=\".\" align=\"char\">70.00</td><td char=\".\" align=\"char\">78.65</td><td align=\"left\">41–96</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">40.57 ± 7.70</td><td char=\".\" align=\"char\">36.00</td><td char=\".\" align=\"char\">40.00</td><td char=\".\" align=\"char\">44.00</td><td char=\".\" align=\"char\">55.00</td><td align=\"left\">22–74</td></tr><tr><td align=\"left\"> <italic>1 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">94.38 ± 8.93</td><td char=\".\" align=\"char\">88.00</td><td char=\".\" align=\"char\">94.00</td><td char=\".\" align=\"char\">99.25</td><td char=\".\" align=\"char\">110.00</td><td align=\"left\">70–126</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">53.68 ± 7.32</td><td char=\".\" align=\"char\">50.00</td><td char=\".\" align=\"char\">52.00</td><td char=\".\" align=\"char\">57.00</td><td char=\".\" align=\"char\">68.00</td><td align=\"left\">36–79</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">40.70 ± 6.97</td><td char=\".\" align=\"char\">36.00</td><td char=\".\" align=\"char\">40.00</td><td char=\".\" align=\"char\">45.00</td><td char=\".\" align=\"char\">52.00</td><td align=\"left\">20–60</td></tr><tr><td align=\"left\">20° (<italic>N</italic> = 354)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 0 h</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">104.18 ± 9.63</td><td char=\".\" align=\"char\">97.75</td><td char=\".\" align=\"char\">104.00</td><td char=\".\" align=\"char\">111.00</td><td char=\".\" align=\"char\">121.00</td><td align=\"left\">83–132</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">62.66 ± 8.74</td><td char=\".\" align=\"char\">56.00</td><td char=\".\" align=\"char\">62.00</td><td char=\".\" align=\"char\">68.00</td><td char=\".\" align=\"char\">78.00</td><td align=\"left\">37–88</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">41.52 ± 7.52</td><td char=\".\" align=\"char\">37.00</td><td char=\".\" align=\"char\">41.00</td><td char=\".\" align=\"char\">46.00</td><td char=\".\" align=\"char\">54.00</td><td align=\"left\">15–68</td></tr><tr><td align=\"left\"> <italic>1 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">95.72 ± 7.93</td><td char=\".\" align=\"char\">90.00</td><td char=\".\" align=\"char\">95.00</td><td char=\".\" align=\"char\">100.00</td><td char=\".\" align=\"char\">110.00</td><td align=\"left\">76–122</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">51.37 ± 8.24</td><td char=\".\" align=\"char\">46.00</td><td char=\".\" align=\"char\">51.00</td><td char=\".\" align=\"char\">56.25</td><td char=\".\" align=\"char\">65.25</td><td align=\"left\">33–77</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">44.35 ± 7.61</td><td char=\".\" align=\"char\">39.00</td><td char=\".\" align=\"char\">44.00</td><td char=\".\" align=\"char\">49.00</td><td char=\".\" align=\"char\">58.00</td><td align=\"left\">21–65</td></tr><tr><td align=\"left\"> <italic>2 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">92.19 ± 9.03</td><td char=\".\" align=\"char\">86.00</td><td char=\".\" align=\"char\">92.00</td><td char=\".\" align=\"char\">97.00</td><td char=\".\" align=\"char\">108.00</td><td align=\"left\">69–127</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">49.58 ± 8.30</td><td char=\".\" align=\"char\">43.00</td><td char=\".\" align=\"char\">49.00</td><td char=\".\" align=\"char\">55.00</td><td char=\".\" align=\"char\">65.25</td><td align=\"left\">30–81</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">42.60 ± 8.02</td><td char=\".\" align=\"char\">37.00</td><td char=\".\" align=\"char\">43.00</td><td char=\".\" align=\"char\">48.00</td><td char=\".\" align=\"char\">55.25</td><td align=\"left\">17–71</td></tr><tr><td align=\"left\"> <italic>3 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">93.62 ± 10.00</td><td char=\".\" align=\"char\">87.00</td><td char=\".\" align=\"char\">93.00</td><td char=\".\" align=\"char\">99.00</td><td char=\".\" align=\"char\">112.00</td><td align=\"left\">62–132</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">50.10 ± 8.52</td><td char=\".\" align=\"char\">44.00</td><td char=\".\" align=\"char\">50.00</td><td char=\".\" align=\"char\">55.00</td><td char=\".\" align=\"char\">67.00</td><td align=\"left\">30–78</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">43.52 ± 8.20</td><td char=\".\" align=\"char\">39.00</td><td char=\".\" align=\"char\">44.00</td><td char=\".\" align=\"char\">48.00</td><td char=\".\" align=\"char\">57.00</td><td align=\"left\">17–72</td></tr><tr><td align=\"left\"> <italic>4 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">96.55 ± 8.98</td><td char=\".\" align=\"char\">91.00</td><td char=\".\" align=\"char\">96.00</td><td char=\".\" align=\"char\">102.00</td><td char=\".\" align=\"char\">112.00</td><td align=\"left\">70–129</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">53.58 ± 8.13</td><td char=\".\" align=\"char\">49.00</td><td char=\".\" align=\"char\">53.00</td><td char=\".\" align=\"char\">59.00</td><td char=\".\" align=\"char\">66.00</td><td align=\"left\">32–85</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">42.98 ± 7.97</td><td char=\".\" align=\"char\">38.00</td><td char=\".\" align=\"char\">43.00</td><td char=\".\" align=\"char\">48.00</td><td char=\".\" align=\"char\">56.00</td><td align=\"left\">20–70</td></tr><tr><td align=\"left\">40° (<italic>N</italic> = 500)</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> <italic>0 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">104.99 ± 10.43</td><td char=\".\" align=\"char\">98.00</td><td char=\".\" align=\"char\">104.00</td><td char=\".\" align=\"char\">112.00</td><td char=\".\" align=\"char\">123.00</td><td align=\"left\">68–138</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">63.51 ± 8.38</td><td char=\".\" align=\"char\">58.00</td><td char=\".\" align=\"char\">63.00</td><td char=\".\" align=\"char\">69.00</td><td char=\".\" align=\"char\">78.95</td><td align=\"left\">42–87</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">41.48 ± 8.62</td><td char=\".\" align=\"char\">36.00</td><td char=\".\" align=\"char\">41.00</td><td char=\".\" align=\"char\">46.00</td><td char=\".\" align=\"char\">56.95</td><td align=\"left\">18–71</td></tr><tr><td align=\"left\"> <italic>1 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">95.95 ± 9.39</td><td char=\".\" align=\"char\">89.00</td><td char=\".\" align=\"char\">95.00</td><td char=\".\" align=\"char\">101.00</td><td char=\".\" align=\"char\">114.00</td><td align=\"left\">76–131</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">52.29 ± 9.58</td><td char=\".\" align=\"char\">46.00</td><td char=\".\" align=\"char\">51.00</td><td char=\".\" align=\"char\">58.00</td><td char=\".\" align=\"char\">70.00</td><td align=\"left\">30–97</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">43.66 ± 8.26</td><td char=\".\" align=\"char\">38.00</td><td char=\".\" align=\"char\">43.00</td><td char=\".\" align=\"char\">48.00</td><td char=\".\" align=\"char\">58.00</td><td align=\"left\">14–77</td></tr><tr><td align=\"left\"> <italic>2 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">93.65 ± 8.46</td><td char=\".\" align=\"char\">88.00</td><td char=\".\" align=\"char\">93.00</td><td char=\".\" align=\"char\">99.00</td><td char=\".\" align=\"char\">109.00</td><td align=\"left\">73–124</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">50.14 ± 8.02</td><td char=\".\" align=\"char\">45.00</td><td char=\".\" align=\"char\">50.00</td><td char=\".\" align=\"char\">55.00</td><td char=\".\" align=\"char\">64.95</td><td align=\"left\">27–89</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">43.52 ± 8.63</td><td char=\".\" align=\"char\">38.00</td><td char=\".\" align=\"char\">43.00</td><td char=\".\" align=\"char\">49.00</td><td char=\".\" align=\"char\">59.00</td><td align=\"left\">8–74</td></tr><tr><td align=\"left\"> <italic>3 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">94.90 ± 9.05</td><td char=\".\" align=\"char\">89.00</td><td char=\".\" align=\"char\">94.00</td><td char=\".\" align=\"char\">100.00</td><td char=\".\" align=\"char\">110.00</td><td align=\"left\">75–153</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">50.81 ± 7.93</td><td char=\".\" align=\"char\">45.00</td><td char=\".\" align=\"char\">50.00</td><td char=\".\" align=\"char\">56.00</td><td char=\".\" align=\"char\">64.00</td><td align=\"left\">32–93</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">44.09 ± 8.17</td><td char=\".\" align=\"char\">39.00</td><td char=\".\" align=\"char\">43.00</td><td char=\".\" align=\"char\">49.00</td><td char=\".\" align=\"char\">59.00</td><td align=\"left\">15–69</td></tr><tr><td align=\"left\"> <italic>4 h</italic></td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">  Systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">97.24 ± 8.04</td><td char=\".\" align=\"char\">92.00</td><td char=\".\" align=\"char\">97.00</td><td char=\".\" align=\"char\">101.00</td><td char=\".\" align=\"char\">112.00</td><td align=\"left\">72–129</td></tr><tr><td align=\"left\">  Diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">55.80 ± 7.02</td><td char=\".\" align=\"char\">50.25</td><td char=\".\" align=\"char\">56.00</td><td char=\".\" align=\"char\">60.00</td><td char=\".\" align=\"char\">67.00</td><td align=\"left\">35–80</td></tr><tr><td align=\"left\">  Pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">41.43 ± 7.76</td><td char=\".\" align=\"char\">37.00</td><td char=\".\" align=\"char\">41.00</td><td char=\".\" align=\"char\">46.00</td><td char=\".\" align=\"char\">54.95</td><td align=\"left\">19–73</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Comparison of age, gender and basal blood pressure in children with different positions at admission</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">0°</th><th align=\"left\">20°</th><th align=\"left\">40°</th><th align=\"left\"><italic>F</italic>/χ<sup>2</sup></th><th align=\"left\">\n<italic>P</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Age (y)</td><td align=\"left\">7.66 ± 2.507</td><td align=\"left\">7.60 ± 2.649</td><td align=\"left\">7.52 ± 2.626</td><td char=\".\" align=\"char\">0.305</td><td char=\".\" align=\"char\">0.737</td></tr><tr><td align=\"left\">Gender</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td char=\".\" align=\"char\">0.838</td><td char=\".\" align=\"char\">0.658</td></tr><tr><td align=\"left\"> Male</td><td align=\"left\">182</td><td align=\"left\">189</td><td align=\"left\">278</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Female</td><td align=\"left\">164</td><td align=\"left\">165</td><td align=\"left\">222</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Weight (kg)</td><td align=\"left\">22.39 ± 7.56</td><td align=\"left\">22.65 ± 7.97</td><td align=\"left\">22.28 ± 7.66</td><td char=\".\" align=\"char\">0.238</td><td char=\".\" align=\"char\">0.788</td></tr><tr><td align=\"left\">Dosage (µg)</td><td align=\"left\">88.69 ± 27.38</td><td align=\"left\">88.91 ± 28.08</td><td align=\"left\">88.29 ± 28.54</td><td char=\".\" align=\"char\">0.053</td><td char=\".\" align=\"char\">0.948</td></tr><tr><td align=\"left\">Diastolic blood pressure (mmHg)</td><td align=\"left\">63.58 ± 9.453</td><td align=\"left\">62.66 ± 8.743</td><td align=\"left\">63.28 ± 8.810</td><td char=\".\" align=\"char\">1.228</td><td char=\".\" align=\"char\">0.293</td></tr><tr><td align=\"left\">Systolic blood pressure (mmHg)</td><td align=\"left\">104.14 ± 10.150</td><td align=\"left\">104.18 ± 9.632</td><td align=\"left\">104.99 ± 10.433</td><td char=\".\" align=\"char\">0.967</td><td char=\".\" align=\"char\">0.380</td></tr><tr><td align=\"left\">Pulse pressure (mmHg)</td><td align=\"left\">40.57 ± 7.704</td><td align=\"left\">41.52 ± 7.523</td><td align=\"left\">41.48 ± 8.619</td><td char=\".\" align=\"char\">1.637</td><td char=\".\" align=\"char\">0.195</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Comparison of blood pressure changes at 1 h after clonidine stimulation test in children with different positions</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">0°</th><th align=\"left\">20°</th><th align=\"left\">40°</th><th align=\"left\">\n<italic>F</italic>\n</th><th align=\"left\">\n<italic>P</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Δ diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-9.90 ± 10.54</td><td char=\"?\" align=\"char\">-11.30 ± 10.93</td><td char=\"?\" align=\"char\">-11.22 ± 11.83</td><td char=\".\" align=\"char\">1.805</td><td char=\".\" align=\"char\">0.165</td></tr><tr><td align=\"left\">Δ systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-9.77 ± 11.498</td><td char=\"?\" align=\"char\">-8.47 ± 10.321</td><td char=\"?\" align=\"char\">-9.03 ± 12.13</td><td char=\".\" align=\"char\">1.135</td><td char=\".\" align=\"char\">0.322</td></tr><tr><td align=\"left\">Δ pulse pressure (mmHg) <sup>*, †, ‡</sup></td><td char=\"?\" align=\"char\">0.13 ± 9.67</td><td char=\"?\" align=\"char\">2.83 ± 9.58</td><td char=\"?\" align=\"char\">2.18 ± 11.30</td><td char=\".\" align=\"char\">6.594</td><td char=\".\" align=\"char\">0.001</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Comparison of blood pressure changes at 2,3 and 4 h after clonidine stimulation test in children with 20° and 40°</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">20°</th><th align=\"left\">40°</th><th align=\"left\">\n<italic>t</italic>\n</th><th align=\"left\">\n<italic>P</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">\n<italic>2 h</italic>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Δ systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-11.99 ± 11.48</td><td char=\"?\" align=\"char\">-11.33 ± 11.80</td><td char=\".\" align=\"char\">-0.815</td><td char=\".\" align=\"char\">0.415</td></tr><tr><td align=\"left\"> Δ diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-13.08 ± 10.83</td><td char=\"?\" align=\"char\">-13.37 ± 10.48</td><td char=\".\" align=\"char\">0.397</td><td char=\".\" align=\"char\">0.692</td></tr><tr><td align=\"left\"> Δ pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">1.08 ± 10.29</td><td char=\"?\" align=\"char\">2.04 ± 11.33</td><td char=\".\" align=\"char\">-1.258</td><td char=\".\" align=\"char\">0.209</td></tr><tr><td align=\"left\">\n<italic>3 h</italic>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Δ systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-10.57 ± 12.48</td><td char=\"?\" align=\"char\">-10.09 ± 12.24</td><td char=\".\" align=\"char\">-0.555</td><td char=\".\" align=\"char\">0.579</td></tr><tr><td align=\"left\"> Δ diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-12.56 ± 11.35</td><td char=\"?\" align=\"char\">-12.70 ± 10.80</td><td char=\".\" align=\"char\">0.176</td><td char=\".\" align=\"char\">0.860</td></tr><tr><td align=\"left\"> Δ pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">2 ± 10.56</td><td char=\"?\" align=\"char\">2.61 ± 11.34</td><td char=\".\" align=\"char\">-0.798</td><td char=\".\" align=\"char\">0.425</td></tr><tr><td align=\"left\">\n<italic>4 h</italic>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Δ systolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-7.63 ± 12.18</td><td char=\"?\" align=\"char\">-7.75 ± 12.32</td><td char=\".\" align=\"char\">0.141</td><td char=\".\" align=\"char\">0.888</td></tr><tr><td align=\"left\"> Δ diastolic blood pressure (mmHg)</td><td char=\"?\" align=\"char\">-9.09 ± 11.66</td><td char=\"?\" align=\"char\">-7.70 ± 9.80</td><td char=\".\" align=\"char\">-1.823</td><td char=\".\" align=\"char\">0.069</td></tr><tr><td align=\"left\"> Δ pulse pressure (mmHg)</td><td char=\"?\" align=\"char\">1.46 ± 10.05</td><td char=\"?\" align=\"char\">-0.05 ± 11.00</td><td char=\".\" align=\"char\">2.039</td><td char=\".\" align=\"char\">0.042</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>*. The difference in pulse pressure changes between 0° group and 20° group was statistically significant (P = 0.001)</p><p>†. The difference in pulse pressure changes between 0° group and 40° group was statistically significant (P = 0.005).</p><p>‡. The difference in pulse pressure changes between 20° group and 40° group was statistically insignificant (P = 0.369).</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Wentao Yang and Shanshan Wang contributed equally to this study and should be regarded as joint first authors.</p></fn></fn-group>" ]
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[{"label": ["1."], "surname": ["World Health"], "given-names": ["O"], "source": ["WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight -for-height and body mass index-for-age : methods and development"], "year": ["2006"], "publisher-loc": ["Geneva"], "publisher-name": ["World Health Organization"]}, {"label": ["7."], "mixed-citation": ["National Conference on Cardiopulmonary R, Emergency Cardiac C. Standards and guidelines for cardiopulmonary resuscitation (CPR) and emergency cardiac care (ECC). Part VIII: Medicolegal considerations and recommendations. JAMA. 1986;255(21):2979-84."]}, {"label": ["11."], "surname": ["Zhu", "Cobb", "Jonas", "Pokorny", "Rani", "Cotner-Pouncy"], "given-names": ["CS", "D", "RB", "D", "M", "T"], "article-title": ["Shock index and pulse pressure as triggers for massive transfusion"], "source": ["J Trauma Acute Care Surg"], "year": ["2019"], "volume": ["87"], "issue": ["1S Suppl 1"], "fpage": ["159"], "lpage": ["S64"], "pub-id": ["10.1097/TA.0000000000002333"]}]
{ "acronym": [ "SD", "CST", "PLR", "SBP", "DBP", "PP" ], "definition": [ "Standard deviations", "Clonidine stimulation test", "Passive leg raising", "Systolic blood pressure", "Diastolic blood pressure", "Pulse pressure" ] }
22
CC BY
no
2024-01-14 23:43:47
BMC Pediatr. 2024 Jan 13; 24:39
oa_package/f0/6b/PMC10787478.tar.gz
PMC10787479
0
[ "<title>Introduction</title>", "<p id=\"Par2\">Reactivating fetal hemoglobin (HbF, α<sub>2</sub>γ<sub>2</sub>) holds a therapeutic target for β-thalassemia and sickle cell disease. Several modulators, such as transcription factors (TFs) BCL11A and LRF, have been uncovered to regulate HbF expression by directly binding to γ-globin promoter [##REF##29610478##1##, ##REF##26816381##2##]. Our previous study also identified the transcription factor ERF as a repressor of HbF that binds to two regulated elements—one located 3.5 kb upstream of <italic>HBG2</italic> and the other 1.5 kb downstream of <italic>HBG1</italic> [##REF##33735615##3##]<italic>.</italic> We found that the hypermethylation-mediated transcriptional inactivation of ERF can reproduce γ-globin in high HbF β-thalassemia patients. However, the molecular mechanism underlying the hypermethylation of the <italic>ERF</italic> prompter in high HbF patients remains unclear. Recently, long noncoding RNAs (lncRNAs) have emerged as critical regulators of gene expression, performing functions in cis or in trans. Such regulators have already been shown to play regulatory roles in normal erythropoiesis and disease conditions, including erythroid cell survival, heme metabolism, globin switching and regulation, etc [##REF##36224385##4##–##REF##35402813##6##]. For example, a lncRNA transcribed from the pseudogene <italic>HBBP1</italic> locus interacts with the TF ELK1 to regulate the expression of γ-globin gene [##REF##33744764##7##]. In addition, HMI-LNCRNA transcribed by <italic>MYB</italic> enhancer region can inhibit HbF expression and delay erythroid maturation [##REF##29227829##8##], but the specific mechanism is not clear. These studies indicate that lncRNAs are involved in the regulation of γ-globin expression, but the mechanism by which lncRNAs regulate γ-globin expression through TFs interaction needs to be further studied. Here, we performed strand-specific RNA-seq analysis of bone marrow (BM)-derived GYPA<sup>+</sup> erythroid cells from 6 β<sup>0</sup>/β<sup>0</sup>-thalassemia patients who were stratified into low- (HbF<sub>L</sub>: 0.1–0.4 g/dL,<italic> n</italic> = 3) and high HbF (HbF<sub>H</sub>: 8.9–9.2 g/dL, <italic>n</italic> = 3) expression groups used in our previous study [##REF##33735615##3##] to screen for differentially expressed lncRNAs (DE-lncRNAs) associated with HbF production and their participation in regulating ERF expression.</p>" ]
[ "<title>Materials and methods</title>", "<title>Patients and RNA sequencing (RNA-seq)</title>", "<p id=\"Par3\">RNA-seq analysis was performed based on the patients in our previous study [##REF##33735615##3##]. These patients were divided into two group (HbF<sub>H</sub>: 8.9–9.2 g/dL, and HbF<sub>L</sub>: 0.1–0.4 g/dL) based on the HbF level. All patients gave the informed consent (Additional file ##SUPPL##0##1##). Differentially expressed lncRNAs (DE-lncRNAs) between HbF<sub>H</sub> and HbF<sub>L</sub> groups of β<sup>0</sup>/β<sup>0</sup>-thalassemia patients were screened according to the following criteria: |log2FoldChange|&gt; 0.5 and probability ≥ 0.8. More details were provided in the Additional file ##SUPPL##0##1##.</p>", "<title>In vitro validation</title>", "<p id=\"Par4\">Coding potential ability of lncRNA <italic>RP11-196G18.23</italic> was performed using open reading frame finder from NCBI and phyloSCF in silico prediction. Subcellular localization of <italic>RP11-196G18.23</italic> in the HUDEP-2 cell line was identified using Fluorescence in situ hybridization (FISH). Chromatin isolation by RNA purification (ChIRP), RNA immunoblotting and RNA immunoprecipitation were employed to detect the interaction among <italic>RP11-196G18.23</italic>, <italic>ERF</italic> promoter and DNA methyltransferases DNMT1and DNMT3A. Chromatin immunoprecipitation (ChIP) was performed to investigate the enrichment of DNMT3A to <italic>ERF</italic> promoter. CRISPR/Cas9 system was used to delete the binding sequences of <italic>RP11-196G18.23</italic> on <italic>ERF</italic> promoter. Bisulfite sequencing was performed to detect methylation level of CpG sites in <italic>ERF</italic> promoter. More details were descried in the Additional file ##SUPPL##0##1##. A two-tailed Student’s <italic>t</italic> test and ANOVA from SPSS v.20 software were used for comparisons between the indicated groups studied. <italic>p</italic> values of less than 0.05 were considered to be statistically significant.</p>" ]
[]
[ "<title><sc>R</sc>esults and discussion</title>", "<p id=\"Par5\">We analyzed the DE-lncRNAs between HbF<sub>H</sub> and HbF<sub>L</sub> groups and identified 62 lncRNAs that showed significant, HbF production-associated alterations. Among them, an HbF-associated upregulated lncRNA <italic>RP11-196G18.23</italic> (LogFC = 0.5 and probability = 0.8; Fig. ##FIG##0##1##A, Additional file ##SUPPL##0##1##: Table S1) was predicted to have binding sites in the <italic>ERF</italic> promoter region using the LongTarget tool (Fig. ##FIG##0##1##B). We then validated the expression of <italic>RP11-196G18.23</italic> in the β<sup>0</sup>/β<sup>0</sup>-thalassemia patients using real-time quantitative reversely transcribed PCR (qRT-PCR) and confirmed that <italic>RP11-196G18.23</italic> expression in the high HbF group was approximately three times higher than that of the low HbF group (Additional file ##SUPPL##0##1##: Fig. S1A). To determine the relationship between <italic>RP11-196G18.23</italic> and <italic>ERF</italic>, we first characterized the protein coding ability and subcellular localization of <italic>RP11-196G18.23</italic>. <italic>RP11-196G18.23</italic> had no protein coding ability, as predicted by in silico analysis (Additional file ##SUPPL##0##1##: Fig. S1B) and an in vitro experiment involving the fusion of open reading frame (ORF) and EGFP (Additional file ##SUPPL##0##1##: Fig. S1C–E), and it was predominantly expressed in the nucleus, as determined by fluorescence in situ hybridization (FISH) (Additional file ##SUPPL##0##1##: Fig. S1F). We then analyzed the public RNA-sequencing data (GSE53983) of CD34<sup>+</sup> HSPCs from Gene Expression Omnibus database (GEO) and observed a negative correlation between <italic>ERF</italic> and <italic>RP11-196G18.23</italic> (Fig. ##FIG##0##1##C). LncRNAs are reported to repress genes by binding to the promoter and recruit DNMTs to mediate the DNA methylation of target regions [##REF##31557618##9##]. In addition, our previously study [##REF##33735615##3##] demonstrated that DNMT3A participates the regulation of ERF. Thus, we hypothesized that <italic>RP11-196G18.23</italic> might mediate <italic>ERF</italic> hypermethylation and downregulation by binding to its promoter, which could be involved in reactivation of <italic>HBG</italic> expression. To validate whether <italic>RP11-196G18.23</italic> could inhibit <italic>ERF</italic> expression by binding to its promoter, we performed ChIRP analysis using <italic>RP11-196G18.23</italic> overexpressed HUDEP-2 cell lysates (Fig. ##FIG##0##1##D). We observed that <italic>RP11-196G18.23</italic> could bind to <italic>ERF</italic>, as demonstrated by qPCR analysis of DNA (Fig. ##FIG##0##1##E) or RNA (Fig. ##FIG##0##1##F) retrieved from <italic>RP11-196G18.23</italic>-ChIRP. We then carried out immunoblotting analysis using anti-DNMT3A and DNMT1 antibodies in HUDEP-2 cells. We observed that <italic>RP11-196G18.23</italic> could bind to DNMT3A but not DNMT1 (Fig. ##FIG##0##1##G, H). Protein retrieved from <italic>RP11-196G18.23</italic>-ChIRP also confirmed this result (F##FIG##0##i##g. ##FIG##0##1##I). ChIP-qPCR analysis of the HUDEP-2 cell lysate confirmed that <italic>RP11-196G18.23</italic> enhanced the recruitment of DNMT3A to the <italic>ERF</italic> promoter region (Fig. ##FIG##0##1##J). These data indicate that lncRNA <italic>RP11-196G18.23</italic> could bind to <italic>ERF</italic> promoter and interact with DNMT3A.</p>", "<p id=\"Par6\">In the nucleus, lncRNAs regulate gene expression by controlling the local chromatin structure or recruiting regulatory molecules to specific loci. A lncRNA <italic>BGLT3</italic> has been reported to regulate γ-globin transcription both in cis and in trans [##REF##35402813##6##]. In cis, BGLT3 gene locus transcriptionally activates fetal γ-globin genes via facilitating chromatin looping between LCR and γ-globin promoters [##REF##36224385##4##]. In trans, BGLT3 interacts with the Mediator complex, such as MED12 on chromatin to aid γ-globin transcriptional assembly [##REF##30150205##10##]. Therefore, we wonder if <italic>RP11-196G18.23</italic> could mediate the <italic>ERF</italic> promoter hypermethylation by recruiting DNMT3A and leads to reactivation of γ-globin. To validate this hypothesis, we overexpressed <italic>RP11-196G18.23</italic> in HUDEP-2 cells and CD34<sup>+</sup> HSPCs (Fig. ##FIG##0##1##D). We observed that the methylation level of <italic>ERF</italic> promoter was significantly increased, while the endogenous <italic>ERF</italic> mRNA and protein levels were decreased both in HUDEP-2 cells (Fig. ##FIG##1##2##A–C) and CD34<sup>+</sup> HSPCs (Fig. ##FIG##1##2##D, E). DNMT3A also enriched in the <italic>ERF</italic> promoter after <italic>RP11-196G18.23</italic> overexpression (F##FIG##0##i##g. ##FIG##0##1##I). More importantly, we observed that <italic>RP11-196G18.23</italic> overexpression could stimulate γ-globin mRNA and protein levels in both HUDEP-2 cells (2.1-fold change relative to the control) (Fig. ##FIG##1##2##B, C) and CD34<sup>+</sup> HSPCs (7.7% of total hemoglobin in <italic>RP11-196G18.23</italic> overexpression CD34<sup>+</sup> HSPCs, compared with 2.0% in control cells) (Fig. ##FIG##1##2##F). However, compared with the effect of major regulators such as BCL11A and LRF on the level of HbF, the effect of <italic>RP11-196G18.23</italic> overexpression on γ-globin reactivation is modest. This is probably due to the indirect effect of <italic>RP11-196G18.23</italic> in regulating γ-globin rather than direct binding to the <italic>HBG</italic> promoter. In addition, there may be some other complexes binding to <italic>ERF</italic> promoter remain to be uncovered. To further determine the association between <italic>RP11-196G18.23</italic> and <italic>ERF</italic> promoter, we disrupted the binding sequences of <italic>RP11-196G18.23</italic> on <italic>ERF</italic> promoter and found that the expression of ERF was significantly increased while the γ-globin was decreased (Fig. ##FIG##1##2##G and Additional file ##SUPPL##0##1##: Figure S2). Our previously study [##REF##33735615##3##] also demonstrated that the expression of ERF was decreased after hypermethylation on <italic>ERF</italic> promoter by site-specific methylation through dCas9-MQ1-sgRNA system, and consequently, the γ-globin expression was increased. Altogether, these results demonstrated that <italic>RP11-196G18.23</italic> could inhibit <italic>ERF</italic> gene expression to reactivate <italic>HBG</italic> expression by recruiting DNMT3A and enhancing <italic>ERF</italic> methylation (Additional file ##SUPPL##0##1##: Figure S3).</p>", "<p id=\"Par7\">In conclusion, our study demonstrated that <italic>RP11-196G18.23</italic> bound to <italic>ERF</italic> promoter and then recruited DNMT3A to mediate hypermethylation of <italic>ERF</italic> promoter, resulting in downregulation of <italic>ERF</italic> and upregulation of γ-globin in patients with high HbF. Our research provides an epigenetic mechanism for the reactivation of fetal γ-globin expression.</p>" ]
[]
[ "<p id=\"Par1\">The mechanism that drives the switch from fetal to adult hemoglobin (Hb) provides a therapeutic target for β-thalassemia. We have previously identified that hypermethylation of transcription factor <italic>ERF</italic> promoter reactivated γ-globin expression. To uncover the mechanism underlying the hypermethylation of <italic>ERF</italic> promoter, we performed RNA sequencing in β<sup>0</sup>/β<sup>0</sup>-thalassemia patients and identified an upregulated long noncoding RNA (<italic>RP11-196G18.23</italic>) associated with HbF production. <italic>RP11-196G18.23</italic> bound to the <italic>ERF</italic> promoter and recruited DNA methyltransferase 3A to promote DNA hypermethylation-mediated ERF downregulation, thereby ameliorating ERF-induced γ-globin inactivation. The identification of <italic>RP11-196G18.23</italic> provides an epigenetic mechanism for the reactivation of fetal γ-globin expression for β-hemoglobinopathies.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13148-023-01614-6.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank Dr. Ryo Kurita and Dr. Yukio Nakamura for providing the HUDEP-2 cells, Qifa Liu and Feijin Chen for providing the CD34<sup>+</sup> HSPCs. We appreciate useful suggestions from Erwei Song and Xichen Bao.</p>", "<title>Author contributions</title>", "<p>XB, CZ and XX designed the study and wrote the paper. XB, ZW, YG, YY and JH performed the experiments and analyzed the data. DC and YZ collected the samples. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study was supported by the National Key R&amp;D Program of China (2018YFA0507800 and 2018YFA0507803), National Natural Science Foundation of China (grant no. 82100136), the Guangzhou Municipal Science and Technology Project (grant no. 202201011361) and Guangdong Basic and Applied Basic Research Foundation (grant no. 2022A1515220207).</p>", "<title>Data availability</title>", "<p>All the data were showed through the whole manuscript and Additional file ##SUPPL##0##1##. Public data (GSE53983) were available in Gene Expression Omnibus database (GEO).</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par8\">Approval for the study was obtained as outlined by the protocol #202201202 approved by Medical Ethics Committee of Guangdong Women and Children Hospital. The study was conducted in accordance with the Declaration of Helsinki.</p>", "<title>Consent to participate</title>", "<p id=\"Par9\">Informed consent was obtained from all the participants prior to the study following presentation of the nature of the procedures.</p>", "<title>Competing interests</title>", "<p id=\"Par10\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>LncRNA <italic>RP11-196G18.23</italic> binds to <italic>ERF</italic> promoter and interacts with DNMT3A. <bold>A</bold> Flowchart of DE-lncRNAs analysis and candidate lncRNAs screening. DE-lncRNAs were analyzed according to log2Ratio &gt; 0.5 and probability &gt; 0.8. LongTarget was used to predict the interactive lncRNAs on <italic>ERF</italic> promoter. <bold>B</bold>\n<italic>RP11-196G18.23</italic> was predicted to bind to the <italic>ERF</italic> promoter shown in the UCSC genome browser. The orange peaks show the binding region of <italic>RP11-196G18.23</italic> in the <italic>ERF</italic> promoter. The number above ‘0’ indicates the maximal number of overlapping triplexes at an address in the region. The shadowed light green bar marks the lncRNA binding sites in the promoter regions. <bold>C</bold> Regression analysis between <italic>ERF</italic> and <italic>RP11-196G18.23</italic> expression based on the data from GEO database (GSE53983). The gray region indicated the 95% confidence interval. <bold>D</bold> Copy number of <italic>RP11-196G18.23</italic> overexpression in HUDEP-2 and CD34<sup>+</sup> HSPCs. <bold>E</bold>, <bold>F</bold> ChIRP analysis of <italic>RP11-196G18.23</italic> interaction with <italic>ERF</italic> in <italic>RP11-196G18.23 OE</italic> HUDEP-2 cells. The retrieved <italic>ERF</italic> DNA (<bold>E</bold>) and RNA (<bold>F</bold>) was quantified by qPCR. <italic>LacZ</italic>, negative control probe. Odd and even, the RP11-196G18.23 probes. ERF p1 and p2, two fragments on <italic>ER</italic>F promoter. <italic>GAPDH</italic>, negative control for qPCR. <bold>G</bold> RIP analysis of interaction of <italic>RP11-196G18.23</italic> with DNMT3A in HUDEP-2 cells. IgG, the control for the specificity of the anti-DNMT3A antibody. <italic>GAPDH</italic>, the negative control. <bold>H</bold> RNA pull-down analysis of specific association of DNMT1 or DNMT3A with lncRNA <italic>RP11-196G18.23</italic> in <italic>RP11-196G18.23</italic> OE HUDEP-2 cells. Non-template control (NTC), negative control. AS, antisense sequence of <italic>RP11-196G18.23</italic>. <bold>I</bold> Western blot analysis of the protein retrieved from <italic>RP11-196G18.23</italic>-ChIRP. <bold>J</bold> ChIP analysis of association of DNMT3A with the <italic>ERF</italic> promoter (p1 and p2 region) was performed using HUDEP-2 cells without (Ctrl) or with <italic>RP11-196G18.23</italic> OE. <italic>MYOD1</italic>, negative control for qPCR. Data are shown as the means ± SEM from at least two independent experiments (*<italic>p</italic> &lt; 0.05; ***<italic>p</italic> &lt; 0.001)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>LncRNA <italic>RP11-196G18.23</italic> mediates <italic>ERF</italic> promoter hypermethylation and leads to reactivation of γ-globin. <bold>A</bold> The <italic>ERF</italic> promoter methylation level examined by clone-seq in HUDEP-2. Each row of eight CpG sites within a group represents a single bisulfite-treated clone with methylated CpGs (●) or unmethylated CpGs (○). <bold>B</bold>, <bold>C</bold> The <italic>ERF</italic> and γ-globin mRNA and protein levels were examined by qPCR (<bold>B</bold>) or Western blotting (<bold>C</bold>) in <italic>RP11-196G18.23</italic> OE HUDEP-2 cells. The band intensities measured by ImageJ were showed underneath each panel. <bold>D</bold> The ERF promoter methylation level in CD34<sup>+</sup> HSPCs. <bold>E, F</bold> The ERF protein level examined by Western blot (<bold>E</bold>) and the Hb F production examined by HPLC <bold>(F</bold>) in CD34<sup>+</sup> HSPCs. <bold>G</bold> qPCR analysis of <italic>ERF</italic> and γ-globin mRNA level in wild type (Ctrl) and RP11-196G18.23 binding sequences disrupted HUDEP-2 cells. Data are shown as the means ± SEM from at least two independent experiments (*<italic>p</italic> &lt; 0.05; ***<italic>p</italic> &lt; 0.001)</p></caption></fig>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13148_2023_1614_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13148_2023_1614_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"13148_2023_1614_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1</bold>. Materials and methods, tables and figures.</p></caption></media>" ]
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{ "acronym": [], "definition": [] }
10
CC BY
no
2024-01-14 23:43:47
Clin Epigenetics. 2024 Jan 13; 16:12
oa_package/35/9c/PMC10787479.tar.gz
PMC10787480
0
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[ "<title>METHODS</title>", "<title>Study Design</title>", "<p>We conducted a quasi-experimental study to investigate the effect of (1) a hospital-based recording intervention that linked PWTB to standard hospital management and referral processes and (2) an alert-and-response patient management intervention to reduce ILTFU among individuals routinely diagnosed with TB. We defined ILTFU as all persons diagnosed with TB (Xpert MTB/RIF positive) for whom there was no evidence of linkage to a public TB treatment facility for TB registration and treatment within 30 days of the date of diagnosis.</p>", "<p>To measure the effect of these interventions, we calculated the relative reduction in ILTFU between the 3-month baseline period (October 2018 to December 2018) and the intervention period (January 2019 to December 2020). Prospective data were collected for both periods.</p>", "<p>Using integrated electronic reports, we identified all persons routinely diagnosed by Xpert MTB/RIF, as per standard of care in South Africa, in the hospital and at primary health care (PHC) facilities and prospectively determined ILTFU.</p>", "<title>Study Setting</title>", "<p>The study was implemented in KwaZulu-Natal (KZN), Gauteng (GP), and the Western Cape (WC) provinces, 3 of the highest TB-burdened provinces in South Africa [##UREF##2##9##]. Study site selection and implementation were in consultation with provincial and district TB program managers. We identified a district within each province: Ugu in KZN, City of Johannesburg in GP, and City of Cape Town in the WC (##SUPPL##0##Supplementary Table 1##, key differences in setting). Two subdistricts within each district were then selected. We liaised with local TB program managers, who used their routine TB data—TB burden and estimated ILTFU among PWTB—to help guide selection of facilities for inclusion. Willingness of subdistrict and facility mangers to be included in the study was also considered.</p>", "<p>In South Africa, TB investigation, diagnosis, and treatment initiation take place at any level of care in the public health care system, but TB reporting systems are maintained at designated TB treatment sites. This includes PHC facilities, where persons with TB receive treatment on an outpatient basis, and specialized TB hospitals, where persons who require hospitalization for TB are treated. PWTB initiated on TB treatment in general hospitals needed to be linked to a PHC facility for recording and continuation of their TB treatment.</p>", "<p>Unique to the WC, the Department of Health houses a provincial health data centre (PHDC) that harmonizes all electronic patient health data from all public sector services in the province, producing a single patient record [##REF##32935043##10##]. The PHDC generates disease-specific reports and, for TB, collates data from laboratory sources (including smear, culture, or Xpert MTB/RIF), pharmacy or clinical records, TB treatment registers, and TB-specific elements recorded in electronic data systems at the PHC or hospital level [##REF##32935043##10##].</p>", "<title>Interventions</title>", "<p>Within each district, we implemented a hospital-recording intervention in 1 subdistrict and an alert-and-response patient management intervention in the second subdistrict (##TAB##0##Table 1##).</p>", "<title>Hospital-Recording Intervention</title>", "<p>Study-appointed data clerks were placed at each hospital and used the routine data system available in the province. In KZN and GP, they used “Xpert Alerts” (a weekly National Health Laboratory Service [NHLS] line list of all people newly diagnosed using the Xpert MTB/RIF ultra-assay). These are sent from NHLS to health district offices for further distribution to health facilities to improve patient management. In the WC, the clerk used the PHDC [##REF##32935043##10##] to identify all newly diagnosed PWTB.</p>", "<p>Lists of newly diagnosed PWTB were shared with hospital staff to confirm whether patients were initiated on treatment in the hospital. There were no additional interventions to assist patients to link to a TB treatment facility once discharged from the hospital, beyond the routine referral mechanisms already in place.</p>", "<title>Alert-and-Response Patient Management Intervention</title>", "<p>Clerks based at the hospitals in the Ray Nkonyeni, Region E, and Khayelitsha subdistricts used Xpert Alerts (KZN/GP) and PHDC (WC) to identify all persons routinely diagnosed with TB at the selected PHC facilities in addition to those identified at the hospital. They monitored linkage and registration at TB treatment facilities for all persons identified with TB. In KZN and GP, they used the electronic TB treatment register (TIER.Net) to check for a TB treatment start date. TIER.Net is an electronic register used to capture patient-level HIV and TB information at the facility level and is integrated with the district health information system (DHIS) for reporting various program data from subdistricts to the national level [##REF##24780511##11##, ##REF##32158556##12##]. In the WC, they used the PHDC to check for evidence of linkage to and registration at a TB treatment facility. All patients eligible to link but with no evidence of linkage were followed up by a short message service (SMS), followed by a phone call and then creating a referral for a community-based health worker (CHW) to do a home visit to facilitate linkage. Persons with TB who had no telephonic details were immediately referred to a CHW. In KZN and GP, SMS messaging and telephone calls were done by data clerks using mobile phones. In the WC, the capabilities within the PHDC enabled SMS messaging initially, and later telephone calls to be made directly via the PHDC.</p>", "<title>Data Collection</title>", "<p>Post intervention, we used the electronic health records to determine ILTFU for the baseline and intervention periods. In KZN and GP, we used matching algorithms to compare individuals with a TB diagnosis against TIER.Net. Linkage to care was confirmed when the PWTB had a TB treatment start date recorded in TIER.Net. Individuals with no TB treatment initiation date or a date &gt;30 days after their date of diagnosis in TIER.Net (TB register) were defined as ILTFU. To account for patient movement between facilities, we searched for PWTB in TIER.Net at the district level for the baseline and intervention periods. To validate the matching algorithm output, data clerks in KZN searched TIER.Net for TB treatment start dates for everyone labeled ILTFU. We were unable to follow this process in GP as permission to access data beyond the subdistrict was not granted beyond the intervention phase. In the WC, linkage to care was confirmed when the PWTB had evidence in the PHDC of accessing a TB treatment facility anywhere in the province for TB treatment within 30 days.</p>", "<p>As LINKEDin was embedded within health services and should reflect the routine TB program, we included data from the period April to June 2020 (coronavirus disease 2019 [COVID-19] lockdown), when study field staff were withdrawn, but routine hospital and PHC activities continued, with restrictions (##SUPPL##0##Supplementary Tables 3–5##, analysis excluding the COVID-19 lockdown period).</p>", "<title>Statistical Analysis</title>", "<p>We conducted a before-and-after analysis comparing ILTFU in the baseline and intervention phases of the study. We calculated the risk of ILTFU in both periods and conducted 1-sided <italic toggle=\"yes\">t</italic> tests to assess if there was a reduction between the baseline and intervention periods. We calculated the relative risk reduction in ILTFU between the intervention and baseline periods equivalent to 1-relative risk. In the WC, through the PHDC, we had data on all PWTB (confirmed and clinical diagnoses) and conducted an additional analysis for the WC (##SUPPL##0##Supplementary Table 2##). SAS software, version 9.4 (SAS Institute Inc., Cary, NC, USA), was used for data analysis.</p>", "<title>Ethics</title>", "<p>The study was approved by the Health Research Ethics Committee at Stellenbosch University (N18/07/069), the University of the Witwatersrand (M190128), and the relevant provincial departments of health. The authors have no conflict of interest to declare.</p>", "<title>Patient Consent</title>", "<p>This study does not include factors necessitating patient consent.</p>" ]
[ "<title>RESULTS</title>", "<p>During the intervention period, there were 1999 PWTB diagnosed in KZN, 5399 in GP, and 9359 in the WC (##TAB##1##Table 2##) at the selected facilities. The proportion of PWTB diagnosed in hospitals was 37.8% in KZN, 29.2% in GP, and 20.7% in the WC, while the proportion of ILTFU diagnosed in the hospital was 42.1% in KZN, 56.8% in GP, and 46.7% in the WC.</p>", "<title>Overall ILTFU Between Baseline and Intervention Periods Across Provinces</title>", "<p>Following the interventions, we found a considerable relative reduction in ILTFU of 42.4% (95% CI, 28.5%–53.7%) in KZN and 22.3% (95% CI, 13.3%–30.4%) in WC. In GP, there was no change in ILTFU (##TAB##1##Table 2##). In the WC, an additional analysis not restricted to Xpert-confirmed TB showed a higher proportion of ILTFU but no difference in the relative reduction of ILTFU compared with the primary analysis (##SUPPL##0##Supplementary Table 2##).</p>", "<title>ILTFU Between the Baseline and Intervention Periods by Subdistricts Across Provinces</title>", "<p>In KZN and WC, the relative reduction in ILTFU appeared greater in subdistricts where the alert-and-response patient management intervention was implemented compared with subdistricts where only the hospital-recording intervention was implemented. The relative reduction in KZN was 49.3% (95% CI, 32.4%–62.0%) vs 32.2% (95% CI, 5.4%–51.4%), and in the WC, it was 34.2% (95% CI, 20.9%–45.3%) vs 13.4% (95% CI, 0.7%–24.4%). In Gauteng, there was no relative reduction in ILTFU (##TAB##2##Table 3##).</p>", "<title>ILTFU in Subdistricts Where the Alert-and-Response Patient Management Intervention Was Implemented</title>", "<p>In subdistricts where the alert-and-response intervention was implemented, there appeared to be greater relative reductions in ILTFU in the PHC facilities surrounding the hospital compared with in the hospital itself (KZN: 56.9%; 95% CI, 41.1%–68.5%; vs 3.4%; 95% CI, –103.7% to 54.2%; and WC: 52.4%; 95% CI, 40.9%–61.7%; reduction vs an increase of 11.6%; 95% CI, –61.4% to 22.9%) (##TAB##3##Table 4##).</p>", "<title>ILTFU in Subdistricts Where Only the Hospital-Recording Intervention Was Implemented</title>", "<p>GJ Crookes Hospital, KZN, had a 40.2% (95% CI, 12.0%–59.4%) relative reduction in ILTFU, while no change was seen in hospitals in GP and the WC. In the PHC facilities surrounding Tygerberg Hospital (WC), there was a relative reduction in ILTFU (24.6%; 95% CI, 9.4%–37.3%) (##TAB##3##Table 4##).</p>" ]
[ "<title>DISCUSSION</title>", "<p>LINKEDin was an operational research study aimed to reduce ILTFU among PWTB in South Africa. With limited data on reducing ILTFU, LINKEDin provides important findings across 3 heterogeneous contexts in South Africa.</p>", "<p>We demonstrated successful reductions in ILTFU in KZN (from 24.8% to 14.3%) and the WC (from 22.4% to 17.4%). The study was implemented in rural subdistricts of KZN, where PHC facilities are further apart, and we hypothesize that PWTB may be more likely to access services within their communities, closest to their homes, where they are known. This may have made these persons easier to track. This, together with the much lower numbers of PWTB, compared with GP and the WC, may have made the manual process of tracking individuals easier and played a role in the reduction in ILTFU observed in KZN. In the WC, the PHDC enabled us to evaluate linkage beyond the district. This is especially important in South Africa, where there is frequent movement of people within and across provinces [##REF##22956415##13##].</p>", "<p>We did not show a reduction in ILTFU in GP overall (from 31.7% to 32.8%). This was potentially driven by the increase in ILTFU by 8.8% in Region D (the subdistrict where we implemented the hospital-recording intervention at the Chris Hani Baragwanath Academic Hospital [CHBAH], a large tertiary-level hospital). The numbers of PWTB in this subdistrict were much higher compared with those in Region E (subdistrict where the alert-and-response patient management intervention was implemented) and where we did find a relative reduction in ILTFU of 10.3%. The disparity across settings makes it extremely difficult to compare results across provinces. What is important to note is that irrespective of geographical location or access to automation, systematically identifying persons with TB and following them up using the data and systems available in each setting can reduce ILTFU.</p>", "<p>There was a tendency toward a greater reduction in ILTFU in settings where the alert-and-response intervention was implemented compared with settings where the hospital-recording intervention was implemented. This implies that while there is some benefit to registering persons with TB in the hospital, additional patient-centered interventions to follow up with PWTB who fail to link to care soon after their diagnosis or discharge from hospital are vital. Previous studies that addressed patient referral and education [##UREF##3##14##] and combined patient education and telephonic follow-up [##REF##32368523##15##] showed improved linkages from hospitals. For sustained impact, an emphasis on health system interventions that support existing services rather than activities that are externally supported are needed.</p>", "<p>ILTFU was higher at hospitals (range, 21.2%–63.9%) compared with PHC facilities (range, 11.5%–23.8%). This is consistent with earlier work in South Africa, which showed that ILTFU was high (between 37% and 50%) among people diagnosed with TB in hospitals [##UREF##4##16##, ##REF##26392930##17##]. Gamalakhe CHC (ILTFU was 11.5%) was used as a proxy for a hospital but is not comparable to other study hospitals, as the referral process to Gamalakhe CHC is more like a PHC facility referral process.</p>", "<p>Reducing ILTU in hospitals is extremely challenging, and LINKEDin could not fully address this challenge, irrespective of the size or level of the hospital. ILTFU is specifically higher at tertiary-level hospitals where the number of people diagnosed with TB is considerably higher than at district-level hospitals. At CHBAH and Tygerberg hospitals, there were 1167 and 1132 people diagnosed with TB, respectively, during the intervention period, compared with 345 at GJ Crookes. ILTFU at CHBAH and Tygerberg was 63.9% and 45%, respectively, during the intervention period, compared with 21.2% at GJ Crookes. Previous studies have observed a similar phenomenon, whereby ILTFU is more likely at high-volume facilities [##REF##29587651##18##] and in high-burden settings [##REF##19843298##19##]. Previous data from Chris Hani Baragwaneth in 2001 demonstrated that only half of the TB patients referred to PHC facilities attended services within 2 weeks [##UREF##4##16##] and, following an intervention between 2003 and 2005, that &gt;90% attended the PHC facility with the help of research staff [##UREF##3##14##]. Our findings differed as we only implemented the hospital-recording intervention at some hospitals and encountered additional complexities within the alert-and-response intervention. Studies in hospitals have shown high workload, staff shortages, and inadequate skills, resulting in insufficient information and health education for persons with TB and their caregivers [##REF##31532797##20##], as well as a fragmented hospital information system without linkages [##REF##29370162##21##], resulting in less-than-optimal linkage to care.</p>", "<p>People diagnosed in the hospital are often sicker, diagnosed late, and therefore more likely to die before they link to a PHC facility [##REF##24623906##6##]. They may also not have accessed a PHC facility previously and be unfamiliar with access to community-level care, thereby delaying linkage. Interventions to promote earlier diagnosis in primary health care are needed. An additional exacerbating factor is that a proportion of PWTB are discharged before their positive TB test result is known, with no systematic process at the hospital level for recall. Improved communication from hospital staff with an emphasis on navigating the organizational barriers in the health system is required to support better linkage for these patients [##REF##36160718##22##, ##UREF##5##23##]. Future work that differentiates the point of diagnosis within the hospital (outpatient vs in-patient) and offers tailored engagement, as reported in a recent cohort from China [##REF##37181365##24##], to PWTB and/or their caregivers during or before discharge is key. The South African Department of Health has launched the National Health Hotline (The National health hotline was implemented after preliminary data from the LINKEDin study showed promise that systematic follow up of TB patients could reduce ILTFU. The hotline is an independent intervention, implemented by NDoH, but not part of the LINKEDin study), which aims to improve contact with persons who test positive, trace, or unsuccessful for TB Xpert through communication of test results and improving linkage to care for access to treatment at a health facility. Having correct patient contact details is vital for the success of any intervention that promotes linkage [##REF##29523100##25##], irrespective of setting, level of care, or patient volume.</p>", "<title>Practical Recommendations</title>", "<p>The challenge of ILTFU can be addressed using setting-specific programmatic data to systematically identify and follow persons diagnosed with TB. This should be done using existing personnel and be embedded within the existing health system interventions. It is important that interventions to reduce ILTFU be part of the routine monitoring and evaluation of TB programs [##REF##32368520##26##]. We recommend updating patient contact details at every health visit to ensure that patients who require additional support with linkage can be easily traced [##REF##36160718##22##].</p>", "<p>Interventions to address ILTFU should be prioritized for hospital-diagnosed patients. We recommend person-centered communication between the health care provider and the patient before discharge that includes practical advice on where and how to access a PHC facility for treatment and offers the PWTB an opportunity to ask questions and better understand their disease [##REF##34797855##27##].</p>", "<p>A major strength of our study was the implementation of interventions in diverse geographical and health care settings, embedded within the routine TB program. The use of existing resources within this operational research study demonstrates the feasibility of implementing the interventions. Despite varying reductions in ILTFU, we reported a notable reduction in ILTFU in 2 settings between the baseline and intervention periods.</p>", "<p>A before-and-after study is vulnerable to temporal and other changes beyond the intervention, and we cannot attribute the successes solely to our interventions. The variation in sample sizes is a limitation for comparability across the settings. This, combined with the small changes in ILTFU in some settings, resulted in significant statistical uncertainty around some of the relative reduction estimates.</p>", "<p>A limitation in our definition was that persons with TB who linked 30 days after diagnosis were categorized as ILTFU, irrespective of where they were diagnosed. This may have overestimated ILTFU. Further analysis is planned to address the time to linkage.</p>", "<p>In Gauteng, we could not search for patients reported as ILTFU in the baseline or intervention periods in other subdistricts, as had been done in the other provinces. This has likely resulted in an overestimation of ILTFU and an underestimation of relative reductions in ILTFU in Gauteng.</p>", "<p>We experienced severe limitations during the COVID-19 pandemic. For a quarter of 2020, no study staff were in place, and all study activities were suspended. Routine clinic activities continued, with many resources redirected away from TB toward COVID-19 services. We conducted an analysis excluding the period when there were no study staff in the field and saw no significant difference in the primary analysis (##SUPPL##0##Supplementary Tables 3–5##). Finally, we could not determine the wider impact of these interventions toward reducing community transmission; this presents an opportunity for further research, for example, modeling.</p>", "<p>LINKEDin was embedded within routine health services and aimed to reduce ILTFU in 3 diverse settings in South Africa. The findings provide important lessons in each setting. By identifying all persons newly diagnosed with TB using existing routine health service data and applying a consistent intervention to trace and recall those not linked to care following diagnosis, we demonstrated an overall reduction in ILTFU of 49% in KZN and 34% in the WC. TB programs must consider ILTFU a priority and develop interventions specific to their settings. The use of operational research to test ILTFU interventions would address the contextual complexity in different settings. Unless there is a shift to include all persons diagnosed with TB in the routine reporting of TB, the TB treatment cohort will continue to exclude ILTFU.</p>" ]
[]
[ "<p>\n<bold>\n<italic toggle=\"yes\">Potential conflicts of interest</italic>.</bold> All authors report no potential conflicts.</p>", "<title>Abstract</title>", "<p>Every person diagnosed with tuberculosis (TB) needs to initiate treatment. The World Health Organization estimated that 61% of people who developed TB in 2021 were included in a TB treatment registration system. Initial loss to follow-up (ILTFU) is the loss of persons to care between diagnosis and treatment initiation/registration. LINKEDin, a quasi-experimental study, evaluated the effect of 2 interventions (hospital recording and an alert-and-response patient management intervention) in 6 subdistricts across 3 high–TB burden provinces of South Africa. Using integrated electronic reports, we identified all persons diagnosed with TB (Xpert MTB/RIF positive) in the hospital and at primary health care facilities. We prospectively determined linkage to care at 30 days after TB diagnosis. We calculated the risk of ILTFU during the baseline and intervention periods and the relative risk reduction in ILTFU between these periods. We found a relative reduction in ILTFU of 42.4% (95% CI, 28.5%–53.7%) in KwaZulu Natal (KZN) and 22.3% (95% CI, 13.3%–30.4%) in the Western Cape (WC), with no significant change in Gauteng. In KZN and the WC, the relative reduction in ILTFU appeared greater in subdistricts where the alert-and-response patient management intervention was implemented (KZN: 49.3%; 95% CI, 32.4%–62%; vs 32.2%; 95% CI, 5.4%–51.4%; and WC: 34.2%; 95% CI, 20.9%–45.3%; vs 13.4%; 95% CI, 0.7%–24.4%). We reported a notable reduction in ILTFU in 2 provinces using existing routine health service data and applying a simple intervention to trace and recall those not linked to care. TB programs need to consider ILTFU a priority and develop interventions specific to their context to ensure improved linkage to care.</p>" ]
[ "<p>Tuberculosis (TB) is the leading cause of death from a single infectious disease [##UREF##0##1##]. In the END TB strategy, all member states of the World Health Organization (WHO) committed to a world free of TB, to be achieved through reductions in TB incidence, mortality, and the catastrophic costs faced by TB-affected households [##UREF##1##2##]. A pillar of this strategy included integrated, patient-centred care and prevention, with an emphasis on early diagnosis and treatment of all people with TB [##UREF##1##2##].</p>", "<p>After accessing TB tests, every person with TB (PWTB) needs to receive their results, initiate TB treatment, and be recorded in a TB reporting system to enable accurate surveillance and monitoring and evaluation of TB care. Initial loss to follow-up (ILTFU) has been defined as the loss of persons to care following their diagnosis of TB, before their inclusion in a TB reporting system. People who are ILTFU are at elevated risk of morbidity and mortality [##REF##34125843##3##, ##REF##33206650##4##], and untreated disease contributes to ongoing transmission of <italic toggle=\"yes\">Mycobacterium tuberculosis</italic> [##REF##34125843##3##, ##REF##27887646##5##]. In 2021, 39% (4.2 million people) of those who developed TB were not treated and/or not recorded in a TB registration system [##UREF##0##1##]. ILTFU is estimated to be between 4% and 38% globally, 18% in Africa [##REF##24623906##6##] and 17.1% in South Africa [##REF##29117342##7##].</p>", "<p>South Africa is a high–TB burden country, with an estimated incidence of 304 000 TB cases in 2021, with &gt;120 000 either not diagnosed or not included in routine reporting [##UREF##0##1##]. In South Africa, 12% of persons with drug-susceptible TB [##REF##29117342##7##] and 37% of persons with drug-resistant TB [##REF##28222095##8##] are lost between diagnosis and TB registration. Reducing ILTFU in South Africa is a priority to improve TB control. Interventions addressing ILTFU could have a substantial impact on the TB epidemic. These persons have accessed health care services and have a laboratory-confirmed diagnosis of TB, yet have not been linked to a TB treatment facility for registration and initiation of treatment. Few studies have evaluated interventions addressing ILTFU across diverse settings. The LINKEDin study evaluated the effect of 2 interventions to reduce ILTFU at the hospital and primary health care facility levels in 3 high-burden provinces in South Africa.</p>", "<title>Supplementary Material</title>" ]
[ "<title>Acknowledgments</title>", "<p>We wish to acknowledge our implementing partners: Interactive Research and Development South Africa (IRD SA) in KwaZulu-Natal Province, Right to Care in Gauteng Province, and the University of Cape Town and the Centre for Infectious Disease Epidemiology and Research (CIDER) in the Western Cape Province. We further acknowledge the staff at the Western Cape Provincial Health Data Centre (PHDC) for their invaluable assistance, especially Alexa Heekes and Catherine Rode. We highly appreciate input from the health staff at the provincial, district, and subdistrict health offices and at the facilities in which the study was implemented.</p>", "<p>\n<bold>\n<italic toggle=\"yes\">Author contributions</italic>.</bold> M.O., S.M., P.N., A.v.D., and A.C.H. designed the study. M.O., S.M., A.v.D., and F.M.M. developed the implementation plan for the study. M.O., S.M., A.v.D., R.D., L.C., J.C., and A.B. oversaw data collection, extraction, and validation. All authors provided critical input for the interpretation of data and contextualization of results. S.M. and M.O. produced the first draft of the manuscript. All authors reviewed the manuscript and provided critical input. All authors have reviewed the final version of the manuscript and approve of its content and submission for publication.</p>", "<p>\n<bold>\n<italic toggle=\"yes\">Financial support</italic>.</bold> This research and publication were supported by the Bill and Melinda Gates Foundation (BMGF), INV- 007130. The contents are the responsibility of the authors and do not necessarily reflect the views of the BMGF. A.C.H. is financially supported by the South African National Research Foundation (NRF) through a South African Research Chairs Initiative (SARChI). The financial assistance of the NRF toward this research is hereby acknowledged. Opinions expressed, and conclusions arrived at, are those of the authors and are not necessarily to be attributed to the NRF. K.D.P. is supported by the Fogarty International Center of the National Institutes of Health under Award Number K43TW011006. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. G.H. receives financial assistance from the European Union (Grant No. DCI-PANAF/2020/420-028) through the African Research Initiative for Scientific Excellence (ARISE) pilot program. ARISE is implemented by the African Academy of Sciences with support from the European Commission and the African Union Commission. The contents of this document are the sole responsibility of the authors and can under no circumstances be regarded as reflecting the position of the European Union, the African Academy of Sciences, or the African Union Commission.</p>", "<title>Supplementary Data</title>", "<p>\n##SUPPL##0##Supplementary materials## are available at <italic toggle=\"yes\">Open Forum Infectious Diseases</italic> online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.</p>" ]
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[ "<table-wrap position=\"float\" id=\"ofad648-T1\"><label>Table 1.</label><caption><p>Health Facilities per Intervention Type by District and Subdistrict Included in the LINKEDin Study</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">District</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Subdistrict Name</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Intervention Type</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Hospital</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">PHC TB Treatment Facilities</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">Ugu (KZN)</td><td rowspan=\"1\" colspan=\"1\">Umdoni</td><td rowspan=\"1\" colspan=\"1\">Hospital recording</td><td rowspan=\"1\" colspan=\"1\">GJ Crookes (district hospital, ∼300 beds)</td><td rowspan=\"1\" colspan=\"1\">N/A</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Ray Nkonyeni</td><td rowspan=\"1\" colspan=\"1\">Alert-and-response patient management</td><td rowspan=\"1\" colspan=\"1\">Gamalakhe<sup><xref rid=\"tblfn2\" ref-type=\"table-fn\">a</xref></sup> (CHC)</td><td rowspan=\"1\" colspan=\"1\">10 surrounding PHC facilities</td></tr><tr><td rowspan=\"1\" colspan=\"1\">City of Johannesburg (GP)</td><td rowspan=\"1\" colspan=\"1\">Region D</td><td rowspan=\"1\" colspan=\"1\">Hospital recording</td><td rowspan=\"1\" colspan=\"1\">Chris Hani Baragwanath (tertiary hospital, ∼3200 beds)</td><td rowspan=\"1\" colspan=\"1\">N/A</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Region E</td><td rowspan=\"1\" colspan=\"1\">Alert-and-response patient management</td><td rowspan=\"1\" colspan=\"1\">Edenvale (district hospital, ∼230 beds)</td><td rowspan=\"1\" colspan=\"1\">9 surrounding PHC facilities</td></tr><tr><td rowspan=\"1\" colspan=\"1\">City of Cape Town (WC)</td><td rowspan=\"1\" colspan=\"1\">Tygerberg</td><td rowspan=\"1\" colspan=\"1\">Hospital recording</td><td rowspan=\"1\" colspan=\"1\">Tygerberg (tertiary hospital ∼1899 beds)</td><td rowspan=\"1\" colspan=\"1\">N/A</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Khayelitsha</td><td rowspan=\"1\" colspan=\"1\">Alert-and-response patient management</td><td rowspan=\"1\" colspan=\"1\">Khayelitsha (district hospital, ∼230 beds)</td><td rowspan=\"1\" colspan=\"1\">13 surrounding PHC facilities</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"ofad648-T2\"><label>Table 2.</label><caption><p>Relative Reduction in ILTFU Between Baseline and Intervention Periods per Province</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"1\"/><th align=\"center\" colspan=\"2\" rowspan=\"1\">Oct–Dec 2018</th><th align=\"center\" colspan=\"2\" rowspan=\"1\">Jan 2019–Dec 2020</th><th align=\"center\" rowspan=\"2\" colspan=\"1\">Relative Reduction ILTFU (95% CI), %</th></tr><tr><th align=\"center\" rowspan=\"1\" colspan=\"1\">Newly Diagnosed PWTB, No.</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">ILTFU, No. (%) (95% CI, %)</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Newly Diagnosed PWTB, No.</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">ILTFU, No. (%) (95% CI, %)</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">KwaZulu-Natal</td><td rowspan=\"1\" colspan=\"1\">327</td><td rowspan=\"1\" colspan=\"1\">81 (24.8) (20.1–29.4)</td><td rowspan=\"1\" colspan=\"1\">1999</td><td rowspan=\"1\" colspan=\"1\">285 (14.3) (12.7–15.8)</td><td rowspan=\"1\" colspan=\"1\">42.4 (28.5–53.7)</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Gauteng</td><td rowspan=\"1\" colspan=\"1\">921</td><td rowspan=\"1\" colspan=\"1\">292 (31.7) (28.7–34.7)</td><td rowspan=\"1\" colspan=\"1\">5399</td><td rowspan=\"1\" colspan=\"1\">1772 (32.8) (31.6–34.1)</td><td rowspan=\"1\" colspan=\"1\">−3.5 (−14.7 to 6.5)</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Western Cape</td><td rowspan=\"1\" colspan=\"1\">1323</td><td rowspan=\"1\" colspan=\"1\">296 (22.4) (20.1–24.6)</td><td rowspan=\"1\" colspan=\"1\">9359</td><td rowspan=\"1\" colspan=\"1\">1627 (17.4) (16.6–18.2)</td><td rowspan=\"1\" colspan=\"1\">22.3 (13.3–30.4)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"ofad648-T3\"><label>Table 3.</label><caption><p>Relative Reduction in ILTFU Between Baseline and Intervention Periods by Subdistricts Across Provinces</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" colspan=\"2\" rowspan=\"2\"/><th align=\"center\" colspan=\"2\" rowspan=\"1\">Oct–Dec 2018</th><th align=\"center\" colspan=\"2\" rowspan=\"1\">Jan 2019–Dec 2020</th><th align=\"center\" rowspan=\"2\" colspan=\"1\">Relative Reduction ILTFU (95% CI), %</th><th align=\"center\" rowspan=\"2\" colspan=\"1\">\n<italic toggle=\"yes\">P</italic> Value 1-Sided <italic toggle=\"yes\">T</italic> Test<sup><xref rid=\"tblfn4\" ref-type=\"table-fn\">a</xref></sup></th></tr><tr><th align=\"center\" rowspan=\"1\" colspan=\"1\">Newly Diagnosed Persons With TB, No.</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">ILTFU, No. (%) (95% CI, %)</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Newly Diagnosed Persons With TB, No.</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">ILTFU, No. (%) (95% CI, %)</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">KwaZulu Natal</td><td rowspan=\"1\" colspan=\"1\">Umdoni (hospital recording)</td><td rowspan=\"1\" colspan=\"1\">131</td><td rowspan=\"1\" colspan=\"1\">33 (25.2) (17.8–32.6)</td><td rowspan=\"1\" colspan=\"1\">790</td><td rowspan=\"1\" colspan=\"1\">135 (17.1) (14.5–19.7)</td><td rowspan=\"1\" colspan=\"1\">32.2 (5.4–51.4)</td><td rowspan=\"1\" colspan=\"1\">.0131</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Ray Nkonyeni (alert and response)</td><td rowspan=\"1\" colspan=\"1\">196</td><td rowspan=\"1\" colspan=\"1\">48 (24.5) (18.5–30.5)</td><td rowspan=\"1\" colspan=\"1\">1209</td><td rowspan=\"1\" colspan=\"1\">150 (12.4) (10.5–14.3)</td><td rowspan=\"1\" colspan=\"1\">49.3 (32.4–62)</td><td rowspan=\"1\" colspan=\"1\">&lt;.0001</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Gauteng</td><td rowspan=\"1\" colspan=\"1\">Region D (hospital recording)</td><td rowspan=\"1\" colspan=\"1\">713</td><td rowspan=\"1\" colspan=\"1\">208 (29.2) (25.8–32.5)</td><td rowspan=\"1\" colspan=\"1\">4099</td><td rowspan=\"1\" colspan=\"1\">1301 (31.7) (30.3–33.2)</td><td rowspan=\"1\" colspan=\"1\">−8.8 (−23.0 to 3.8)</td><td rowspan=\"1\" colspan=\"1\">.9170</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Region E (alert and response)</td><td rowspan=\"1\" colspan=\"1\">208</td><td rowspan=\"1\" colspan=\"1\">84 (40.4) (33.7–47.1)</td><td rowspan=\"1\" colspan=\"1\">1300</td><td rowspan=\"1\" colspan=\"1\">471 (36.2) (33.6–38.8)</td><td rowspan=\"1\" colspan=\"1\">10.3 (−7.4 to 25.1)</td><td rowspan=\"1\" colspan=\"1\">.1288</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Western Cape</td><td rowspan=\"1\" colspan=\"1\">Tygerberg (hospital recording)</td><td rowspan=\"1\" colspan=\"1\">761</td><td rowspan=\"1\" colspan=\"1\">185 (24.3) (21.3–27.4)</td><td rowspan=\"1\" colspan=\"1\">5095</td><td rowspan=\"1\" colspan=\"1\">1073 (21.1) (19.9–22.2)</td><td rowspan=\"1\" colspan=\"1\">13.4 (.7–24.4)</td><td rowspan=\"1\" colspan=\"1\">.0251</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Khayelitsha (alert and response)</td><td rowspan=\"1\" colspan=\"1\">562</td><td rowspan=\"1\" colspan=\"1\">111 (19.8) (16.5–23.0)</td><td rowspan=\"1\" colspan=\"1\">4264</td><td rowspan=\"1\" colspan=\"1\">554 (13) (12.0–14.0)</td><td rowspan=\"1\" colspan=\"1\">34.2 (20.9–45.3)</td><td rowspan=\"1\" colspan=\"1\">&lt;.0001</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"ofad648-T4\"><label>Table 4.</label><caption><p>Relative Reduction in ILTFU Between Baseline and Intervention Periods by Place of Diagnosis for Subdistricts by Intervention Type</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/><col align=\"center\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" colspan=\"2\" rowspan=\"2\"/><th align=\"center\" colspan=\"2\" rowspan=\"1\">Oct–Dec 2018</th><th align=\"center\" colspan=\"2\" rowspan=\"1\">Jan 2019–Dec 2020</th><th align=\"center\" rowspan=\"2\" colspan=\"1\">Relative Reduction ILTFU (95% CI), %</th><th align=\"center\" rowspan=\"2\" colspan=\"1\">\n<italic toggle=\"yes\">P</italic> Value 1-Sided <italic toggle=\"yes\">T</italic> Test<sup><xref rid=\"tblfn6\" ref-type=\"table-fn\">a</xref></sup></th></tr><tr><th align=\"center\" rowspan=\"1\" colspan=\"1\">Newly Diagnosed PWTB, No.</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">ILTFU, No. (%) (95% CI, %)</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Newly Diagnosed PWTB, No.</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">ILTFU, No. (%) (95% CI, %)</th></tr></thead><tbody><tr><td colspan=\"7\" rowspan=\"1\">Subdistricts implementing the hospital-recording intervention (no intervention in surrounding facilities)</td><td align=\"center\" rowspan=\"1\" colspan=\"1\"/></tr><tr><td rowspan=\"1\" colspan=\"1\">Umdoni (KwaZulu-Natal)</td><td rowspan=\"1\" colspan=\"1\">GJ Crookes Hosp</td><td rowspan=\"1\" colspan=\"1\">65</td><td rowspan=\"1\" colspan=\"1\">23 (35.4) (23.8–47)</td><td rowspan=\"1\" colspan=\"1\">345</td><td rowspan=\"1\" colspan=\"1\">73 (21.2) (16.8–25.5)</td><td rowspan=\"1\" colspan=\"1\">40.2 (12–59.4)</td><td rowspan=\"1\" colspan=\"1\">.0141</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Surrounding PHC facilities</td><td rowspan=\"1\" colspan=\"1\">66</td><td rowspan=\"1\" colspan=\"1\">10 (15.2) (6.5–23.8)</td><td rowspan=\"1\" colspan=\"1\">445</td><td rowspan=\"1\" colspan=\"1\">62 (13.9) (10.7–17.2)</td><td rowspan=\"1\" colspan=\"1\">8 (−70.2 to 50.3)</td><td rowspan=\"1\" colspan=\"1\">.3989</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Region D (Gauteng)</td><td rowspan=\"1\" colspan=\"1\">CH Baragwanath Hosp</td><td rowspan=\"1\" colspan=\"1\">169</td><td rowspan=\"1\" colspan=\"1\">94 (55.6) (48.1–63.1)</td><td rowspan=\"1\" colspan=\"1\">1167</td><td rowspan=\"1\" colspan=\"1\">746 (63.9) (61.2–66.7)</td><td rowspan=\"1\" colspan=\"1\">−14.9 (−32.4 to 0.2)</td><td rowspan=\"1\" colspan=\"1\">.9784</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Surrounding PHC facilities</td><td rowspan=\"1\" colspan=\"1\">544</td><td rowspan=\"1\" colspan=\"1\">114 (21.0) (17.5–24.4)</td><td rowspan=\"1\" colspan=\"1\">2932</td><td rowspan=\"1\" colspan=\"1\">555 (18.9) (17.5–20.3)</td><td rowspan=\"1\" colspan=\"1\">9.7 (−7.5 to 2.1)</td><td rowspan=\"1\" colspan=\"1\">.1420</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Tygerberg (Western Cape)</td><td rowspan=\"1\" colspan=\"1\">Tygerberg Hospital</td><td rowspan=\"1\" colspan=\"1\">173</td><td rowspan=\"1\" colspan=\"1\">74 (42.8) (35.4–50.1)</td><td rowspan=\"1\" colspan=\"1\">1132</td><td rowspan=\"1\" colspan=\"1\">509 (45) (42.1–47.9)</td><td rowspan=\"1\" colspan=\"1\">−5.1 (−26.4 to 12.5)</td><td rowspan=\"1\" colspan=\"1\">.7053</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Surrounding PHC facilities</td><td rowspan=\"1\" colspan=\"1\">588</td><td rowspan=\"1\" colspan=\"1\">111 (18.9) (15.7–22)</td><td rowspan=\"1\" colspan=\"1\">3963</td><td rowspan=\"1\" colspan=\"1\">564 (14.2) (13.1–15.3)</td><td rowspan=\"1\" colspan=\"1\">24.6 (9.4–37.3)</td><td rowspan=\"1\" colspan=\"1\">.0015</td></tr><tr><td colspan=\"8\" rowspan=\"1\">Subdistricts implementing the alert-and-response patient management intervention</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Ray Nkonyeni (KwaZulu-Natal)</td><td rowspan=\"1\" colspan=\"1\">Gamalakhe CHC</td><td rowspan=\"1\" colspan=\"1\">59</td><td rowspan=\"1\" colspan=\"1\">7 (11.9) (3.6–20.1)</td><td rowspan=\"1\" colspan=\"1\">410</td><td rowspan=\"1\" colspan=\"1\">47 (11.5) (8.4–14.5)</td><td rowspan=\"1\" colspan=\"1\">3.4 (−103.7 to 54.2)</td><td rowspan=\"1\" colspan=\"1\">.4648</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Surrounding PHC facilities</td><td rowspan=\"1\" colspan=\"1\">137</td><td rowspan=\"1\" colspan=\"1\">41 (29.9) (22.3–37.6)</td><td rowspan=\"1\" colspan=\"1\">799</td><td rowspan=\"1\" colspan=\"1\">103 (12.9) (10.6–15.2)</td><td rowspan=\"1\" colspan=\"1\">56.9 (41.1–68.5)</td><td rowspan=\"1\" colspan=\"1\">&lt;.0001</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Region E (Gauteng)</td><td rowspan=\"1\" colspan=\"1\">Edenvale Hospital</td><td rowspan=\"1\" colspan=\"1\">59</td><td rowspan=\"1\" colspan=\"1\">43 (72.9) (61.5–84.2)</td><td rowspan=\"1\" colspan=\"1\">409</td><td rowspan=\"1\" colspan=\"1\">259 (63.3) (58.7–68)</td><td rowspan=\"1\" colspan=\"1\">13.1 (−3.2 to 26.9)</td><td rowspan=\"1\" colspan=\"1\">.0668</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Surrounding PHC facilities</td><td rowspan=\"1\" colspan=\"1\">149</td><td rowspan=\"1\" colspan=\"1\">41 (27.5) (20.3–34.7)</td><td rowspan=\"1\" colspan=\"1\">891</td><td rowspan=\"1\" colspan=\"1\">212 (23.8) (21.0–26.6)</td><td rowspan=\"1\" colspan=\"1\">13.5 (−15.1 to 35)</td><td rowspan=\"1\" colspan=\"1\">.1728</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Khayelitsha (Western Cape)</td><td rowspan=\"1\" colspan=\"1\">Khayelitsha Hospital</td><td rowspan=\"1\" colspan=\"1\">79</td><td rowspan=\"1\" colspan=\"1\">22 (27.8) (18.0–37.7)</td><td rowspan=\"1\" colspan=\"1\">808</td><td rowspan=\"1\" colspan=\"1\">251 (31.1) (27.9–34.3)</td><td rowspan=\"1\" colspan=\"1\">−11.6 (−61.4 to 22.9)</td><td rowspan=\"1\" colspan=\"1\">.7261</td></tr><tr><td rowspan=\"1\" colspan=\"1\"/><td rowspan=\"1\" colspan=\"1\">Surrounding PHC facilities</td><td rowspan=\"1\" colspan=\"1\">483</td><td rowspan=\"1\" colspan=\"1\">89 (18.4) (15.0–21.9)</td><td rowspan=\"1\" colspan=\"1\">3456</td><td rowspan=\"1\" colspan=\"1\">303 (8.8) (7.8–9.7)</td><td rowspan=\"1\" colspan=\"1\">52.4 (40.9–61.7)</td><td rowspan=\"1\" colspan=\"1\">&lt;.0001</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material id=\"sup1\" position=\"float\" content-type=\"local-data\"><label>ofad648_Supplementary_Data</label></supplementary-material>" ]
[ "<table-wrap-foot><fn id=\"tblfn1\"><p>Abbreviations: CHC, community health center; KZN, KwaZulu Natal; PHC, primary health care; TB, tuberculosis; WC, Western Cape.</p></fn><fn id=\"tblfn2\"><p>\n<sup>a</sup>Gamalakhe is a large CHC but used as a proxy for a hospital in this study at the request of the KZN Department of Health as 10 surrounding PHC facilities refer to it.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"tblfn3\"><p>Abbreviations: ILTFU, initial loss to follow-up; PWTB, person with tuberculosis.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"tblfn4\"><p>\n<sup>a</sup>One-sided <italic toggle=\"yes\">t</italic> test: based on the null hypothesis that the percent ILTFU was not reduced from baseline to intervention.</p></fn><fn id=\"tblfn5\"><p>Abbreviations: ILTFU, initial loss to follow-up; TB, tuberculosis.</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"tblfn6\"><p>\n<sup>a</sup>One-sided <italic toggle=\"yes\">t</italic> test: based on the null hypothesis that the percent ILTFU was not reduced from baseline to intervention.</p></fn><fn id=\"tblfn7\"><p>Abbreviations: ILTFU, initial loss to follow-up; PHC, primary health care; PWTB, person with tuberculosis.</p></fn></table-wrap-foot>" ]
[]
[ "<media xlink:href=\"ofad648_supplementary_data.docx\"><caption><p>Click here for additional data file.</p></caption></media>" ]
[{"label": ["1"], "mixed-citation": ["\n"], "person-group": ["\n"], "collab": ["World Health Organization"], "source": ["Global Tuberculosis Report 2022"], "year": ["2022"]}, {"label": ["2"], "mixed-citation": ["\n"], "person-group": ["\n"], "collab": ["World Health Organization"], "source": ["Digital Health for the END TB Strategy: An Agenda for Action"], "year": ["2015"]}, {"label": ["9"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Massyn", "Barron", "Day", "Ndlovu", "Padarath"], "given-names": ["N", "P", "C", "N", "A"], "source": ["District Health Barometer 2018/19"], "publisher-name": ["Health Systems Trust"], "year": ["2020"]}, {"label": ["14"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Edginton", "Wong", "Hodkinson"], "given-names": ["ME", "ML", "HJ"], "article-title": ["Tuberculosis at Chris Hani Baragwanath Hospital: an intervention to improve patient referrals to district clinics"], "source": ["Int J Tuberc Lung D"], "year": ["2006"], "volume": ["10"], "fpage": ["1018"], "lpage": ["22"]}, {"label": ["16"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Edginton", "Wong", "Phofa", "Mahlaba", "Hodkinson"], "given-names": ["ME", "ML", "R", "D", "HJ"], "article-title": ["Tuberculosis at Chris Hani Baragwanath Hospital: numbers of patients diagnosed and outcomes of referrals to district clinics"], "source": ["Int J Tuberc Lung D"], "year": ["2005"], "volume": ["9"], "fpage": ["398"], "lpage": ["402"]}, {"label": ["23"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Thomas", "Suresh", "Lavanya"], "given-names": ["BE", "C", "J"], "etal": ["et al"], "article-title": ["Understanding pretreatment loss to follow-up of tuberculosis patients: an explanatory qualitative study in Chennai, India"], "source": ["BMJ Glob Health"], "year": ["2020"], "volume": ["5"], "fpage": ["e001974"]}]
{ "acronym": [], "definition": [] }
27
CC BY
no
2024-01-14 23:43:47
Open Forum Infect Dis. 2023 Dec 18; 11(1):ofad648
oa_package/0f/d4/PMC10787480.tar.gz
PMC10787481
38163951
[ "<title>Introduction</title>", "<p>Catheter ablation is an established treatment option for various types of arrhythmias and, in general, has a high success rate and an excellent safety profile.<sup>##REF##32860505##1##</sup> However, despite increasing experience and improved ablation strategies and technologies, complications can occur and can be potentially life-threatening.<sup>##REF##19995881##2–14##</sup> Pericardial tamponade (PT) is the most frequent severe complication during electrophysiology (EP) procedures and requires immediate, co-ordinated, and effective treatment. However, the treatment of PT is not standardized and various aspects are still under debate.<sup>##REF##35713695##15##</sup> Therefore, we conducted a survey evaluating the infrastructure, safety precautions, and treatment strategies in the setting of PT in European and non-European EP centres.</p>" ]
[ "<title>Methods</title>", "<p>An online questionnaire consisting of 26 multiple-choice questions was sent to the European Heart Rhythm (EHRA) Research Network and was also distributed via social media platforms. The exact questionnaire is provided as ##SUPPL##0##Supplementary material online##. The EHRA survey was conducted between May and June 2023.</p>" ]
[ "<title>Results</title>", "<title>Baseline data</title>", "<p>We received a total of 213 replies. The majority of respondents were from European countries (87%) and 13% were from non-European countries (<italic toggle=\"yes\">Figure ##FIG##1##1##</italic>). A total of 68% of all participants practice at academic institutions and 32% at non-academic hospitals. The number of ablation procedures per year varied from up to 500 EP procedures in 45% of participants, 501–1000 procedures in 27%, 1001–1500 procedures in 14%, and finally, more than 1500 procedures in the remaining 15%. While 92% of all participating EPs report to perform diagnostic EP-procedures, 95% perform ablations of supraventricular tachycardias, 92% of atrial fibrillation, 94% of atrial flutter, and 91% of ventricular tachycardia (VT). Of note, a total of 58% of responders perform epicardial VT ablation and 62% offer interventional occlusion of the left atrial appendage (<italic toggle=\"yes\">Figure ##FIG##2##2##</italic>).</p>", "<title>Electrophysiology infrastructure and equipment</title>", "<p>Reflecting the spectrum and load of EP procedures, 90.2% of all participants perform their interventions in dedicated EP labs. With 91%, three-dimensional (3D) mapping, in combination with irrigated contact force–enabled radiofrequency (RF) catheters, is the most frequently available ablation modality, followed by cryoballoon technology (79.5%). Conventional RF ablation is applied in (71.4%), and non-contact-force-guided RF ablation with 3D mapping in (44.6%). Of note, pulsed field ablation (PFA) is already widely spread and applied by 29.5% of all participants. Another 7.1% are also equipped with other ablation platforms.</p>", "<p>About two-thirds (65.8%) of all responders have institutional cardiac surgery available on site. A total of 88.2% of the participants report to have echocardiography permanently available inside the EP lab. Moreover, 94.6% answered to have a pre-prepared epicardial puncture set inside the lab that contains all necessary items for emergency epicardial puncture and drainage.</p>", "<title>Pre-procedural considerations</title>", "<p>While 72.7% of participants report to have no restrictions for the patient’s body mass index (BMI), 8.2% answered to have BMI limits for all procedures, and another 19.1% have BMI restrictions for left atrial and left ventricular ablation procedures only. Body mass index limits ranged between 35 and 55 kg/m<sup>2</sup>. With regard to age, 85.2% have no age limits, while 3.7% have age limits for all procedures, and 11.1% for left atrial and left ventricular interventions only (ranging from 75 to 85 years). International normalized ratio (INR) limits for patients on vitamin K-antagonists were reported by 32.7%, with INR limits ranging from 2 to 4. The remaining participants did not report INR restrictions for any EP procedures. A total of 20.9% of responders do not interrupt novel oral anticoagulants (NOAC) therapy, 15.5% stop it the day before, 18.2% the evening before, and 41.8% at the day of the procedure. A total of 3.6% report other strategies.</p>", "<title>Procedural aspects and safety considerations</title>", "<p>A total of 1.8% of participants monitor blood pressure invasively during diagnostic EP procedures, 9% during ablation of atrial flutter or atrial tachycardia, 13.6% during ablation of atrial fibrillation, and 13.6% for interventional closure of the left atrial appendage. In VT ablation procedures, blood pressure is monitored invasively by 84.5%. Another 13.6% report to uniquely use non-invasive blood pressure monitoring for all procedures.</p>", "<p>Transseptal puncture is guided by fluoroscopy only in 48.9% of respondents. Transoesopageal echocardiography (TOE) as an additional imaging mode is used by 27.5% and intracardiac echocardiography (ICE) by 24.8% of the participants. A total of 48.9% purely rely on fluoroscopy and 6.4% report to use other guiding modalities for transseptal puncture (<italic toggle=\"yes\">Figure ##FIG##3##3##</italic>). Diagnostic catheters are positioned within the coronary sinus by the majority of participants (86.1%). A total of 23.1% also place a diagnostic catheter at the His bundle region for transseptal puncture, and 8.3% use a pigtail catheter or wire inside the aorta. The remaining 9.3% report to use no diagnostic catheter for guidance of transseptal punctures.</p>", "<p>Additional modalities used for transseptal puncture (TP) are pressure control (50.1%), contrast staining of the fossa ovalis before advancing the transseptal needle (29.4%), introduction of a guidewire into the left atrium or the left superior pulmonary vein once transseptal puncture is performed (55.9%), and/or contrast injection after transseptal access (49%), respectively (<italic toggle=\"yes\">Figure ##FIG##3##3##</italic>).</p>", "<title>Treatment of pericardial tamponade</title>", "<p>For pericardiocentesis of a PT, most participants report to use X-ray as the main imaging modality to guide pericardial puncture. The most frequently used views are anterior-posterior (58.7%) and left anterior oblique (45.2%). A total of 14.2% also perform the puncture in a right anterior oblique angulation (14.4%). In addition to X-ray, echocardiography is used by 61.5%. A minority of responders does not use any imaging modality and 5.8% report to use other modalities. Pericardial puncture can be targeted on the anterior and the posterior sites. An anterior access is preferred by most (67.3%). Once epicardial access is gained, most physicians (84.3%) introduce sheaths of different sizes into the pericardial space (5F 9.8%, 6F 35.3%, 7F 14.7%, 8F 21.6%, other sizes 2.9%), followed by a pigtail catheter (5F 23.5%, 6F 50%, 7F 19.6%, other sizes 6.7%).</p>", "<p>The majority of respondents (84.6%) applies protamine in case of a PT. The timing of protamine injection varies with injection immediately upon a diagnosis of PT in 42.7%, after complete drainage of PT in 35.4%, and after successful access to the pericardium in 17.7%. Some (4.2%) report other strategies regarding protamine application (<italic toggle=\"yes\">Figure ##FIG##4##4##</italic>). The protamine dose is adjusted according to the last measured activated clotting time (ACT) level in 43.3%, and 37.1% apply protaminin at a ratio of 1:1 to previous heparin administration. Among the remaining participants, 3000 and 5000 I.E. are given as an institutional standard in 4.1 and 9.3%, respectively.</p>", "<p>NOAC antidotes are routinely administered by 15.2% of respondents, while 73.3% of them never use antidotes. Another 11.4% apply NOAC antidotes only in certain situations such as unresponsiveness of bleeding to protamine administration. Additional application of clotting factors is not considered by 91.7% of centres. However, 8.3% would apply prothrombin complex, fresh frozen plasma, or tranexamic acid as necessary.</p>", "<p>Auto-transfusion of aspirated blood is reported to be done by 76% of all participants. Some start auto-transfusion before protamine administration (18.2%), others after protamine administration (13.5%), and others only if pericardial effusion cannot be controlled (40.4%). Another 1.9% report to have other strategies regarding re- or auto-transfusion. For auto-transfusion, 72.4% of the participants do not use a blood filter, 15.8% use a blood filter, and another 11.8% auto-transfuse via a cell safer only (<italic toggle=\"yes\">Figure ##FIG##5##5##</italic>). While 90.4% do not have a maximal limit of re-transfused blood, 6.4% have defined limits (maximum of 1–2 L), and 3.2% have different strategies.</p>", "<p>The decision for surgical intervention is mostly taken if bleeding continues despite all interventional measures. Accordingly, 55.7% of the participants answered to decide for surgical backup and intervention if the bleeding continues for more than 60–80 min. Another 25.4% consider surgical assistance if the amount of aspirated blood exceeds a predefined limit, ranging from 1000 to 3000 mL among centres. Another 18.9% consider other measures such as no reduction of aspirated blood per minute, haemodynamic instability, or a suspicion of a left atrial/ventricular defect.</p>", "<title>Post-interventional aspects</title>", "<p>After successful epicardial puncture, drainage, and stabilization of the patient, most respondents (48.5%) keep the pigtail catheter until there is no evidence of further bleeding after re-initiation of an indicated anticoagulation. Another 7.9% remove the pigtail as soon as the bleeding stops, and 43.6% report other strategies such as keeping the pigtail for 2–72 h and including repeat echocardiography showing complete drainage of effusion without further aspiration.</p>", "<p>Specific medications applied after PT drainage are non-steroidal anti-inflammatory drugs (NSAIDs) in 48.6% of participants for a mean of 10 days, colchicine in 47.2% for a mean of 19 days, cortisone in 8.3% as a single shot in the majority, and/or antibiotics in 31.9% for a mean of 2 days.</p>", "<p>If indicated, anticoagulation therapy is re-initiated within 0–72 h after pigtail removal.</p>", "<title>Onsite cardiac surgery vs. no onsite cardiac surgery</title>", "<p>While many aspects between centres with and without onsite cardiac surgery are comparable, there are also major differences. The mean total number of procedures in participant’s centres with onsite cardiac surgery is higher with 850 ± 595 vs. 634 ± 569. Operators at centres without cardiac surgery less frequently report to perform epicardia VT ablation (37 vs. 72%), and protamine is more often regularly applied in case of PT (81 vs. 70%).</p>" ]
[ "<title>Discussion</title>", "<p>Despite technological advancements and procedural expertise, PT remains a frequent and potentially life-threatening complication in the EP lab. However, in reputed centres and when managed by experienced operators, PT can be effectively treated. There are no general recommendations on how to prevent and how to treat PT. The current survey found the following:</p>", "<p>Most centres have no restrictions regarding age and BMI even for complex left atrial/ventricular procedures.</p>", "<p>Transseptal puncture is mostly performed fluoroscopically and is frequently facilitated by diagnostic catheters and/or additional imaging modalities such as TOE or ICE.</p>", "<p>In case of PT, pericardial puncture is mainly guided by fluoroscopy and echocardiography, and most responders aim for an anterior puncture site, followed by the introduction of a sheath and a pigtail catheter.</p>", "<p>Protamine is applied by a majority of participants immediately when PT is diagnosed or after complete drainage of pericardial effusion. NOAC antidotes are administered only by a minority of respondents.</p>", "<p>A majority does directly auto-transfuse aspirated blood without a blood filter and with no maximal limit for blood re-transfusion.</p>", "<p>Surgical intervention is mainly considered if bleeding continues despite all interventional measures.</p>", "<title>Electrophysiology-infrastructure and equipment</title>", "<p>While two-thirds of all responders report to have institutional cardiac surgery, almost all state to have echocardiography permanently available inside the EP lab and prepared epicardial puncture sets. Although institutional cardiac surgery might extend the window for interventional measures to treat PT, echocardiography permanently on hand and prepared puncture sets allow for straightforward and time-efficient diagnosis and emergency treatment without unnecessary loss of time.</p>", "<title>Procedural aspects and safety considerations</title>", "<p>Transseptal mispuncture is one of the main reasons for PT. Different techniques can be applied, and finally, the mode of transseptal puncture is influenced by individualized strategies and by personal experience. However, the ultimate demand is to perform transseptal punctures as controlled and as safe as possible. To facilitate transseptal puncture, many centres use catheters at different anatomical positions to improve understanding of the individual anatomy. A catheter inside the coronary sinus will provide a rough visualization of the mitral valve and left atrial dimensions. In addition, a synchronous movement of the transseptal sheath and transseptal needle assembly positioned at the fossa ovalis with the coronary sinus catheter indicates adequate septal contact and position. Some participants use an additional catheter at the His bundle region or a pigtail catheter or wire inside the aorta to mark the aortic root to prevent inadvertent aortic puncture.<sup>##REF##27001035##16##,##REF##30887036##17##</sup> Mostly, transseptal puncture is guided by fluoroscopy only, but other imaging modalities might be added, such as transoesophageal or ICE. Both echo modalities will not only help to guide the transseptal sheath and needle to the fossa ovalis but will also facilitate to specifically target anterior or posterior puncture sites within the fossa ovalis depending on the ablation system used (e.g. cryoballoon ablation posterior and inferior, in PFA ablation rather midseptal and inferior) or the intended ablation strategy (e.g. pulmonary vein isolation or antegrade left ventricular access). Transseptal puncture with pressure control is applied by most operators. Verification of successful left atrial access before advancing the transseptal sheath by either introducing a guidewire into the left atrium or a pulmonary vein or injecting a contrast medium helps to avoid advancement of the sheath in case of inadvertent pericardial puncture.</p>", "<title>Treatment of pericardial tamponade</title>", "<p>There are different ways to gain epicardial access, but two-thirds of all responders prefer an anterior epicardial puncture site that has been shown to be safer than a posterior one.<sup>##REF##32719917##18##</sup> In an analysis by Mathew <italic toggle=\"yes\">et al</italic>.,<sup>##REF##32719917##18##</sup> a posterior epicardial access was strongly associated with a higher rate of severe puncture-related complications and a higher necessity for later surgical repair. Fluoroscopy in different views and additional echocardiography as answered by three out of four EPs are the leading imaging modalities to guide the puncture. Almost all participants introduce a sheath into the pericardial space as soon as access is established. A sheath has two major procedural advantages. First, it can be used for direct aspiration of blood, and the bigger the size, the more volume can be mobilized. Second, blood inside the pigtail catheter, which is introduced by a majority of participating EPs, can clot, and in a worst-case scenario, the pigtail has to be exchanged. This is facilitated over the sheath as a continuous and safe access to the pericardial space. Of note, in tall or obese patients, it might be beneficial to use a longer or even a transseptal sheath.</p>", "<p>Haemostasis and anticoagulation play a major role in the acute treatment of PT. Protamine administration in order to antagonize previously applied heparin in left atrial/left ventricular procedures is an essential step. Particularly in centres without institutional cardiac surgery backup, early application of protamine is the strategy of choice. However, the administration of protamine also bears a risk for clot formation inside the pericardial space, which can complicate the situation by impeding further and complete drainage of the pericardial effusion. This is probably the reason why about one-third of responders decide to first aspirate all blood from the pericardium before protamine is administered. In ∼80%, the dose of protamine depends on previously measured ACT levels or the total dose of applied heparin.</p>", "<p>Additional application of clotting factors or NOAC antidotes is not performed by the majority of responders. While clotting factors such as prothrombin complex concentrate, prothrombin complex, or fresh frozen plasma are considered only by 8.3%, NOAC antidotes are routinely applied by only 15.2%. The decision to administer NOAC antidotes might be influenced by costs but also by the fact that PT even in patients under NOAC therapy might be safely and effectively managed without antidotes.</p>", "<p>Auto-transfusion of aspirated blood is an important but disputatious aspect in PT management. Its potential advantages are immediate use, easy implementation, low costs, and avoidance of volume and blood loss, and thus, there is mostly no need for donor blood transfusion. Accordingly, 74% of all participants perform re-transfusion of aspirated blood, and almost three-thirds do it directly and without a mechanical blood filter. About 16% use a blood filter and 12% would re-transfuse via a cell safer. However, the latter is time-consuming to prepare and is therefore often not practicable in an emergency situation. Of note, 90% report to not have a fixed volume limit and would re-transfuse aspirated blood as long as necessary and reasonable.</p>", "<p>Involvement of surgical backup and repair is also a controversial issue. Centres having an institutional cardiac surgery may have more leeway, since the decision for surgical repair can be taken anytime if the patient’s condition demands. However, if there is no institutional cardiac surgery but rather external cardiac surgical cooperation partners, the decision for potential surgical repair might be taken at earlier stages of the treatment cascade. The important aspect is to have cardiac surgical backup that is permanently available or on demand. The point in time to decide for surgical intervention is certainly a very individualistic decision to take. In our survey, 56% stated to involve surgeons if bleeding continues for more than 60–80 min, while another 25% would do if the total amount of aspirated blood would exceed an amount of up to 3000 mL.</p>", "<title>Post-interventional aspects</title>", "<p>Keeping the pigtail catheter in place for several hours after successful treatment of PT is a double-edged weapon.<sup>##REF##31904158##19##</sup> First, further drainage from the pericardium might be necessary in case of ongoing or recurring bleeding. On the other hand, pericarditis might develop if the pigtail catheter is kept and patients normally complain about thoracic discomfort. In the survey, almost 50% of respondents state to keep the pigtail catheter until there is no evidence of further bleeding after re-initiation of an indicated anticoagulation. There are different types of medical strategies following pericardial puncture and drainage aiming mainly for pain relief and prevention of pericarditis including NSAIDs and colchicine applied by almost 50% of responders each. Also, antibiotics are applied by more than 30% of responders, but mostly for only 2 days.</p>", "<p>The decision for re-initiation of an indicated oral anticoagulation after pigtail removal has to be carefully taken. On the one hand, left atrial thrombus formation and potential ischaemic stroke need to be prevented, and on the other hand, there would be the risk of ongoing or recurrent bleeding. With 0–72 h, there is a broad window within which anticoagulation is re-initiated by respondents.</p>", "<title>Onsite cardiac surgery vs. no onsite cardiac surgery</title>", "<p>Having onsite cardiac surgery may affect not only the spectrum of EP procedures that is performed but also the mode of treatment in case of a PT. While many parameters of our analysis given by the participants are comparable, there are also differences: in centres with onsite cardiac surgery, the mean number of performed procedures is higher. Although epicardial VT ablation is frequently offered at centres with onsite cardiac surgery, the number of participants reporting on epicardial VT ablation without having onsite cardiac surgery is considerably high, with a rate of 37%. This finding is of interest when considering the ongoing debate on whether a procedure with a rather high incidence of major complications such as severe PT should be offered and performed at such centres. Moreover, protamine is less often applied by participants at onsite cardiac surgery centres. In centres without cardiac surgery, usually all efforts are taken to stop bleeding as soon as possible, and thus, protamine might be applied at earlier stages of the treatment cascade.</p>", "<title>Limitations</title>", "<p>The analysed data in this study are based on per physician and not per centre level, and thus, an overestimation of the perspectives of large EP centres cannot be ruled out. The voluntary nature of the survey favours selection bias and raises questions whether these results represent a realistic reflection of the current practice. The survey included a limited number of only 26 questions. Therefore, further details such as incidences of PT or the need for surgical intervention could not be provided.</p>" ]
[ "<title>Conclusions</title>", "<p>The current survey demonstrates that the management of cardiac tamponade differs among EP centres. The findings of this survey may help to guide operators in their treatment and decision-making in the setting of PT.</p>" ]
[ "<p>\n<bold>Conflict of interest:</bold> none declared.</p>", "<title>Abstract</title>", "<title>Aims</title>", "<p>Pericardial tamponade (PT) is the most frequent severe complication during electrophysiology (EP) procedures and requires immediate, co-ordinated, and effective treatment. However, multiple aspects of PT treatment are either not standardized or are under ongoing debate.</p>", "<title>Methods and results</title>", "<p>An online questionnaire consisting of 26 multiple-choice questions was sent out to the European Heart Rhythm (EHRA) Research Network and also distributed via social media outputs. The EHRA survey was conducted between May and June 2023. A total of 213 replies were received from European (87%) and non-European countries. Ninety per cent of all participants perform interventions in dedicated EP labs equipped with different ablation platforms. In case of PT, most participants use X-ray as the main imaging modality guiding pericardial puncture, predominantly aiming for an anterior puncture site. Sheaths of different sizes are introduced into the pericardial space (84.3%), followed by a pigtail catheter. Application of protamine is an established but variable step in the majority (84.6%). Novel oral anticoagulants (NOAC) antidotes are not used by 73.3% of participants, while 15.2% routinely apply them. Re-transfusion of aspirated blood is performed by 72.1% [before protamine administration (18.2%), after protamine administration (13.5%), if pericardial effusion cannot be controlled (40.4%)]. A total of 72.4% re-transfuse without blood filter systems. A decision for surgical intervention is mostly taken if bleeding continues despite all interventional measures.</p>", "<title>Conclusion</title>", "<p>The current survey demonstrates that the management of PT is heterogeneous among centres. The findings of this survey may help to guide operators in their treatment and decisions in the setting of PT.</p>", "<title>Graphical Abstract</title>", "<p>\n\n</p>" ]
[ "<title>Supplementary Material</title>" ]
[ "<title>Acknowledgements</title>", "<p>The production of this document is under the responsibility of the Scientific Initiatives Committee of the European Heart Rhythm Association: Julian K.R. Chun (Chair), Sergio Castrejon (Co-Chair), Ante Anic, Giulio Conte, Piotr Futyma, Andreas Metzner, Federico Migliore, Giacomo Mugnai, Laura Perrotta, Rui Providencia, Sergio Richter, Laurent Roten, and Arian Sultan. The authors acknowledge the EHRA Scientific Research Network centres participating in this survey. A list of these centres can be found on the EHRA website.</p>", "<title>Supplementary material</title>", "<p>\n##SUPPL##0##Supplementary material## is available at <italic toggle=\"yes\">Europace</italic> online.</p>", "<title>Funding</title>", "<p>None declared.</p>", "<title>Data availability</title>", "<p>All relevant data are within the manuscript and its ##SUPPL##0##Supplementary material online## files.</p>" ]
[ "<fig position=\"anchor\" id=\"euad378_ga1\"><label>Graphical Abstract</label></fig>", "<fig position=\"float\" id=\"euad378-F1\" fig-type=\"figure\"><label>Figure 1</label><caption><p>Participating countries.</p></caption></fig>", "<fig position=\"float\" id=\"euad378-F2\" fig-type=\"figure\"><label>Figure 2</label><caption><p>A spectrum of procedures.</p></caption></fig>", "<fig position=\"float\" id=\"euad378-F3\" fig-type=\"figure\"><label>Figure 3</label><caption><p>Imaging modalities for transseptal puncture.</p></caption></fig>", "<fig position=\"float\" id=\"euad378-F4\" fig-type=\"figure\"><label>Figure 4</label><caption><p>The application of protamine.</p></caption></fig>", "<fig position=\"float\" id=\"euad378-F5\" fig-type=\"figure\"><label>Figure 5</label><caption><p>An auto-transfusion of aspirated blood and the mode of auto-transfusion.</p></caption></fig>" ]
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[ "<boxed-text id=\"euad378-box1\" position=\"anchor\"><caption><title>What’s new?</title></caption><list list-type=\"bullet\"><list-item><p>Most centres have no restrictions regarding age and body mass index even for complex left atrial/ventricular procedures.</p></list-item><list-item><p>Transseptal puncture is mostly performed fluoroscopically and frequently facilitated by diagnostic catheters and/or additional imaging modalities such as transoesophageal echocardiography or intracardiac echocardiography.</p></list-item><list-item><p>In case of pericardial tamponade (PT), pericardial puncture is mainly guided by fluoroscopy and echocardiography and most responders aim for an anterior puncture site, followed by the introduction of a sheath and a pigtail catheter.</p></list-item><list-item><p>Protamine is applied by a majority of participants immediately when PT is diagnosed or after complete drainage of pericardial effusion. Novel oral anticoagulants (NOAC) antidotes are administered only by a minority of respondents.</p></list-item><list-item><p>A majority does directly auto-transfuse aspirated blood without a blood filter and with no maximal limit for blood re-transfusion.</p></list-item><list-item><p>Surgical intervention is mainly considered if bleeding continues despite all interventional measures.</p></list-item></list></boxed-text>" ]
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[ "<supplementary-material id=\"sup1\" position=\"float\" content-type=\"local-data\"><label>euad378_Supplementary_Data</label></supplementary-material>" ]
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{ "acronym": [], "definition": [] }
19
CC BY
no
2024-01-14 23:43:47
Europace. 2024 Jan 2; 26(1):euad378
oa_package/7e/6c/PMC10787481.tar.gz
PMC10787482
0
[ "<title>Introduction</title>", "<p id=\"Par14\">Lung cancer remains the leading cause of cancer-related deaths globally [##REF##30955514##1##]. Achieving early detection of lung cancer through screening represents a significant milestone in enhancing prognosis [##REF##37875852##2##]. Chest X-ray is a routine radiologic examination in clinical practice [##REF##36980318##3##]. With the advancement of imaging technology, the adoption of low-dose computed tomography (CT) for lung cancer screening in high-risk individuals holds the potential for detecting lung cancer at an early stage, with the potential to reduce associated mortality rates [##REF##35253286##4##]. When a potentially malignant nodule is identified, obtaining tissue samples through biopsy is included as part of the clinical evaluation process [##UREF##0##5##].</p>", "<p id=\"Par15\">Percutaneous transthoracic lung biopsy (PTLB) is a dependable approach for the diagnosis of pulmonary nodules [##REF##33051730##6##]. Conventional computed tomography (CCT)-guided PTLB is commonly used due to its widespread availability and high diagnostic accuracy [##REF##19429718##7##, ##REF##36548528##8##]. However, the limitation of CCT-guided PTLB is the lack of real-time visualization during needle insertion. This can increase the procedure time and radiation doses, particularly in cases where deep pulmonary nodules require oblique needle angles to avoid major vessels, ribs, or airways, or in older patients who have difficulty holding their breath [##REF##16541227##9##]. C-arm cone-beam computed tomography (CBCT) combines a C-arm gantry with cone-beam X-ray tube and flat panel detectors to provide high-resolution imaging along with the real-time needle guiding capability of fluoroscopic systems [##REF##24356655##10##, ##UREF##1##11##]. Utilizing path-planning software and the rotational ability of a C-arm, CBCT empowers operators to approach challenging lesions with greater confidence [##REF##35054282##12##–##REF##28392852##14##].</p>", "<p id=\"Par16\">In addition to its real-time needle guiding capability, CBCT-guided PTLB is considered a safe procedure with pneumothorax (PTX) and pulmonary hemorrhage (PH) being the main procedural complications [##REF##26310371##15##]. Recent studies have demonstrated comparable incidences of PTX and PH when utilizing CBCT guidance and CCT guidance [##REF##20393715##16##–##REF##31218410##22##]. Several studies reported risk factors for PTX and PH such as old age, presence of pulmonary emphysema, lower lobar location, small target size, and deep location [##REF##20393715##16##, ##REF##33938644##17##, ##REF##24865938##19##, ##REF##24475839##23##]. However, iatrogenic PTX is self-limiting in most cases, and only in a very small percentage, it necessitates chest tube insertion (CTI) [##REF##33938644##17##]. Similarly, PH is generally asymptomatic, or it may clinically manifest as light hemoptysis [##REF##33938644##17##]. Massive bleeding is exceptional, but it is a serious condition that may require endobronchial procedures or endovascular embolization [##REF##25163758##24##].</p>", "<p id=\"Par17\">Thus, the purpose of our study was to evaluate the incidence and clinical significance of PTX and PH after CBCT-guided PTLB and to test correlations of PTX and PH with demographics, clinical characteristics, imaging, and PTLB parameters.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study population and patient selection</title>", "<p id=\"Par18\">From January 2019 to October 2022, 275 consecutive patients who received CBCT-guided PTLB were retrospectively included in this study. The following exclusion criteria were applied: (1) Patients with PTX or PH identified during pre-procedural imaging; (2) Patients with a history of PTLB; (3) Patients with target lesions located in the mediastinum, pleura, or chest wall; and (4) Patients with incomplete bioptic records or imaging data. Eighty-three patients were excluded, and thus, a final study population of 192 patients was included (Fig. ##FIG##0##1##). The Institutional Review Board approved this study.</p>", "<title>Pre- procedural preparation</title>", "<p id=\"Par19\">Patients were subjected to either plain or enhanced CT of the chest, which was conducted within 1 week before the PTLB. Any regular intake of anticoagulants or platelet inhibitors by patients was stopped for at least 3 days before the procedure. Patients were given breathing instructions and advised to maintain consistent breathing during the procedure. Before the PTLB, patients were fully informed about the necessity and possible risks associated with the biopsy procedure, and they were required to provide their written informed consent.</p>", "<title>Overview of PTLB procedure</title>", "<p id=\"Par20\">The puncture procedure was performed by three senior interventional radiologists with over a decade of experience in puncture biopsy. All PTLBs were carried out under local anesthesia with the help of a CBCT virtual navigation guidance system. A coaxial cutting needle technique was used, involving an 18-gauge cutting needle and a 17-gauge biopsy coaxial cannula. Patients were positioned in either the supine or prone position, depending on their lesion location and the presence of ribs or large blood vessels. Before the biopsy, a pre-procedural CBCT scan was conducted of the entire lung to identify the safest and most accessible route to the target nodule(s), while avoiding obstacles and minimizing pleural contact and needle travel distance through the lung parenchyma. To reduce needle course complexity and improve accuracy, needle angulation was kept to the vertical plane of rotation during CBCT procedures. Following PTLB, a strip of sample measuring approximately 1 to 2 cm in diameter and 1.2 mm in width was obtained and immediately fixed in 10% formalin.</p>", "<p id=\"Par21\">For patients with a high suspicion of malignant lung nodules (e.g., ground-glass nodules larger than 1 cm) on pre-procedural CT or those with clinical features consistent with malignancy (e.g., concurrent hepatocellular carcinoma), we use a 17-gauge radiofrequency ablation (RFA) coaxial cannula instead of a 17-gauge biopsy coaxial cannula during the PTLB procedure. After the PTLB, the cutting needle was retrieved, and an RFA needle was inserted through the coaxial cannula that remained in place to perform RFA therapy. Besides, some patients were provided with a gelfoam slurry (created from an absorbable gelatin sponge) to embolize the needle tract following the procedure. The specific procedure is as follows: The 1000-1200 μm gelfoam is placed into a 10-ml syringe. A three-way stopcock was attached and another 10-ml syringe with 10 ml iodinated contrast. The mixture was rapidly agitated between the syringes until the mixture appeared homogenous. After withdrawing the biopsy or RFA needle, slowly remove the coaxial cannula while simultaneously injecting approximately 2-3 ml of the slurry through the coaxial cannula to embolize the needle tract, ensuring this procedure is performed under fluoroscopy.</p>", "<p id=\"Par22\">Post-procedural CBCT images were taken to identify any procedure-related complications. If the post-procedural CBCT indicates the presence of PTX or PH, the patient should undergo evaluation by an interventional radiologist and receive appropriate treatment. After the PTLB, patients were transferred to the ward and monitored for 24 hours. A follow-up chest CT scan was conducted after 24 hours to detect any delayed complications.</p>", "<title>Data collection</title>", "<p id=\"Par23\">The retrospective collection of data for each study participant involved gathering all pertinent demographic, clinical characteristics, imaging, and PTLB parameters. The CT images of each patient were analyzed by two independent readers, including the PTLB operator and an attending-level radiologist. The size of the nodules was determined by measuring the longest diameter of the lesion. The nodules were categorized based on their features, including solid, ground-glass, and cavitary. The presence of pulmonary emphysema was defined as disrupted lung vasculature and parenchyma with low attenuation occupying any lung zone (at least trace) at chest CT [##REF##25961632##25##]. Patients with smoking history were categorized as individuals who have smoked a minimum of 30 packs per year and either currently smoked or have ceased smoking within the last 15 years [##REF##32721652##26##].</p>", "<p id=\"Par24\">Both PTX and PH are defined based on imaging. The definition of PTX was based on the presence of air in the pleural space and classified according to the timing of appearance: immediate PTX observed on CBCT following PTLB and delayed PTX observed on CT plain scan 24 hours after PTLB. Clinically significant PTX was defined as the occurrence of severe respiratory or circulatory dysfunction that necessitated the insertion of a chest tube for treatment (Fig. ##FIG##1##2##). PH was defined as the presence of ground-glass opacity in the pulmonary parenchyma, which occurs due to the filling of alveolar spaces with blood (Fig. ##FIG##2##3##). PH was categorized into four groups: asymptomatic, mild hemoptysis (blood loss less than 100 ml in 24 hours), moderate hemoptysis (blood loss between 100 ml and 500 ml in 24 hours), and severe hemoptysis (blood loss exceeding 500 ml in 24 hours). Clinically significant PH was defined as the need for invasive medical interventions such as bronchoscopes or endovascular treatments to achieve hemostasis.</p>", "<title>Statistical methods</title>", "<p id=\"Par25\">Statistical analysis was performed with SPSS software (version 27.0; SPSS, Chicago, IL). To identify significant factors, subgroup analysis was performed using Student’s <italic>t</italic>-test for continuous variables and Pearson’s chi-squared test for categorical data. Due to the limited sample size, Fisher’s exact test was used. Logistic regression analyses were then used to further determine the effects of evaluated parameters on the likelihood of developing PTX and PH. The results are reported in terms of odd ratios (OR), with their 95% confidence intervals. A <italic>p</italic>-value less than 5% (<italic>p</italic> &lt; 0.05) was considered to be statistically significant.</p>" ]
[ "<title>Results</title>", "<title>Baseline clinical characteristics and PTLB parameters</title>", "<p id=\"Par26\">The demographic and clinical characteristics of patients and the imaging and procedural parameters are summarized in Table ##TAB##0##1##. A total of 192 patients underwent PTLB (males 129, 67.2%) with a mean age of 62.1 ± 13.4 years. Of all patients, 29 (15.1%) had a history of smoking, and 47 (24.5%) were diagnosed with pulmonary emphysema. Among those with pulmonary emphysema, 16 patients (34.0%) later experienced post-procedural PTX. The mean diameter of lung lesions was found to be 3.40 ± 2.20 cm, with 51 patients (26.6%) exhibiting lesions in the left upper lobe. Solid nodules were present in 164 of the patients (85.4%), while ground glass and cavity nodules were observed in 22 and 6 patients (11.5 and 3.1%), respectively. During the PTLB procedure, 43 patients (22.4%) proceeded to undergo RFA after PTLB. Gelfoam was utilized to seal the puncture tract in 77 patients (40.1%) following the PTLB procedure.\n</p>", "<p id=\"Par27\">Among the pathological biopsies conducted after PTLB, 3 patients (1.6%) were deemed inconclusive due to insufficient material for diagnosis. Out of the 192 patients, 141 (73.4%) were diagnosed with malignant tumors, with 113 patients identified with primary lung cancer and 28 patients with metastatic lesions. Additionally, 48 patients (25.0%) were determined to be benign.</p>", "<title>Complication</title>", "<p id=\"Par28\">PTX was observed in 67 patients (34.9%). Among these patients, immediate PTX occurred in 42 patients (62.7%), while 25 patients (37.3%) experienced PTX within 24 hours. The majority of PTX were self-limiting and resolved spontaneously, as CTI was required in 5 of 67 patients (7.5%). The mean duration of catheter placement was 2.6 ± 0.9 days (Table ##TAB##1##2##). Due to the limited number of patients requiring CTI, regression analysis examining the factors influencing CTI was not conducted in our study. PH occurred in 63 patients (32.8%). Among these patients, 39 patients (61.9%) were asymptomatic, while 15 patients (23.8%) had mild hemoptysis without the need for any medical intervention. Although 9 patients (14.3%) experienced moderate hemoptysis, these patients showed improvement with appropriate hemostatic drug treatment. None of the patients experienced severe hemoptysis that necessitated invasive medical interventions (Table ##TAB##1##2##).\n</p>", "<title>Subgroup analysis</title>", "<p id=\"Par29\">The outcomes of the subgroup analysis on PTX and PH are presented in Table ##TAB##2##3## and Table ##TAB##3##4##. The analysis revealed that the incidence of PTX was associated with lesion diameter, the use of gelfoam, and RFA (<italic>P</italic> &lt; 0.05). PH was found to be associated with the presence of pulmonary emphysema, lesion diameter, the use of gelfoam, RFA, and the number of samples (<italic>P</italic> &lt; 0.05).\n</p>", "<title>Logistic regression</title>", "<p id=\"Par30\">Significant factors for subgroup analysis were incorporated into the logistic regression analyses. Table ##TAB##4##5## displays the findings of the logistic regression analysis conducted to assess the impact of parameters on PTX and PH. Lesion diameter (OR = 0.822, per centimeter), the use of gelfoam (OR = 0.474), and RFA therapy (OR = 2.351) were identified as potential influencing factors for PTX. Lesion diameter (OR = 0.785, per centimeter), the use of gelfoam (OR = 0.341), RFA therapy (OR = 3.443), the presence of pulmonary emphysema (OR = 2.148), and the number of samples (OR = 1.834, per sample) were identified as potential influencing factors for PH.\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par31\">CBCT is a technology that integrates flat detectors with cone-beam CT within an angiography-interventional C-arm, demonstrating sufficient bone and soft-tissue resolution in preclinical investigations to aid minimally invasive head and neck surgery [##REF##18029850##27##]. The primary advantage of using CBCT systems for percutaneous needle procedures is the real-time imaging during needle insertion, which simplifies needle path planning and improves the accuracy of reaching target lesions. Furthermore, the use of flat-panel CBCT systems has the potential to reduce procedure times and, subsequently, radiation doses for patients. The objective of our study was to analyze the incidence, clinical significance, and correlation of two complications, PTX and PH.</p>", "<p id=\"Par32\">PTX and PH have a tangible impact on patient management and discomfort levels. Mild cases of PTX and PH can contribute to prolonged hospital stays for patients, while severe cases of PTX and PH can lead to respiratory and circulatory system disorders, posing a significant risk to patient safety. The incidence of PTX and PH in this study were similar (34.9 and 32.8%, respectively), consistent with previous literature on CT-guided procedures [##REF##27108299##28##–##REF##35227506##33##]. Conservative treatment is effective in improving the vast majority of PTX and PH cases. The requirement for CTI was observed in only 7.5% of cases, which aligns with the incidence previously reported, ranging from 2.4 to 15% [##REF##24475839##23##, ##REF##28478642##34##, ##REF##20173164##35##]. None of those with PH required bronchoscopes or endovascular treatments. Furthermore, no major complications, such as liver or spleen injury, air embolism, or mortality, were observed in our study. These findings suggest that CBCT-guided PTLB is a relatively safe procedure, characterized by a low incidence of clinically significant complications and no requirement for a prolonged hospital stay in the majority of patients.</p>", "<p id=\"Par33\">While considering many factors such as demographic, clinical characteristics, imaging, and PTLB parameters, only a handful of them showed statistically significant results. The most significant finding is the impact of gelfoam on reducing the incidence of PTX and PH (OR value decreased by 56.8 and 69% respectively). This finding holds clinical significance due to the accessibility and simplicity of using gelfoam in medical practice. Since the initial performance of PTLB, interventional radiologists have explored different techniques to reduce the risk of complications [##REF##23701059##36##–##REF##28185770##38##]. Among these methods, the closure of the needle tract using various embolizing materials has received considerable research attention. The injection of gelfoam leads to its expansion within the needle tract, creating a dense filling that conforms to the shape of the tract. This effectively prevents bleeding and the entry of intrapulmonary air into the pleural cavity through the puncture tract, as well as pleural rupture. Renier et al. created a slurry by cutting 15 pieces of a 2 × 6 cm absorbable gelatin sponge into roughly equal sizes and mixing them with 2 ml of saline [##REF##31792589##39##]. They successfully reduced the incidence of PTX and CTI by sealing the puncture tract with this slurry. In contrast to previous studies, our study utilized smaller gelatin sponge particles with a size range of 1000–1200 μm. This approach not only reduced the preparation time of the slurry but also allowed for a more dense sealing of the puncture tract.</p>", "<p id=\"Par34\">A larger diameter demonstrated a protective effect against both PTX and PH, with OR of 0.822 and 0.785 per centimeter, respectively. On the contrary, an increased number of samples extracted during PTLB was associated with a higher likelihood of developing PH, with a corresponding increase in the OR (83.4% for each additional piece of samples removed). These two observations are in line with previous findings and highlight the correlation between the level of technical complexity of the PTLB procedure and the incidence of complications [##REF##33938644##17##, ##REF##22146973##20##]. Biopsying large lesions is easier and requires less time for needle placement within the parenchyma, resulting in a lower probability of developing procedural complications. In contrast, obtaining samples from repeated punctures can be challenging, require a longer procedure time, and have a higher risk of complications.</p>", "<p id=\"Par35\">Our study reveals that RFA therapy performed after PTLB is associated with an increased risk of both PTX and PH (OR<sub>PTX</sub> = 2.351; OR<sub>PH</sub> = 3.443). Previous studies have shown that performing PTLB and RFA therapy in the same procedure can avoid multiple punctures [##REF##27300196##40##]. Therefore, in our study, patients with a high suspicion of malignant lung nodules underwent RFA following PTLB. Schneider et al. reported in their study that performing a biopsy immediately before RFA may result in PH or PTX, which can compromise the accuracy of subsequent RFA needle placement by blurring or displacing the tumor [##REF##24561446##41##]. This is because an additional puncture was necessary during the biopsy due to the unavailability of a suitable guiding cannula. However, in our study, no additional punctures were required during the establishment of the puncture tract due to the use of a multifunctional coaxial cannula. Following the PTLB, only the cutting needle was retrieved while the coaxial cannula remained in place. This method not only guarantees the accuracy of pathological results but also reduces the number of required punctures. Izaaryene et al. conducted pathological investigations after radiofrequency ablation of the lung in pigs and observed distinct needle tracts compared to a simple biopsy. They identified unique histological changes within the ablation tracts, which were likely attributable to thermal effects [##UREF##2##42##]. This study indicates that the needle tract created after RFA may tend to remain open for an extended period compared to biopsy alone, potentially leading to PTX and PH.</p>", "<p id=\"Par36\">In addition, our study discovered that the occurrence of pulmonary emphysema increases the risk of PH. This finding is in line with previous research [##REF##33938644##17##]. A previous study has demonstrated a significant correlation between pulmonary emphysema and PH and proposed that the heightened risk could be a result of pulmonary hypertension [##REF##18620122##43##]. An alternative explanation is that in patients with pulmonary emphysema, the destruction of air-space walls beyond the terminal bronchioles could create additional space for the PH to expand, leading to an increased risk of complications [##REF##26479161##44##]. In conclusion, heightened vigilance is necessary when conducting biopsies on patients with pulmonary emphysema due to the increased risk of complications.</p>", "<p id=\"Par37\">Several limitations of this study should be acknowledged. Firstly, the study is retrospective. Due to the limitations of the available procedure records, we were unable to further explore several influencing factors, such as the distance between the puncture site and the lesion. Secondly, it is a single-center study, which may limit the generalizability of the results. Thirdly, the limited number of patients requiring CTI, bronchoscopes, or endovascular treatments restricted our ability to conduct a comprehensive analysis of the factors influencing the rate of these interventions.</p>" ]
[ "<title> Conclusion</title>", "<p id=\"Par38\">In conclusion, CBCT-guided PTLB is a reliable technique that is widely used in the diagnosis of pulmonary lesions. Nonetheless, akin to CT-guided PTLB, PTX and PH persist as prominent complications. To reduce these complications, this study introduces an innovative and feasible approach—using gelfoam to embolize the puncture tract. This method has demonstrated a noteworthy reduction in the complication rate.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">This study aimed to assess the incidence and clinical significance of pneumothorax (PTX) and pulmonary hemorrhage (PH) after percutaneous transthoracic lung biopsy (PTLB) guided by C-arm cone-beam computed tomography (CBCT). Furthermore, this study aimed to examine the relationships between PTX and PH with demographics, clinical characteristics, imaging, and PTLB parameters.</p>", "<title>Methods</title>", "<p id=\"Par2\">A retrospective analysis was conducted on 192 patients who underwent PTLB at our hospital between January 2019 and October 2022. Incidences of PTX and PH were recorded. PTX was considered clinically significant if treated with chest tube insertion (CTI), and PH if treated with bronchoscopes or endovascular treatments. The various factors on PTX and PH were analyzed using the Chi-squared test and Student t-test. Logistic regression analyses were then used to determine these factors on the correlation to develop PTX and PH.</p>", "<title>Results</title>", "<p id=\"Par3\">PTX occurred in 67/192 cases (34.9%); CTI was required in 5/67 (7.5%). PH occurred in 63/192 cases (32.8%) and none of these cases required bronchoscopes or endovascular treatments. Lesion diameter (OR<sub>PTX</sub> = 0.822; OR<sub>PH</sub> = 0.785), presence of pulmonary emphysema (OR<sub>PH</sub> = 2.148), the number of samples (OR<sub>PH</sub> = 1.834), the use of gelfoam (OR<sub>PTX</sub> = 0.474; OR<sub>PH</sub> = 0.341) and ablation (OR<sub>PTX</sub> = 2.351; OR<sub>PH</sub> = 3.443) showed statistically significant correlation to PTX and PH.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">CBCT-guided PTLB is a safe and effective method for performing lung biopsies. The use of gelfoam has been shown to reduce the occurrence of PTX and PH. However, caution should be exercised when combining radiofrequency ablation with PTLB, as it may increase the risk of PTX and PH.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>There are no acknowledgments to be made.</p>", "<title>Authors’ contributions</title>", "<p>Zhiping Yan and Wen Zhang participated in the design of this study and manuscript editing. Wen Zhang made an equal contribution and should be acknowledged as a co-corresponding author. Yanjie Yang participated in the literature search, data collection, data analysis, statistical analysis, and manuscript preparation. Jingqin Ma participated in manuscript preparation and manuscript revise. Zhijie Peng participated in the literature search, data collection, and data analysis. Jingqin Ma and Zhijie Peng made an equal contribution and should be recognized as co-first authors. Xin Zhou participated in data analysis. Nan Du participated in the manuscript review. All authors have read and approved the content of the manuscript.</p>", "<title>Funding</title>", "<p>This work was funded by the Shanghai Key Clinical Specialty Construction Program – Extending Two Wings: Interventional Therapy (shslczdzk06003).</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par39\">The Institutional Review Board (IRB) of Zhongshan Hospital of Fudan University approved the study (IRB No. B2022–612). All patients provided written informed consent before treatment, in compliance with the Declaration of Helsinki. The donation process conformed to the Declaration of Istanbul. All organs were donated voluntarily with written informed consent.</p>", "<title>Consent for publication</title>", "<p id=\"Par40\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par41\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow chart showing the enrolled patients. PTLB percutaneous transthoracic lung biopsy, CBCT C-arm cone-beam computed tomography, pneumothorax (PTX), pulmonary hemorrhage (PH)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p><bold>a</bold> Pre-procedure CT: A 79-year-old man with a history of hepatectomy for hepatocellular carcinoma 2 years ago presented with a 24-mm solid pulmonary lesion in the left lower lobe. <bold>b</bold> Following the combined procedure of percutaneous transthoracic lung biopsy (PTLB) and radiofrequency ablation (RFA), the patient experienced a severe pneumothorax, which necessitated chest tube insertion (CTI). The chest tube was left in place for drainage purposes for 2 days</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p><bold>a</bold> Pre-procedure CT: A 69-year-old man with a 29-mm solid pulmonary lesion in the left lower lobe. <bold>b</bold> On the post-procedural CT scan, a ground-glass opacity was observed in the pulmonary parenchyma. However, the patient did not experience any episodes of hemoptysis</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics of all included patients</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th colspan=\"2\">Characteristics (<italic>n</italic> = 192)</th></tr></thead><tbody><tr><td>Sex</td><td/></tr><tr><td> Male</td><td>129(67.2%)</td></tr><tr><td> Female</td><td>63(32.8%)</td></tr><tr><td>Age (years)</td><td/></tr><tr><td> Mean ± SD</td><td>62.1 ± 13.4</td></tr><tr><td> Range</td><td>18 ~ 86</td></tr><tr><td>Smoking history</td><td/></tr><tr><td> Yes</td><td>29(15.1%)</td></tr><tr><td> No</td><td>163(84.9%)</td></tr><tr><td>Pulmonary emphysema</td><td/></tr><tr><td> Yes</td><td>47(24.5%)</td></tr><tr><td> No</td><td>145(75.5%)</td></tr><tr><td>Lesion diameter (cm)</td><td/></tr><tr><td> Mean ± SD</td><td>3.4 ± 2.2</td></tr><tr><td> Range</td><td>0.6 ~ 13.8</td></tr><tr><td>Lesion feature</td><td/></tr><tr><td> Solid</td><td>164(85.4%)</td></tr><tr><td> Ground glass</td><td>22(11.5%)</td></tr><tr><td> Cavity</td><td>6(3.1%)</td></tr><tr><td>Lesion location</td><td/></tr><tr><td> Right upper lobe</td><td>39(20.3%)</td></tr><tr><td> Right middle lobe</td><td>12(6.3%)</td></tr><tr><td> Right lower lobe</td><td>49(25.5%)</td></tr><tr><td> Left upper lobe</td><td>51(26.6%)</td></tr><tr><td> Left lower lobe</td><td>41(21.4%)</td></tr><tr><td>Patient position</td><td/></tr><tr><td> Supine</td><td>72(37.5%)</td></tr><tr><td> Prone</td><td>120(62.5%)</td></tr><tr><td>Gelfoam</td><td/></tr><tr><td> Yes</td><td>77(40.1%)</td></tr><tr><td> No</td><td>115(59.9%)</td></tr><tr><td>Pathology results</td><td/></tr><tr><td> Benign</td><td>48(25.0%)</td></tr><tr><td> Malignant</td><td>141(73.4%)</td></tr><tr><td> Insufficient material</td><td>3(1.6%)</td></tr><tr><td>Radiofrequency ablation</td><td/></tr><tr><td> Yes</td><td>43(22.4%)</td></tr><tr><td> No</td><td>149(77.6%)</td></tr><tr><td>The number of samples extracted</td><td/></tr><tr><td> 1</td><td>69(35.9%)</td></tr><tr><td> 2</td><td>96(50.0%)</td></tr><tr><td> 3</td><td>21(10.9%)</td></tr><tr><td> 4</td><td>6(3.1%)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Incidence and types of pneumothorax and pulmonary hemorrhage</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th>Pneumothorax</th><th>Incidence</th><th>Chest tube insertion</th></tr></thead><tbody><tr><td>Total</td><td>67/192 (34.9%)</td><td>5/67 (7.5%)</td></tr><tr><td> Immediate CBCT scan</td><td>42/67 (62.7%)</td><td>2/5 (40%)</td></tr><tr><td> 24 h on CT scan</td><td>25/67 (37.3%)</td><td>3/5 (60%)</td></tr><tr><td>Pulmonary hemorrhage</td><td>Incidence</td><td>Bronchoscopes or endovascular treatments</td></tr><tr><td>Total</td><td>63/192 (32.8%)</td><td>0/63 (0%)</td></tr><tr><td> Asymptomatic</td><td>39/63 (61.9%)</td><td/></tr><tr><td> Mild hemoptysis</td><td>15/63 (23.8%)</td><td/></tr><tr><td> Moderate hemoptysis</td><td>9/63 (14.3%)</td><td/></tr><tr><td> Severe hemoptysis</td><td>0/63 (0%)</td><td/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Subgroup analysis of pneumothorax</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Influence factor</th><th align=\"left\" colspan=\"2\">Pneumothorax</th><th align=\"left\" rowspan=\"2\"><italic>t</italic>/c<sup><italic>2</italic></sup>,<italic>P</italic></th></tr><tr><th align=\"left\">Yes(<italic>n</italic> = 67)</th><th align=\"left\">No(<italic>n</italic> = 125)</th></tr></thead><tbody><tr><td align=\"left\">Sex (Male/female)</td><td align=\"left\">45/22</td><td align=\"left\">84/41</td><td align=\"left\">0.000, 0.996</td></tr><tr><td align=\"left\">Age (years)</td><td align=\"left\">61.8 ± 15.0</td><td align=\"left\">62.3 ± 12.6</td><td align=\"left\">0.213, 0.831</td></tr><tr><td align=\"left\">Smoking history (Yes/No)</td><td align=\"left\">11/56</td><td align=\"left\">18/107</td><td align=\"left\">0.139, 0.710</td></tr><tr><td align=\"left\">Pulmonary emphysema (Yes/No)</td><td align=\"left\">16/51</td><td align=\"left\">31/94</td><td align=\"left\">0.020, 0.888</td></tr><tr><td align=\"left\">Lesion diameter</td><td align=\"left\">2.8 ± 1.6</td><td align=\"left\">3.7 ± 2.4</td><td align=\"left\">3.125, 0.002</td></tr><tr><td align=\"left\">Lesion feature</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Solid</td><td align=\"left\">59</td><td align=\"left\">105</td><td align=\"left\" rowspan=\"3\">2.167, 0.352</td></tr><tr><td align=\"left\"> Ground glass</td><td align=\"left\">5</td><td align=\"left\">17</td></tr><tr><td align=\"left\"> Cavity</td><td align=\"left\">3</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Lesion location</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Right upper lobe</td><td align=\"left\">16</td><td align=\"left\">23</td><td align=\"left\" rowspan=\"5\">5.549, 0.234</td></tr><tr><td align=\"left\"> Right middle lobe</td><td align=\"left\">3</td><td align=\"left\">9</td></tr><tr><td align=\"left\"> Right lower lobe</td><td align=\"left\">21</td><td align=\"left\">28</td></tr><tr><td align=\"left\"> Left upper lobe</td><td align=\"left\">18</td><td align=\"left\">33</td></tr><tr><td align=\"left\"> Left lower lobe</td><td align=\"left\">9</td><td align=\"left\">32</td></tr><tr><td align=\"left\">Patient position (Supine/Prone)</td><td align=\"left\">25/42</td><td align=\"left\">47/78</td><td align=\"left\">0.002, 0.969</td></tr><tr><td align=\"left\">Gelfoam (Yes/No)</td><td align=\"left\">18/49</td><td align=\"left\">59/66</td><td align=\"left\">7.509, 0.006</td></tr><tr><td align=\"left\">Pathology results(Benign/Malignant/ Insufficient material)</td><td align=\"left\">19/46/2</td><td align=\"left\">29/95/1</td><td align=\"left\">2.228, 0.310</td></tr><tr><td align=\"left\">Radiofrequency ablation (Yes/No)</td><td align=\"left\">23/44</td><td align=\"left\">20/105</td><td align=\"left\">8.431, 0.004</td></tr><tr><td align=\"left\">The number of samples</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 1</td><td align=\"left\">28</td><td align=\"left\">41</td><td align=\"left\" rowspan=\"4\">1.668, 0.647</td></tr><tr><td align=\"left\"> 2</td><td align=\"left\">31</td><td align=\"left\">65</td></tr><tr><td align=\"left\"> 3</td><td align=\"left\">6</td><td align=\"left\">15</td></tr><tr><td align=\"left\"> 4</td><td align=\"left\">2</td><td align=\"left\">4</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Subgroup analysis of pulmonary hemorrhage</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Influence factor</th><th align=\"left\" colspan=\"2\">Pulmonary hemorrhage</th><th align=\"left\" rowspan=\"2\"><italic>t</italic>/c<sup><italic>2</italic></sup>,<italic>P</italic></th></tr><tr><th align=\"left\">Yes(<italic>n</italic> = 63)</th><th align=\"left\">No(<italic>n</italic> = 129)</th></tr></thead><tbody><tr><td align=\"left\">Sex (Male/female)</td><td align=\"left\">45/18</td><td align=\"left\">84/45</td><td align=\"left\">0.765, 0.382</td></tr><tr><td align=\"left\">Age (years)</td><td align=\"left\">62.0 ± 14.5</td><td align=\"left\">62.2 ± 13.0</td><td align=\"left\">0.098, 0.922</td></tr><tr><td align=\"left\">Smoking history (Yes/No)</td><td align=\"left\">12/51</td><td align=\"left\">17/112</td><td align=\"left\">1.137, 0.286</td></tr><tr><td align=\"left\">Pulmonary emphysema (Yes/No)</td><td align=\"left\">21/42</td><td align=\"left\">26/103</td><td align=\"left\">3.976, 0.046</td></tr><tr><td align=\"left\">Lesion diameter</td><td align=\"left\">2.7 ± 1.7</td><td align=\"left\">3.7 ± 2.3</td><td align=\"left\">3.567, 0.001</td></tr><tr><td align=\"left\">Lesion feature</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Solid</td><td align=\"left\">55</td><td align=\"left\">109</td><td align=\"left\" rowspan=\"3\">1.904, 0.393</td></tr><tr><td align=\"left\"> Ground glass</td><td align=\"left\">5</td><td align=\"left\">17</td></tr><tr><td align=\"left\"> Cavity</td><td align=\"left\">3</td><td align=\"left\">3</td></tr><tr><td align=\"left\">Lesion location</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> Right upper lobe</td><td align=\"left\">18</td><td align=\"left\">21</td><td align=\"left\" rowspan=\"5\">5.094, 0.277</td></tr><tr><td align=\"left\"> Right middle lobe</td><td align=\"left\">5</td><td align=\"left\">7</td></tr><tr><td align=\"left\"> Right lower lobe</td><td align=\"left\">13</td><td align=\"left\">36</td></tr><tr><td align=\"left\"> Left upper lobe</td><td align=\"left\">16</td><td align=\"left\">35</td></tr><tr><td align=\"left\"> Left lower lobe</td><td align=\"left\">11</td><td align=\"left\">30</td></tr><tr><td align=\"left\">Patient position (Supine/Prone)</td><td align=\"left\">24/39</td><td align=\"left\">48/81</td><td align=\"left\">0.014, 0.905</td></tr><tr><td align=\"left\">Gelfoam (Yes/No)</td><td align=\"left\">15/48</td><td align=\"left\">62/67</td><td align=\"left\">10.365, 0.001</td></tr><tr><td align=\"left\">Pathology results(Benign/Malignant/ Insufficient material)</td><td align=\"left\">17/45/1</td><td align=\"left\">31/96/2</td><td align=\"left\">0.431, 0.876</td></tr><tr><td align=\"left\">Radiofrequency ablation (Yes/No)</td><td align=\"left\">20/43</td><td align=\"left\">20/109</td><td align=\"left\">10.744, 0.001</td></tr><tr><td align=\"left\">The number of samples</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 1</td><td align=\"left\">18</td><td align=\"left\">51</td><td align=\"left\" rowspan=\"4\">8.048, 0.038</td></tr><tr><td align=\"left\"> 2</td><td align=\"left\">34</td><td align=\"left\">62</td></tr><tr><td align=\"left\"> 3</td><td align=\"left\">6</td><td align=\"left\">15</td></tr><tr><td align=\"left\"> 4</td><td align=\"left\">5</td><td align=\"left\">1</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Logistic regression analyses of pneumothorax and pulmonary hemorrhage</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th/><th><italic>P</italic></th><th>OR</th><th>CI</th></tr></thead><tbody><tr><td>Pneumothorax</td><td/><td/><td/></tr><tr><td> Lesion diameter</td><td>0.025</td><td>0.822</td><td>0.692–0.975</td></tr><tr><td> Gelfoam</td><td>0.028</td><td>0.474</td><td>0.244–0.923</td></tr><tr><td> Radiofrequency ablation</td><td>0.020</td><td>2.351</td><td>1.147–4.820</td></tr><tr><td>Pulmonary hemorrhage</td><td/><td/><td/></tr><tr><td> Lesion diameter</td><td>0.014</td><td>0.785</td><td>0.648–0.952</td></tr><tr><td> Gelfoam</td><td>0.005</td><td>0.341</td><td>0.162–0.718</td></tr><tr><td> Pulmonary emphysema</td><td>0.047</td><td>2.148</td><td>1.009–4.572</td></tr><tr><td> The number of samples</td><td>0.013</td><td>1.834</td><td>1.138–2.956</td></tr><tr><td> Radiofrequency ablation</td><td>0.002</td><td>3.443</td><td>1.555–7.627</td></tr></tbody></table></table-wrap>" ]
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[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Yanjie Yang, Jingqin Ma and Zhijie Peng contributed equally to this work and should be considered co-first authors.</p></fn><fn><p>Wen Zhang and Zhiping Yan contributed equally to this work and should be considered co-corresponding authors.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12890_2023_2822_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12890_2023_2822_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12890_2023_2822_Fig3_HTML\" id=\"MO3\"/>" ]
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[{"label": ["5."], "mixed-citation": ["Sali R, Jiang Y, Attaranzadeh A, et al. Morphological diversity of cancer cells predicts prognosis across tumor types. J Natl Cancer Inst. 2023:djad243."]}, {"label": ["11."], "surname": ["Strocchi", "Colli", "Conte"], "given-names": ["S", "V", "L"], "article-title": ["Multidetector CT fluoroscopy and cone-beam CT-guided percutaneous transthoracic biopsy: comparison based on patient doses"], "source": ["Radiat Prot Dosim."], "year": ["2012"], "volume": ["151"], "issue": ["1"], "fpage": ["162"], "lpage": ["165"], "pub-id": ["10.1093/rpd/ncr464"]}, {"label": ["42."], "surname": ["Izaaryene", "Cohen", "Souteyrand"], "given-names": ["J", "F", "P"], "article-title": ["Pathological effects of lung radiofrequency ablation that contribute to pneumothorax, using a porcine model"], "source": ["Int J Hyperth."], "year": ["2017"], "volume": ["33"], "issue": ["7"], "fpage": ["713"], "lpage": ["716"]}]
{ "acronym": [ "CT", "PTLB", "CCT", "CBCT", "PTX", "PH", "CTI", "RFA", "OR" ], "definition": [ "Computed tomography", "Percutaneous transthoracic lung biopsy", "Conventional computed tomography", "C-arm cone-beam computed tomography", "Pneumothorax", "Pulmonary hemorrhage", "Chest tube insertion", "Radiofrequency ablation", "Odd ratios" ] }
44
CC BY
no
2024-01-14 23:43:47
BMC Pulm Med. 2024 Jan 13; 24:33
oa_package/64/74/PMC10787482.tar.gz
PMC10787483
38170474
[ "<title>Introduction</title>", "<p>Follow up of recipients of implantable cardiac electronic devices has been facilitated by automatic remote monitoring (RM) which offers early event detection and enables, when needed, timely treatment.<sup>##REF##20625110##1##</sup> For example, insertable cardiac monitors (ICM) permit much longer monitoring of patients with suspected atrial fibrillation (AF) compared to usual care<sup>##REF##34756594##2##</sup> or standard 24-h ambulatory ECG recordings.<sup>##REF##28624331##3##</sup> ICMs are now widely and increasingly used in routine care and represent an important diagnostic instrument, most notably for cryptogenic strokes, unexplained syncope, palpitations, and a variety of arrhythmias, and particularly AF.<sup>##REF##7671366##4##,##REF##30466842##5##</sup> However, adjudication of device events presents a huge workload to clinic staff. While ICM diagnostic algorithms differ among manufacturers and device models, clinical experience and peer-reviewed medical literature suggest consistently that these systems are highly sensitive to arrhythmias, but are vulnerable to a high rate of FP detections<sup>##REF##20160169##6–8##</sup> reported to be between 46% and 86%, depending on implant indication.<sup>##REF##31323348##9##</sup> Several solutions have been proposed to increase specificity. Among them, artificial intelligence (AI) may filter only the most actionable data to clinicians.<sup>##REF##28919290##10##</sup> These algorithms use large amounts of data to ‘train’ the computer by labelling each case according to one of many predefined abnormalities, allowing the machine to discern what characteristics of the ECG are associated with any given abnormality.</p>", "<p>Here, we hypothesized that the ILR-ECG Analyzer™ (ILR-ECG-A) machine learning algorithm (Implicity™, Paris, France) designed to reclassify ICM recorded arrhythmias, would diminish the percentage of FP episodes i.e. increase specificity. This algorithm is CE marked class I and Food and Drug Administration (FDA) cleared class II.</p>" ]
[ "<title>Methods</title>", "<title>Study design</title>", "<p>Among 2643 recipients of Reveal LINQ, DX, or XT ICM entered in the Implicity database, we selected on 2020-11 546 patients (as was required by a preliminary sample size calculation) from 18 French and 13 US medical centres, with a random draw from a uniform distribution. Three different versions of the manufacturers’ ICM are then included in this study, in proportion close to what they were in this RM platform at the time of patient selection. The data for these patients had been transmitted between the ICM and the platform as part of the patients’ routine care. For these patients, we extracted all episodes transmitted from January 2014 to October 2020. For this study, the daily transmissions were anonymized, and the events were collected towards a retrospective analysis of the new ILR-ECG-A algorithm’s performance. Since this was a retrospective analysis of clinical data, this study was exempt from reviews and approvals by the institutional review boards of the participating institutions, in accordance with the European ‘General Data Protection Regulation’ (UE 2016/679). All patients had granted their written approval to contribute the data at the time of activation of RM. All data were de-identified to ensure the protection of personal health data, according to the regulation and French reference methodology.</p>", "<title>ICM-detected events</title>", "<p>The three ICM algorithms can detect four main types of abnormal rhythms:</p>", "<p>\n<italic toggle=\"yes\">Asystole</italic>, defined as the absence of ventricular activity for a duration longer than a programmable value (1.5 s, 3 s, 4.5 s—the default is 3 s).</p>", "<p>\n<italic toggle=\"yes\">Bradycardia</italic>, defined as consecutive RR intervals (the intervals between two consecutive R-waves) above a programmable value (1.2 s, 1.5 s, 2.0 s—the default is 2.0 s).</p>", "<p>\n<italic toggle=\"yes\">Atrial tachycardia</italic> or <italic toggle=\"yes\">atrial fibrillation</italic> (AT/AF) is detected using an automatic algorithm based on the R-R interval variability within a 2-min period. The differences between consecutive R-R intervals are displayed in a Lorenz plot. Pattern recognition is used to identify the AT and AF episodes; R-R intervals are highly irregular and uncorrelated during episodes of AF, whereas they are regular during episodes of AT. In addition, for Reveal LINQ specifically, a <italic toggle=\"yes\">P</italic>-wave presence algorithm allows for the filtering of episodes that presents detectable <italic toggle=\"yes\">P</italic>-wave in R-R intervals.</p>", "<p>\n<italic toggle=\"yes\">Tachycardia</italic> (Tachy) is defined as a ventricular rhythm with consecutive RR intervals below a programmable value (ranging from 0.27 s to 0.50 s—the default is 0.34 s).</p>", "<p>These episodes are programmed at the time of ICM implantation and may be modified during follow-up. ICM has two means of recording the episodes:</p>", "<p>The device analyzes the cardiac signal incessantly and records and stores the ECG when an episode is detected by the algorithm. Such episodes have durations ranging from 5 s to 2 min, with a sampling rate of 256 Hz for each of the three considered ICM devices.</p>", "<p>The ICM captures an episode upon manual activation by the patient, who uses an assistant device or, in the latest models, a smartphone application. These episodes are usually activated when the patient experiences a symptomatic event, establishing a temporal relationship between symptoms and ICM recording.</p>", "<p>While programming of the algorithm closely adapts the device to the patient’s needs, it is often insufficient to control the high rate of FP detections, mostly due to loss of R-wave amplitude, premature atrial and ventricular events, oversensing of <italic toggle=\"yes\">P</italic> and T waves, or noise artefacts.</p>", "<title>Artificial intelligence-based detections by the ILR-ECG-A</title>", "<p>ILR-ECG-A, an AI-based algorithm, was developed to reclassify episodes recorded by the ICM, with a view of limiting the rate of FP detections. This algorithm uses the ICM signals as input and detects either a ‘Normal Rhythm’ or a list of abnormal events, classified as ‘Asystole’, ‘Bradycardia’, ‘AT/AF’, ‘VT’ (‘ventricular tachycardia’), ‘Artefact’ (uninterpretable signals), or ‘Unspecified Abnormality’. This algorithm comes with a suggestion to healthcare professionals to review in priority every episode not diagnosed as ‘Normal Rhythm’ with the same level of importance, as it is optimized to identify as few abnormal episodes as possible with this diagnosis. It is compatible with the transmission files of the ICM and can be interfaced with the RM platform. This allows access to the ECG signals with the highest accuracy and the transmission of its results to the interface used by the caregiver to follow patients remotely (<italic toggle=\"yes\">Figure ##FIG##0##1##</italic>). To classify the episodes, the AI-based algorithm automatically uses the settings of asystole, bradycardia, and tachycardia intervals programmed during ICM implantation. The algorithm was developed by a combination of expert features, which include morphological and frequential analyses of sensed QRS and P waves. For example, in addition to the pattern recognition applied to the Lorenz plot included in the ICM algorithms, the acceleration of the heart rate and the related time span between subsequent identifiable rhythms is computed as a feature. This allows us a better differentiation atrial tachycardias from normal sinus tachycardias. An improved QRS detection algorithms using an Optimized Knowledge-Based method<sup>##REF##30617320##11##</sup> also allowed for better algorithmic interpretations of Lorenz plots. To these expert features, a neural network was added to provide additional automatic features. The underlying architecture is a 1D Convolutional Neural Network (CNN), employing shortcut connections in a manner similar to the Residual Network architecture, as described by Hannun et al.<sup>##REF##24066054##12##</sup> It has six output classes instead of twelve, corresponding to the first six classes detected by ILR-ECG-A (The ‘Unspecified Abnormality’ output corresponding to the absence of the other six classes). The activations of the penultimate layer are then concatenated to expert features, to extend the information provided by these features. The resulting features are used as input of six machine learning classifiers, which compute scores for each of the possible diagnoses, and classify signal according to the outputs of the classifiers and fixed thresholds determined at the training stage.<sup>##UREF##0##13##</sup></p>", "<title>Training methodology of the ILR-ECG-A</title>", "<p>A development dataset of 3405 ICM episodes diagnosed by a panel of 9 expert cardiac electrophysiologists was used to train and validate the algorithm (<italic toggle=\"yes\">Figure ##FIG##1##2##</italic>). These episodes were collected from 870 patients of 22 European medical centres using the Implicity™ platform to follow their patients. They were selected to have a high variety of ICM episode types: these episodes were selected so that at most 5 episodes per patient and per ICM diagnosis could be selected. As such, the episodes were balanced with respect to the ICM diagnosis. On each of these episodes, the experts annotated the start and end of each diagnosis on the ECG trace. Using a subset of these episodes with expert adjudication, six machine learning algorithms (XGBoost) were trained to qualify the samples as sequentially ‘Artefact or not Artefact’, ‘Asystole or not Asystole’, ‘Bradycardia or not Bradycardia’, ‘AT/AF or not AT/AF’, ‘VT/ventricular fibrillation (VF) or not VT/VF’ and ‘Normal Rhythm or not Normal Rhythm’. The evaluation of each of these classifiers successively on any episode returns a qualification of this episode according to each qualification type. These six algorithms were all trained on binary classification tasks, with the previously described features as input, to which the output of previously trained classifiers, and with the binary label corresponding to their specific task as an optimization target. A hyper-optimization had been performed for each of the six algorithms, with the training dataset, sequentially, to determine their optimal hyper-parameters, and the optimal sequence of algorithms (i.e. the order in which the six algorithms were trained and evaluated).</p>", "<p>These qualifications were converted into a final diagnosis by the ILR-ECG-A algorithm using the following rules:</p>", "<p>If any of the abnormal qualification are fulfilled, the final diagnosis is the exhaustive list of abnormal qualification fulfilled for the episode</p>", "<p>Else, if the ‘Normal Rhythm’ qualification was fulfilled, the final diagnosis is ‘Normal Rhythm’</p>", "<p>Else, the final diagnosis was ‘Unspecified Abnormality’</p>", "<p>As such, ILR-ECG-A algorithm is conservative on the ‘Normal Rhythm’ diagnosis, as the final diagnosis of an episode can only be ‘Normal Rhythm’ if no abnormality was detected by ILR-ECG-A in any part of the ECG trace.</p>", "<p>The performances of the trained algorithms were evaluated on a subset of the development dataset (of patients not included in the training of the algorithm) using the endpoints described in the ‘Study endpoints’ section. The overall expected performance for the algorithm was a sensitivity over 90%, and a specificity over 60%. The performance target set for each individual label was that no Asystole, Bradycardia, or VT would be misdiagnosed as Normal Rhythm by ILR-ECG-A. The fixed thresholds used to classify signals were obtained by optimizing for these expected performances on the validation dataset. The algorithms reached these performance targets on the validation dataset, before the collection and evaluation of this study.</p>", "<title>Episode selection</title>", "<p>To test the ILR-ECG-A algorithm’s performance in a variety of arrhythmias, we sampled unique episodes of each type of arrhythmia transmitted by the patients. When multiple episodes of the same type were transmitted by the same patient, a single sample was retained for the analysis, using a uniform random sampling among the episodes of the same patient and type, to prevent a cluster effect. This data collection method was designed to sample the widest variety of abnormalities and discard redundant episodes. We expected this method to result in a low within-patient correlation among signals, conferring sufficient statistical power to our analysis. This episode selection method selected 1000 episodes for analysis (<italic toggle=\"yes\">Figure ##FIG##2##3##</italic>). All patient-activated episodes were excluded from the analysis, as the ILR-ECG-A algorithm, which implements the rules used by ICM to detect abnormal episodes, does not reclassify these signals. Events &lt;9.5 s in duration, too short for analysis by the algorithm, were likewise excluded.</p>", "<title>Study endpoints</title>", "<p>This study was designed to evaluate the ability of the ILR-ECG-A algorithm to decrease the rate of FP events recorded by Reveal ICM. As such, this study evaluated the ability of the ILR-ECG-A algorithm to detect FP events (i.e. diagnose these episodes as ‘Normal Rhythm’), while misdiagnosing few true positive (TP) episodes—‘Abnormality’—as ‘Normal Rhythm’. Therefore, this study uses a binary endpoint to describe the results of ILR-ECG-A. ‘Artefact’ episodes are defined in this study as episodes where the presence of a non-cardiac signal distorts the ECG enough to prevent medical interpretation. They were then not clearly identifiable as TP or FP events, as it was not possible in the scope of this study to associate them with real patient events. They then constituted a third category, to be analyzed separately from ‘Normal Rhythm’ and ‘Abnormality’. Events were collected by medical centres different from those where the machine learning classifier was trained and selected as described earlier. Therefore, no patient included in this study had episodes that had been used to train or validate the algorithm. The same events were analyzed by an independent adjudication committee (AC) and by the AI-based algorithm. The AC included five experienced cardiac electrophysiologists (Appendix <xref rid=\"app1\" ref-type=\"app\">1</xref>), who did not participate in the review of the algorithm’s training data, and who had no access to the patients’ clinical information. They examined each ECG recording and classified them as (i) ‘Abnormality’ (asystole, bradycardia, AT/AF, VT/VF, or other abnormalities), (ii) ‘Normal (sinus) Rhythm’, or (iii) ‘Artefact’, considering the settings of the ICM as the only rule for the events’ classification. Each event was reviewed by two members of the AC and, in case of disagreement, was adjudicated by the Chairman or in a consensus meeting of the Committee. The AC diagnoses were considered as the reference for the evaluation of the manufacturer’s and Implicity’s algorithms.</p>", "<p>The ILR-ECG-A algorithm diagnoses were compared with the AC adjudications as a binary classification, excluding ‘Artefacts’ for primary endpoints. The successful or unsuccessful identification of ‘Normal Rhythm’ and ‘Abnormality’ events by the AI-based algorithm was classified as TP<sub>AI</sub>, FP<sub>AI</sub>, True Negative (TN<sub>AI</sub>) or False Negative (FN<sub>AI</sub>). The sensitivity of the ILR-ECG-A algorithm was the proportion of arrhythmic episodes not classified as ‘Normal Rhythm’, calculated as TP<sub>AI</sub>/(TP<sub>AI</sub> + FN<sub>AI</sub>). Its specificity was the proportion of FP diagnoses by the ICM reclassified as ‘Normal Rhythm’ by the algorithm, calculated as TN<sub>AI</sub>/(FP<sub>AI</sub> + TN<sub>AI</sub>). The sensitivity and specificity of the ILR-ECG-A algorithm were the primary endpoints of the study. In the context of this study, only signals which were diagnosed as ‘Abnormality’ (positive) by ICMs were available.</p>", "<title>Statistical analyses</title>", "<p>No adjustment for multiplicity was made. A single device may have transmitted multiple events. Hence, a patient represents a cluster of personal signals. To minimize a within-cluster/patient correlation of the binary endpoint, the episodes were selected as described earlier. Therefore, the within-patient correlation among signals was assumed to be very low, and independence among signals was assumed in the primary analysis. In presence of multiple signals per patient, a generalized estimating equation (GEE) model assuming a compound symmetry correlation structure was fitted to account for signal correlation within each patient, to verify this assumption. The confidence intervals (CI) were calculated with the Clopper-Pearson exact test, assuming independence between episodes.</p>", "<p>The statistical calculations were made, using the SAS software (SAS Institute, Cary, NC). Binary endpoints were estimated along with 95% CI. Tests were performed at the 0.05, two-sided, α-level of significance.</p>" ]
[ "<title>Results</title>", "<p>The mean age of the 546 patients included in this study, of whom 331 (60.6%) underwent implants in the United States and 215 (39.4%) in Europe, was 68.0 ± 17.2 years. The ICM models included 455 (83.3%) LNQ11, 87 (16.0%) REVEAL XT 9529 and 4 (0.7%) REVEAL DX 9528. <italic toggle=\"yes\">Figure ##FIG##2##3##</italic> summarizes the event-sampling procedure. Of the 1000 episodes sampled (mean = 1.6 ± 0.8/patient), 117 patient-activated and 4 lasting &lt;9.5 s were excluded from the analysis. All the 546 patients had at least one episode included in the analysis. <italic toggle=\"yes\">Table ##TAB##0##1##</italic> lists the diagnoses made by the AC vs. the ICM for the 879 remaining episodes. Since &gt;1 abnormal rhythm might have been identified in a single event, by the AC or by ILR-ECG-A, the overall ‘Abnormality’ event count was inferior to the sum of the count of episodes annotated with each specific abnormality type. The AC annotated more AT/AF episodes than the ICM devices, as among the 241 episodes classified as ‘Tachy’ by ICM devices, 154 (63.9%) were diagnosed as AT, i.e. AT/AF by the AC.</p>", "<p>The AC identified 516 episodes as ‘Abnormality’ and 283 as ‘Normal Rhythm’. The sensitivity and specificity were calculated for the overall sample, and for each ICM model and event type subgroups. A GEE model was fitted for each endpoint and ensured the validity of the assumption of independence between episodes, thus validating the use of Clopper-Pearson exact 95% CI.</p>", "<title>Study endpoints</title>", "<p>The overall sensitivity of the ILR-ECG-A algorithm, i.e. the proportion of arrhythmic events which were not classified as ‘Normal Rhythm’ by the AI-based algorithm, was 98.6% (97.2%—99.5%) (superior to the 90% objective). The sensitivity measured by event type is presented in <italic toggle=\"yes\">Table ##TAB##1##2A##</italic>. A detailed analysis of the FN events, performed to verify the detection of all serious events, and the associated comments by the AC, are shown in <italic toggle=\"yes\">Table ##TAB##2##3##</italic>. None of these 7 FN episodes was considered diagnostically unambiguous by the AC, they were all diagnosed as Normal Rhythm by one annotator before being adjudicated as Other or AT/AF by the AC. Among these False Negatives, three had been identified as AT/AF by the ICM, three as Tachy, and one as Asytole. The sensitivities were consistent in subgroup analyses by event types (<italic toggle=\"yes\">Table ##TAB##1##2A##</italic>), by territories (USA vs. Europe) and device models (see ##SUPPL##0##Supplementary Material, Supplementary material online##, <italic toggle=\"yes\">##SUPPL##0##Table S1##</italic>).</p>", "<p>The overall specificity of the ILR-ECG-A algorithm (<italic toggle=\"yes\">Table ##TAB##1##2B##</italic>), i.e. the proportion of FP classifications by the ICM reclassified as ‘Normal Rhythm’ by the algorithm was 76.0% (95% CI: 70.6—80.8) (superior to the 60% objective). In the analysis by ICM event type, the lowest specificity of the algorithm (29/43–67.4%) was on the VT label. As among episodes diagnosed as VT by the ICM, many were normal sinus tachycardia and AT. These events are particularly difficult to differentiate on ICM traces, especially when the atrial activity is not visible on the ECG and/or the start and end of the episode were not recorded as part of the episode. For this reason, ILR-ECG-A misdiagnosed multiple Tachycardia ICM FP as AT instead of Normal Rhythm (for a normal sinus tachycardia) in such cases. The proportion of FP classifications by ICM reclassified as ‘Normal Rhythm’ by the algorithm cannot be described by AC event type, as the only FP classification available to the AC was ‘Normal Rhythm’ without further details.</p>", "<p>To better visualize the trade-off between sensitivity and specificity, the receiver operating characteristic curve (ROC-curve) of ILR-ECG-A was computed for the ‘Abnormality’ score, which is to classify signals as either ‘Abnormality’ or ‘Normal Rhythm’ (<italic toggle=\"yes\">Figure ##FIG##3##4##</italic>). The figure displays the decision thresholds lines, which intersect the ROC-curve at the threshold used by ILR-ECG-A trained algorithm and then corresponds to the overall sensitivity and specificity of the algorithm.</p>", "<p>Six examples of signals included in this study are presented in <italic toggle=\"yes\">Figure ##FIG##4##5##</italic>, with their diagnosis by the AC, the ICM, and ILR-ECG-A. The <italic toggle=\"yes\">Figure</italic><italic toggle=\"yes\">##FIG##4##5A, C##</italic> and <italic toggle=\"yes\">##FIG##4##D##</italic> are TNAI for ILR-ECG-A (TN<sub>AI</sub>), the <italic toggle=\"yes\">Figure ##FIG##4##5B##</italic> is a TP<sub>AI</sub>, the <italic toggle=\"yes\">Figure ##FIG##4##5E##</italic> is a FN<sub>AI</sub>, which corresponds to the fourth line of <italic toggle=\"yes\">Table ##TAB##2##3##</italic>. and the <italic toggle=\"yes\">Figure ##FIG##4##5F##</italic> is a FP<sub>AI</sub>.</p>" ]
[ "<title>Discussion</title>", "<p>This international study showed that ILR-ECG-A machine learning algorithm led to a correct reclassification of 76.0% of FP episodes, attributable to the filtering of the ICM episodes. Moreover, the algorithm sensitivity was 98.6%, and no critical episode, i.e. asystole, bradycardia, or VT, was identified as ‘Normal Rhythm’ by the device.</p>", "<p>Although RM decreases the need for on-site evaluations, management of associated transmissions consumes healthcare resources, with limited reimbursement. The volume of transmissions that trained professionals need to interpret has grown by several orders of magnitude in the past three decades and continues to increase.<sup>##REF##33516715##14##</sup> False positives are a source of increasing frustration and current proposed solutions include changes from the device nominal settings,<sup>##REF##33516715##14##</sup> with no evaluated impact on sensitivity. An AI system, such as the algorithm evaluated in this study, is an alternate strategy that can be directly connected to the ICM data transmissions and integrated in the clinician workflow, helping healthcare professionals improve their interpretation of alerts, especially when the volume of data increases. Moreover, AI algorithms may support the medical team focus on fewer ‘actionable’ signals without missing important events. In comparison with a change in the device settings, this allows an equivalent decrease in the rate of FPs to be reviewed, while keeping the filtered episodes in store in the RM platform, should further examinations or investigations be needed. Importantly, the AI algorithm should not filter TP episodes. We found a 98.6% overall sensitivity of the AI-based algorithm, due to 7 FN events (<italic toggle=\"yes\">Table ##TAB##2##3##</italic>). Although this study focused on the detection of FP events as ‘Normal Rhythm’, the clinical usefulness of such AI algorithm could be analyzed further by evaluating its performance as a multi-class classifier. This would assess its capability to identify the correct list of abnormalities shown in a given ICM episode, in addition to correctly identifying them as abnormal.</p>", "<p>In one prior study of AI applied to ICM diagnosed AF episodes, the most common reason for FP AF events was premature atrial contractions, and the algorithm reduced AF FP events by 39.5% to 66.4%, depending on the cohort. However, that study differs significantly from ours since it analyzed total episodes labelled as AF by ICM devices i.e. 1500 episodes for 425 patients. In comparison, we sampled one episode per patient per ICM diagnosis, and included a wider range of diagnoses i.e. asystole, bradycardia and VT, which represent an important proportion of FP alerts emitted by ICM.</p>", "<p>A study using a single-lead ECG combined with a machine learning algorithm demonstrated the possibility to improve the early identification of patients at risk for AF-induced cardiomyopathy.<sup>##REF##35295255##15##</sup> In a recent publication, it has been demonstrated the ability of a AI-based algorithm to predict the risk of AF from sinus rhythm recordings.<sup>##REF##36179758##16##</sup> Thus, AI-based algorithms are probably the future of atrial fibrillation diagnosis, either for ICM or for wearable devices.<sup>##REF##35640917##17##</sup> This study focused on the Reveal DX, XT and LINQ I (Medtronic) devices, with limited analytical capabilities; the new generation of ICM, such as the Linq II (Medtronic), introduces an algorithm based on AI, improving sensitivity. The main challenge in the near future will be to convince healthcare professionals to trust AI algorithms in their clinical practice, without delegating their responsibility.<sup>##REF##35969422##18##</sup> To achieve this goal, AI algorithms must integrate transparency, traceability,<sup>##REF##36426221##19##</sup> and explicability<sup>##REF##36248519##20##</sup> The use of AI in medicine is no more a novelty. It is used in cardiology and in particular in rhythm analysis, such as ECG<sup>##REF##36053812##21##</sup> and atrial fibrillation.<sup>##REF##36179758##16##,##REF##36215993##22##</sup></p>", "<p>The Implicity platform is designed as an agnostic tool, able to display all manufacturers devices data with the same ergonomics. In addition, alerts are filtered and sorted by severity. This approach has been shown to reduce reviews by 57%.<sup>##UREF##1##23##</sup> For this reason, we can expect a reduction in the workload of the medical team. By extension, costs can be expected to be reduced, as health professionals can focus their activities on relevant alerts requiring early intervention.</p>", "<title>Study limitations</title>", "<p>As mentioned in its FDA 510(k) approval, ILR-ECG-A interpretation results are not intended to be the sole means of diagnosis. It is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information.</p>", "<p>The study included only 16% and 0.7% of patients with a Reveal XT or Reveal DX. These proportions were obtained by randomly sampling patients followed with the Implicity™ platform on 2020–2011, and are expected to be representative of the Medtronic device repartition as that time, but it means that the level of proof for ILR-ECG-A sensitivity and specificity is lower on older devices than on the more recent Reveal LINQ I. Additionally, the ethnicity and gender of the patients included in this study were not collected. Hence, potential bias of the algorithm results across ethnicity and gender are not evaluated in this study and is only mitigated by the variety of medical centres included in this study.</p>", "<p>One hundred and seventeen patient-activated episodes were excluded from the analysis, as the ILR-ECG-A algorithm, which implements the rules used by ICM to detect abnormal episodes, does not reclassify these signals. Further development of the algorithm could allow it to provide clinical value with a reclassification of these episodes.</p>", "<p>Data collection in each patient selected a single type of episode, potentially introducing a selection bias in favour of rare kinds of episodes. This procedure was used to minimize the intra-patient correlations and expose the algorithm to a variety of events. A preliminary study evaluating the proportion of episodes diagnosed as Normal Rhythm in an unbiased dataset was conducted and showed that 33% of all episodes (including episodes without ECG trace and patient-activated episodes) were reclassified as Normal Rhythm by ILR-ECG-A.<sup>##UREF##2##24##</sup></p>" ]
[ "<title>Conclusion</title>", "<p>Given that ICM implant volume coupled to RM is expected to grow in upcoming years, the novel ILR-ECG-A AI-based algorithm that filters nearly 100% of FP ICM events and can be easily integrated into current workflow provides an opportunity to alleviate the heavy device clinic workload associated with ICM management.</p>" ]
[ "<p>\n<bold>Conflict of interest:</bold> Eliot Crespin, Issam Ibnouhsein, Alexandre Gozlan and Jean-Luc Bonnet are employed by Implicity. Arnaud Rosier is CEO and major shareholder of Implicity. Niraj Varma is consultant for Implicity. Arnaud Lazarus is a minor shareholder of Implicity. All remaining authors have declared no conflicts of interest.</p>", "<title>Abstract</title>", "<title>Aims</title>", "<p>The increasing use of insertable cardiac monitors (ICM) produces a high rate of false positive (FP) diagnoses. Their verification results in a high workload for caregivers. We evaluated the performance of an artificial intelligence (AI)-based ILR-ECG Analyzer™ (ILR-ECG-A). This machine-learning algorithm reclassifies ICM-transmitted events to minimize the rate of FP diagnoses, while preserving device sensitivity.</p>", "<title>Methods and results</title>", "<p>We selected 546 recipients of ICM followed by the Implicity™ monitoring platform. To avoid clusterization, a single episode per ICM abnormal diagnosis (e.g. asystole, bradycardia, atrial tachycardia (AT)/atrial fibrillation (AF), ventricular tachycardia, artefact) was selected per patient, and analyzed by the ILR-ECG-A, applying the same diagnoses as the ICM. All episodes were reviewed by an adjudication committee (AC) and the results were compared. Among 879 episodes classified as abnormal by the ICM, 80 (9.1%) were adjudicated as ‘Artefacts’, 283 (32.2%) as FP, and 516 (58.7%) as ‘abnormal’ by the AC. The algorithm reclassified 215 of the 283 FP as normal (76.0%), and confirmed 509 of the 516 episodes as abnormal (98.6%). Seven undiagnosed false negatives were adjudicated as AT or non-specific abnormality. The overall diagnostic specificity was 76.0% and the sensitivity was 98.6%.</p>", "<title>Conclusion</title>", "<p>The new AI-based ILR-ECG-A lowered the rate of FP ICM diagnoses significantly while retaining a &gt; 98% sensitivity. This will likely alleviate considerably the clinical burden represented by the review of ICM events.</p>" ]
[ "<title>Supplementary Material</title>" ]
[ "<title>Supplementary material</title>", "<p>\n##SUPPL##0##Supplementary material## is available at <italic toggle=\"yes\">Europace</italic> online.</p>", "<title>Funding</title>", "<p>No funding declared.</p>", "<title>Data availability</title>", "<p>The data underlying this article cannot be shared publicly due to the European GDPR (UE 2016/679). The data will be shared on reasonable request to the corresponding author in accordance with anonymization process and GDPR.</p>", "<title>Patient consent</title>", "<p>All patients had granted their written approval to contribute the data at the time of RM activation, in particular for its use for the purpose of research &amp; development activities, including design of algorithms. All data were de-identified to ensure the protection of personal health data, according to the European regulation and French reference methodology (MR-004), and in accordance with the HIPAA de-identification requirements in the US.</p>", "<title>Ethics statement</title>", "<p>Since this was a retrospective analysis of prospectively collected clinical data in real-life practice, this study was exempt from reviews and approvals by the institutional review boards of the participating institutions, the post-processing is conducted in accordance with the European ‘General Data Protection Regulation’ (UE 2016/679—article 5) and FDA regulations in the US.</p>", "<title>Appendix</title>", "<p>The AC was composed of the following board-certified cardiac electrophysiologists:</p>", "<p>\n<bold>Chairman:</bold> Etienne Aliot, MD, FHRS, Centre Hospitalier Régional Universitaire, Nancy, France</p>", "<p>\n<bold>Members:</bold>\n</p>", "<p>Nicolas Sadoul, MD PhD, Centre Hospitalier Régional Universitaire, Nancy, France</p>", "<p>Hugues Blangy, MD, PhD, Centre Hospitalier Régional Universitaire, Nancy, France</p>", "<p>Laurence Guédon-Moreau, MD, Centre Hospitalier Universitaire, Lille, France</p>", "<p>Claude Kouakam, MD, Centre Hospitalier Universitaire, Lille, France</p>" ]
[ "<fig position=\"float\" id=\"euad375-F1\" fig-type=\"figure\"><label>Figure 1</label><caption><p>Progression of an ILR event with the addition of the ILR-ECG-a algorithm to the diagnostics. As is usual with RM, the event emitted by the device is transmitted to the manufacturer’s Internet-based platform via the Patient Monitor. From there, the event is transmitted to a RM Platform interfaced with ILR-ECG-A. The event is sent to the algorithm, which adds its diagnostic results before the final transmission to the caregiver.</p></caption></fig>", "<fig position=\"float\" id=\"euad375-F2\" fig-type=\"figure\"><label>Figure 2</label><caption><p>Training of the AI-based ILR-ECG-a, and its evaluation, using an independent dataset, as described in the ‘methods’.</p></caption></fig>", "<fig position=\"float\" id=\"euad375-F3\" fig-type=\"figure\"><label>Figure 3</label><caption><p>Patient selection and flow of events from the initial inclusion of a predetermined sample of 1000 to the final inclusion of 879 events in the analysis.</p></caption></fig>", "<fig position=\"float\" id=\"euad375-F4\" fig-type=\"figure\"><label>Figure 4</label><caption><p>This ROC-curve was plotted for the ‘abnormality’ decision criteria of ILR-ECG-a. The ‘Decision Threshold’ lines display the Sensitivity and Specificity with the threshold used by the algorithm—which correspond to the results Overall Analysis line of <italic toggle=\"yes\">Table ##TAB##1##2##</italic>.</p></caption></fig>", "<fig position=\"float\" id=\"euad375-F5\" fig-type=\"figure\"><label>Figure 5</label><caption><p>Excerpts of ECG episodes reclassified by ILR-ECG-a, representative of several situations that occurred in this study. (A) ICM diagnosis: AT/AF; ILR-ECG-A diagnosis: Normal Rhythm; AC adjudication: Normal Rhythm. (B) ICM diagnosis: AT/AF; ILR-ECG-A diagnosis: AT/AF; AC adjudication: AT/AF. (C) ICM diagnosis: Asystole; ILR-ECG-A diagnosis: Normal Rhythm; AC adjudication: Normal Rhythm. (D) ICM diagnosis: VT; ILR-ECG-A diagnosis: Normal Rhythm; AC adjudication: Normal Rhythm. (E) ICM diagnosis: VT; ILR-ECG-A diagnosis: Normal Rhythm; AC adjudication: AT/AF. (F) ICM diagnosis: VT; ILR-ECG-A diagnosis: AT/AF; AC adjudication: Normal Rhythm.</p></caption></fig>" ]
[ "<table-wrap position=\"float\" id=\"euad375-T1\"><label>Table 1</label><caption><p>Episodes and diagnoses made by the AC and by the ICM, without and with the ILR-ECG-a algorithm</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" rowspan=\"2\" colspan=\"1\">Events diagnoses</th><th align=\"center\" rowspan=\"2\" colspan=\"1\">By the AC</th><th align=\"center\" colspan=\"2\" rowspan=\"1\">By the ICM</th></tr><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">Without ILR-ECG-A</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">With ILR-ECG-A</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">Normal rhythm</td><td rowspan=\"1\" colspan=\"1\">283 (32.2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not applicable</td><td rowspan=\"1\" colspan=\"1\">229 (26.1)</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Abnormality</td><td rowspan=\"1\" colspan=\"1\">516 (58.7)</td><td rowspan=\"1\" colspan=\"1\">879 (100)</td><td rowspan=\"1\" colspan=\"1\">577 (65.6)</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Artefact</td><td rowspan=\"1\" colspan=\"1\">80 (9.1)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not applicable</td><td rowspan=\"1\" colspan=\"1\">91 (10.3)</td></tr><tr><td colspan=\"4\" rowspan=\"1\">\n<bold>Abnormality details</bold>\n</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> AT or AF</td><td rowspan=\"1\" colspan=\"1\">370 (42.1)</td><td rowspan=\"1\" colspan=\"1\">313 (35.6)</td><td rowspan=\"1\" colspan=\"1\">451 (51.3)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Asystole</td><td rowspan=\"1\" colspan=\"1\">90 (10.2)</td><td rowspan=\"1\" colspan=\"1\">208 (23.7)</td><td rowspan=\"1\" colspan=\"1\">98 (11.1)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Bradycardia</td><td rowspan=\"1\" colspan=\"1\">58 (6.6)</td><td rowspan=\"1\" colspan=\"1\">117 (13.3)</td><td rowspan=\"1\" colspan=\"1\">63 (7.2)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Other</td><td rowspan=\"1\" colspan=\"1\">28 (3.2)</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not applicable</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not applicable</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> VT or VF</td><td rowspan=\"1\" colspan=\"1\">10 (1.1)</td><td rowspan=\"1\" colspan=\"1\">241 (27.4)</td><td rowspan=\"1\" colspan=\"1\">18 (2.0)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Unspecified abnormality</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not applicable</td><td align=\"left\" rowspan=\"1\" colspan=\"1\">Not applicable</td><td rowspan=\"1\" colspan=\"1\">31 (3.5)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"euad375-T2\"><label>Table 2</label><caption><p>A. Sensitivity and B. Specificity of the ILR-ECG-A algorithm</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/></colgroup><thead><tr><th rowspan=\"1\" colspan=\"1\"/><th align=\"center\" rowspan=\"1\" colspan=\"1\">A. Sensitivity</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">(n/N)</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">\n<bold>Overall analysis</bold>\n</td><td rowspan=\"1\" colspan=\"1\">98.6 [97.2–99.5]</td><td rowspan=\"1\" colspan=\"1\">(509/516)</td></tr><tr><td colspan=\"3\" rowspan=\"1\">\n<bold>By AC event type</bold>\n</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> AT/AF</td><td rowspan=\"1\" colspan=\"1\">98.7</td><td rowspan=\"1\" colspan=\"1\">(365/370)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Asystole</td><td rowspan=\"1\" colspan=\"1\">100.0</td><td rowspan=\"1\" colspan=\"1\">(90/90)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Bradycardia</td><td rowspan=\"1\" colspan=\"1\">100.0</td><td rowspan=\"1\" colspan=\"1\">(58/58)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Other</td><td rowspan=\"1\" colspan=\"1\">92.9</td><td rowspan=\"1\" colspan=\"1\">(26/28)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> VT</td><td rowspan=\"1\" colspan=\"1\">100.0</td><td rowspan=\"1\" colspan=\"1\">(10/10)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Artefact</td><td rowspan=\"1\" colspan=\"1\">92.5</td><td rowspan=\"1\" colspan=\"1\">(74/80)</td></tr><tr><td rowspan=\"1\" colspan=\"1\">\n<bold>Abnormalities + artefacts</bold>\n</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">97.7 [96.09–98.71]</td><td rowspan=\"1\" colspan=\"1\">(582/596)</td></tr></tbody></table><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/></colgroup><thead><tr><th rowspan=\"1\" colspan=\"1\"/><th align=\"center\" rowspan=\"1\" colspan=\"1\">B. Specificity</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">(n/N)</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">\n<bold>Overall analysis</bold>\n</td><td align=\"center\" rowspan=\"1\" colspan=\"1\">76.0 [70.6–80.8]</td><td rowspan=\"1\" colspan=\"1\">(215/283)</td></tr><tr><td colspan=\"3\" rowspan=\"1\">\n<bold>By ICM event type</bold>\n</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> AT/AF</td><td rowspan=\"1\" colspan=\"1\">75.0</td><td rowspan=\"1\" colspan=\"1\">(89/120)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Asystole</td><td rowspan=\"1\" colspan=\"1\">85.7</td><td rowspan=\"1\" colspan=\"1\">(54/63)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> Bradycardia</td><td rowspan=\"1\" colspan=\"1\">73.7</td><td rowspan=\"1\" colspan=\"1\">(42/57)</td></tr><tr><td rowspan=\"1\" colspan=\"1\"> VT</td><td rowspan=\"1\" colspan=\"1\">67.4</td><td rowspan=\"1\" colspan=\"1\">(29/43)</td></tr></tbody></table></table-wrap>", "<table-wrap position=\"float\" id=\"euad375-T3\"><label>Table 3</label><caption><p>FN events detected by the ILR-ECG-a algorithm</p></caption><table frame=\"hsides\" rules=\"groups\"><colgroup span=\"1\"><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/><col align=\"left\" valign=\"top\" span=\"1\"/></colgroup><thead><tr><th align=\"left\" colspan=\"2\" rowspan=\"1\">Diagnoses</th><th rowspan=\"2\" colspan=\"1\">Additional AC comments</th></tr><tr><th align=\"left\" rowspan=\"1\" colspan=\"1\">By the ICM</th><th align=\"center\" rowspan=\"1\" colspan=\"1\">Adjudicated by AC</th></tr></thead><tbody><tr><td rowspan=\"1\" colspan=\"1\">Tachy<break/>Tachy</td><td rowspan=\"1\" colspan=\"1\">AT/AF<break/>AT/AF</td><td rowspan=\"1\" colspan=\"1\">While these events appeared normal, the clockwise regularity of the rhythm at a 400-ms cycle length favoured the diagnosis of AT</td></tr><tr><td rowspan=\"1\" colspan=\"1\">Asystole<break/>Tachy<break/>AT/AF</td><td rowspan=\"1\" colspan=\"1\">AT/AF<break/>AT/AF<break/>AT/AF</td><td rowspan=\"1\" colspan=\"1\">These events were very noisy and their analysis was most challenging. Nevertheless, they appeared to be normal rhythm or AT</td></tr><tr><td rowspan=\"1\" colspan=\"1\">AT/AF</td><td rowspan=\"1\" colspan=\"1\">Other</td><td rowspan=\"1\" colspan=\"1\">P waves are visible in a type I second degree atrioventricular block periodicity, therefore not abnormal and classified as ‘Other’.</td></tr><tr><td rowspan=\"1\" colspan=\"1\">AT/AF</td><td rowspan=\"1\" colspan=\"1\">Other</td><td rowspan=\"1\" colspan=\"1\">The baseline rhythm was normal with brief ‘pauses’ consistent with mild sinus node dysfunction, classified as ‘Other’.</td></tr></tbody></table></table-wrap>" ]
[]
[ "<boxed-text id=\"euad375-box1\" position=\"anchor\"><caption><title>What’s new?</title></caption><list list-type=\"bullet\"><list-item><p>A new artificial intelligence (AI)-based ILR-ECG Analyzer™ (ILR-ECG-A) has been developed to lower the rate of false positive (FP) diagnoses in insertable cardiac monitors (ICM), while retaining a sensitivity of over 98%.</p></list-item><list-item><p>The ILR-ECG-A algorithm reclassified 76% of the episodes that were originally identified as FP by the ICM as normal, thus reducing the workload for caregivers in verifying these false positives.</p></list-item><list-item><p>The ILR-ECG-A retained a high sensitivity of 98.6% in detecting abnormal episodes, which makes it a reliable diagnostic tool for arrhythmias, including atrial tachycardia (AT) and atrial fibrillation (AF).</p></list-item><list-item><p>The ILR-ECG-A algorithm uses machine learning to discern the characteristics of the ECG associated with each abnormality, thereby reducing the number of FP detections.</p></list-item><list-item><p>The ILR-ECG-A is CE marked class I and Food and Drug Administration (FDA) cleared class II through a 510(k) submission.</p></list-item><list-item><p>The ILR-ECG-A has the potential to alleviate the clinical burden associated with the review of ICM events, allowing caregivers to focus on patients who require urgent attention.</p></list-item></list></boxed-text>" ]
[]
[]
[]
[ "<supplementary-material id=\"sup1\" position=\"float\" content-type=\"local-data\"><label>euad375_Supplementary_Data</label></supplementary-material>" ]
[ "<table-wrap-foot><fn id=\"tblfn1\"><p>Values are numbers (%) of observations</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"tblfn2\"><p>Table A, the sensitivity is firstly computed for all ‘Abnormality’ events. Then, the Table presents the same sensitivity statistics computed for each particular ‘Abnormality’ event (as diagnosed by the AC). In the last line, the sensitivity on ‘Abnormality’ and ‘Artefact’ events was computed considering ‘Artefacts’ as ‘Abnormality’, as ILR-ECG-A device suggests healthcare professionals using it to consider ‘Artefact’ and all other ‘Abnormality’ outputs with the same level of importance.</p></fn><fn id=\"tblfn3\"><p>B, the specificity is firstly computed for all ‘Normal Rhythm’ events. Then, the table presents the same specificity statistics on the episodes diagnosed with a particular event type by the ICM device. Values are percentages (95% CI).</p></fn></table-wrap-foot>", "<table-wrap-foot><fn id=\"tblfn4\"><p>AC, adjudication committee</p></fn></table-wrap-foot>" ]
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[ "<media xlink:href=\"euad375_supplementary_data.pdf\"><caption><p>Click here for additional data file.</p></caption></media>" ]
[{"label": ["13"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Hong", "Wu", "Zhou", "Wang", "Shang", "Li"], "given-names": ["S", "M", "Y", "Q", "J", "H"], "etal": ["et al"], "comment": ["ENCASE: an ENsemble ClASsifiEr for ECG classification using expert features and deep neural networks. 2017 Computing in Cardiology Conference 2017:1\u20134"]}, {"label": ["23"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Rosier", "Gentils", "Durand", "Bensaber"], "given-names": ["A", "M", "J", "A"], "article-title": ["Potential impact of a new generation of remote monitoring platform: evaluation of the yearly triage burden for 35 595 patients"], "source": ["Eur Heart J"], "year": ["2021"], "volume": ["42"], "fpage": ["3098"]}, {"label": ["24"], "mixed-citation": ["\n"], "person-group": ["\n"], "string-name": ["\n"], "surname": ["Rosier", "Crespin", "Lazarus", "Laurent", "Menet", "Gozlan"], "given-names": ["A", "E", "A", "G", "A", "A"], "etal": ["et al"], "article-title": ["A novel machine learning algorithm has the potential to reduce by 1/3 the quantity of ILR episodes needing review"], "source": ["Eur Heart J"], "year": ["2021"], "volume": ["42"], "fpage": ["316"]}]
{ "acronym": [], "definition": [] }
24
CC BY
no
2024-01-14 23:43:47
Europace. 2024 Jan 3; 26(1):euad375
oa_package/c8/69/PMC10787483.tar.gz
PMC10787484
38217018
[ "<title>Background</title>", "<p id=\"Par5\">Endometrial cancer is the leading cause of gynecologic cancer mortality in high-income countries and is increasing in incidence in low- and middle-income countries, in part due to increasing rates of obesity, physical inactivity, and changes in child-bearing patterns. Between 1990 and 2017, there was a 75.7% increase in the total disability-adjusted life years (DALYs) due to endometrial cancer in sub–Saharan Africa [##REF##31537368##1##]. The burden of endometrial cancer in Africa is projected to continue on an upward trajectory, as IARC estimates a twofold increase in both endometrial cancer incidence and mortality over the next two decades [##UREF##0##2##]. While the current distribution of incident endometrial cancer cases is similar across the regions in Africa, the situation is not as straightforward when assessing the context of its burden. The impact of the rising endometrial cancer burden is expected to be more severe in East and Southern Africa, accounting for 42.4% of Africa’s new endometrial cancer cases (11.5 out of 27.1 thousand) by 2040 despite only making up approximately one-third of the continent’s population as of 2019 [##REF##33538338##3##, ##UREF##1##4##].</p>", "<p id=\"Par6\">In the United States, where endometrial cancer is the most common gynecologic cancer, African American (AA) women experience an 80% higher mortality rate and a 22% difference in 5-year survival compared to Caucasian women [##REF##23386565##5##, ##REF##17559136##6##]. This disparity remains across stage and histologic subtypes, with studies showing a 2–3 times higher rate of more aggressive histologic subtypes (serous and clear cell adenocarcinoma as well as sarcomas) in AA women [##REF##23386565##5##–##REF##24399786##9##]. This histologic distribution is mirrored in sub-Saharan Africa, where 60% of endometrial cancer cases in one Nigerian cohort had poorly differentiated histology [##UREF##3##10##]. The causes of survival disparities across races are multifactorial, with differences attributed to socioeconomic, biological, and cultural factors. In Africa, where cancers are frequently diagnosed in advanced stages due to late presentation [##REF##30532993##11##, ##UREF##4##12##], infrastructural challenges also result in diagnostic and treatment delays, further worsening survival outcomes [##REF##25734382##13##, ##REF##20005175##14##]. Differences in genetic makeup are another important contributor to survival disparities between races. Notably, of the 370 tumors included in the endometrial cancer molecular profiling by The Cancer Genome Atlas (TCGA), the majority were from Caucasian women, and few had the high-risk histology categories that appear in women of African descent [##REF##29605044##15##, ##REF##23636398##16##].</p>", "<p id=\"Par7\">Although endometrial cancer is the third most common gynecological cancer in Africa, it is likely that this distribution will be altered over the coming decades to reflect the current situation in high-income countries [##REF##33538338##3##]. This shift is anticipated due to an increasing adaptation of “western” lifestyles, including dietary and behavioral patterns. This growing disease burden highlights the need for endometrial cancer research in Africa to curb this trend and provide knowledge that will assist in prioritizing funding and directing efforts for prevention and control [##REF##27980610##17##]. Several evidence-based initiatives have recently been employed to improve the standard of care for cancer patients in Africa. For instance, in Botswana, healthcare professionals and trainees in two oncology centers participate in monthly virtual tumor boards under the BOTSOGO collaboration with Massachusetts General Hospital [##UREF##5##18##]. Despite these advances, given the growing endometrial cancer burden in Africa and the paucity of prospectively collected data or endometrial cancer clinical trials, there is still a need for more research to guide evidence-based strategies in Africa [##REF##31552120##19##]. We thus aim to describe the current landscape of endometrial cancer clinical research in Africa, which may help identify gaps and serve as support for future studies. We will also describe the histologic distribution of endometrial cancer in African countries.</p>" ]
[ "<title>Methods</title>", "<p id=\"Par8\">According to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines [##REF##33782057##20##], we conducted a systematic literature search of Ovid MEDLINE, Ovid EMBASE, Clarivate Analytics Web of Science, Wiley-Blackwell Cochrane Library, and WHO African Index Medicus database for publications in all languages from January 1, 2011, to July 20, 2021. This study was institutional review board-exempt given that it is a systematic review. The concepts searched included “<italic>endometrial neoplasms</italic>”, <italic>“endometrial cancer</italic>”, “<italic>Africa</italic>” and <italic>“African countries</italic>”. Both subject headings and keywords were utilized. The list of African countries was based on the United Nations and African Union member states [##UREF##6##21##, ##UREF##7##22##]. All languages were included. The complete search strategies are detailed in Additional file ##SUPPL##0##1##: Appendix Tables S1–S5.</p>", "<p id=\"Par9\">Inclusion criteria included experimental studies (i.e., clinical trials), observational studies (prospective cohort and cross-sectional studies) and retrospective studies conducted in Africa that focus on the management of endometrial cancer. There was no restriction based on the language of publication. Exclusion criteria included animal or nonhuman studies, in vitro studies, studies only available as meeting abstracts, review papers, editorials, commentaries, reports, pathology studies, case reports, and studies on screening and diagnosis of endometrial cancer.</p>", "<p id=\"Par10\">Two independent reviewers examined the titles and abstracts of selected articles and assessed studies for inclusion using the inclusion and exclusion criteria above. The full text was reviewed for abstracts without sufficient information or in the case of a disagreement. Covidence software was used to screen studies, report data, and document study quality. For abstracts that passed the initial screening, the full text was retrieved for secondary screening. For articles that were not easily accessible, we contacted study authors and/or requested the article via interlibrary loan. In cases where we were unable to obtain the full texts, the articles were excluded. The full texts of the selected studies were reviewed independently by two reviewers to confirm eligibility. A study was included when both reviewers independently assessed it as satisfying the selection criteria after review of the full text. A third reviewer mediated in the event of disagreement following discussion. Reasons for exclusion were recorded.</p>", "<p id=\"Par11\">Data extraction and quality assessment were performed in duplicate by two independent reviewers with discordances resolved by a third reviewer. We used a spreadsheet to collect information regarding title, first author, journal, year of publication, country, study design, study setting, and type of interventions performed. We assessed whether the study included stage at diagnosis, survival probability outcomes or both. We recorded the number of included patients, year of diagnosis, age at diagnosis, other reported demographic characteristics, histologic and molecular type, and tumor grade (Table ##TAB##0##1##). Quality assessment results are presented in Additional file ##SUPPL##0##1##: Appendix Tables S6–S7.</p>", "<p id=\"Par12\">Data were reported in narrative and statistical form using figures, tables, and graphs. A PRISMA flowchart was created (Fig. ##FIG##0##1##). We reported the study design, country/region, human development index, focus of research, type of interventions performed, and histologic and molecular type to illustrate the breadth of research coverage in each region. We described the number and types of articles included. The Human Development Index was used to group countries for subgroup analyses. The Newcastle‒Ottawa Quality Assessment Scales [##UREF##8##23##] for the cohort and case control studies were used to assess the risk of bias. A modified Newcastle‒Ottawa scale [##UREF##8##23##] was used for bias assessment of the cross-sectional studies, and the Cochrane Risk Of Bias 2 (ROB2) scale [##REF##31462531##24##] was utilized for assessing bias in the randomized control trials. These involved assessment of bias risk in each of the following three categories: selection, compatibility, and outcome (see Table ##TAB##1##2##). Two independent reviewers reviewed the studies for risk of bias, and potential dependencies were resolved by consultation with a third researcher.</p>" ]
[ "<title>Results</title>", "<p id=\"Par13\">A total of 18 research articles comprising 991 patients were included in this review. Although 19 studies (with a total of 1136 patients) met the inclusion and exclusion criteria, all aggregate values and percentages were based on 18 studies (i.e., one was excluded). This was because 2 studies that were performed by the same lead author utilized the same patient population, which they alternately described as a cohort versus a cross-sectional/diagnostic accuracy study.</p>", "<p id=\"Par14\">As illustrated in Fig. ##FIG##1##2##, the majority of papers were from Egypt, followed by South Africa. The majority (88.89%) of prospective endometrial cancer research in Africa was from North Africa, with Egypt encompassing 83.33% of all papers. Most of these studies focused on advanced imaging modalities. Research on the treatment of endometrial cancer is still emerging, with only one-third of the reviewed publications addressing it and 67% being diagnostic related. Of all the included articles, only 11.11% represented Sub-Saharan Africa, all from South Africa. While the average Human Development Index (HDI) in Africa is 0.536 [##UREF##9##25##], the average HDI of the represented countries in this study was 0.709 (min 0.707, max 0.740). The three countries represented, Egypt, South Africa, and Tunisia, all had high HDIs of 0.707, 0.709, and 0.740, respectively.</p>", "<p id=\"Par15\">There has been an increase in the number of studies published recently, with 50.01% of papers having been published from 2019 to 2021 compared with 27.7% of papers from 2010 to 2013 and 22.2% from 2015 to 2018. Although these studies were mostly designed as cohort studies (61.11%), cross-sectional studies and randomized controlled trials were the second- and third-most common study designs (both 11.1%). All but one study was performed at a single center (94.5%). Only 16.67% of studies had confirmed funding sources, 33.33% were unfunded and 49.96% had unknown funding. The majority (89.4%) of studies were performed in the university setting. The remaining population was equally divided between an oncology institute setting (5.56%) and the urban setting of Soweto (5.56%).</p>", "<p id=\"Par16\">There were a total of 991 patients in these studies. For studies that reported age of diagnosis (<italic>n</italic> = <italic>15</italic>, 83.3%), there was no consensus method of reporting age, with 12 studies (66.7%) reporting age ranges for a cumulative range of 31–81 years old. Thirteen studies (72.2%) reported the mean age with an average of 57.97 years old (min 49.5, max 66.4) across all studies, and 4 studies (22.2%) reported the median age with an average of 59.25 years old (min 58, max 60) across all studies. Three out of 4 studies reporting median age had a median age &lt; 60 years old. The majority of studies (n = 8, 44.4%) reported mean age at diagnosis to be &lt; 60 years old compared with “mean age ≥ 60” and “unknown mean age” each at 27.7% (n = 5).</p>", "<p id=\"Par17\">Although multiple articles included multiple histologies of endometrial cancer, most articles addressed endometroid adenocarcinoma (n = 13, 72.2%) and serous/papillary serous carcinoma (n = 6, 33.3%). Molecular classification was not well documented in all studies. Data on stage distribution were only reported in 7 studies (38.9%), and all these studies were from Egypt. Similarly, survival probability data were available for only 4 studies (22.2%), all from Egypt.</p>", "<p id=\"Par18\">Critical appraisal of study quality &amp; bias, performed using the appropriate bias tools for each study design (see Tables ##TAB##1##2##, ##TAB##2##3## below), showed that apart from the randomized controlled trials, all other studies were scored as either “fair” or “good” quality when translated to AHRQ standards. Case‒control and cross-sectional studies with a range of 7–8 points were scored as “Good” studies, with each study attaining “3 or 4 stars in the selection domain AND 1 or 2 stars in the comparability domain AND 2 or 3 stars in the outcome/exposure domain” [##UREF##8##23##]. The cohort studies, with a range of 7–9 points, were scored as either “Good” (<italic>n</italic> = <italic>8</italic>) or “Fair” (<italic>n</italic> = <italic>4</italic>) studies, with the majority of studies attaining “3 or 4 stars in the selection domain AND 1 or 2 stars in the comparability domain AND 2 or 3 stars in the outcome/exposure domain” [##UREF##8##23##]. Cohort studies scored as “Fair”, either had deficiency in the selection or comparability domains. The two randomized controlled trials were scored as “High risk of bias” and “Some concerns”, respectively, due in large part to deficiencies in the “Outcome” and “Reporting” sections, suggesting a need for improvement of these sections during the study-planning phase.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par19\">The incidence rate of endometrial cancer has increased in several countries over successive generations, particularly in countries with rapid socioeconomic changes [##REF##29045681##26##]. Given that over the past two decades, there has been a 75.7% increase in DALYs due to endometrial cancer in sub–Saharan Africa [##REF##31537368##1##] and that the IARC has projected a twofold increase in its incidence and mortality over the next two decades [##UREF##0##2##], our systematic review is a timely attempt to define the state of endometrial cancer research from countries in Africa. We demonstrate that there is a dearth of data, with only 18 publications on this topic over the past 2 decades. Moreover, these data are concentrated in countries with high HDI and are mostly from North African nations, which has important implications for the generalizability of their findings to Sub-Saharan Africa.</p>", "<p id=\"Par20\">In the United States, histology and socioeconomic factors have been shown to account for the difference in incidence, morbidity, and mortality between Caucasians and African Americans [##REF##23707671##27##]. High-income countries often have different racial and ethnic variations in gynecologic cancers compared to low-to-middle-income countries [##REF##25522857##28##]. As far back as 1992, Cronje et al. showed that preoperatively black women in Bloemfontein, South Africa were more likely to have advanced stages (II-IV) (<italic>p</italic> = <italic>0.0024</italic>) of endometrial adenocarcinoma per FIGO (Fédération Internationale de Gynécologie et d’Obstétrique) criteria and poorer tumor differentiation (<italic>p</italic> &lt; <italic>0.0001</italic>) [##UREF##10##29##]. In addition, black women within those societies often have different genetic or hormonal factors contributing to the pathophysiology of their cancer [##UREF##11##30##]. Our systematic review showed that age at diagnosis was notably &lt; 60 years old in the majority of recorded cases. Although this was unexpected and may be explained by the lower life expectancy in African countries, it also has important implications for diagnostic considerations in these settings.</p>", "<p id=\"Par21\">As shown in low-income areas in the United States, patients from high-income settings have more access to research funding, improved treatment facilities, cutting-edge research trials, enhanced transportation for radiation, and improved monitoring of toxicities [##REF##34693080##31##]. The ramifications for treatment options, including chemo- and immunotherapy, radiation therapy, and surgical resection, are innumerable; hence, marked improvement in outcome measures such as 5- and 10-year mortality in low- to middle-income countries may be difficult to achieve. The scarcity of research on endometrial cancer in Africa has resulted in a stagnation of the development of regional, evidence-based treatment guidelines. This deficiency has also impeded the build-up of relevant healthcare infrastructure and hindered the allocation of funding for both endometrial cancer treatment and prevention initiatives in the region. Addressing these research gaps is crucial for advancing comprehensive and effective strategies in the fight against endometrial cancer in Africa. As such, more needs to be done to invest in building research capacity in the form of infrastructure and research personnel in low-to-middle income countries.</p>", "<p id=\"Par22\">Our systematic review showed that approximately two-thirds of the studies addressed diagnosis-associated issues, while one-third were treatment-related. Of these studies, only 2 (11.1%) were randomized controlled trials, whereas the rest were retrospective case‒control, cohort, or cross-sectional studies. In Western countries, a variety of research designs have been used to assess the use of biomarker-driven targeted therapy, adjuvant pelvic radiotherapy, lymphadenectomy, and hysterectomy approaches (i.e., laparoscopy vs laparotomy) for the management of endometrial cancer [##REF##29843906##32##–##UREF##14##38##]. This diversity in clinical trial options is also needed in LMICs to help define treatment paradigms relevant to the local African context. In a systematic review of all phase 3 oncology RCTs published globally from 2014 to 2017, Wells et al. demonstrated that although RCTs are predominantly performed in HICs, RCTs from LMICs more successfully identify effective therapies and have larger effect sizes [##REF##33507236##39##]. They also showed that RCTs in HICs were more likely to be industry-funded (464 [73%] vs. 24 [41%]; <italic>P</italic> &lt; 0.001) and were disproportionately focused on breast cancer compared to other cancers (e.g., cervical cancer) relative to their global cancer mortality burden [##REF##33507236##39##]. This disparity likely contributes to publication and funding bias against RCTs in LMICs.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par23\">Endometrial cancer research in Africa is extremely limited, with the majority being concentrated in African countries with higher HDIs. As the incidence of endometrial cancer rises in Sub-Saharan Africa, there is a pressing need for more prospective clinical research to tackle the growing disease burden and tailor treatment to each patient’s biology, local environment, and socio-politico-economic environment. Our systematic review demonstrates that the landscape of endometrial cancer research in Africa does not match the increasing burden of endometrial cancer. Moreover, the endometrial cancer data that exist globally cannot be generalized to the majority of women in sub-Saharan Africa, who tend to have more aggressive histologies, present with later stages of cancer, and lack access to all treatment modalities. This review should serve as a call to action to increase the number and quality of endometrial cancer research studies in Sub-Saharan Africa.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Women in Africa are experiencing a rising burden of endometrial cancer. Research and investment to improve treatment and outcomes are critically needed. We systematically reviewed and characterized endometrial cancer-related research within a clinically relevant context to help organize and assess existing endometrial cancer research in Africa.</p>", "<title>Methods</title>", "<p id=\"Par2\">According to PRISMA guidelines, we searched online databases for published endometrial cancer articles from African countries from January 1, 2011, to July 20, 2021. Based on our inclusion and exclusion criteria, independent reviewers documented the study design, country/region, human development index, focus of research, type of interventions performed, and histologic and molecular type to illustrate the breadth of research coverage in each region.</p>", "<title>Results</title>", "<p id=\"Par3\">A total of 18 research articles were included. With an average Human Development Index (HDI) in Africa of 0.536, the average HDI of the represented countries in this study was 0.709. The majority (88.9%) of prospective endometrial cancer research articles in Africa were from North Africa, with Egypt encompassing 83.3% of the papers. Most of these studies focused on endometrial cancer diagnosis. Research on the treatment of endometrial cancer is still emerging (33% of papers). Of all included articles, only 11.1% represented Sub-Saharan Africa, where the majority population of black Africans reside.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Endometrial cancer research in Africa is extremely limited, with the majority being concentrated in African countries with higher HDIs. As the incidence of endometrial cancer rises in Sub-Saharan Africa, there is a pressing need for more prospective clinical research to tackle the growing disease burden and improve outcomes.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13027-023-00563-2.</p>", "<title>Keywords</title>" ]
[ "<title>Limitations</title>", "<p id=\"Par24\">There are some limitations to our study. Stage data were not widely available in the included studies. Available data would not be helpful due to the selective nature of some of the papers (i.e., paper on select stages rather than on all stages). Most of the studies were retrospective and lacked a formal control.</p>", "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>None.</p>", "<title>Disclaimers</title>", "<p id=\"Par25\">The views expressed in this submitted article are the authors' own and not an official position of their institutions or funders.</p>", "<title>Author contributions</title>", "<p>CPA, Study Design, Data Extraction, Manuscript writing and review. ODB, Study Design, Manuscript writing and review. COC, Data Extraction, Manuscript writing and review. AE, Data Extraction, Manuscript writing and review. YG, Study Design, Manuscript writing and review. AJ, Study Design, Manuscript writing and review. NL, Study Design, Manuscript writing and review. AN, Study Design, Manuscript writing and review. KO, Manuscript writing and review. PO, Manuscript writing and review. LO, Manuscript writing and review. AO, Data Extraction, Manuscript writing and review. LV, MD, Data Extraction, Manuscript writing and review.</p>", "<title>Funding</title>", "<p>CPA has grant funding from American Society for Radiation Oncology (863607). Thid funding source did not have any additional role in the preparation of or decision to submit this manuscript. There were otherwise no other internal or external grants, equipment, drugs, and/or other support that facilitated the conduct of the work described in the article or the writing of the article itself.</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par26\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par27\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par28\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>PRISMA flow diagram of the number of searches yielded, excluded, and reviewed. <sup>A</sup>Includes 2 South African studies from the same patient population and same author (1 study was excluded during further analysis)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Geographic Distribution of Prospective Endometrial Cancer Research within Africa. The map represents individual countries only and does not clearly illustrate some of the smaller African countries</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Study characteristics</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Country region<sup>a</sup></th><th align=\"left\">North (n, %)</th><th align=\"left\">South (n, %)</th><th align=\"left\">Total (n)</th></tr></thead><tbody><tr><td align=\"left\">No. of studies</td><td align=\"left\">16 (88.89%)</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">18</td></tr><tr><td align=\"left\" colspan=\"4\">Human Development Index [##UREF##15##40##]</td></tr><tr><td align=\"left\"> Low (&lt; 0.550)</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> Middle (0.550–0.699)</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\"> High (0.700–0.799)</td><td align=\"left\">16 (88.89%)</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">18</td></tr><tr><td align=\"left\"> Very high (≥ 0.800)</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">–</td></tr><tr><td align=\"left\" colspan=\"4\">Study design</td></tr><tr><td align=\"left\"> Case control</td><td align=\"left\">–</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\"> Cohort</td><td align=\"left\">11 (61.11%)</td><td align=\"left\">–</td><td align=\"left\">11</td></tr><tr><td align=\"left\"> Cross-sectional</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">–</td><td align=\"left\">2</td></tr><tr><td align=\"left\"> Cross-sectional/diagnostic accuracy<sup>b</sup></td><td align=\"left\">–</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">1</td></tr><tr><td align=\"left\"> Nonrandomized experimental</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">–</td><td align=\"left\">1</td></tr><tr><td align=\"left\"> Randomized controlled</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">–</td><td align=\"left\">2</td></tr><tr><td align=\"left\" colspan=\"4\">Funded</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">3</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">6 (33.33%)</td><td align=\"left\">–</td><td align=\"left\">6</td></tr><tr><td align=\"left\"> Not specified</td><td align=\"left\">8 (44.4%)<sup>c</sup></td><td align=\"left\">1 (5.56%)</td><td align=\"left\">9</td></tr><tr><td align=\"left\" colspan=\"4\">No. of centers</td></tr><tr><td align=\"left\"> Single</td><td align=\"left\">15 (83.33%)</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">17</td></tr><tr><td align=\"left\"> Multiple</td><td align=\"left\">1 (5.56%)<sup>d</sup></td><td align=\"left\">-</td><td align=\"left\">1</td></tr><tr><td align=\"left\" colspan=\"4\">Patient population</td></tr><tr><td align=\"left\"> Oncology institute</td><td align=\"left\">1 (5.56%)<sup>c</sup></td><td align=\"left\">–</td><td align=\"left\">1</td></tr><tr><td align=\"left\">University</td><td align=\"left\">15 (83.33%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">16</td></tr><tr><td align=\"left\"> Not specified (in urban area)</td><td align=\"left\">–</td><td align=\"left\">1 (5.56%)<sup>d</sup></td><td align=\"left\">1</td></tr><tr><td align=\"left\" colspan=\"4\">Year of study publication</td></tr><tr><td align=\"left\"> 2010–2013 (included)</td><td align=\"left\">5 (27.7%)</td><td align=\"left\">–</td><td align=\"left\">5</td></tr><tr><td align=\"left\"> 2015–2018</td><td align=\"left\">4 (22.2%)</td><td align=\"left\">–</td><td align=\"left\">4</td></tr><tr><td align=\"left\"> 2019–2021</td><td align=\"left\">7(38.9%)</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">9</td></tr><tr><td align=\"left\" colspan=\"4\">Conflict of interest</td></tr><tr><td align=\"left\"> None</td><td align=\"left\">14 (87.5%)<sup>c</sup></td><td align=\"left\">1 (5.56%)</td><td align=\"left\">16</td></tr><tr><td align=\"left\"> Not specified</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">3</td></tr><tr><td align=\"left\" colspan=\"4\">Funded</td></tr><tr><td align=\"left\"> Yes</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">3</td></tr><tr><td align=\"left\"> No</td><td align=\"left\">6 (33.3%)</td><td align=\"left\">–</td><td align=\"left\">6</td></tr><tr><td align=\"left\">Not specified</td><td align=\"left\">8 (44.4%)<sup>c</sup></td><td align=\"left\">1 (5.56%)</td><td align=\"left\">9</td></tr><tr><td align=\"left\" colspan=\"4\">Histology (%)<sup>f</sup></td></tr><tr><td align=\"left\"> Endometroid adenocarcinoma</td><td align=\"left\">12 (66.67%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">12</td></tr><tr><td align=\"left\"> Serous/papillary serous carcinoma</td><td align=\"left\">6 (33.3%)<sup>c</sup></td><td align=\"left\">–</td><td align=\"left\">6</td></tr><tr><td align=\"left\"> Clear cell carcinoma</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">–</td><td align=\"left\">2</td></tr><tr><td align=\"left\"> Carcinosarcoma</td><td align=\"left\">1 (5.56%)<sup>c</sup></td><td align=\"left\">–</td><td align=\"left\">1</td></tr><tr><td align=\"left\"> Uterine sarcoma</td><td align=\"left\">–</td><td align=\"left\">–</td><td align=\"left\">0</td></tr><tr><td align=\"left\"> Unknown</td><td align=\"left\">2 (11.11%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">3</td></tr><tr><td align=\"left\" colspan=\"4\">Mean age at diagnosis (years)</td></tr><tr><td align=\"left\"> &lt; 60</td><td align=\"left\">8 (44.4%)</td><td align=\"left\">–</td><td align=\"left\">8</td></tr><tr><td align=\"left\"><bold> ≥ </bold>60</td><td align=\"left\">4 (22.2%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">5</td></tr><tr><td align=\"left\"> Unknown</td><td align=\"left\">4 (22.2%)</td><td align=\"left\">1 (5.56%)</td><td align=\"left\">5</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Results of critical appraisal of included randomized controlled trials using Cochrane Risk Of Bias 2</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Study</th><th align=\"left\">Study design</th><th align=\"left\">Total bias risk</th></tr></thead><tbody><tr><td align=\"left\">El-Agwany, 2018</td><td align=\"left\">Randomized control</td><td align=\"left\">High</td></tr><tr><td align=\"left\">Fayallah, 2011</td><td align=\"left\">Randomized control</td><td align=\"left\">Some concern</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Results of critical appraisal of included observational studies using Newcastle‒Ottawa scores</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Study</th><th align=\"left\">Study design</th><th align=\"left\">Total score</th></tr></thead><tbody><tr><td align=\"left\">Ray, 2019</td><td align=\"left\">Case control</td><td align=\"left\">7, Good</td></tr><tr><td align=\"left\">Ghazala, 2021</td><td align=\"left\">Cohort</td><td align=\"left\">7, Fair</td></tr><tr><td align=\"left\">Abouhashem, 2016</td><td align=\"left\">Cohort</td><td align=\"left\">8, Good</td></tr><tr><td align=\"left\">Aly, 2013</td><td align=\"left\">Cohort</td><td align=\"left\">9, Good</td></tr><tr><td align=\"left\">El Sokkary, 2014</td><td align=\"left\">Cohort</td><td align=\"left\">8, Good</td></tr><tr><td align=\"left\">Gharib, 2020</td><td align=\"left\">Cohort</td><td align=\"left\">7, Good</td></tr><tr><td align=\"left\">Hamed, 2012</td><td align=\"left\">Cohort</td><td align=\"left\">8, Good</td></tr><tr><td align=\"left\">Mourad, 2017</td><td align=\"left\">Cohort</td><td align=\"left\">9, Good</td></tr><tr><td align=\"left\">Sanad, 2019</td><td align=\"left\">Cohort<sup>a</sup></td><td align=\"left\">7, Fair<sup>a</sup></td></tr><tr><td align=\"left\">Shady, 2016</td><td align=\"left\">Cohort</td><td align=\"left\">9, Good</td></tr><tr><td align=\"left\">Shatat, 2019</td><td align=\"left\">Cohort<sup>a</sup></td><td align=\"left\">7, Fair<sup>a</sup></td></tr><tr><td align=\"left\">Soliman, 2011</td><td align=\"left\">Cohort<sup>a</sup></td><td align=\"left\">7, Fair<sup>a</sup></td></tr><tr><td align=\"left\">Rady, 2019<sup>b</sup></td><td align=\"left\">Nonrandomized experimental study</td><td align=\"left\">8, Good</td></tr><tr><td align=\"left\">Wadee, 2021<sup>c</sup></td><td align=\"left\">Cross- sectional</td><td align=\"left\">8, Good</td></tr><tr><td align=\"left\">Elmahdy, 2019</td><td align=\"left\">Cross- sectional</td><td align=\"left\">7, Good</td></tr><tr><td align=\"left\">Ghorbel, 2020</td><td align=\"left\">Cross- sectional</td><td align=\"left\">7, Good</td></tr></tbody></table></table-wrap>" ]
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[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>" ]
[ "<table-wrap-foot><p><sup>a</sup>There were no data from the east and west regions, so they were not included in this table</p><p><sup>b</sup>This study is 1 of 2 South African studies from the same patient population and same author (the study that described the population as a cohort was excluded)</p><p><sup>c</sup>Includes 1 Tunisian study</p><p><sup>d</sup>Includes 1 Egyptian study</p><p><sup>e</sup>Includes 1 South African study</p><p><sup>f</sup>Many articles addressed more than one histology. Other histologies not included in the table include adenosquamous, nonendometroid, and mixed endometrioid adenocarcinoma</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>These studies had an inadequate degree of control; thus, the total score was based on this</p><p><sup>b</sup>This nonrandomized experimental study was evaluated as a cohort study</p><p><sup>c</sup>This author utilized the same patient population for 2 studies, alternately describing the design as a cohort vs a cross-sectional/diagnostic accuracy study. The cohort study was excluded</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Onyinye D. Balogun and Atara Ntekim: Cosenior authors.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"13027_2023_563_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"13027_2023_563_Fig2_HTML\" id=\"MO2\"/>" ]
[ "<media xlink:href=\"13027_2023_563_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1. Tables S1–S7: Supplementary Table S1. </bold>Ovid MEDLINE search strategy. <bold>Supplementary Table S2</bold>. Ovid Embase search strategy.<bold> Supplementary Table S3. </bold>Clarivate Analytics Web of Science search strategy.<bold> Supplementary Table S4. </bold>Wiley-Blackwell Cochrane Library search strategy.<bold> Supplementary Table S5. </bold>WHO African Index Medicus Database.<bold> Supplementary Table S6. </bold>Results of critical appraisal of included observational studies using Newcastle‒Ottawa scores.<bold> Supplementary Table S7. </bold>Results of critical appraisal of included randomized controlled trials using Cochrane Risk Of Bias 2.</p></caption></media>" ]
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{ "acronym": [], "definition": [] }
40
CC BY
no
2024-01-14 23:43:47
Infect Agent Cancer. 2024 Jan 12; 19:2
oa_package/4a/9a/PMC10787484.tar.gz
PMC10787485
0
[ "<title>Introduction</title>", "<title>Background and rationale</title>", "<p id=\"Par24\">Hypertension is the most common cardio-cerebrovascular disease worldwide, with a significant population affected, substantial health risks, and a heavy economic burden [##REF##31080465##1##–##UREF##0##4##]. However, the awareness, treatment, and control rates of hypertension remain suboptimal, with data from China indicating rates of only 50.0%, 38.1%, and 11.1%, respectively [##REF##29102084##5##].</p>", "<p id=\"Par25\">Current hypertension guidelines have recognized the efficacy of dual combination therapy as an initial antihypertensive treatment [##REF##31080465##1##, ##REF##29146533##6##–##REF##32371787##11##]. However, hypertension involves multiple mechanisms [##UREF##1##12##, ##REF##24117126##13##], and the goal of blood pressure control has become more stringent. As a result, dual combination therapy may not be sufficient to meet the needs of patients. Consequently, some researchers have explored the use of low-dose three-drug or four-drug combinations [##REF##17178976##14##–##REF##34469767##18##]. However, these studies employed monotherapy or placebo as controls, which are not consistent with current guidelines for initial hypertension treatment. Furthermore, these studies did not demonstrate whether low-dose multidrug (≥ 3) combinations were more effective than the current recommended dual combinations, and none of these studies included Chinese population. Therefore, this trial will be the first to investigate the effectiveness and safety of low-dose quadruple combination therapy compared to dual combination therapy in the Chinese population.</p>", "<title>Objective</title>", "<p id=\"Par26\">The objective is as follows: to evaluate and compare the efficacy and safety of half-dose quadruple therapy versus standard-dose dual therapy in the initial treatment of hypertensive patients with mild to moderate blood pressure (140–179/90–109 mmHg).</p>" ]
[ "<title>Study methods</title>", "<title>Trial design</title>", "<p id=\"Par27\">This is a randomized, double-blind, two-agent, two-cycle, two-sequence crossover clinical trial, comparing the effectiveness and safety of low-dose quadruple antihypertensives (irbesartan 75 mg + metoprolol 23.75 mg + amlodipine 2.5 mg + indapamide 1.25 mg) with standard-dose dual drugs (irbesartan 150 mg + amlodipine 5 mg) in initial antihypertensive treatment in patients with mild to moderate hypertension (140–179/90–109 mmHg). We will enroll 90 patients in the Third Xiangya Hospital of Central South University. The design of this trial has been described in detail in our protocol for this trial [##REF##37276913##19##]. This statistical analysis plan (SAP) was written following the guidelines for the content of statistical analysis plans in clinical trials [##REF##29260229##20##].</p>", "<title>Randomization and blinding</title>", "<p id=\"Par28\">In this trial, stratified blocked randomization and individual random crossover will be adopted to minimize the influence of seasonal and temperature changes on the results, dividing participants into 2 crossover groups in a 1:1 ratio. Randomization and blinding will be established by an independent statistician.</p>", "<p id=\"Par29\">Except for randomizing, blinding, and drug coding investigators, all others (including participants, clinical investigators, coordinators, clinical research associates, all members of the Clinical Endpoint Committee (CEC), data managers, statistical analysts, drug manufacturers, and administration) are blinded to patient grouping and drug assignment.</p>", "<p id=\"Par30\">This trial will use two-time unblinding method. When the data file is confirmed and locked, the first unblinding will be performed, which only lists the group to which each case belongs for analysis (such as group A or group B). After the statistical analysis is complete, the second unblinding will be performed to determine which treatment option is used in the two groups.</p>", "<title>Sample size</title>", "<p id=\"Par31\">In the 2021 QUARTET study [##REF##34469767##18##], the 1/4 dose quadruple combination (irbesartan 37.5 mg, amlodipine 1.25 mg, indapamide 0.625 mg, and bisoprolol 2.5 mg) further reduced systolic blood pressure (SBP) by 6.9 mmHg (95% CI 4.9–8.9) compared to single drug (irbesartan 150 mg), with an estimated standard deviation (SD) of 15 mmHg.</p>", "<p id=\"Par32\">At the same time, based on the previous clinical observation results of the research group on low-dose quadruple combination and standard-dose dual combination, it is estimated that the difference in 24-h mean SBP reduction between the two groups is 6 mmHg, with an SD 15 mmHg. Power is set at 90% (beta = 0.1) and an acceptable risk of type I error is 5% (two-sided alpha level).</p>", "<p id=\"Par33\">We use the following formula, which is specially for sample size calculation of cross-over design, [##UREF##3##21##] to calculate the total number:</p>", "<p id=\"Par34\">The result is <italic>n</italic> = 66. And we also calculate the sample size via PASS 11.0 (Power Analysis &amp; Sample Size, NCSS, LLC.) (for 2 × 2 cross-over design) with the result <italic>n</italic> = 68. Taking the larger one and considering 20% loss to follow-up, 85 participants are calculated, and considering the random factors of the block group, a final sample size of 90 participants with 45 in each crossover group is needed.</p>", "<title>Data monitoring</title>", "<p id=\"Par35\">This trial will establish an independent data monitoring committee (IDMC) to report to the clinical trial research center and ethics committee. The purpose of the IDMC is to protect the safety of the participants, ensure the validity of the data, and decide the timely termination of the trial when a significant benefit or risk is demonstrated or a successful conclusion is impossible. The IDMC will be responsible for assessing the safety of therapeutic interventions during the study period, thereby protecting the interests of patients, and for reviewing the overall conduct of the clinical trial.</p>", "<title>Timing of final analysis</title>", "<p id=\"Par36\">All outcomes will be analyzed collectively after data entry and data monitoring have been completed and the database has been cleaned and closed.</p>", "<title>Statistical principles</title>", "<title>Confidence intervals and <italic>P</italic> values</title>", "<p id=\"Par37\">In this study, <italic>P</italic> &lt; 0.05 will be considered statistically significant and 95% confidence interval will be reported if applicable.</p>", "<title>Adherence and protocol deviations</title>", "<p id=\"Par38\">Medication compliance = (total number of pills issued—number of pills recovered)/days of medication × 100%. Medication compliance will be demonstrated. Medication compliance of 80–120% will be considered as condition of per-protocol set (PPS).</p>", "<title>Analysis populations</title>", "<p id=\"Par39\">According to the principle of intention to treat (ITT), there are three analysis populations involved in this study: the full analysis set (FAS), PPS, and the safety set (SS). The definitions of each analysis set are given below:</p>", "<title>FAS</title>", "<p id=\"Par40\">All cases that do not violate the main inclusion/exclusion criteria, use the drug at least once after randomization, and have at least 1 post-dose efficacy evaluation data will be considered as the FAS for the analysis of efficacy. For those who do not complete treatment as planned, the last observation will be used as the final outcome (last observation carried forward, LOCF).</p>", "<title>PPS</title>", "<p id=\"Par41\">It is the subset of the FAS that is more compliant with the protocol. These participants are more adherent to the protocol. Individuals in the PPS are required to meet the following characteristics:<list list-type=\"bullet\"><list-item><p id=\"Par42\">Medication compliance is 80–120%;</p></list-item><list-item><p id=\"Par43\">Treatment meets efficacy endpoints as protocol required, and the primary outcomes are measurable;</p></list-item><list-item><p id=\"Par44\">No major violations of the protocol (including inclusion and exclusion criteria).</p></list-item></list></p>", "<title>SS</title>", "<p id=\"Par45\">All participants who use the drug at least once after randomization are part of this subset.</p>", "<title>Trial population</title>", "<p id=\"Par46\">All hypertensive patients who have never taken antihypertensive medications or have not taken antihypertensive medications in the past 1 month will be eligible and screened consecutively with inclusion and exclusion criteria in the department of cardiology at the Third Xiangya Hospital, Central South University. A Consolidated Standards of Reporting Trials (CONSORT) flow diagram (Fig. ##FIG##0##1##) will be produced according to CONSORT 2010 Statement [##REF##20332509##22##].</p>", "<title>Demographic and baseline characteristics</title>", "<p id=\"Par47\">Demographic and baseline characteristics will be descriptively tabulated and summarized for all subjects in FAS. For continuous variables, the mean and SD (normal distribution) or median and 25th/75th percentile (non-normal distribution) will be given. For categorical variables, the number and percentage of subjects will be given.</p>", "<title>Analysis</title>", "<title>Outcome definitions</title>", "<title>Primary outcome</title>", "<p id=\"Par48\">The primary outcome is established as the reduction in mean 24-h SBP by ambulatory blood pressure monitoring (ABPM) after 4 weeks of drug administration.</p>", "<title>Secondary outcomes</title>", "<p id=\"Par49\">\n<list list-type=\"bullet\"><list-item><p id=\"Par50\">Mean daytime and nighttime SBP in ABPM, change from baseline</p></list-item><list-item><p id=\"Par51\">24-h, daytime, and nighttime mean diastolic blood pressure (DBP) in ABPM, change from baseline</p></list-item><list-item><p id=\"Par52\">Morning BP surge in ABPM, change from baseline</p></list-item><list-item><p id=\"Par53\">Office blood pressure measurement (OBPM), change from baseline</p></list-item><list-item><p id=\"Par54\">Home blood pressure measurement (HBPM), change from baseline</p></list-item><list-item><p id=\"Par55\">Heart rate, change from baseline</p></list-item><list-item><p id=\"Par555\">Blood pressure control rate</p></list-item></list>\n</p>", "<title>Safety outcomes</title>", "<p id=\"Par56\">The safety outcomes are as follows: adverse event (AE), serious adverse event (SAE), adverse drug reaction (ADR), and changes in biochemistry results and QT interval of the electrocardiogram from baseline.</p>", "<p id=\"Par57\">Timings of outcome assessments are listed in Table ##TAB##0##1##. Blood pressure measurement methods (including ABPM, OBPM, and HBPM) were detailed in the previously published protocol [##REF##37276913##19##]. For HBPM, 4–6 BP data will be recorded in “Patient Manual” by participants according to the agreement. The average of all the BPs for 1 day will be used as the BP value for that day. HBPM on the day before the follow-up visit will be used as the HBPM at the end of this period.\n</p>", "<title>Criteria for blood pressure control</title>", "<p id=\"Par58\">ABPM: 24-h average blood pressure &lt; 130/80 mmHg; daytime average blood pressure &lt; 135/85 mmHg; nighttime average blood pressure &lt; 120/70 mmHg.</p>", "<p id=\"Par59\">OBPM: SBP/DBP &lt; 140/90 mmHg.</p>", "<p id=\"Par60\">HBPM: SBP/DBP &lt; 135/85 mmHg; time in target range (TTR) of HBPM = days meet target/days of medication × 100%.</p>", "<title>Definition of baseline</title>", "<p id=\"Par61\">This crossover trial includes three phases: treatment phase 1 (weeks 1–4), washout phase (weeks 5–6), and treatment phase 2 (weeks 6–10). The baselines of treatment phase 1 are defined as the results obtained from enrolment period, including all primary, secondary, and safety indicators. The baselines of treatment phase 2 are defined as the results obtained from the end of the washout phase (for ABMP, OBPM, and HBPM) and enrolment period (for the rest of the indicators).</p>", "<title>Statistical hypothesis</title>", "<p id=\"Par62\">For this exploratory study, the following hypotheses will be used for the primary outcome:where is for the mean effect of half-dose quadruple therapy, and is for the mean effect of standard-dose dual therapy.</p>", "<title>Analysis of primary outcome</title>", "<p id=\"Par63\">PPS will be mainly used for analysis of primary outcome. Linear mixed-effects model will be used to analyze treatment effects, stage effects, and order effects (residual carryover effect) [##UREF##4##23##, ##UREF##5##24##]. In this model, treatment, group, and stage will be the fixed effects, baseline blood pressure will be the covariates, and subjects will be the random effects. The model is as follows:where <italic>i</italic> is the group (2 crossover groups, 0 or 1), <italic>j</italic> is the number of stages (2 stages, 1 or 2), <italic>t</italic> is the drug (2 drugs, 0 and 1), and <italic>k</italic> represents the individual (90 subjects). <italic>Y</italic><sub>ijtk</sub> is the observed trial effect (mean SBP reduction in ABPM after 4 weeks of drug administration) for the <italic>k</italic> th subject in group <italic>i</italic>, at phase <italic>j</italic>, and with drug <italic>t</italic>. is the overall mean effect, is the fixed effect for group <italic>i</italic>, is the fixed effect for the <italic>j</italic> th stage, is the fixed effect for the <italic>t</italic> th drug, is the random effect for the <italic>k</italic> th subject with the <italic>t</italic> th drug, is the residual of <italic>Y</italic><sub>ijtk</sub>, or random error.</p>", "<p id=\"Par64\">On the basis of the above model, baseline characteristics such as age, gender, nationality, time of hypertension, smoking, alcohol, body mass index, waistline, diabetes, and estimated glomerular filtration rate will be corrected to construct an adjusted model.</p>", "<title>Analysis of secondary outcomes</title>", "<p id=\"Par65\">PPS will be used for analysis of secondary outcomes. Measurement data (changes of blood pressure and pulse rate, TTR, etc.) will be analyzed using the linear mixed-effects model described above, and counting data (blood pressure control rate) will be analyzed using the paired chi-square test or Fisher’s exact probability methods.</p>", "<title>Analysis of safety outcomes</title>", "<p id=\"Par66\">SS will be used for analysis of safety outcomes.</p>", "<p id=\"Par67\">The incidence of AEs, SAEs, and ADRs will be summarized by system and organ, counted in terms of number, severity, and relationship to each therapeutic drug, which will be compared between the two medications using chi-square tests or Fisher’s exact probability method.</p>", "<p id=\"Par68\">Changes in biochemistry results and QT interval of the electrocardiogram will be analyzed using linear mixed-effects model. The incidence of concerned abnormal values (including hypokalemia; hyponatremia; serum creatinine, uric acid, urea, ALT, AST, TBL, DBL, blood glucose, QT and QTc elevated above the upper limit of normal (ULN), etc.) will be summarized and analyzed using chi-square test or Fisher’s exact probability method. Analysis methods for different outcomes are list in Table ##TAB##1##2##.</p>", "<title>Sensitivity analysis</title>", "<p id=\"Par69\">Sensitivity analysis will be conducted in the following situations:<list list-type=\"bullet\"><list-item><p id=\"Par70\">FAS for analysis of primary and secondary outcomes;</p></list-item><list-item><p id=\"Par71\">Different ways of managing missing data for analysis of HBPM;</p></list-item><list-item><p id=\"Par72\">Retention or exclusion of outliers if applicable.</p></list-item></list></p>", "<title>Subgroup analysis</title>", "<p id=\"Par73\">Subgroup analysis will be performed based on the following situation:<list list-type=\"bullet\"><list-item><p id=\"Par74\">Sex (male or female)</p></list-item><list-item><p id=\"Par75\">Age (&lt; 45 years or ≥ 45years, which is used to classify youth and middle age)</p></list-item><list-item><p id=\"Par76\">Diabetes mellitus (with or without)</p></list-item></list></p>", "<title>Handling of missing data</title>", "<p id=\"Par77\">We will impute missing data of HBPM using LOCF method. Sensitivity analysis will use multiple imputation. For analyses of primary and remaining secondary outcomes, imputation will not be used.</p>", "<title>Handling of outliers</title>", "<p id=\"Par78\">Outliers, if applicable, will not be excluded while a sensitivity analysis will be conducted with or without outliers.</p>", "<title>Statistical software</title>", "<p id=\"Par79\">All statistical analyses will be performed by statistician using IBM SPSS Statistics Version 23 and RStudio 2023.06.0 + 421.</p>" ]
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[ "<title>Background</title>", "<p id=\"Par1\">Combined antihypertensive therapy has obvious advantages over single drug therapy. Hypertension guidelines fully affirm the efficacy of dual combination in initial antihypertensive therapy. Recent studies have also pointed out that the quadruple combination of very low-dose antihypertensive drugs is superior to single drugs. However, whether low-dose quadruple therapy is better than dual combination is unknown.</p>", "<title>Methods/design</title>", "<p id=\"Par2\">A randomized double-blind crossover clinical trial will be conducted to compare the efficacy and safety of low-dose quadruple antihypertensives (irbesartan 75 mg + metoprolol 23.75 mg + amlodipine 2.5 mg + indapamide 1.25 mg) with standard-dose dual antihypertensives (irbesartan 150 mg + amlodipine 5 mg) in the initial treatment of patients with mild to moderate hypertension (140–179/90–109 mmHg). Ninety patients are required and will be recruited and randomly assigned in a 1:1 ratio to two crossover groups. Two groups will receive a different combination therapy for 4 weeks, then switch to the other combination therapy for 4 weeks, with a 2-week wash-out. Antihypertensive effects and related adverse effects of the two antihypertensive combination treatments will be compared. The primary outcome, i.e., mean 24-h systolic blood pressure in ambulatory blood pressure monitoring, will be assessed via linear mixed-effects model.</p>", "<title>Discussion</title>", "<p id=\"Par3\">This statistical analysis plan will be confirmed prior to blind review and data lock before un-blinding and is sought to increase the validity of the QUADUAL trial.</p>", "<title>Trial registration</title>", "<p id=\"Par4\">ClinicalTrials.gov, NCT05377203. Registered May 11, 2022, <ext-link ext-link-type=\"uri\" xlink:href=\"https://clinicaltrials.gov/study/NCT05377203\">https://clinicaltrials.gov/study/NCT05377203</ext-link>.</p>", "<title>Keywords</title>" ]
[ "<title>Trial status</title>", "<p id=\"Par80\">The trial was initiated on July 4, 2022, in the Third Xiangya Hospital of Central South University. The trial began enrolling on July 13, 2022, finished enrolling on April 20, 2023, and finished last participant’s last visit on July 4, 2023. Data entry is currently in progress. We anticipate blind review and database lock to be conducted by the end of August, 2023.</p>", "<title>SAP version</title>", "<p id=\"Par81\">Version 1.0 (dated July 25, 2023) based on QUADUAL protocol (Version V1.0, dated April 8, 2022).</p>" ]
[ "<title>Acknowledgements</title>", "<p>The authors acknowledge Jie Xu (statistician) for giving suggestions to this SAP.</p>", "<title>Authors’ contributions</title>", "<p>XXZ designed this trial and together with XLL wrote the first draft of the QUADUAL SAP. XLL also provided technical guidance of statistics and epidemiology. GPY provided guidance of study design and ethical consideration. TL, YC, MH, and LZ gave suggestions for revising the manuscript. XGL funded this trial and provided critical review of the manuscript. WHJ is the chief investigator, funded this trial, and provided critical review of the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>The study was supported by the Key Research and Development Program of Hunan Province (NO.2022SK2029) and the National Natural Science Foundation of China Projects (NO.81800271).</p>", "<title>Availability of data and materials</title>", "<p>The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par82\">The study has been approved by the Institutional Review Board of the Third Xiangya Hospital of Central South University (R22023). All patients can voluntarily participate in and withdraw from the study. The purpose and method of the study will be informed in detail and the informed consent will be obtained. All investigators ensure the confidentiality of patient data.</p>", "<title>Consent for publication</title>", "<p id=\"Par83\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par84\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Flow diagram of the QUADUAL trial. <bold>A</bold> Angiotensin receptor blocker (irbesartan 150 mg). <bold>B</bold> Beta-blocker (metoprolol 47.5 mg). <bold>C</bold> Calcium channel blocker (amlodipine 5 mg). <bold>D</bold> Diuretic (indapamide 2.5 mg)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Timing of outcome assessments</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"><bold>Timepoint</bold></th><th align=\"left\"><bold>Enrolment and allocation</bold></th><th align=\"left\" colspan=\"2\"><bold>Treatment phase 1</bold></th><th align=\"left\" colspan=\"2\"><bold>Washout phase</bold></th><th align=\"left\" colspan=\"2\"><bold>Treatment phase 2</bold></th></tr><tr><th align=\"left\"><bold>0 day</bold></th><th align=\"left\"><bold>1–4 weeks</bold></th><th align=\"left\"><bold>4th week</bold></th><th align=\"left\"><bold>5–6 weeks</bold></th><th align=\"left\"><bold>6th week</bold></th><th align=\"left\"><bold>7–10 weeks</bold></th><th align=\"left\"><bold>10th week</bold></th></tr></thead><tbody><tr><td align=\"left\">HBPM</td><td align=\"left\">X</td><td align=\"left\">X</td><td align=\"left\">X</td><td align=\"left\">X</td><td align=\"left\">X</td><td align=\"left\">X</td><td align=\"left\">X</td></tr><tr><td align=\"left\">OBPM</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\" colspan=\"8\">Biochemistry results</td></tr><tr><td align=\"left\"> Electrolyte</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\"> FBG</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\"> Renal function</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\"> Liver function</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\"> Urine routine</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\" colspan=\"8\">Tests</td></tr><tr><td align=\"left\"> ECG</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">X</td></tr><tr><td align=\"left\"> ABPM</td><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td><td align=\"left\"/><td align=\"left\">X</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Analysis methods for different outcomes</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Outcomes</th><th align=\"left\">Analysis methods</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"2\"><bold>Primary outcome</bold></td></tr><tr><td align=\"left\"> Changes in 24-h SBP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Secondary outcomes</bold></td></tr><tr><td align=\"left\"> Changes in 24-h DBP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in daytime BP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in nighttime BP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in morning BP surge</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in office BP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in home BP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in heart rate</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> BP control rate</td><td align=\"left\">Paired chi-square test</td></tr><tr><td align=\"left\"> TTR of home BP</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\" colspan=\"2\"><bold>Safety outcomes</bold></td></tr><tr><td align=\"left\"> Adverse event</td><td align=\"left\">Chi-square tests or Fisher’s exact probability method</td></tr><tr><td align=\"left\"> Changes in biochemistry results</td><td align=\"left\">Linear mixed-effects model</td></tr><tr><td align=\"left\"> Changes in QT interval</td><td align=\"left\">Linear mixed-effects model</td></tr></tbody></table></table-wrap>" ]
[ "<disp-formula id=\"Equa\"><alternatives><tex-math id=\"M1\">\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${n = [\\frac{({t}_{\\alpha }+{t}_{2\\beta })S}{\\delta }]^{2}}$$\\end{document}</tex-math><mml:math id=\"M2\" display=\"block\"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:msup><mml:mrow><mml:mo stretchy=\"false\">[</mml:mo><mml:mfrac><mml:mrow><mml:mo stretchy=\"false\">(</mml:mo><mml:msub><mml:mi>t</mml:mi><mml:mi>α</mml:mi></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>t</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mi>β</mml:mi></mml:mrow></mml:msub><mml:mo stretchy=\"false\">)</mml:mo><mml:mi>S</mml:mi></mml:mrow><mml:mi>δ</mml:mi></mml:mfrac><mml:mo 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[ "<table-wrap-foot><p><italic>ABMP</italic> ambulatory blood pressure monitoring, <italic>ECG</italic> electrocardiogram, <italic>FBG</italic> fasting blood-glucose, <italic>HBPM</italic> home blood pressure measurement, <italic>OBPM</italic> office blood pressure measurement</p></table-wrap-foot>", "<table-wrap-foot><p><italic>BP</italic> blood pressure, <italic>DBP</italic> diastolic blood pressure, <italic>SBP</italic> systolic blood pressure, <italic>TTR</italic> time in target range</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["4."], "mixed-citation": ["The Writing Committee of the Report on Cardiovascular Health and Diseases in China. Report on cardiovascular health and diseases burden in China: an updated summary of 2020. Chinese Circ J. 2021;36(6):521\u201345. 10.3969/j.issn.1000-3614.2021.06.001."]}, {"label": ["12."], "surname": ["Junbo", "Yongjian", "Chen"], "given-names": ["G", "X", "W"], "source": ["Internal medicines"], "year": ["2018"], "publisher-loc": ["Beijing"], "publisher-name": ["People\u2019s Medical Publishing House"]}, {"label": ["17."], "surname": ["Hong", "Sung", "Lim", "Kim", "Kim", "Shin"], "given-names": ["SJ", "KC", "SW", "SY", "W", "J"], "article-title": ["Low-dose triple antihypertensive combination therapy in patients with hypertension: a randomized, double-blind, phase II study"], "source": ["Drug Des Dev Ther"], "year": ["2020"], "volume": ["14"], "fpage": ["5735"], "lpage": ["5746"], "pub-id": ["10.2147/DDDT.S286586"]}, {"label": ["21."], "surname": ["Hu"], "given-names": ["L"], "source": ["Application of statistical triad theory to experimental design"], "year": ["2006"], "publisher-loc": ["Beijing"], "publisher-name": ["People's Military Medical Press"]}, {"label": ["23."], "surname": ["Lawrence", "Yu"], "given-names": ["X", "BVL"], "source": ["FDA bioequivalence standards"], "year": ["2014"], "publisher-loc": ["London"], "publisher-name": ["Springer, New York Heidelberg Dordrecht London"]}, {"label": ["24"], "surname": ["Twisk"], "given-names": ["JWR"], "source": ["Analysis of data from randomized controlled trials: a practical guide"], "year": ["2021"], "publisher-loc": ["Switzerland"], "publisher-name": ["Springer Nature Switzerland AG"]}]
{ "acronym": [ "ABPM", "ADR", "AE", "CEC", "DBP", "FAS", "HBPM", "IDMC", "ITT", "LOCF", "OBPM", "PPS", "SAE", "SAP", "SBP", "SD", "SS", "TTR", "ULN" ], "definition": [ "Ambulatory blood pressure monitoring", "Adverse drug reaction", "Adverse event", "Clinical endpoint committee", "Diastolic blood pressure", "Full analysis set", "Home blood pressure measurement", "Independent data monitoring committee", "Intention to treat", "Last observation carried forward", "Office blood pressure measurement", "Per-protocol set", "Serious adverse event", "Statistical analysis plan", "Systolic blood pressure", "Standard deviation", "Safety set", "Time in target range", "Upper limit of normal" ] }
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CC BY
no
2024-01-14 23:43:47
Trials. 2024 Jan 13; 25:45
oa_package/83/fe/PMC10787485.tar.gz
PMC10787486
38217047
[ "<title>Background</title>", "<p id=\"Par5\">Ecuador saw a sustained decline in malaria incidence between 2000 and 2015, opening the possibility of achieving the elimination of this disease from the national territory by 2020 [##UREF##0##1##]. In fact, malaria eradication was achieved for approximately 20 years in the Ecuador-Peru border due to binational collaborative efforts for malaria control [##REF##27894320##2##]. However, since 2016, the country has experienced a significant increase in the number of locally-transmitted malaria cases in both the coastal and Amazon regions of more than 1000 cases/year, challenging the elimination goal [##UREF##1##3##]. The administrative transition from the National Service of Vector-borne Diseases to the Ministry of Public Health (MoH) is perceived to have contribute to this increase in malaria incidence by both weakening early case detection, and thwarting vector control strategies that were effective in previous years [##REF##30486839##4##]. The World Health Organization (WHO) has associated the changes in malaria incidence with multiple possible causes, including decreased funding to continue antimalarial programs or the monitoring of insecticide resistance [##UREF##1##3##]. The latter has been considered one of the main factors that severely complicates the control of malaria at a global scale.</p>", "<p id=\"Par6\">The main types of insecticides used for vector control are organochlorines (OGs), carbamates (CMs), organophosphates (OPs) and pyrethroids (PYs) [##UREF##2##5##, ##REF##27779925##6##]. Currently, PYs such as deltamethrin, permethrin and cypermethrin are the most widely used insecticides due to their high efficacy, low cost, high environmental stability, broad-spectrum and low toxicity to humans and the environment [##REF##25564745##7##–##UREF##4##9##]. However, the constant exposure to PYs by indoor residual spraying (IRS), long-lasting insecticidal nets (LLINs) and the extensive use of insecticides in agriculture have caused the appearance of resistant insect populations in some areas [##REF##30409140##10##, ##REF##26895980##11##]. Resistance to PYs has been widely documented in the main African malaria vectors, such as <italic>Anopheles arabiensis</italic>, <italic>Anopheles funestus</italic> and <italic>Anopheles gambiae </italic>sensu lato (<italic>s.l</italic>.) [##REF##29084560##12##–##REF##25261072##14##]. In Latin America, insecticide resistance has been reported with varying magnitude in populations of some of the main malaria vectors, such as <italic>Anopheles albimanus</italic>, <italic>Anopheles darlingi</italic> and <italic>Anopheles nuneztovari</italic> [##REF##17710279##15##–##REF##30228990##18##].</p>", "<p id=\"Par7\">Resistance to PYs is has been associated with a target-site insensitivity mechanism known as knockdown resistance (<italic>kdr</italic>). This mechanism involves highly specific genetic changes, such as single nucleotide polymorphisms (SNPs) or substitutions in codons 1014, 1013, 1010 and 1575 of the voltage-gated sodium channel gene (<italic>VGSC</italic>). Mutations that confer <italic>kdr</italic> resistance have been reported in codons 1010 and 1013 in <italic>Anopheles</italic> species from Africa and Asia. The most common type of mutations have been reported in codon 1014 and generate an amino acid change from leucine to serine (L1014S), cysteine (L1014C), phenylalanine (L1014F), or tryptophan (L1014W), thereby severely decreasing the interaction between cellular chemical receptors and insecticides [##REF##25292318##19##].</p>", "<p id=\"Par8\">The presence of resistant <italic>kdr</italic> alleles has been reported in populations of <italic>An. albimanus</italic> in Central America (México, Nicaragua and Costa Rica) [##REF##24330978##20##]. In South America (Colombia and Peru), resistance to PYs in <italic>An. albimanus</italic> populations is somewhat less frequent, and does not pose an immediate threat to malaria control [##REF##30228990##18##, ##UREF##5##21##].</p>", "<p id=\"Par9\">In Ecuador, deltamethrin (a member of the PYs group) and malathion (a member of the OPs group) are the most commonly used insecticides for vector control [##UREF##6##22##]. Since 2018, the WHO, the Ecuadorian MoH and independent researchers have reported phenotypic resistance to both types of insecticides in <italic>Aedes aegypti</italic> and <italic>An. albimanus</italic> from the coastal areas of the country [##UREF##7##23##, ##UREF##8##24##]. However, in <italic>An. albimanus</italic>, the genetic traits conferring resistance have not been evaluated. As an initial step in assessing deltamethrin resistance in <italic>Anopheles</italic> populations in Ecuador, an evaluation was conducted on the presence of phenotypic and genotypic resistance linked to mutations in the <italic>VGSC</italic> gene in <italic>An</italic>. <italic>albimanus</italic> populations from southern coastal region. Furthermore, to evaluate the potential impact of land use on insecticide resistance frequency, this study compared <italic>An. albimanus</italic> populations from two localities with varying degrees of agricultural activity.</p>" ]
[ "<title>Methods</title>", "<title>Study area</title>", "<p id=\"Par10\">This study was carried out in the malaria-endemic province of El Oro. This coastal province is located in the south-west region of Ecuador, and shares a border with Peru (Fig. ##FIG##0##1##). The economy of El Oro province is based on agriculture (particularly banana production), livestock and trade. During the 1980s and early 2000s, this province presented a high incidence of malaria cases; since then, a constant decline was observed, until 2011 it was deemed to be free of local malaria transmission [##REF##27894320##2##]. Between 2017 and 2021, only 62 cases were reported comprising three cases of with <italic>P. falciparum</italic> infection and 59 cases with <italic>P. vivax</italic> infection [##UREF##9##25##–##UREF##13##29##].</p>", "<p id=\"Par11\">Specimens for this study were collected in the counties of Santa Rosa and Huaquillas. Santa Rosa is one El Oro’s counties with the largest surface area dedicated to agriculture, fisheries and animal husbandry (62.68%). About 16% of the land is used for banana and cacao plantations [##UREF##14##30##]. Approximately 30% of the county’s economically-active population is involved in these activities [##UREF##14##30##]. Average precipitation during the rainy seasons (February–May and October–November) fluctuates between 500 and 2000 mm, while in the dry season (January–April) &lt; 500 mm. Temperature in the area fluctuates from 18 to 26 °C [##UREF##14##30##]. Information regarding the use of insecticides in agriculture is limited: however, there are reports of their extensive use in areas with high agricultural activity in the province [##UREF##8##24##, ##REF##33514015##31##]. In contrast, Huaquillas is a county that borders with Peru. The main economic activity is commercial trade (both formal and informal) while agriculture only contributes with 3.43% of the economic productive component [##UREF##15##32##]. Average precipitation varies from 125 to 250 mm during the rainy season (December-May) to &lt; 20 mm during the dry season (July–December). Temperature fluctuates between 20.7 and 31 °C [##UREF##15##32##].</p>", "<title>Collection of immature stages and breeding</title>", "<p id=\"Par12\">Immature stages (larvae and pupae) of <italic>An. albimanus</italic> were collected from March to August 2019 from temporal water ponds. In Santa Rosa, collections were carried out in livestock farms near banana plantations, while in Huaquillas specimens were collected from holes in the ground used for artisanal brick production (Fig. ##FIG##0##1##). Collections were performed using standard larval dippers (10 dips/m<sup>2</sup>).</p>", "<p id=\"Par13\">Collected samples were transported live to the Intermediate Reference Laboratory CZ7 07D02 of the MoH, located in the city of Machala. Because this laboratory is located on an area where <italic>An. albimanus</italic> is endemic, environmental conditions were monitored but not regulated throughout the rearing process. Average environmental conditions in the area during this study were 29 ± 3 °C temperature, 80 ± 10% relative humidity.</p>", "<p id=\"Par14\">To rear the larvae, standard guidelines for larval culture were adhere (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.beiresources.org/Publications/MethodsinAnophelesResearch.aspx\">https://www.beiresources.org/Publications/MethodsinAnophelesResearch.aspx</ext-link>). Larvae were placed in ceramic-coated steel trays (23 cm × 30 cm) in a density of one larva (L3/L4 stage) per ml of natural water (level 0.5 to 1 cm depth), and were fed with fish food (Levein, Quito, Ecuador). Pupae were picked daily and placed in cardboard cups covered with polyester mesh. Emerging adults were transferred to small plastic vials, identified as <italic>An. albimanus</italic> at the morphological level by the presence of pale-scales in the hind tarsomere 3 and 4, and the hind tarsomere 5 with a basal dark-scale [##REF##33208196##33##], separated by sex and were fed with a 10% sucrose solution ad libitum.</p>", "<title>Phenotypic resistance by CDC bioassays</title>", "<p id=\"Par15\">Monitoring of resistance to deltamethrin in the sampled <italic>An</italic>. <italic>albimanus</italic> populations was performed following the protocol for bottle bioassays issued by the CDC [##UREF##16##34##]. The efficiency of the deltamethrin stock technical grade (Sigma-Aldrich, Missouri, USA) used in this study was previously established in a bioassay with a susceptible strain of <italic>Ae.aegypti</italic> (Rockefeller strain) at a diagnosis dose of 10 µg/ml and time of 30 min.</p>", "<p id=\"Par16\">The standardization of the CDC bottle bioassay to determine a specific diagnostic dose and diagnostic time was not feasible due to the lack of known susceptible <italic>An</italic>. <italic>albimanus</italic> strain. Thus, bioassays were conducted with the diagnostic dose (12.5 µg/ml) and time (30 min) established by CDC in susceptible <italic>Anopheles</italic> populations [##UREF##16##34##]. Each bioassay consisted of one control group and one to four experimental replicates, depending on specimen availability. Each assay bottle (250 ml Wheaton bottles with scroll caps) was previously impregnated with either 1 ml of deltamethrin solution (for experimental groups) or 1 ml ethanol (for control groups). Ten to 25 mosquitoes, aged 2–5 days old, were introduced in each bottle using a mouth aspirator. Due to the limited number of emerging adults, some bioassays were carried out with specimens of both sexes; in these cases, males and females were always assayed in separate bottles.</p>", "<p id=\"Par17\">After setting up each bioassay, knockdown individuals (mosquitoes that cannot stand and that slide along the curve of the test bottle) were counted every 15 min, for a total period of 120 min. An additional counting, to estimate the mortality rate, was performed at 24 h (1440 min). After the assay, each mosquito was individually stored in a 0.6 ml microcentrifuge tube at − 20 °C for molecular analysis.</p>", "<title>Statistical analysis</title>", "<p id=\"Par18\">Following CDC guidelines, each bioassay was considered valid if the mortality rate in the control bottle was up to 3% after 120 min. Assays with mortality above this threshold in the control group were not included in the analysis. If the mortality in the control bottle was between 3 and 10%, Abbott’s formula was used to correct results. A mosquito population was considered susceptible with a knockdown rate of 98% to 100%, resistance that must be confirmed from 80 to 97% and resistance if knockdown was &lt; 80% [##UREF##16##34##].</p>", "<p id=\"Par19\">Shapiro–Wilk test was calculated to evaluate the normality of the data and median was selected to represent the data. The non-parametric Mann Whitney test was used to compare distributions of knockdown rate between localities and sex at 30 min (diagnostic time), and to compare mortality rate at 120 min and 24 h. All analyses were performed using the STATA software (v. 15.0) [##UREF##17##35##] with a significance level for decision-making of p &lt; 0.05. Data of bioassays are detailed in the Additional file ##SUPPL##0##1##: Table S1.</p>", "<title>Knockdown resistance (<italic>kdr</italic>) genotyping</title>", "<p id=\"Par20\">A sub-sample of 50% of the mosquitoes (n = 115) used in each bioassay was selected for molecular analysis (Huaquillas n = 58, Santa Rosa n = 57). DNA extraction was carried out with a DNeasy kit (Qiagen, USA) or DNAzol (ThermoFisher, USA), following the manufacturer procedures. A 225 bp segment of the <italic>VGSC</italic> gene was amplified in a 25 µl reaction mixture containing 1X GoTaq<sup>®</sup> Colorless Master Mix (Promega, USA) with 1.5 µM MgCl<sub>2</sub>, 0.2 mM dNTPs, 2.5 µM of each primer AAKDRF2 (5′-CAT TCA TTT ATG ATT GTG TTT CGT G-′3) and AAKDRR (5′-GCA ANG CTA AGA ANA GRT TNA G ′3) and 10 to 50 µg of genomic DNA [##REF##24330978##20##]. This segment contains codons 1010, 1013 and 1014, and codifies for most amino acids of the <italic>VGSC</italic>’s sixth segment of domain II, which is critical for interaction with PYs [##REF##25292318##19##, ##REF##24704279##36##].</p>", "<p id=\"Par21\">Amplification was performed using a SimpliAmp Thermocycler (Applied Biosystems, USA). Amplification conditions included an initial denaturation at 95 °C for 3 min, followed by 40 cycles at 95 °C for 45 s, 51.5 °C for 45 s and 72 °C for 1 min, and a final extension step at 72 °C for 5 min [##REF##24330978##20##]. Amplification products were visualized in a 1.5% agarose gel stained with SYBR® Safe (Invitrogen, USA). Products were sequenced using a commercial service (Macrogen Inc., Korea).</p>", "<p id=\"Par22\">Forward and reverse sequences of each sample were manually curated using MEGA11:Molecular Evolutionary Genetics Analysis version 11 [##REF##33892491##37##]. Consensus alignments were established and chromatograms were manually analysed to determine the codon composition at positions 1010, 1013 and 1014. Finally, a complete alignment with all the sequences was performed, together with reference sequences of <italic>An. albimanus</italic> from Colombia and Guatemala (GenBank accessions MN087505 and KF137581.1, respectively). Sequence data are shown in Additional file ##SUPPL##1##2##: Table S2.</p>" ]
[ "<title>Results</title>", "<title>Phenotypic resistance</title>", "<p id=\"Par23\">Bioassay analysis was conducted on a total of 231 <italic>An. albimanus</italic> specimens, with 116 from Huaquillas and 115 from Santa Rosa (Table ##TAB##0##1##). Data from five bioassays were excluded due to the absence of control bottles, control bottle mortality rates exceeding 10%, and a mix of males and females in the same experiment bottle. Knockdown rate was determined based on the median, according with the data distribution (Shapiro Wilk test, <italic>p</italic> = 0.03795). Mosquitoes from Santa Rosa presented phenotypic resistance with a knockdown rate of 63.3% (IQR 45.6–80.0), while in Huaquillas, suspected resistance was found with 82.1% knockdown rate (IQR 20.0–84.0). No statistical differences were found between the distributions of knockdown rate for the two localities (<italic>p</italic> = 0.6048) (Table ##TAB##0##1## and Fig. ##FIG##1##2##a, b).</p>", "<p id=\"Par24\">The analysis included an examination of the influence of sex on the oucomes. A total of 147 females (63.63% of total) and 84 males (36.36% of total) were used in the bioassays. Females presented a higher median knockdown rate (83.7%, IQR 73.8–89.5) than males (45.6%, IQR 20.0–60.0) (<italic>p</italic> = 0.0278), however no significant differences were found within localities (Huaquillas, <italic>p</italic> = 0.0603; Santa Rosa, <italic>p</italic> = 0.3836) (Table ##TAB##1##2##).</p>", "<p id=\"Par25\">Comparison of knockdown rates was conducted at specific intervals: 30 min (diagnostic time), 120 min (the end of the experiment according to the protocol) and 24 h (additional record). Statistical analysis indicated significant differences when comparing knockdown rates at 30 min versus 120 min (<italic>p</italic> &lt; 0.001) and versus 24 h (<italic>p</italic> = 0.0016), regardless the locality (Fig. ##FIG##1##2##a). Additionally, an observed increase of 13.5% and 2.9% in knockdown rate occurred between 30 and 120 min and 24 h, respectively. No statistical differences were found when comparing knockdown rate at 120 min and 24 h, regardless the locality (<italic>p</italic> = 0.2859) (Fig. ##FIG##1##2##a).</p>", "<title>Knockdown resistance (<italic>kdr</italic>) genotyping</title>", "<p id=\"Par26\">The analysis of the mutations in codons 1010, 1013 and 1014 of the <italic>VSCG</italic> gene was performed in 109 of the 115 sequenced samples (53 specimens from Huaquillas, 56 specimens from Santa Rosa). Six samples (5.2%) presented non-legible chromatograms and were excluded from the analysis. Only susceptible sequence (i.e. wild-type) for codons 1010 (GTT) and 1013 (AAC) were found in all samples. The susceptible sequence for codon 1014 (TTG, coding for leucine) was present in 90.6% (n = 48) of samples from Huaquillas and in 94.6% (n = 53) of samples from Santa Rosa. Ambiguous nucleotide for G/T (TKK) were found in 7.5% (n = 4) and 1.78% (n = 1) of the samples from Huaquillas and Santa Rosa, respectively. While the C/T (TYG) were found in 1.9% (n = 1) samples from Huaquillas and 3.6% (n = 2) from Santa Rosa. The codon sequences reported as confering resistance were not observed in a homozygous state in the experimental specimens (Fig. ##FIG##2##3##).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par27\">This study reveal the presence of phenotypic resistance to deltamethrin in <italic>An. albimanus</italic> populations from southern Ecuador. However, this resistance is evidenced although it was not related with <italic>kdr</italic> mutations, suggesting the existence of alternative resistance mechanisms in the area.</p>", "<p id=\"Par28\">Despite the recent success of some South and CentralAmerican countries in eradicating malaria (Argentina, El Salvador and Paraguay have been certified as malaria free since 2018) [##UREF##1##3##], the elimination goal in the Americas is currently at risk. The region has failed to achieve the goal of 40% reduction on malaria rates initially set by the WHO [##UREF##1##3##], and several countries (including Honduras, Panamá, Ecuador and Bolivia) have actually reported recent increases in malaria incidence [##UREF##1##3##]. </p>", "<p id=\"Par29\">One of the fundamental strategies advocated by the WHO for an effective response to outbreaks is the monitoring of insecticide resistance [##UREF##1##3##]. Of the 88 malaria endemic countries, 78 have reported instances of resistance to at least one category of insecticides within their malaria vectors. The prevalence of resistance to PYs and OGs is widespread and cause alarm [##UREF##1##3##]. In the Americas, a majority of countries have actively reported plans for insecticide monitoring and management [##UREF##1##3##], underlining the pivotal role of such monitoring as an integral part of insecticide-based interventions to prevent outbreaks. Resistance status of the most important malaria vectors can be tracked by WHO-sponsored ‘Malaria Threats Map’ [##UREF##18##38##]. </p>", "<p id=\"Par30\">In Latin America, phenotypic resistance to insecticides (PY, OP and CM) has been reported in main malaria vectors, such as <italic>An. albimanus</italic>, <italic>An. darlingi, An. nuneztovari</italic> [##REF##19274371##17##, ##REF##30228990##18##, ##REF##24330978##20##, ##REF##9737593##39##–##REF##25889700##41##]. However, the genetic traits associated with resistance in these populations are not well established. </p>", "<p id=\"Par31\">In Ecuador, the MoH and the National Institute of Public Health Research (INSPI, by its Spanish acronym) have reported <italic>An. albimanus</italic> populations resistant to PYs (Deltamethrin 0.05%), and OPs (Malathion 5%) by the discriminating concentration bioassay of the WHO [##UREF##18##38##]. Official reports have revealed deltamethrin resistance or probability of resistance in four provinces [##UREF##18##38##], including the southern coastal province of El Oro, where this study was carried out. In a 2019 report, <italic>An. albimanus</italic> from Huaquillas and Santa Rosa were resistant to deltamethrin (62% and 68.8% mortality rate, respectively) [##UREF##7##23##]; however, there is no data about the genetic traits or resistance mechanisms involved. </p>", "<p id=\"Par32\">Information regarding the use of pesticides and insecticides in El Oro province is limited; however, the use of pesticides in an area can be reflected in the number of cases related to the toxic effect of pesticides treated within the public health system. In 2019, in Santa Rosa, 20 such cases were reported, while Huaquillas had only four cases (<ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ecuadorencifras.gob.ec/camas-y-egresos-hospitalarios/\">https://www.ecuadorencifras.gob.ec/camas-y-egresos-hospitalarios/</ext-link>). Although Huaquillas does not have a large area of land for agriculture, a previous survey indicated that 18.9% of homes purchase pyrethroid insecticides to use at home [##UREF##8##24##]. While the extensive use of insecticides in agriculture and urban areas have been linked to the emergence of resistant insect populations [##REF##26895980##11##, ##REF##35885989##42##, ##REF##29267961##43##], this trend was not evident in this study. Even though a lower knockdown rate is reported in Santa Rosa (locality with higher agricultural activity), no significant differences were detected when compared to Huaquillas (low agricultural activity). These results suggest a limited influence of the use of PYs in agriculture as selective pressure for mosquitos; however, certain limitations in this study (such as sample size and the use of males and females) need to be considered, as discussed below. </p>", "<p id=\"Par33\">One limitation to consider in this study was the limited availability of females for the bioassays that can lead to a variation of the reported knockdown proportions. In this study, female mosquitoes from 2–5 day old were used in the bioassays. However, the insufficient number of females hindering achieving an adequate sample size, thus males were included as well. Although bioassay protocols for other mosquitoes (i.e. <italic>Aedes, Culex</italic>) allow the inclusion of males and females as both contribute equally to the genes of their progeny [##UREF##19##44##], the modification in the methodology of this study could influence the reported knockdown proportion at diagnostic time as females presented higher rate than males. While there have not been reports of sex-linked mechanism for PYs resistance in <italic>Anopheles</italic>, an effect driven by sex should be considered as differential immune response and expression of insecticide resistant genes have been reported in other mosquitoes species such as <italic>Culex pipiens</italic> and <italic>Ae. aegypti</italic> [##REF##31027587##45##, ##REF##24499651##46##].</p>", "<p id=\"Par34\">Another limitation of the study was the lack of a susceptible strain of <italic>An. albimanus</italic> to test the deltamethrin concentration, even though the viability of the chemical was tested in a susceptible strain of <italic>Ae. aegypti</italic> (Rockefeller). In this context, the recommended concentration [##UREF##16##34##] was applied and the knockdown rate was evaluated, instead of the mortality rate, during the CDC bioassay methodology. Additionally, an evaluation of the post-exposure effects of the insecticide were carried out by analyzing records at 120 min (the end of the experiment) and an additional reading at 24 hours, which is considered to reflect the mortality rate. The knockdown rates at 30 min were significantly lower than those at 120 min and 24 hours. This suggests that biological effects can occur not only during the period immediately following exposure to the pesticide (0-120 min), but also during the post-exposure period (120 min-24 hr). Furthermore, the decrease in the number of knockdown individuals between 120 min and 24 hour indicated that some specimens can recover after exposure to the diagnostic dose.This observation hints at the posible existence of alternative resistance mechanisms in these populations, such as metabolic resistance involving the production of detoxifying enzymes. Further exploration of the biological post-exposure effects is necessary [##REF##26148484##47##].</p>", "<p id=\"Par35\">At genetic level, <italic>kdr</italic> resistance on the <italic>VGCS</italic> gene has shown a strong causal relationship with DDT and PYs [##REF##19369117##48##]. Studies in the main malaria vector species in Africa and Asia have reported non-synonymous mutation in at least four codons (1010, 1013, 1014 and 1575) of this gene [##REF##25292318##19##]. In Central America, populations of <italic>An. albimanus</italic> have shown mutations in codon 1014 that conferred resistance to PY [##REF##24330978##20##]. In South America (Colombia and Peru), phenotypically resistant populations of <italic>Anopheles</italic> have shown low frequency or absence of <italic>kdr</italic> mutations [##REF##25292318##19##, ##REF##30699158##50##]. These reports agree with the results of this study that reported susceptible codon sequences at position 1010 and 1013, and only eight samples (7.3%) showed polymorphisms in codon 1014.</p>", "<p id=\"Par36\">Taken together, the presence of susceptible sequences on codons 1010 and 1013, as well as the low frequency of variants on codon 1014, suggest that the levels of resistance observed in the bioassays are most likely due to the existence of alternative resistance mechanisms in the study populations. These results are in agreement with other reports which suggest that the frequency of <italic>kdr</italic> mutations in a population is not necessarily the best predictor of phenotypic resistance, with other mechanisms (such as metabolic resistance) playing important roles [##REF##26381877##51##, ##REF##34958768##52##]. </p>", "<p id=\"Par37\">Furthermore, both the phenotypic and genetic results of this study agree with the description of <italic>An. albimanus</italic> as a panmictic population with high gene flow, particularly at microgeographic scales [##REF##24704285##53##, ##REF##36607981##54##]. However, as local and environmental characteristics may influence the variations observed in this vector species [##REF##36607981##54##], further analysis of the impact of environment and interventions might be considered along the geographic distribution of <italic>An. albimanus</italic> in Ecuador. </p>", "<p id=\"Par38\">Between 2017 and 2021, malaria outbreaks in Ecuador were mainly reported in the Amazon region, where no data on pesticide resistance is available, and in the northern coastal area, where the only study available did not found resistance to deltamethrin in <italic>An. albimanus</italic> [##UREF##18##38##]. Phenotypic and genetic characterization of resistance to PYs in malaria vectors from endemic areas in Ecuador is an important step towards an early response to outbreaks. Monitoring will allow us to elucidate the mechanism involved in the development of the resistance to PYs, and to propose alternative insecticides or strategies for vector control in areas where resistance is present. This valuable information could provide a new path to control future outbreaks of malaria both locally and regionally.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Decrease in malaria rates (e.g. incidence and cases) in Latin America maintains this region on track to achieve the goal of elimination. During the last 5 years, three countries have been certified as malaria free. However, the region fails to achieve the goal of 40% reduction on malaria rates and an increase of cases has been reported in some countries, including Ecuador. This scenario has been associated with multiple causes, such as decrease of funding to continue anti-malarial programmes and the development of insecticide resistance of the main malaria vectors. In Ecuador, official reports indicated phenotypic resistance in <italic>Aedes aegypti</italic> and <italic>Anopheles albimanus</italic> to deltamethrin and malathion, particularly in the coastal areas of Ecuador, however, information about the mechanisms of resistance have not been yet elucidated. This study aims to evaluate phenotypic response to deltamethrin and its relationship with <italic>kdr</italic> mutations in <italic>An</italic>. <italic>albimanus</italic> from two localities with different agricultural activities in southern coastal Ecuador.</p>", "<title>Methods</title>", "<p id=\"Par2\">The CDC bottle assay was carried out to evaluate the phenotypic status of the mosquito’s population. Sequencing the voltage gated sodium channel gene (<italic>VGSC</italic>) sought knockdown mutations (<italic>kdr</italic>) in codons 1010, 1013 and 1014 associated with resistance.</p>", "<title>Results</title>", "<p id=\"Par3\">Phenotypic resistance was found in Santa Rosa (63.3%) and suspected resistance in Huaquillas (82.1%); with females presenting a higher median of knockdown rate (83.7%) than males (45.6%). No statistical differences were found between the distributions of knockdown rate for the two localities (<italic>p</italic> = 0.6048) which indicates no influence of agricultural activity. Although phenotypic resistance was confirmed, genetic analysis demonstrate that this resistance was not related with the <italic>kdr</italic> mechanism of the <italic>VGSC</italic> gene because no mutations were found in codons 1010 and 1013, while in codon 1014, 90.6% showed the susceptible sequence (TTG) and 7.3% ambiguous nucleotides (TKK and TYG).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">These results highlighted the importance of continuous monitoring of resistance in malaria vectors in Ecuador, particularly in areas that have reported outbreaks during the last years. It is also important to elucidate the mechanism involved in the development of the resistance to PYs to propose alternative insecticides or strategies for vector control in areas where resistance is present.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12936-023-04818-6.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We want to thank to Valeria Sánchez from the Universidad Técnica de Machala for their support in field logistic, also to Sarah Vaca, Rogerio Feijoo, Alejandra Zurita and César Yumiseva from CISeAL for their support in the field collection of samples and management of data. We also want to thank Peter Ramírez and Franklin Ruiz, from the Laboratorio de Referencia Intermedio de Entomología CZ707D02 for their support in the field laboratory.</p>", "<title>Author contributions</title>", "<p>SRJ: Acquisition, analysis and interpretation of data and have drafted the manuscript. JJB: Acquisition, analysis and interpretation of data and review of the manuscript. ALM: Analysis and interpretation of data and review of the manuscript. MN: Analysis and interpretation of data and review of the manuscript. LF: Acquisition data and review of the manuscript. SOM: Conception and design of the study, interpretation of data and review of the manuscript.</p>", "<title>Funding</title>", "<p>This study was founded by grants by the Pontificia Universidad Católica del Ecuador QINV0076-IINV529010100 and Publicalo award 2019.</p>", "<title>Availability of data and materials</title>", "<p>All data generated or analysed during this study are included in this published article and its additional files.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par39\">Not applicable.</p>", "<title>Consent for publication</title>", "<p id=\"Par40\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par41\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Geographical location of the collection sites in southern Ecuador (El Oro province). The red circular points showed the sampling sites from Santa Rosa (high agricultural activity) and the green points from Huaquillas (low agricultural activity)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Median knockdown rate of <italic>An. albimanus</italic> exposed to deltamethrin at the diagnostic dose of 12.5 µg/ml. Diagnostic time was considered at 30 min. Error bars represented the maximum and minimum values. <bold>a</bold> Comparison of the distribution of knockdown rates by locality and <bold>b</bold> Total median knockdown rate</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Alignment of a region of the <italic>VGSC</italic> gene of <italic>An. albimanus</italic>. Susceptible sequence (GTT) was detected for codon 1010 that codifies valine (V110) (blue box) and codon 1013 (AAC) that codifies asparagine (N113) (green box). Codon 1014 presented the susceptible sequence (TTG) that codifies leucine (red box) with the exception of certain individuals from Huaquillas (HQ) and Santa Rosa (SR) that presented ambiguous nucleotides G/T (TKK) and C/T (TYG). Alignment was performed by comparison with GenBank sequences of <italic>An. albimanus</italic> from Colombia (Col) (MN087505) and Guatemala (Gt) (KF137581.1). Identical positions are indicated with an asterisk</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Knockdown median proportion for <italic>An. albimanus</italic> in Huaquillas (HQ) and Santa Rosa (SR) in El Oro province, Ecuador. </p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" colspan=\"4\">Huaquillas (HQ)</th><th align=\"left\" colspan=\"4\">Santa Rosa (SR)</th></tr><tr><th align=\"left\">Time (minutes)</th><th align=\"left\"># Knockdown</th><th align=\"left\"># Non- affected</th><th align=\"left\">Kd %</th><th align=\"left\"># Knockdown</th><th align=\"left\"># Non- affected</th><th align=\"left\">Kd %</th><th align=\"left\"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align=\"left\">0</td><td char=\".\" align=\"char\">0</td><td char=\".\" align=\"char\">116</td><td char=\".\" align=\"char\">0.00</td><td char=\".\" align=\"char\">0</td><td char=\".\" align=\"char\">115</td><td char=\".\" align=\"char\">0.00</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">15</td><td char=\".\" align=\"char\">74</td><td char=\".\" align=\"char\">42</td><td char=\".\" align=\"char\">74.2</td><td char=\".\" align=\"char\">50</td><td char=\".\" align=\"char\">65</td><td char=\".\" align=\"char\">45.6</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\"><bold>30</bold></td><td char=\".\" align=\"char\">79</td><td char=\".\" align=\"char\">37</td><td char=\".\" align=\"char\"><bold>82.1</bold></td><td char=\".\" align=\"char\">74</td><td char=\".\" align=\"char\">41</td><td char=\".\" align=\"char\"><bold>63.3</bold></td><td char=\".\" align=\"char\">0.06048</td></tr><tr><td align=\"left\">45</td><td char=\".\" align=\"char\">82</td><td char=\".\" align=\"char\">34</td><td char=\".\" align=\"char\">82.1</td><td char=\".\" align=\"char\">87</td><td char=\".\" align=\"char\">28</td><td char=\".\" align=\"char\">70.3</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">60</td><td char=\".\" align=\"char\">95</td><td char=\".\" align=\"char\">21</td><td char=\".\" align=\"char\">81.7</td><td char=\".\" align=\"char\">95</td><td char=\".\" align=\"char\">20</td><td char=\".\" align=\"char\">83.2</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">75</td><td char=\".\" align=\"char\">99</td><td char=\".\" align=\"char\">17</td><td char=\".\" align=\"char\">82.5</td><td char=\".\" align=\"char\">100</td><td char=\".\" align=\"char\">15</td><td char=\".\" align=\"char\">90.0</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">90</td><td char=\".\" align=\"char\">101</td><td char=\".\" align=\"char\">15</td><td char=\".\" align=\"char\">88.4</td><td char=\".\" align=\"char\">106</td><td char=\".\" align=\"char\">9</td><td char=\".\" align=\"char\">94.4</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">105</td><td char=\".\" align=\"char\">111</td><td char=\".\" align=\"char\">5</td><td char=\".\" align=\"char\">95.5</td><td char=\".\" align=\"char\">109</td><td char=\".\" align=\"char\">6</td><td char=\".\" align=\"char\">94.4</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">120</td><td char=\".\" align=\"char\">108</td><td char=\".\" align=\"char\">8</td><td char=\".\" align=\"char\">93.2</td><td char=\".\" align=\"char\">110</td><td char=\".\" align=\"char\">5</td><td char=\".\" align=\"char\">97.4</td><td char=\".\" align=\"char\"/></tr><tr><td align=\"left\">1440</td><td char=\".\" align=\"char\">98</td><td char=\".\" align=\"char\">18</td><td char=\".\" align=\"char\">84.5</td><td char=\".\" align=\"char\">107</td><td char=\".\" align=\"char\">8</td><td char=\".\" align=\"char\">97.1</td><td char=\".\" align=\"char\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Number of individuals by sex and knockdown median proportion at 30 min for <italic>An. albimanus</italic> from Huaquillas (HQ) and Santa Rosa (SR) in southern coastal Ecuador</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\"/><th align=\"left\" colspan=\"2\">Female</th><th align=\"left\" colspan=\"2\">Male</th><th align=\"left\"/></tr><tr><th align=\"left\">No. individuals (%)</th><th align=\"left\">Kd %</th><th align=\"left\">No. individuals (%)</th><th align=\"left\">Kd %</th><th align=\"left\"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align=\"left\">HQ</td><td char=\"(\" align=\"char\">86 (74.13)</td><td char=\".\" align=\"char\">83.7</td><td align=\"left\">30 (25.86)</td><td char=\".\" align=\"char\">20.0</td><td char=\".\" align=\"char\">0.0603</td></tr><tr><td align=\"left\">SR</td><td char=\"(\" align=\"char\">61 (53.04)</td><td char=\".\" align=\"char\">78.1</td><td align=\"left\">54 (46.95)</td><td char=\".\" align=\"char\">55.0</td><td char=\".\" align=\"char\">0.3836</td></tr><tr><td align=\"left\">HQ + SR</td><td char=\"(\" align=\"char\">147 (63.63)</td><td char=\".\" align=\"char\">83.7</td><td align=\"left\">84 (36.36)</td><td char=\".\" align=\"char\">45.6</td><td char=\".\" align=\"char\">0.0278</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>" ]
[ "<table-wrap-foot><p>Bold values corresponded to the median knockdown rate obtained at 30 minutes which constitutes the diagnosis time to determine the state of susceptibility or resistance of the population</p><p>Number of individuals counted as knockdown and alive (non-affected) by time and locality. In bold, the knockdown percentage at diagnostic time (30 min) and the associated <italic>p</italic> value by Wilcoxon test</p><p>Kd%: median knockdown rate</p></table-wrap-foot>", "<table-wrap-foot><p>Kd%: median knockdown rate, (%) proportion of individuals of each sex per locality</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher's Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12936_2023_4818_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12936_2023_4818_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12936_2023_4818_Fig3_HTML\" id=\"MO3\"/>" ]
[ "<media xlink:href=\"12936_2023_4818_MOESM1_ESM.xlsx\"><caption><p><bold>Additional file 1: Table S1.</bold> Counting of individuals alive and knockdown of five CDC bioassays carried out in An. albimanus from Huaquillas and Santa Rosa (southern coastal Ecuador) of 2–5 days old exposed to a deltamethrin dose of 12,5 mg/ml.</p></caption></media>", "<media xlink:href=\"12936_2023_4818_MOESM2_ESM.xlsx\"><caption><p><bold>Additional file 2</bold><bold>: </bold><bold>Table S2.</bold> Sequence of codon 1010, 1013 and 1014 of the VSG gen in An. albimanus exposed to deltamethrin 12.5 mg/ml from Huaquillas and Santa Rosa, southern coastal Ecuador.</p></caption></media>" ]
[{"label": ["1."], "collab": ["WHO"], "source": ["World malaria report 2018"], "year": ["2018"], "publisher-loc": ["Geneva"], "publisher-name": ["World Health Organization"]}, {"label": ["3."], "collab": ["WHO"], "source": ["World malaria report 2022"], "year": ["2022"], "publisher-loc": ["Geneva"], "publisher-name": ["World Health Organization"]}, {"label": ["5."], "surname": ["Najera", "Zaim"], "given-names": ["JA", "M"], "source": ["Insecticides for indoor residual spraying"], "year": ["2001"], "publisher-loc": ["Geneva"], "publisher-name": ["World Health Organization, Division of Communicable Diseases"]}, {"label": ["8."], "surname": ["Schleier", "Peterson", "Lopez", "Fernandez-Bolanos"], "given-names": ["JJ", "RK", "O", "JG"], "article-title": ["Pyrethrins and pyrethroid insecticides"], "source": ["Green trends in insect control"], "year": ["2011"], "edition": ["3"], "publisher-loc": ["London"], "publisher-name": ["The Royal Society of Chemistry"]}, {"label": ["9."], "surname": ["Wirtz", "Bala", "Amann", "Elbert"], "given-names": ["K", "S", "A", "A"], "article-title": ["A promise extended\u2014future role of pyrethroids in agriculture"], "source": ["Pyrethroid Scientific Forum"], "year": ["2009"], "volume": ["62"], "issue": ["2"], "fpage": ["145"], "lpage": ["58"]}, {"label": ["21."], "surname": ["Vargas", "C\u00f3rdova", "Alvarado"], "given-names": ["F", "O", "A"], "article-title": ["Determinaci\u00f3n de la resistencia a insecticidas en "], "italic": ["Aedes aegypti", "Anopheles albimanus", "Lutzomyia peruensis"], "source": ["Rev Peruana Med Exp Salud P\u00fablica"], "year": ["2006"], "volume": ["23"], "fpage": ["259"], "lpage": ["264"]}, {"label": ["22."], "collab": [" Ministerio de Salud Publica del Ecuador"], "source": ["Instructivo para la transferencia del talento humano, activos fijos y metodolog\u00eda t\u00e9cnica del SNEM a las entidades operativas desconcentradas del Ministerio de Salud P\u00fablica"], "year": ["2015"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["23."], "collab": [" Ministerio de Salud Publica del Ecuador"], "source": ["Vigilancia de la resistencia a insecticidas Enero\u2014Junio 2019"], "year": ["2019"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["24."], "surname": ["Ryan", "Mundis", "Aguirre", "Lippi", "Beltran", "Heras"], "given-names": ["SJ", "SJ", "A", "CA", "E", "F"], "article-title": ["Seasonal and geographic variation in insecticide resistance in "], "italic": ["Aedes aegypti"], "source": ["PLoS Negl Trop Dis"], "year": ["2019"], "volume": ["3"], "fpage": ["e0007448"], "pub-id": ["10.1371/journal.pntd.0007448"]}, {"label": ["25."], "collab": [" Ministerio de Salud Publica del Ecuador"], "source": ["Subsistema de Vigilancia SIVE-ALERTA, Enfermedades Transmitidas por Vectores Ecuador SE 1\u201352"], "year": ["2017"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["26."], "collab": ["Ministerio de Salud Publica del Ecuador"], "source": ["Subsistema de Vigilancia SIVE-ALERTA, Enfermedades Transmitidas por Vectores Ecuador SE 1\u201352"], "year": ["2018"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["27."], "collab": ["Ministerio de Salud Publica del Ecuador"], "source": ["Subsistema de Vigilancia SIVE-ALERTA, Enfermedades Transmitidas por Vectores Ecuador SE 1\u201352"], "year": ["2019"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["28."], "collab": ["Ministerio de Salud Publica del Ecuador"], "source": ["Subsistema de Vigilancia SIVE-ALERTA, Enfermedades Transmitidas por Vectores Ecuador SE 1\u201352"], "year": ["2020"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["29."], "collab": ["Ministerio de Salud Publica del Ecuador"], "source": ["Subsistema de Vigilancia SIVE-ALERTA, Enfermedades Transmitidas por Vectores Ecuador SE 1\u201352"], "year": ["2021"], "publisher-loc": ["Quito"], "publisher-name": ["Ministerio de Salud Publica del Ecuador"]}, {"label": ["30."], "collab": ["GAD"], "source": ["Plan de Desarrollo y Ordenamiento Territorial del Cant\u00f3n Santa Rosa"], "year": ["2019"], "publisher-loc": ["Santa Rosa"], "publisher-name": ["Gobierno Aut\u00f3nomo Descentralizado de Santa Rosa"]}, {"label": ["32."], "collab": ["GAD"], "source": ["Plan de Desarrollo y Ordenamiento Territorial del Cant\u00f3n Huaquillas 2019\u20132023"], "year": ["2019"], "publisher-loc": ["Huaquillas"], "publisher-name": ["Gobierno Aut\u00f3nomo Descentralizado de Huaquillas"]}, {"label": ["34."], "surname": ["Brogdon", "Chan"], "given-names": ["W", "A"], "source": ["Guideline for evaluating insecticide resistance in vectors using the CDC bottle bioassay"], "year": ["2010"], "publisher-loc": ["Atlanta"], "publisher-name": ["Center for Disease Control and Prevention (CDC)"]}, {"label": ["35."], "collab": ["StataCorp"], "source": ["Stata Statistical Software Release 15"], "year": ["2017"], "publisher-loc": ["College Station"], "publisher-name": ["StataCorp"]}, {"label": ["38."], "mixed-citation": ["World Health Organization. Vector insecticide resistance. Malaria Threats Map. 2022. ["], "ext-link": ["https://www.who.int/teams/global-malaria-programme/surveillance/malaria-threats-map"]}, {"label": ["44."], "surname": ["McAllister", "Scott"], "given-names": ["JC", "M"], "source": ["CONUS manual for evaluating insecticide resistance in mosquitoes using the CDC bottle bioassay kit"], "year": ["2020"], "publisher-loc": ["Fort Collins"], "publisher-name": ["Centers for Disease Control and Prevention"]}]
{ "acronym": [], "definition": [] }
54
CC BY
no
2024-01-14 23:43:47
Malar J. 2024 Jan 12; 23:17
oa_package/79/92/PMC10787486.tar.gz
PMC10787487
0
[ "<title>Background</title>", "<p id=\"Par19\">Febrile seizures (FS) are the most common type of convulsions in infants and children and typically occur in association with a fever more than 100.4°F (38 °C) in children 6 months to 5 years of age, who have no evidence of any central nervous system infection or metabolic disturbance. Its overall prevalence in children is approximately 2%-14% worldwide [##REF##26286537##1##]. Although single short FS (generalized seizures lasting &lt; 15 min) are generally benign, prolonged FS (pFS) (FS lasting &gt; 15 min) are more likely to develop into temporal lobe epilepsy (TLE) later in life [##REF##25304962##2##–##UREF##0##6##]. Retrospective studies have shown that 30%-60% of patients with TLE have a history of pFS [##REF##15940665##7##]. Therefore, understanding the pathogenesis of FS is clinically important, because, if it is associated with subsequent epilepsy, then predictive biomarkers and preventive therapies might be feasible.</p>", "<p id=\"Par20\">High mobility group box 1 (HMGB1) is a highly conserved, ubiquitously expressed nonhistone DNA-binding protein present in eukaryotic cells that functions in stabilizing nucleosomes and regulating gene transcription [##UREF##1##8##]. Previous studies have revealed increased expression levels of serum HMGB1 in FS patients [##REF##25319229##9##–##REF##21989210##11##]. Ito et al. found that HMGB1 enhances hyperthermia-induced seizures, contributes to FS pathogenesis and plays an important role in the acquired epileptogenesis of secondary epilepsy associated with pFS [##REF##28879430##12##], indicating that HMGB1 related signalling contributes to the generation of FS in children. Furthermore, Choi and colleagues found that increased expression of HMGB1 was associated with elevated serum levels of interleukin (IL)-1β in children who had FS [##REF##21989210##11##]. Yang and colleagues found that increased expression levels of HMGB1 and toll-like receptor (TLR)-4 showed a positive correlation with elevated serum levels of tumour necrosis factor-α (TNF-α) and IL-1β in a rat model and in children with TLE [##REF##28176142##13##]. Taken together, the above data indicate a correlation between HMGB1 expression and IL-1β production. However, the nature of the link between HMGB1 and IL-1β has not been clarified in children with FS.</p>", "<p id=\"Par21\">The role of HMGB1 and IL-1β in generating and perpetuating seizures is well-documented [##REF##35837232##14##]. Physiologically, HMGB1 resides in the nucleus translocates to the cytosol under conditions of stress and is subsequently released into the extracellular space [##REF##24937773##15##]. Once released into the extracellular space, HMGB1 protein serves as a typical alarmin or damage-associated molecular pattern (DAMP) that binds to cell membrane pattern recognition receptors (PRRs), including TLR2, TLR4 and the receptor for advanced glycation end products (RAGE), which are predominantly expressed by activated monocytes, macrophages, T-lymphocytes in plasma, microglia in the central nervous system [##REF##25568124##16##]. Activation of TLR2 and TLR4 causes the recruitment of MyD88 to activate several mitogen-activated protein kinases (MAPKs) that activate the downstream transcription factor nuclear factor kappa B (NF-κB). Activated NF-κB moves into the nucleus and promotes the formation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, thus enhancing the release of the proinflammatory cytokine IL-1β [##REF##33221489##17##–##REF##30618088##19##]. Therefore, it was speculated that the extracellular HMGB1 activated NLRP3 inflammasome possibly mediates IL-1β secretion in children with FS.</p>", "<p id=\"Par22\">Given the correlation between HMGB1 and the NLRP3 inflammasome, the aim of the current study was to investigate whether HMGB1-induced activation of the NLRP3 inflammasome contributes to generation of FS by evaluating the protein expression levels of HMGB1, NLRP3, caspase-1, IL-1β, IL-6, and TNF-α in the peripheral serum of FS patients.</p>" ]
[ "<title>Methods</title>", "<title>Participants</title>", "<p id=\"Par23\">A total of 30 FS patients (aged 6 months to 5 years) who visited the Department of Paediatrics or or Emergency Department of Foshan Women and Children Hospital from January 2019 and April 2020 were included in this study (Table ##TAB##0##1##). All individuals enrolled were unrelated ethnic Han Chinese who lived in southern China. None of the biological grandparents of the participants were from other ethnicities. Peripheral blood was obtained from patients within 1 h of the time of seizure, and serum was immediately separated and frozen for subsequent cytokine assays. Patient inclusion criteria were age between 6 months and 5 years, body temperature ≥ 38.5 °C, and patients with conditions known or suspected to cause seizures without fever were systematically excluded as in our previous report [##REF##31937421##20##].\n</p>", "<p id=\"Par24\">Clinical data for familial FS history, previous FS attacks, and the duration and semiology of FS were obtained from the patients’ parents. Family history was regarded as positive when FS occurred in first-degree relatives. Laboratory findings, including complete blood counts, blood chemistry, and C-reactive protein levels, were checked at the time of seizure. Control samples were collected from children with febrile illness, without convulsion. Control groups were matched for age and temperature criteria and had no convulsions during febrile illness and no known history of previous FS. Thirty controls were included in the final analysis. Control blood serum was collected and frozen as described above. A diagnosis of FS was determined according to the International Classification of Diseases; Ninth Revision (ICD-9) codes (ICD-9 780.31, 780.32). All patients were followed for more than 1 year.</p>", "<p id=\"Par25\">The study was approved by the Ethics Committee of Foshan Women and Children Hospital (Approved number: FSFY-MEC-2018–016). All experiments and methods were performed in accordance with the relevant guidelines and regulations. Informed consent was obtained from the patients’ legal guardians.</p>", "<title>Cytokine measurement</title>", "<p id=\"Par26\">Four millilitres of blood were taken from the peripheral vessels of children in all the groups, and serum was obtained by centrifugation at 4000 rpm for 5 min at 4 °C. The serum was then added to acid-washed tubes and stored in a refrigerator at -80 °C until assay. Serum levels of HMGB1, NLRP3, caspase-1, and proinflammatory cytokines, including, IL-1β, IL-6, and TNF-α, were examined in FS patients and febrile controls using commercial enzyme-linked immunosorbent assay kits according to the manufacturer’s instructions (Cusabio Biotech, Wuhan, China).</p>", "<title>Statistical analysis</title>", "<p id=\"Par27\">Statistical analyses were performed using SPSS Statistics 19.0 for Windows (SPSS Inc., Chicago, IL, USA). The chi-square test or t test was used for the comparison of clinical characteristics between FS patients and the controls. The Mann‒Whitney <italic>U</italic> test was used to compare serum cytokine levels and laboratory findings between FS patients and controls. Spearman’s rank correlation coefficient was calculated to detect significant correlations between cytokine levels. GraphPad Prism v.7.0 (GraphPad Software Inc., San Diego, CA, USA) was used to perform the above tests. Values are expressed as means. Statistical significance was defined as <italic>P</italic> &lt; 0.05.</p>" ]
[ "<title>Results</title>", "<p id=\"Par28\">Table ##TAB##0##1## shows the comparison of the selected patients’ clinical data. Thirty children with FS and 30 age matched control children with febrile illness without convulsion were included in this study. The mean age was 22.67 ± 11.08 months in the FS group and 28.33 ± 16.85 months in the febrile control group. FS was more prevalent in boys than in girls (66.7% vs. 33.3%, respectively). All patients had their first FS attack and 73.3% (22/30) of patients had a duration of seizure &lt; 5 min and a single seizure. There were no statistically significant differences between the two groups with respect to sex, age, severity of temperature, C-reactive protein levels, leukocytes or type of febrile disease (<italic>p</italic> &gt; 0.05).</p>", "<p id=\"Par29\">When we compared the FS group with the febrile control group, the serum levels of HMGB1 (Fig. ##FIG##0##1##a, <italic>p</italic> = 0.023), NLRP3 (Fig. ##FIG##0##1##b, <italic>p</italic> = 0.016), caspase-1 (Fig. ##FIG##0##1##c, <italic>p</italic> = 0.001), IL-1β (Fig. ##FIG##0##1##d, <italic>p</italic> = 0.007), IL-6 (Fig. ##FIG##0##1##e, <italic>p</italic> = 0.023), and TNF-α (Fig. ##FIG##0##1##f, <italic>p</italic> = 0.026) were significantly higher in the FS group than in the febrile control group (Table ##TAB##1##2##). Additionally, HMGB1 serum levels were significantly correlated with NLRP3, caspase-1, and IL-1β (Fig. ##FIG##1##2##a, b, and c; <italic>r</italic> = 0.814, <italic>r </italic>= 0.652, and <italic>r</italic> = 0.675, respectively, all <italic>p</italic> &lt; 0.001). Caspase-1 serum levels were significantly correlated with IL-1β expression (Fig. ##FIG##1##2##D, <italic>r</italic> = 0.589; <italic>p</italic> &lt; 0.001). Serum IL-1β levels were significantly correlated with IL-6 and TNF-α levels (Fig. ##FIG##1##2##E and F; <italic>r</italic> = 0.564 and <italic>r</italic> = 0.668, respectively, both <italic>p</italic> &lt; 0.001).</p>", "<p id=\"Par30\">In this study, all the cases with FS were divided into simple FS according to the recorded seizure data (generalized and non-recurrent seizure within 24 h, and duration of seizure ≤ 15 min). Then we divided all the cases with FS into two groups: group1 (duration of seizure ≤ 5 min) and group2 (duration of seizure &gt; 5 min). There were no statistically significant differences between the groups with respect to level of HMGB1, NLRP3, Caspase-1, IL-1β, IL-6, and TNF-a (<italic>p</italic> &gt; 0.05) (Table ##TAB##2##3##).\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par31\">In the current study, we evaluated the expression of HMGB1 and the NLRP3 inflammasome alongside caspase-1 and IL-1β in FS patients compared with febrile controls. Despite their role in triggering the neuroinflammatory response, HMGB1 and the NLRP3 inflammasome have been poorly studied in FS. We confirmed the results of previous studies of increased HMGB1 and NLRP3 expression in FS [##REF##21989210##11##, ##REF##31937421##20##], reporting that increased expression of NLRP3 was associated with elevated plasma levels of HMGB1 in FS for the first time. Moreover, serum levels of other proinflammatory cytokines, including IL-1β, TNF-α, and IL-6 were significantly higher among patients with FS.</p>", "<p id=\"Par32\">Over the past two decades, the neuroinflammatory response and the release of proinflammatory,cytokines including HMGB1, IL-1β, TNF-α, and IL-6, have been implicated in the pathophysiology of FS [##REF##21989210##11##, ##REF##29428914##21##–##REF##12546429##24##]. Of these proinflammatory cytokines, HMGB1 and IL-1β are key initiators of neuroinflammation contributing not only to the generation of FS but also to epileptogenesis after prolonged FS [##REF##28879430##12##, ##REF##28176142##13##, ##UREF##2##25##–##REF##34548070##30##]. Experimental studies have shown that increased levels of HMGB1 and IL-1β contribute to chronic inflammation, neuronal excitotoxicity and a reduction in the seizure threshold [##REF##28879430##12##, ##REF##35837232##14##, ##REF##33221489##17##, ##REF##28222432##27##–##REF##24936172##29##, ##REF##21473909##31##–##UREF##3##33##]. Moreover, HMGB1 and IL-1β levels are increased in epileptogenic brain tissue [##REF##28176142##13##, ##REF##20348922##28##, ##REF##34548070##30##]. Interestingly, the levels of HMGB1 were positively correlated with the serum levels of IL-1β in a rat model and in children with TLE, while HMGB1 treatment of hippocampal neurons induced a significant increase in the levels of IL-1β [##REF##28176142##13##]. These data suggested that HMGB1-IL-1β network may contribute to the generation of seizures. In this study, we showed that patients with FS also display higher circulating (i.e. plasma) levels of HMGB1 and IL-1β. We also found that increased expression of HMGB1 was associated with elevated serum levels of IL-1β in peripheral blood after FS in children, indicating that there is a correlation between HMGB1 and IL-1β in children with FS. However, it was unclear how HMGB1 induces IL-1β expression.</p>", "<p id=\"Par33\">HMGB1 is a highly conserved, ubiquitously expressed protein that can serve as a representative DAMP [##UREF##3##33##]. DAMPs are pivotal for the activation of NLRP3 inflammasome pathways [##REF##27291964##34##]. Under normal circumstances, microglia and astrocytes express insufficient amounts and the NLRP3 inflammasome exists in an inactive form. When cells are subjected to specific stimuli, such as lipopolysaccharide (LPS), the NLRP3 inflammasome can be activated [##UREF##4##35##]. Assembly and activation of the NLRP3 inflammasome requires two functionally distinct steps: ‘priming’ and ‘activation’ [##REF##30046112##36##]. Recent studies have demonstrated that HMGB1 can stimulate increased expression of NLRP3 to a critical level necessary for inflammasome formation, thus causing the priming process of the NLRP3 inflammasome via the TLR4/NF-κB signaling pathway [##REF##25816800##37##], and causing sustained activation of the NLRP3 inflammasome [##REF##34666797##32##, ##REF##29643819##38##]. NLRP3 inflammasome-dependent caspase-1 activation is an important pathway related to IL-1β release [##REF##33385378##39##] and has been implicated in the pathophysiology of neurological diseases, including Parkinson’s disease, Alzheimer’s disease, multiple sclerosis, and epilepsy [##REF##27486046##40##–##REF##25516224##42##]. In this study, we demonstrated a significant increase in the expression of NLRP3 in peripheral blood after FS in children, and a significant correlation between caspase-1 expression and serum levels of IL-1β, as described in our previous study [##REF##31937421##20##]. As expected, we also observed a positive correlation between HMGB1 and NLRP3 expression, and a positive correlation between HMGB1 and caspase-1. Given that activated caspase-1 directly regulates the expression of mature IL-1β and positively correlates with activation of the NLRP3 inflammasome [##REF##31937421##20##], our results suggest that increased levels of peripheral HMGB1 possibly mediate IL-1β secretion through the activation of the NLRP3 inflammasome in children with FS, and HMGB1/NLRP3 inflammasome/caspase-1/IL-1β pathway may contribute to the generation of FS in children. Further studies are needed to verify the mechanism.</p>", "<p id=\"Par34\">In addition to IL-1β and HMGB1, inflammatory cytokines, including IL-6 and TNF-α, might also have facilitatory effects on the development of FS [##REF##34439695##43##]. IL-1β can bind to IL-1 receptor type 1 (IL-1R1), a Toll receptor family member, and induce the transcription of various genes that encode several downstream mediators of inflammation, including TNF-α and IL-6, via an NF-κB-related pathway [##REF##21473909##31##, ##REF##18952671##44##]. In this study, we found that IL-6 and TNF-α serum levels were significantly higher in FS patients than in febrile children without seizures, and IL-6 and TNF-α levels positively correlated with the serum levels of IL-1β in children with FS. These observations, together with experimental animal studies in which transgenic mice overexpressing high amounts of IL-6 or TNF-α in astrocytes were reported to have increased seizure susceptibility [##REF##19476542##45##–##REF##12836160##48##], support the possibility that IL-1β is a pluripotent proinflammatory cytokine and the key interleukin involved in FS pathogenesis.</p>", "<p id=\"Par35\">The current study has several limitations. First, the limited number of samples weakens the strength of this study. Second, levels of the HMGB1, NLRP3, Caspase-1 and the proinflammatory cytokines were not measured in the cerebrospinal fluid, which would make a significant contribution to the evaluation. Last, the follow-up time was relatively short, no valuable data from this follow-up were obtained. Long-term follow-up data could provide valuable insights into the prognosis and outcomes of children with FS.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par36\">In conclusion, our present study showed that HMGB1 is up-regulated in peripheral serum of FS patients, which may be responsible, at least in part, for the increased expression of NLRP3 and caspase-1. Increased expression of caspase-1 was significantly associated with elevated serum levels of IL-1β. Our data suggest that increased levels of peripheral HMGB1 possibly mediate IL-1β secretion through the activation of the NLRP3 inflammasome in peripheral blood after FS. Thus, both HMGB1 and the NLRP3 inflammasome might be potential targets for preventing or limiting FS.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">High mobility group box-1 (HMGB1) is an endogenous danger signal that mediates activation of the innate immune response including NLR pyrin domain containing 3 (NLRP3) inflammasome activation and proinflammatory cytokine release. Although HMGB1 and NLRP3 have been implicated in the pathophysiology of seizures, the correlation between HMGB1 and NLRP3 expression has not been determined in children with febrile seizures (FS). To explore the relationship between extra-cellular HMGB1 and NLRP3 in children with FS, we analyzed serum HMGB1, NLRP3, caspase-1, and proinflammatory cytokines in patients with FS.</p>", "<title>Methods</title>", "<p id=\"Par2\">Thirty children with FS and thirty age-matched febrile controls were included in this study. Blood was obtained from the children with FS within 1 h of the time of the seizure; subsequently, the serum contents of HMGB1, NLRP3, caspase-1, interleukin (IL)-1β, interleukin (IL)-6, and tumour necrosis factor-α (TNF-α) were determined by enzyme-linked immunosorbent assay. The Mann‒Whitney <italic>U</italic> test was used to compare serum cytokine levels between FS patients and controls. Spearman’s rank correlation coefficient was calculated to detect significant correlations between cytokine levels.</p>", "<title>Results</title>", "<p id=\"Par3\">Serum levels of HMGB1, NLRP3, caspase-1, IL-1β, IL-6, and TNF-α were significantly higher in FS patients than in febrile controls (<italic>p</italic> &lt; 0.05). Serum levels of HMGB1 were significantly correlated with levels of NLRP3 and caspase-1 (both, <italic>p</italic> &lt; 0.05). Serum levels of caspase-1 were significantly correlated with levels of IL-1β (<italic>p</italic> &lt; 0.05). Serum levels of IL-1β were significantly correlated with levels of IL-6 and TNF-α (<italic>p</italic> &lt; 0.05).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">HMGB1 is up-regulated in the peripheral serum of FS patients, which may be responsible, at least in part, for the increased expression of NLRP3 and Caspase-1. Increased expression of caspase-1 was significantly associated with elevated serum levels of IL-1β. Given that activated Caspase-1 directly regulates the expression of mature IL-1β and positively correlates with activation of the NLRP3 inflammasome, our data suggest that increased levels of peripheral HMGB1 possibly mediate IL-1β secretion through the activation of the NLRP3 inflammasome in children with FS. Thus, both HMGB1 and NLRP3 might be potential targets for preventing or limiting FS.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>We are deeply grateful to the patients and clinicians who participated in this work.</p>", "<title>Authors’ contributions</title>", "<p>Zhi-Gang Liu contributed to the conception of the study. Xing-Guang Ye and Feng-Zhi She contributed to the interpretation of clinical data and drafting of the figures and wrote the main manuscript text. Dong-Ni Yu, Li-Qian Wu, and Yan Tang examined the patient and participated in drafting of the manuscript. Ben-Ze Wu, Shi-Wei Dong, Jie-Min Dai, and Xing Zhou contributed to the collection and analysis of clinical data. Zhi-Gang Liu provided critical review and substantially revised the manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by Foshan Science and Technology Bureau (Grant Nos. 2020001003419).</p>", "<title>Availability of data and materials</title>", "<p>The datasets for this article are not publicly available due to concerns regarding participant/patient anonymity. Requests to access the datasets should be directed to the corresponding author.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par37\">The research related to human use has been complied with all the relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the ethics committee of Foshan Women and Children Hospital (Approve number: FSFY-MEC-2018–016).</p>", "<p id=\"Par38\">Written informed consent to participate in this study was obtained from all the study participants and their legal guardian involved in the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par39\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par40\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Comparison of serum levels of HMGB1 (<bold>a</bold>), NLRP3 (<bold>b</bold>), caspase-1 (<bold>c</bold>), IL-1β (<bold>d</bold>), IL-6 (<bold>e</bold>), and TNF-α (<bold>f</bold>) between the febrile seizure group and the control group. The median (interquartile range) values are indicated by three parallel lines. Analysis of serum cytokine levels between the two groups was performed by the Mann‒Whitney U test. HMGB1, NLRP3, caspase-1, IL-1β, IL-6, and TNF-α levels were significantly higher in the febrile seizure group than in the control group (<italic>p</italic> &lt; 0.05 indicates a significant difference)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Correlation between serum cytokine levels in the febrile seizure group. (<bold>a-f</bold>) Correlation between serum levels of NLRP3 and HMGB1 (<bold>a</bold>), caspase-1 and HMGB1 (<bold>b</bold>), IL-1β and HMGB1 (<bold>c</bold>), IL-1β and caspase-1 (<bold>d</bold>), IL-6 and IL-1β (<bold>e</bold>), and TNF-α and IL-1β (<bold>f</bold>) in children with febrile seizure. HMGB1 levels were significantly correlated with NLRP3, caspase-1, and IL-1β levels (all, <italic>p</italic> &lt; 0.05, r = 0.814, <italic>r</italic> = 0.652, and <italic>r</italic> = 0.675, respectively). Caspase-1 levels were significantly correlated with IL-1β levels (<italic>p</italic> &lt; 0.05, <italic>r</italic> = 0.589). IL-1β levels were significantly correlated with IL-6 and TNF-α levels (both, <italic>p</italic> &lt; 0.05, <italic>r</italic> = 0.564 and 0.668, respectively)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Clinical findings of febrile seizures and control children</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Febrile seizures<break/>(<italic>N</italic> = 30)</th><th align=\"left\">Febrile controls<break/>(<italic>N</italic> = 30)</th><th align=\"left\"><italic>P</italic> Value</th></tr></thead><tbody><tr><td align=\"left\">Male/Female</td><td align=\"left\">20/10</td><td align=\"left\">16/14</td><td align=\"left\">0.292</td></tr><tr><td align=\"left\">Age (months)<sup>a</sup></td><td align=\"left\">22.67 ± 11.08</td><td align=\"left\">28.33 ± 16.85</td><td align=\"left\">0.129</td></tr><tr><td align=\"left\">Severity of temperature (℃)<sup>a</sup></td><td align=\"left\">39.16 ± 0.50</td><td align=\"left\">38.95 ± 0.61</td><td align=\"left\">0.216</td></tr><tr><td align=\"left\">C-reactive protein (mg/l)<sup>a</sup></td><td align=\"left\">5.50 ± 8.85</td><td align=\"left\">6.57 ± 10.58</td><td align=\"left\">0.673</td></tr><tr><td align=\"left\">Leukocytes (× 10<sup>9</sup>/l)</td><td align=\"left\">10.65 ± 4.34</td><td align=\"left\">10.53 ± 6.57</td><td align=\"left\">0.936</td></tr><tr><td align=\"left\">Etiology of infection (viral/bacterial)</td><td align=\"left\">21/9</td><td align=\"left\">24/6</td><td align=\"left\">0.371</td></tr><tr><td align=\"left\" colspan=\"4\">Duration of seizure</td></tr><tr><td align=\"left\"> &lt; 5 min</td><td align=\"left\">22</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 5-15 min</td><td align=\"left\">8</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> &gt; 15 min</td><td align=\"left\">0</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\" colspan=\"4\">Number of seizure</td></tr><tr><td align=\"left\"> 1</td><td align=\"left\">22</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 2</td><td align=\"left\">6</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> 3</td><td align=\"left\">2</td><td align=\"left\"/><td align=\"left\"/></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Comparison of HMGB1, NLRP3, Capase-1, and cytokine levels between the febrile seizures group and febrile control group</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">FS group<sup>a</sup> (<italic>N</italic> = 30)</th><th align=\"left\">Control group<sup>a</sup> (<italic>N</italic> = 30)</th><th align=\"left\"><italic>P-</italic>Value</th></tr></thead><tbody><tr><td align=\"left\">HMGB1 (pg/ml)</td><td align=\"left\">399.84 (329.69–626.52)</td><td align=\"left\">304.56 (240.86–495.16)</td><td align=\"left\">0.023*</td></tr><tr><td align=\"left\">NLRP3 (pg/ml)</td><td align=\"left\">2330.15 (1956.64–3179.77)</td><td align=\"left\">1666.14 (1302.69–3231.45)</td><td align=\"left\">0.016*</td></tr><tr><td align=\"left\">Capase-1 (pg/ml)</td><td align=\"left\">2550.69 (1845.07–3560.79)</td><td align=\"left\">1504.81 (1134.57–2909.78)</td><td align=\"left\">0.001*</td></tr><tr><td align=\"left\">IL-1β (pg/ml)</td><td align=\"left\">87.90 (75.58–139.83)</td><td align=\"left\">65.31 (45.66–142.17)</td><td align=\"left\">0.007*</td></tr><tr><td align=\"left\">IL-6 (pg/ml)</td><td align=\"left\">40.87 (27.15–53.46)</td><td align=\"left\">25.06 (16.94–42.56)</td><td align=\"left\">0.003*</td></tr><tr><td align=\"left\">TNF-α (pg/ml)</td><td align=\"left\">181.05 (146.58–239.76)</td><td align=\"left\">134.39 (87.23–213.34)</td><td align=\"left\">0.026*</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Comparison of HMGB1, NLRP3, Capase-1, and cytokine levels in patients with different duration of seizure</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">duration of seizure ≤ 5 min<break/>(<italic>N</italic> = 22)<sup>a</sup></th><th align=\"left\">duration of seizure &gt; 5minnutes<break/>(<italic>N</italic> = 8)<sup>a</sup></th><th align=\"left\"><italic>P Value</italic></th></tr></thead><tbody><tr><td align=\"left\">HMGB1 (pg/ml)</td><td align=\"left\">411.9 (338.0–626.5)</td><td align=\"left\">357.8 (325.1–656.2)</td><td align=\"left\">0.798</td></tr><tr><td align=\"left\">NLRP3 (pg/ml)</td><td align=\"left\">2365 (1964–3187)</td><td align=\"left\">2071 (1625–3128)</td><td align=\"left\">0.440</td></tr><tr><td align=\"left\">Capase-1 (pg/ml)</td><td align=\"left\">2551 (1862–3571)</td><td align=\"left\">2498 (1801–3481)</td><td align=\"left\">0.977</td></tr><tr><td align=\"left\">IL-1β (pg/ml)</td><td align=\"left\">82.55 (73.92–131.97)</td><td align=\"left\">121.5 (76.4–164.7)</td><td align=\"left\">0.238</td></tr><tr><td align=\"left\">IL-6 (pg/ml)</td><td align=\"left\">40.87 (26.90–55.57)</td><td align=\"left\">37.72 (27.53–52.55)</td><td align=\"left\">0.842</td></tr><tr><td align=\"left\">TNF-α (pg/ml)</td><td align=\"left\">181.1 (146.6–284.4)</td><td align=\"left\">191.6 (135.9–234.4)</td><td align=\"left\">0.842</td></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[]
[ "<table-wrap-foot><p><sup>a</sup>Mean ± Standard deviation</p></table-wrap-foot>", "<table-wrap-foot><p><italic>FS</italic> febrile seizure, <italic>HMGB1</italic> high mobility group box-1, <italic>IL-1β</italic> interleukin-1beta, <italic>N</italic> number, <italic>TNF-α</italic> tumor necrosis factor α. The <italic>P</italic>-value is for Mann–Whitney U-test</p><p><sup>a</sup>Median (interquartile range)</p><p><sup><bold>*</bold></sup>Indicates a significant difference</p></table-wrap-foot>", "<table-wrap-foot><p><italic>FS</italic> febrile seizure, <italic>HMGB1</italic> high mobility group box-1, <italic>IL-1β</italic> interleukin-1beta, <italic>N</italic> number, <italic>TNF-α</italic> tumor necrosis factor α. The <italic>P</italic>-value is for Mann–Whitney U-test</p><p><sup>a</sup>Median (interquartile range)</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Xing-Guang Ye, Feng-Zhi She, Dong-Ni Yu contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12887_2024_4533_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12887_2024_4533_Fig2_HTML\" id=\"MO2\"/>" ]
[]
[{"label": ["6."], "surname": ["Dub\u00e9", "Brewster", "Baram"], "given-names": ["CM", "AL", "TZ"], "article-title": ["Febrile seizures: mechanisms and relationship to epilepsy"], "source": ["Brain Develop"], "year": ["2009"], "volume": ["31"], "fpage": ["366"], "lpage": ["371"], "pub-id": ["10.1016/j.braindev.2008.11.010"]}, {"label": ["8."], "surname": ["Kang", "Chen", "Zhang", "Hou", "Wu", "Cao"], "given-names": ["R", "R", "Q", "W", "S", "L"], "article-title": ["HMGB1 in health and disease"], "source": ["Mol Aspects Med"], "year": ["2014"], "volume": ["40"], "fpage": ["111"], "lpage": ["116"], "pub-id": ["10.1016/j.mam.2014.05.001"]}, {"label": ["25."], "surname": ["Feng", "Tang", "Chen", "Xu", "Wang", "Dai"], "given-names": ["B", "Y", "B", "C", "Y", "Y"], "article-title": ["Transient increase of interleukin-1\u03b2 after prolonged febrile seizures promotes adult epileptogenesis through long-lasting upregulating endocannabinoid signaling"], "source": ["Sci Rep"], "year": ["2016"], "volume": ["6"], "fpage": ["621931"]}, {"label": ["33."], "surname": ["Paudel", "Shaikh", "Chakraborti", "Kumari", "Aledo-Serrano", "Aleksovska"], "given-names": ["YN", "MF", "A", "Y", "\u00c1", "K"], "article-title": ["HMGB1: a common biomarker and potential target for TBI, neuroinflammation, epilepsy, and cognitive dysfunction"], "source": ["Front NeuroSci"], "year": ["2018"], "volume": ["12"], "fpage": ["12628"], "pub-id": ["10.3389/fnins.2018.00628"]}, {"label": ["35."], "surname": ["Church", "Savic", "McDermott"], "given-names": ["LD", "S", "MF"], "article-title": ["Long term management of patients with cryopyrin-associated periodic syndromes (CAPS): focus on rilonacept (IL-1 trap)"], "source": ["Biol Targets Ther"], "year": ["2008"], "volume": ["2"], "fpage": ["733"], "lpage": ["742"], "pub-id": ["10.2147/BTT.S3167"]}]
{ "acronym": [ "DAMPs", "FS", "HMGB1", "IL-1β", "IL-6", "LPS", "MAPKs", "NLRP3", "NF-κB", "PRRs", "RAGE", "TNF-α", "TLE", "TLR" ], "definition": [ "Damage associated molecular patterns", "Febrile seizures", "High mobility group box-1", "Interleukin-1β", "Interleukin-6", "Lipopolysaccharide", "Mitogen-activated protein kinases", "NLR pyrin domain containing 3", "Nuclear factor kappa B", "Pattern recognition receptors", "Receptor for advanced glycation end products", "Tumor necrosis factor-α", "Temporal lobe epilepsy", "Toll-like receptor" ] }
48
CC BY
no
2024-01-14 23:43:47
BMC Pediatr. 2024 Jan 13; 24:44
oa_package/cb/49/PMC10787487.tar.gz
PMC10787488
38216934
[ "<title>Background</title>", "<p id=\"Par24\">Cardiac arrhythmias encompass a wide range of heart rhythm and heart rate disorders [##UREF##0##1##]. Clinical presentation can range from asymptomatic to life-threatening, such as sudden cardiac arrest [##UREF##0##1##]. Arrhythmias can be managed with antiarrhythmic medication or various electrophysiological (EP) procedures, such as ablation or implantation of pacemakers or defibrillators [##UREF##1##2##]. The most common type of arrhythmia is atrial fibrillation (AF) [##REF##16908781##3##], which is linked to higher risks of stroke, heart failure, dementia, and death [##REF##1866765##4##–##REF##9737513##9##]. This significantly impacts healthcare costs owing to hospitalizations and loss of productivity [##REF##22689930##10##].</p>", "<p id=\"Par25\">The prevalence of AF in China is estimated to be 1.6% and increases with age [##REF##35800039##11##]. This poses a formidable challenge to China’s healthcare system owing to its aging population [##REF##26304837##12##]. While the ablation treatment rate among Chinese AF patients is unclear, it is reasonable to assume that over 176,000 ablation procedures may be needed based on the US ablation rate of 0.79% in 2005 [##REF##19753578##13##].</p>", "<p id=\"Par26\">Furthermore, overcrowding at tertiary public hospitals is a major problem in China [##REF##30258653##14##]. While economic growth slows, rapid expansion of hospital operations and infrastructure is not a viable option to meet the demand for EP treatments [##UREF##3##15##]. Thus, decision-makers must utilize limited medical resources to deliver healthcare services more efficiently [##UREF##3##15##] in order to meet this growing demand.</p>", "<p id=\"Par27\">To this end, China’s National Health Commission has issued guidelines to improve public hospital operational management and healthcare delivery [##UREF##4##16##]. The Commission not only recommends optimizing resource allocation and processes but also emphasizes data collection and analysis, as well as improving the quality of decision-making [##UREF##4##16##]. Public hospitals are urged to collect and manage operational data for analysis, establish an analytical decision-making framework, and implement analysis results [##UREF##4##16##].</p>", "<p id=\"Par28\">Optimizing EP service delivery efficiency is a complex, multidimensional problem involving factors ranging from patient flow management to novel technology adoption. Discrete event simulation (DES) is an operational research tool that helps decision-makers assess different management strategies, enabling them to evaluate not only the performance of current healthcare delivery systems but also that of hypothetical scenarios [##UREF##5##17##]. This allows them to choose between different approaches of healthcare delivery to prioritize and pursue without undesirably impacting current systems [##UREF##5##17##].</p>", "<p id=\"Par29\">This study established a generalized DES model of an inpatient EP treatment process, which can be applied across tertiary hospitals in China. The model examines how cardiology departments under different resource constraints can serve more EP patients by improving the efficiency of each phase of the healthcare delivery process, including pre-operative preparation, operative time, or post-operative recovery. This enables hospital decision-makers to clarify which phases of the EP care delivery process to prioritize in different situations in order to better meet the demand for EP treatment.</p>" ]
[ "<title>Methods</title>", "<title>Model setting and perspective</title>", "<p id=\"Par30\">We constructed a model to simulate the inpatient journey of individual EP patients from admission to discharge in the cardiology department of a tertiary hospital in China, using the “simmer” package [##UREF##6##18##] in R [##UREF##7##19##]. To build a generalized model applicable to different hospitals in China, clinicians from two large tertiary hospitals were consulted. We established a preliminary design for the model based on the inpatient management process of the Cardiology Department of the First Affiliated Hospital of Zhejiang University (FAHZU). We further examined the patient care delivery flow at Shanghai General Hospital’s Cardiology Department, fine-tuning the preliminary design. The final model abstracted and generalized a common inpatient care pathway without focusing on implementation details specific to an individual hospital.</p>", "<p id=\"Par31\">These two cardiology departments have a number of catheter laboratories, some of which are dedicated electrophysiology laboratories (EP labs) that are prioritized for EP procedures. They can only be used for other cardiology procedures after all EP procedures scheduled for that day are completed.</p>", "<p id=\"Par32\">The primary study population is EP patients who pass through the EP labs (i.e., the target EP patients, TEP patients). The model explicitly tracks the pre-operative phase, operation, and post-operative stay of these patients. The other two patient types include catheter lab EP patients (CLEP patients) who receive their procedure in the catheter labs and non-EP cardiology patients (NEP patients). Both CLEP and NEP patients compete with TEP patients for hospitalization resources, but not for resources used in EP lab operations. Therefore, only the hospitalization stays of CLEP and NEP patients were included in the model.</p>", "<title>Model structure</title>", "<title>Arrival process</title>", "<p id=\"Par33\">The model generates three patient types: TEP, CLEP, and NEP. Unlike patients receiving care in outpatient facilities or emergency rooms, inpatient visits for elective procedures do not arrive randomly at the hospital. Patients in this model are scheduled to arrive at the same time daily (one hour before working hours). The daily arrivals of each type of patient was randomly generated.</p>", "<title>Resources</title>", "<p id=\"Par34\">The model considers three resource types: cardiology ward beds, electrophysiologists, and EP labs. All three types of patients share bed resources, but only TEP patients require electrophysiologists and EP labs. The schedules for electrophysiologists and EP labs are managed by hospital staff.</p>", "<title>Inpatient process</title>", "<p id=\"Par35\">The process for TEP patients is shown in Fig. ##FIG##0##1##. Upon arrival, the TEP patient is assigned to one of several EP procedures and admitted if a ward bed is available. The patient’s stay consists of three phases: pre-operative stay, EP procedure, and post-operative stay. Once the patient’s pre-operative phase is complete, they are assigned to an electrophysiologist and enter the queue for EP lab procedures the next day. If the EP labs are not open the next day, the patient waits until the subsequent workday. Once the patient’s assigned electrophysiologist and an EP lab become available during working hours, the patient enters the EP lab to undergo the procedure. Once a procedure is started, it will continue until completion, regardless of the pre-defined working hours. However, no new procedures are allowed after working hours. Upon procedure completion, the electrophysiologist leaves the EP lab and the patient returns to the ward. The catheter lab becomes available after cleanup and preparation for the next procedure. After post-operative recovery, the patient is discharged.</p>", "<p id=\"Par36\">\n\n</p>", "<p id=\"Par37\">For CLEP and NEP patients, the process is simpler. Patients are admitted if ward beds are available and discharged after their length of stay is reached.</p>", "<title>Model inputs</title>", "<p id=\"Par38\">Model inputs were based on actual data collected between May 1–June 30, 2022 from FAHZU’s Cardiology Department. Admission and discharge dates were recorded for TEP, CLEP, and NEP patients. Inputs related to the number of admissions per day and length of stay were based on patients admitted between May 1–June 25, as both admission and discharge dates were available for these patients. In addition, for TEP patients, procedure dates, procedure types, procedure start and end times, and assigned electrophysiologists were also collected.</p>", "<title>Simulation</title>", "<p id=\"Par39\">The daily arrival of TEP, CLEP, and NEP patients is modeled according to a negative binomial distribution. The procedure type for TEP patients is randomly drawn according to the proportions of the different EP procedures. Their electrophysiologist is randomly assigned based on the day of the week of their procedure and the average allocation of patients between different electrophysiologists on that day.</p>", "<p id=\"Par40\">Processing times of TEP patients are determined by procedure type. The length of stay and days of pre-operative stay are randomly generated from a truncated lognormal distribution and rounded to integers. The post-operative stay is the difference between the length of stay and the pre-operative stay. The operative time, in minutes, is also modeled by a truncated lognormal distribution.</p>", "<p id=\"Par41\">Following ISPOR guidelines, the simulation first runs for ten days with CLEP and NEP patients as a “warm up” period [##UREF##8##20##]. The TEP patient flow is generated from day 11. The simulation is then run for an additional 61 days, corresponding to the observation period of the actual data. Each scenario was simulated 1000 times.</p>", "<title>Validation</title>", "<p id=\"Par42\">The simulated total number of discharged TEP patients per replication and the simulated daily discharges were compared against actual data. Means and standard deviations are reported. The simulated and real daily discharges were also compared using the Mann-Whitney U test.</p>", "<title>Scenario analyses</title>", "<p id=\"Par43\">There are two significant capacity-limiting scenarios (CLS) for hospital cardiology departments in China. First, cardiology departments often must manage inpatient beds as a shared resource. Therefore, in this CLS, the inpatient ward is fully occupied before the EP labs reach their capacity. Second, EP lab capacity may be overwhelmed by demand. The second CLS usually occurs in hospitals with insufficient EP labs compared to ward beds.</p>", "<p id=\"Par44\">Based on data from FAHZU, we performed scenario analyses to first investigate the patient throughput capacities under both CLSs and then the potential throughput when different phases of the inpatient process were optimized. Since optimizing all procedure types simultaneously in the real world is difficult, AF ablations (for paroxysmal and persistent AF) were selected for scenario analysis, as these were the most common procedures accounting for almost 30% of TEP patients. Patient throughput was measured as the total number of discharged TEP patients. For each CLS, we report the mean and standard deviation of the results from 1000 simulations.</p>", "<p id=\"Par45\">First, we examined the scenarios with fully occupied cardiology ward beds. Because input from FAHZU had higher bed utilization than that of EP labs, changing the number of resources was not necessary. We increased the number of TEP patients arriving daily so that they would fully occupy any available beds remaining after the other two types of patients were admitted. This was considered the base case scenario under the condition of a fully occupied cardiology ward. Under this scenario, we reduced total length of stay of paroxysmal and persistent AF ablation patients by 10%, 20%, and 30% as the test cases. For each level of reduction, we calculated the expected difference in days and applied this reduction to different phases: the pre-operative stay (the minimum pre-operative stay remained 1 day); the post-operative stay; and both the pre-operative and post-operative stays reduced proportionally (the minimum pre-operative stay remained 1 day). For comprehensiveness, we also examined a scenario where operative times of paroxysmal and persistent AF ablation were reduced by 10%, 20%, and 30%, although this was expected to result in minimal change while EP labs were not at capacity.</p>", "<p id=\"Par46\">We then analyzed scenarios with fully occupied EP labs. In addition to adjusting the patient flow as described above, the number of ward beds and EP lab resources were adjusted. This was the base case scenario under the condition of fully occupied EP labs. For comparison, we generated scenarios with reduced length of stay and reduced operative time in the same manner as above.</p>" ]
[ "<title>Results</title>", "<title>Model inputs</title>", "<p id=\"Par47\">FAHZU’s cardiology department has 87 ward beds, two EP labs, and eight electrophysiologists. Two EP labs are available every workday (Monday to Friday) from 8:00 AM to 10:00 PM. Two electrophysiologists are on duty during the working hours of each workday. Average patient allocation between the two electrophysiologists on duty each day is shown in Table ##TAB##0##1##.</p>", "<p id=\"Par48\">\n\n</p>", "<p id=\"Par49\">The number of daily arrivals by patient type is shown in Table ##TAB##1##2##. Inputs relating to processing times for each phase in the TEP patient’s journey are summarized in Tables.</p>", "<p id=\"Par50\">\n\n</p>", "<p id=\"Par51\">Table ##TAB##2##3##, stratified by EP procedure type. Average length of stay for CLEP and NEP patients was 5.427 (SD 4.261) and 3.758 (SD 2.718), respectively.</p>", "<p id=\"Par52\">\n\n</p>", "<title>Model validation</title>", "<p id=\"Par53\">The simulated total number of TEP patients discharged per replication was 137.167 (SD 17.856), compared to 137 in the actual data. The distribution of the simulated results is shown in Fig. ##FIG##1##2##A.</p>", "<p id=\"Par54\">\n\n</p>", "<p id=\"Par55\">The simulated daily number of discharges was 2.249 (SD 2.455), compared with the actual figure of 2.245 (SD 2.364). Distribution of the simulated results, compared with that of actual results, is shown in Fig. ##FIG##2##3##. The Mann-Whitney U test showed no significant difference between the locations of the two distributions (<italic>p</italic> = 0.747).</p>", "<p id=\"Par56\">\n\n</p>", "<title>Scenario analysis</title>", "<p id=\"Par57\">In the base case scenario with fully occupied cardiology wards, the total number of discharges per replication was 220.612 (SD 44.110), the distribution of which is shown in Fig. ##FIG##1##2##B. The results of this group of scenarios are presented in Table ##TAB##3##4##; Fig. ##FIG##3##4##. Paroxysmal and persistent AF ablation patients, whose processing times are adjusted in these scenarios, comprise approximately 30% of all patients. Reducing their length of stay increased the total number of discharges by 1–7%, regardless of which phase the reduction was applied to. Reducing operative time did not have any apparent effect.</p>", "<p id=\"Par58\">\n\n</p>", "<p id=\"Par59\">\n\n</p>", "<p id=\"Par60\">To simulate conditions with fully occupied EP labs, the number of ward beds was increased to 110 and the number of EP labs was decreased to one. The results of these scenarios are shown in Table ##TAB##4##5##; Fig. ##FIG##4##5##. Average total discharges was 271.634 (SD 10.379) in the base case scenario. The distribution is shown in Fig. ##FIG##1##2##C. Reducing operative time increased the total number of discharges by 3–12%. A reduction in the length of stay did not affect the total number of discharges.</p>", "<p id=\"Par61\">\n\n</p>", "<p id=\"Par62\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par63\">In this study, we developed and validated a generalizable DES model based on inpatient EP care delivery processes from two large tertiary hospitals in China. We used the model to simulate hospitalization stays of EP patients in scenarios with fully occupied ward beds and EP labs, and evaluated the effects of accelerating different phases of the delivery process under the two conditions. The model can support hospital decision-makers to identify which phase of the EP care delivery process to prioritize under different resource constraints in order to best satisfy demand for EP treatment. Decision-makers can then consider different methods of EP care delivery to target the relevant phase.</p>", "<p id=\"Par64\">Under the condition of a fully occupied ward, reducing operative time had little to no effect, as this was not the bottleneck. On the other hand, reducing length of stay by 10–30% in paroxysmal and persistent AF ablation patients, which account for approximately 30% of all patients, increased total discharges by 1–7%. There was no difference whether the reduction was applied in the pre-operative or post-operative phase. However, it is imperative that reduction in hospitalization time does not compromise the quality of care. This goal can be achieved by integrating evidence-supported new technology or practices. For instance, the prevailing practice in China involves a pre-operative transesophageal echocardiogram (TEE), typically necessitating a hospital stay of 2 to 3 days prior to the procedure [##REF##36301182##21##]. Intracardiac echocardiography (ICE) has been demonstrated as a safe and effective alternative to TEE, conducted during the procedure, thereby requiring only a 0–1 day pre-operative stay [##REF##36301182##21##]. Pertaining to the post-operative phase, proactive prevention of complications contributes to reducing the length of stay while maintaining the quality of care [##REF##29478273##22##]. This can be realized through careful management of patients with pre-existing medical conditions [##REF##32477758##23##] and the accumulation of physician experience [##REF##33650749##24##]. However, in the context of large tertiary hospitals in China, as in our study, the complication rate is generally well managed, leaving limited room for further improvement. In addition, the post-operative stay in China exceeds that of the US, where the standard practice leans towards an overnight stay [##REF##32435349##25##], or even outpatient procedures in some instances [##REF##29478273##22##]. This disparity may be attributed to the US’s adoption of diagnostic-related groups (DRGs) [##REF##19107594##26##]. It is expected that the length of stay in China may decrease as the DRG payment system gains traction in the Chinese healthcare landscape [##REF##34306429##27##].</p>", "<p id=\"Par65\">When EP labs were fully occupied, reducing operative time by 10–30% in AF ablation patients led to a 3–12% increase in total discharges This improvement is made possible by several technological innovations that can reduce AF ablation operative times. The key to AF ablation is achieving pulmonary vein isolation [##REF##27567408##28##]. Conventional point-to-point radiofrequency (RF) ablation involves creating multiple lesions, which may leave gaps in between [##REF##25053659##29##] and drive long operative times [##REF##26260733##30##]. Better navigation techniques, such as remote magnetic navigation-guided RF ablation, may reduce operative times [##REF##31139295##31##]. The Q-FFICIENCY trial showed that very high-power, short-duration ablation using contact force-sensing RF catheters can reduce operative times by almost 50% [##REF##34381869##32##], which is higher than the 30% reduction used in our analyses. According to the model, this reduction level would result in 330 total discharges (21% increase) using the specifications described previously.</p>", "<p id=\"Par66\">In simulations of fully utilized EP labs, reducing operative time led to a more significant increase in discharges compared to reducing the length of stay in scenarios with fully occupied ward beds. This discrepancy may stem from the fact that the existing length of stay is already brief, allowing limited room for reduction, while there is more potential for improving EP lab efficiency. Our real-world data revealed that, over a two-month period, on 25 out of 40 working days, the working hours in the EP labs exceeded 8 h, with 29 days surpassing 7 h. This underscores the high utilization rate of the EP labs on a substantial number of days. However, it’s essential to note that reducing operative time does not necessarily ensure improved throughput, given the inherent variability in operational processes, including fluctuating patient flows. This variability in real-world settings emphasizes the need for adaptable and versatile modeling approaches. Our model aims not only to analyze the specific hospital from which the data originated but also to demonstrate its broader applicability as a decision-making tool for hospital managers. Recognizing the variability in hospital conditions, we tested two scenarios reflecting significant operational challenges, particularly relevant in China. These scenarios illustrate how our model can adapt to different settings, providing insights into potential operational improvements. The high utilization of the EP labs observed in our data exemplifies one of these challenges, highlighting the necessity for contextually informed strategies to enhance hospital efficiency.</p>", "<p id=\"Par67\">While US practices and technologies provide useful insights as described above, it is crucial to tailor these approaches to align with China’s unique healthcare landscape. For instance, the adaptation from the DRG system to the diagnosis-intervention packet (DIP) system in China arose from challenges faced during a DRG pilot program [##REF##36103333##33##]. The DIP system offered a less technically demanding and more scalable approach [##REF##36103333##33##]. Since 2020, China has been piloting a dual-track arrangement with both DRGs and DIP, acknowledging the diverse regional capacities of local health systems [##REF##36103333##33##]. This initiative underlines the importance of contextualizing global practices to improve resource allocation and potentially reduce hospital stay lengths without compromising care quality, aligning with the overarching objective of enhancing efficiency in healthcare delivery.</p>", "<p id=\"Par68\">A previous study by Kowalski et al. investigated the economic value of reducing AF ablation operative times using DES [##REF##26984931##34##]. However, this study differed from ours conducted in China. Kowalski et al. did not include a hospitalization process [##REF##26984931##34##], which may have been a choice in the model design or because AF ablations in their study were day surgeries. In addition, ablation procedures were arranged in block schedules such that two ablations were performed in an EP lab each day, with the possibility of one additional procedure [##REF##26984931##34##], placing a hard limit on the number of procedures per day. In our model, accounting for competition of ward beds was important because of the almost 100% utilization of hospital beds in large tertiary hospitals in China [##UREF##9##35##]. Furthermore, EP procedures in China do not follow a block schedule. Procedures can start as soon as the previous procedure is completed and the EP lab is ready. Therefore, there is more potential to increase the number of procedures by reducing operative time.</p>", "<p id=\"Par69\">Although the DES technique is increasingly used in healthcare research, applying it as a generalized decision-making tool is challenging. First, a DES model based on the detailed practices of one hospital may not be suitable for other settings. In addition, employing a DES requires a large amount of data, and more detailed data increases cost and time [##UREF##10##36##]. Adapting a DES model to a new setting requires new data [##REF##30180848##37##], and new data is again required if the system undergoes a change [##UREF##11##38##]. Furthermore, the simulated results of specific actions may differ from actual implementation owing to human variation [##REF##30251549##39##].</p>", "<p id=\"Par70\">In complex systems such as healthcare, a decision-making tool may be more helpful to clarify generic activity patterns instead of focusing excessively on specific processes of one particular site [##UREF##11##38##]. Therefore, we summarized and abstracted the processes at two different hospitals to build a generalized DES model of the inpatient EP care delivery process. Lowering the complexity of the model would also greatly reduce the effort required to collect data and facilitate model updates if system changes are made. This model does not prescribe specific actions but instead identifies the bottleneck of the care delivery process. Knowing which phase of the process to prioritize, the decision-maker can consider several different options to improve the healthcare delivery process and use the model to understand the expected results of these options. Further, they can also select the most worthwhile option by considering the time and effort involved compared to the expected increase in total discharges.</p>", "<p id=\"Par71\">This study has several limitations. First, the generalizability of this model may be constrained as it was based on data from two tertiary hospitals collected over a span of two months. This model might not fully reflect the care delivery processes in other hospitals within China or in other countries. The input data may not account for potential seasonal or procedural variations. Additional research is needed to validate the applicability of the approach in more diverse settings. In addition, our approach involved testing scenarios where hospitalization time was reduced by a specified percentage. However, depending on the technology or practice applied to improve the workflow, not all patients may benefit; identifying the proportion of affected patients would yield a more robust analysis. Due to the absence of such data currently, we opted to test scenarios with varying degrees of hospitalization stay reduction to characterize the uncertainty surrounding this aspect. Furthermore, we did not include scenarios with reduced variability, although this may also impact total discharges. However, we tested several scenarios, and the changes were relatively minor. Moreover, reducing variability without changing the mean in practice is difficult, and therefore these scenarios were not included in the results. Finally, the distributions of the simulated number of discharges in some scenarios are quite wide, implying that even if the simulations are accurate, the implementation results would still be uncertain.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par72\">This study developed a generalized DES model to simulate an EP patient’s hospitalization and treatment at a tertiary hospital in China. Using this model, hospital decision-makers dealing with different resource constraints can identify which phase of the care delivery process to optimize in order to better meet demand for EP treatment. Simulations showed that if ward beds are fully occupied, reducing the length of stay of AF ablation patients by 10–30% resulted in a 1–7% increase in the total number of patients discharged. On the other hand, under the condition of fully occupied EP labs, reducing the operative time of AF ablation patients by 10–30% increased discharges by 3–12%.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The growing demand for electrophysiology (EP) treatment in China presents a challenge for current EP care delivery systems. This study constructed a discrete event simulation (DES) model of an inpatient EP care delivery process, simulating a generalized inpatient journey of EP patients from admission to discharge in the cardiology department of a tertiary hospital in China. The model shows how many more patients the system can serve under different resource constraints by optimizing various phases of the care delivery process.</p>", "<title>Methods</title>", "<p id=\"Par2\">Model inputs were based on and validated using real-world data, simulating the scheduling of limited resources among competing demands from different patient types. The patient stay consists of three stages, namely: the pre-operative stay, the EP procedure, and the post-operative stay. The model outcome was the total number of discharges during the simulation period. The scenario analysis presented in this paper covers two capacity-limiting scenarios (CLS): (1) fully occupied ward beds and (2) fully occupied electrophysiology laboratories (EP labs). Within each CLS, we investigated potential throughput when the length of stay or operative time was reduced by 10%, 20%, and 30%. The reductions were applied to patients with atrial fibrillation, the most common indication accounting for almost 30% of patients.</p>", "<title>Results</title>", "<p id=\"Par3\">Model validation showed simulation results approximated actual data (137.2 discharges calculated vs. 137 observed). With fully occupied wards, reducing pre- and/or post-operative stay time resulted in a 1–7% increased throughput. With fully occupied EP labs, reduced operative time increased throughput by 3–12%.</p>", "<title>Conclusions</title>", "<p id=\"Par4\">Model validation and scenario analyses demonstrated that the DES model reliably reflects the EP care delivery process. Simulations identified which phases of the process should be optimized under different resource constraints, and the expected increases in patients served.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>WL contributed to study design, data collection, analysis and interpretation of data, model validation, and manuscript writing and revision. SW contributed to study design, analysis and interpretation of data, model design, and manuscript writing and revision. LZ, FY, YZ, XX, FZ, ZF, and LS contributed to data collection, analysis and interpretation of data, and manuscript writing and revision. YH contributed to study design, analysis and interpretation of data, model design, and manuscript writing and revision. All authors have approved the submitted version.</p>", "<title>Funding</title>", "<p>This study was funded by Johnson &amp; Johnson Medical (Shanghai) Ltd. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for preparation.</p>", "<title>Data availability</title>", "<p>Data used in this study are available for research only. Data requests will be reviewed by the review committee of the First Affiliated Hospital of Zhejiang University.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par73\">This study was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital of Zhejiang University (reference number IIT20220102B) on March 25th, 2022. The Clinical Research Ethics Committee of the First Affiliated Hospital of Zhejiang University has waived the requirement for informed consent due to retrospective nature of the study. All methods were carried out in accordance with relevant guidelines and regulations.</p>", "<title>Consent for publication</title>", "<p id=\"Par74\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par75\">SW and YH have received research support from Johnson &amp; Johnson Medical (Shanghai) Ltd. The remaining authors have no competing interests to declare.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Model process</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Distributions of total TEP patients discharged per replication</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Model validation-distributions of real and simulated daily discharges</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Boxplots of total discharges per replication with fully occupied ward beds</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Boxplots of total discharges per replication with fully occupied ward beds</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Division of patients between 2 electrophysiologists each weekday</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Weekday</th><th align=\"left\">Proportions</th></tr></thead><tbody><tr><td align=\"left\">Monday</td><td align=\"left\">72.7% / 27.3%</td></tr><tr><td align=\"left\">Tuesday</td><td align=\"left\">18.4% / 81.6%</td></tr><tr><td align=\"left\">Wednesday</td><td align=\"left\">50.0% / 50.0%</td></tr><tr><td align=\"left\">Thursday</td><td align=\"left\">53.2% / 46.8%</td></tr><tr><td align=\"left\">Friday</td><td align=\"left\">29.2% / 70.8%</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Daily arrivals by patient type</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Patient type</th><th align=\"left\">Mean (SD)</th></tr></thead><tbody><tr><td align=\"left\">TEP patients</td><td align=\"left\">2.446 (2.358)</td></tr><tr><td align=\"left\">CLEP patients</td><td align=\"left\">3.875 (2.684)</td></tr><tr><td align=\"left\">NEP patients</td><td align=\"left\">13.161 (5.990)</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Model inputs of TEP patients by EP procedure type</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">EP procedure type</th><th align=\"left\" rowspan=\"2\">Proportion</th><th align=\"left\" colspan=\"2\">Operative time, minutes</th><th align=\"left\" colspan=\"2\">EP lab clean-up and preparation, minutes</th><th align=\"left\" colspan=\"2\">Length of stay, days</th><th align=\"left\" colspan=\"2\">Pre-operative stay, days</th></tr><tr><th align=\"left\">Mean (SD)</th><th align=\"left\">Min-Max</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Min-Max</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Min-Max</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Min-Max</th></tr></thead><tbody><tr><td align=\"left\">Paroxysmal AF ablation</td><td align=\"left\">18.4%</td><td align=\"left\">204.947 (66.735)</td><td align=\"left\">65–340</td><td align=\"left\">7.467 (7.477)</td><td align=\"left\">2–40</td><td align=\"left\">5.050 (2.350)</td><td align=\"left\">3–11</td><td align=\"left\">2.000 (2.151)</td><td align=\"left\">1–8</td></tr><tr><td align=\"left\">Persistent AF ablation</td><td align=\"left\">9.6%</td><td align=\"left\">208.688 (51.927)</td><td align=\"left\">128–321</td><td align=\"left\">5.800 (2.833)</td><td align=\"left\">2–11</td><td align=\"left\">3.375 (1.061)</td><td align=\"left\">3–6</td><td align=\"left\">1.375 (1.061)</td><td align=\"left\">1–4</td></tr><tr><td align=\"left\">PVC ablation</td><td align=\"left\">16.2%</td><td align=\"left\">107.206 (40.630)</td><td align=\"left\">35–202</td><td align=\"left\">6.963 (4.485)</td><td align=\"left\">1–25</td><td align=\"left\">2.810 (1.209)</td><td align=\"left\">2–7</td><td align=\"left\">1.400 (0.681)</td><td align=\"left\">0–3</td></tr><tr><td align=\"left\">SVT ablation</td><td align=\"left\">17.6%</td><td align=\"left\">99.067 (30.770)</td><td align=\"left\">70–209</td><td align=\"left\">5.130 (2.117)</td><td align=\"left\">1–10</td><td align=\"left\">2.478 (0.730)</td><td align=\"left\">1–4</td><td align=\"left\">1.250 (0.550)</td><td align=\"left\">0–2</td></tr><tr><td align=\"left\">AFlutter/PAC/AT ablation</td><td align=\"left\">5.9%</td><td align=\"left\">212.545 (149.095)</td><td align=\"left\">70–574</td><td align=\"left\">9.286 (9.032)</td><td align=\"left\">1–28</td><td align=\"left\">4.000 (2.646)</td><td align=\"left\">2–9</td><td align=\"left\">1.333 (0.816)</td><td align=\"left\">1–3</td></tr><tr><td align=\"left\">GP ablation</td><td align=\"left\">2.2%</td><td align=\"left\">99.000 (52.849)</td><td align=\"left\">50–155</td><td align=\"left\">6.500 (2.121)</td><td align=\"left\">5–8</td><td align=\"left\">2.500 (0.707)</td><td align=\"left\">2–3</td><td align=\"left\">2.000 (0.000)</td><td align=\"left\">2–2</td></tr><tr><td align=\"left\">PFO closure</td><td align=\"left\">2.2%</td><td align=\"left\">35.333 (6.110)</td><td align=\"left\">30–42</td><td align=\"left\">7.500 (3.536)</td><td align=\"left\">5–10</td><td align=\"left\">3.000 (0.000)</td><td align=\"left\">3–3</td><td align=\"left\">1.000 (0.000)</td><td align=\"left\">1–1</td></tr><tr><td align=\"left\">ICD implant</td><td align=\"left\">1.5%</td><td align=\"left\">99.250 (41.979)</td><td align=\"left\">65–160</td><td align=\"left\">6.667 (2.887)</td><td align=\"left\">5–10</td><td align=\"left\">5.000 (0.000)</td><td align=\"left\">5–5</td><td align=\"left\">1.000 (0.000)</td><td align=\"left\">1–1</td></tr><tr><td align=\"left\">Dual-chamber PM implant</td><td align=\"left\">5.9%</td><td align=\"left\">104.063 (31.693)</td><td align=\"left\">49–167</td><td align=\"left\">8.444 (4.773)</td><td align=\"left\">2–15</td><td align=\"left\">4.500 (1.732)</td><td align=\"left\">3–7</td><td align=\"left\">2.000 (1.414)</td><td align=\"left\">1–3</td></tr><tr><td align=\"left\">CRT PM implant</td><td align=\"left\">3.7%</td><td align=\"left\">190.200 (67.087)</td><td align=\"left\">94–267</td><td align=\"left\">5.600 (3.362)</td><td align=\"left\">2–10</td><td align=\"left\">6.600 (3.715)</td><td align=\"left\">4–12</td><td align=\"left\">2.200 (2.168)</td><td align=\"left\">1–6</td></tr><tr><td align=\"left\">Miscellaneous EP procedures</td><td align=\"left\">16.9%</td><td align=\"left\">86.741 (54.488)</td><td align=\"left\">27–305</td><td align=\"left\">6.600 (4.619)</td><td align=\"left\">2–25</td><td align=\"left\">2.917 (1.165)</td><td align=\"left\">2–5</td><td align=\"left\">1.167 (0.577)</td><td align=\"left\">1–3</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Total TEP patients discharged per replication with fully occupied ward beds</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Scenario</th><th align=\"left\">Mean (SD)</th><th align=\"left\">Percent difference*</th></tr></thead><tbody><tr><td align=\"left\">Base case</td><td align=\"left\">220.612 (44.110)</td><td align=\"left\">--</td></tr><tr><td align=\"left\">Reduce operative time</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\"> By 10%</td><td align=\"left\">218.594 (45.473)</td><td align=\"left\">-0.9%</td></tr><tr><td align=\"left\"> By 20%</td><td align=\"left\">219.996 (46.620)</td><td align=\"left\">-0.3%</td></tr><tr><td align=\"left\"> By 30%</td><td align=\"left\">222.142 (46.260)</td><td align=\"left\">0.7%</td></tr><tr><td align=\"left\" colspan=\"3\">Reduce pre-operative stay</td></tr><tr><td align=\"left\"> By 10% of length of stay</td><td align=\"left\">223.433 (46.153)</td><td align=\"left\">1.3%</td></tr><tr><td align=\"left\"> By 20% of length of stay</td><td align=\"left\">225.816 (45.295)</td><td align=\"left\">2.4%</td></tr><tr><td align=\"left\"> By 30% of length of stay</td><td align=\"left\">234.709 (47.664)</td><td align=\"left\">6.4%</td></tr><tr><td align=\"left\" colspan=\"3\">Reduce post-operative stay</td></tr><tr><td align=\"left\"> By 10% of length of stay</td><td align=\"left\">222.007 (45.804)</td><td align=\"left\">0.6%</td></tr><tr><td align=\"left\"> By 20% of length of stay</td><td align=\"left\">228.884 (45.141)</td><td align=\"left\">3.7%</td></tr><tr><td align=\"left\"> By 30% of length of stay</td><td align=\"left\">232.116 (45.233)</td><td align=\"left\">5.2%</td></tr><tr><td align=\"left\" colspan=\"3\"><p>Reduce pre- and</p><p> post-operative stay</p></td></tr><tr><td align=\"left\"> By 10% of length of stay</td><td align=\"left\">221.757 (44.698)</td><td align=\"left\">0.5%</td></tr><tr><td align=\"left\"> By 20% of length of stay</td><td align=\"left\">228.324 (47.395)</td><td align=\"left\">3.5%</td></tr><tr><td align=\"left\"> By 30% of length of stay</td><td align=\"left\">236.724 (47.252)</td><td align=\"left\">7.3%</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab5\"><label>Table 5</label><caption><p>Total TEP patients discharged per replication with fully occupied EP labs</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Scenario</th><th align=\"left\" colspan=\"2\">Mean (SD)</th><th align=\"left\">Percent difference*</th></tr></thead><tbody><tr><td align=\"left\">Base case</td><td align=\"left\" colspan=\"2\">271.634 (10.379)</td><td align=\"left\">--</td></tr><tr><td align=\"left\" colspan=\"2\">Reduce operative time</td><td align=\"left\" colspan=\"2\"/></tr><tr><td align=\"left\"> By 10%</td><td align=\"left\" colspan=\"2\">281.774 (10.519)</td><td align=\"left\">3.7%</td></tr><tr><td align=\"left\"> By 20%</td><td align=\"left\" colspan=\"2\">292.445 (11.163)</td><td align=\"left\">7.7%</td></tr><tr><td align=\"left\"> By 30%</td><td align=\"left\" colspan=\"2\">304.253 (12.181)</td><td align=\"left\">12.0%</td></tr><tr><td align=\"left\" colspan=\"4\">Reduce pre-operative stay</td></tr><tr><td align=\"left\"> By 10% of length of stay</td><td align=\"left\" colspan=\"2\">271.300 (10.546)</td><td align=\"left\">-0.1%</td></tr><tr><td align=\"left\"> By 20% of length of stay</td><td align=\"left\" colspan=\"2\">271.297 (9.931)</td><td align=\"left\">-0.1%</td></tr><tr><td align=\"left\"> By 30% of length of stay</td><td align=\"left\" colspan=\"2\">271.301 (9.688)</td><td align=\"left\">-0.1%</td></tr><tr><td align=\"left\" colspan=\"4\">Reduce post-operative stay</td></tr><tr><td align=\"left\"> By 10% of length of stay</td><td align=\"left\" colspan=\"2\">271.207 (10.229)</td><td align=\"left\">-0.2%</td></tr><tr><td align=\"left\"> By 20% of length of stay</td><td align=\"left\" colspan=\"2\">271.297 (10.512)</td><td align=\"left\">-0.1%</td></tr><tr><td align=\"left\"> By 30% of length of stay</td><td align=\"left\" colspan=\"2\">271.643 (10.205)</td><td align=\"left\">0.0%</td></tr><tr><td align=\"left\" colspan=\"4\"><p>Reduce pre- and</p><p>post-operative stay</p></td></tr><tr><td align=\"left\"> By 10% of length of stay</td><td align=\"left\" colspan=\"2\">271.225 (10.439)</td><td align=\"left\">-0.2%</td></tr><tr><td align=\"left\"> By 20% of length of stay</td><td align=\"left\" colspan=\"2\">271.434 (10.353)</td><td align=\"left\">-0.1%</td></tr><tr><td align=\"left\"> By 30% of length of stay</td><td align=\"left\" colspan=\"2\">271.213 (9.380)</td><td align=\"left\">-0.2%</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>PVC, premature ventricular complex; SVT, supraventricular tachycardia; AFlutter, atrial flutter; PAC, premature atrial contraction; AT, atrial tachycardia; GP, ganglionated plexi; PFO, patent foramen ovale; ICD, implantable cardioverter defibrillator; PM, pacemaker; CRT, cardiac resynchronization therapy</p></table-wrap-foot>", "<table-wrap-foot><p>*Relative to base case scenario</p></table-wrap-foot>", "<table-wrap-foot><p>*Relative to base case scenario</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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{ "acronym": [ "DES", "EP", "CLS", "AF", "FAHZU", "TEP patients", "CLEP patients", "NEP", "PVC", "SVT", "AFlutter", "PAC", "AT", "GP", "PFO", "ICD", "PM", "CRT" ], "definition": [ "discrete event simulation", "electrophysiology", "capacity-limiting scenario", "atrial fibrillation", "First Affiliated Hospital of Zhejiang University", "target electrophysiology patients", "catheter lab electrophysiology patients", "non- electrophysiology patients", "premature ventricular complex", "supraventricular tachycardia", "atrial flutter", "premature atrial contraction", "atrial tachycardia", "ganglionated plexi", "patent foramen ovale", "implantable cardioverter defibrillator", "pacemaker", "cardiac resynchronization therapy" ] }
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2024-01-14 23:43:47
BMC Health Serv Res. 2024 Jan 12; 24:67
oa_package/83/af/PMC10787488.tar.gz
PMC10787489
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[ "<title>Background</title>", "<p id=\"Par37\">Rheumatoid arthritis (RA) is a highly disabling autoimmune disease characterized by persistent synovitis and joint damage [##REF##36780677##1##, ##REF##36068354##2##]. Excessive production of abnormal autoantibodies, including anti-cyclic peptide containing citrulline (anti-CCP), play a pivotal role in the onset and progression of RA, which can even be detected in the stage of pre-clinical RA (Pre-RA) [##REF##34495490##3##, ##REF##33746022##4##]. A comprehensive exploration of the intricate process of antibody generation is vital to achieving targeted therapy, early remission, and the prevention of RA. The complex etiopathogenesis of RA involves the loss of immune tolerance resulting from genetic and environmental factors, which has been confirmed to be a crucial contributor to the over-production of abnormal antibodies, and it always occurs in the Pre-RA stage to promote the further progression of RA [##REF##33257900##5##, ##REF##34598926##6##]. Therefore, inducing and restoring immune tolerance are promising in the prevention and treatment of RA.</p>", "<p id=\"Par38\">The CD4 + CD25 + Forkhead Box 3 (FoxP3) + regulatory T (Treg) cells play a critical role in maintaining immune tolerance not only by producing the anti-inflammatory cytokine (such as interleukin-10) but also by suppressing the activation and proliferation of effector T cells, specifically helper T(Th)17 cells, which secret the pro-inflammatory cytokine, interleukin-17 [##REF##31862128##7##]. It has been reported that RA patients had an imbalance of Th17/Treg cells, especially the reduced Treg cells [##UREF##0##8##, ##REF##35925523##9##]. Exploiting the suppressive capacities of Treg cells to enhance immune tolerance has been an emerging field to treat autoimmune diseases such as the application of low-dose interleukin-2 (IL-2) in RA [##REF##32801037##10##, ##UREF##1##11##]. However, the breakdown of immune tolerance mediated by the aberrant Treg cells seems to be difficult to explain the over-production of antibodies in RA.</p>", "<p id=\"Par39\">The autoantibody production in RA depends on the response of lymphoid follicular germinal centers (GCs), which are essential for B cells to complete the series of reactions including affinity maturation, class switch recombination, and somatic hypermutation to produce a large number of high-affinity antibodies and memory B cells finally [##REF##33326765##12##]. The discovery of a novel CD4 + T subset cells localized in lymphoid follicular GCs is termed follicular regulatory T (Tfr) cells, which is characterized by the expression of C-X-C chemokine receptor type 5 (CXCR5, a chemokine receptor homing to the T-cell zone) and Foxp3 [##REF##21785430##13##–##REF##21785433##15##]. While the exact differentiation mechanism of Tfr cells is still poorly defined, existing evidence supports that they originate de novo from thymic-derived FoxP3 + Treg precursors under multiple stimulations. As a specific subpopulation of Treg cells, Tfr cells contribute to maintaining immune tolerance by inhibiting follicular helper T (Tfh) cells, another GC-residing cell type to facilitate the production of antibodies by promoting the formation and response of GC [##REF##31477921##16##, ##REF##30874350##17##]. The function of Tfr cells provides a new understanding of maintaining immune tolerance and antibody production, which may contribute to the further exploration of RA pathogenesis. It has been found that RA patients had imbalanced Tfr/Tfh cells [##REF##30284646##18##, ##REF##32610164##19##], especially those with decreased Tfr cells exhibited high disease activity and antibodies, suggesting that the aberrant Tfr cells could lead to the over-production of antibodies to destroy the immune tolerance. And those with active RA showed higher Tfh cells which was associated with the enhanced IL-6/pSTAT3 signaling [##REF##30157931##20##]. Of note, the imbalance was altered after treatment and patients with RA in stable remission with lower levels of autoantibodies exhibited increased Tfr cells [##REF##29381842##21##, ##REF##36582249##22##], indicating that targeting Tfr cells to restore immune tolerance had significant therapeutic potential for RA. It has become a consensus that impaired immune tolerance and antibody production are the core pathogenesis of RA and the Pre-RA, and Tfr cells play an important role in inhibiting the production of antibodies and maintaining immune tolerance. Therefore, the impaired immune tolerance and the over-production of antibodies caused by aberrant Tfr cells play a crucial role in the pathogenesis of RA. Nevertheless, the potential upstream factors regulating Tfr cell-mediated immune tolerance remain to be fully elucidated, which is the aim of our study.</p>", "<p id=\"Par40\">There is substantial evidence suggesting that the initiation of RA might originate in mucosal sites far away from joints, such as the gut, which emphasizes the effect of the gut-joint axis exerted in RA [##UREF##2##23##, ##REF##33674813##24##]. The gut microbiota as the most critical component in the gut is important for balancing health and disease, and it is associated with autoimmune diseases including RA [##REF##35105664##25##, ##UREF##3##26##]. Some significant studies have reported that gut microbiota dysbiosis in RA was correlated with disease activity [##REF##30760471##27##–##REF##26214836##29##]. For instance, patients with RA exhibited elevated <italic>Prevotella copri</italic>, particularly those with high disease activity [##REF##30760471##27##, ##REF##31699813##28##], while the reduced <italic>Haemophilus</italic> spp. in untreated RA patients was associated with high-level abnormal autoantibodies negatively [##REF##26214836##29##]. Gut microbiota plays an immunomodulatory role in maintaining immune homeostasis under normal conditions [##REF##35617387##30##], while gut microbiota dysbiosis could activate both innate and adaptive immune cells, which may serve as the mechanistic connection between mucosal changes and arthritis development [##REF##27256713##31##, ##REF##30111803##32##]. Moreover, gut microbiota-derived metabolites including short-chain fatty acids (SCFAs), bile acids and tryptophan and its derivatives have been recognized as the crosstalk of the gut-joint axis to exert effects [##REF##35531300##33##, ##REF##32968241##34##]. Altered metabolite profiles have been observed in RA patients indicating their significant role in the pathological mechanism of RA [##REF##34670873##35##, ##REF##35145919##36##]. The main mechanism driving the onset of RA through the gut-joint axis revolves around the impact of gut microbiotas and their metabolites to activate pro-inflammatory immune cells and promote their trafficking from the gut to joints [##REF##35945456##37##, ##REF##27096318##38##]. Notably, the altered gut microbiotas and their metabolites may also play a role in the gut-joint axis by destroying immune tolerance. The present studies focus on whether and how gut microbiotas and their metabolites affect immune tolerance mediated by Treg and Tfr cells to exert critical components within the gut-joint axis. To date, some studies on collagen-induced arthritis (CIA) and SKG arthritis models have found that microbiota-derived butyrate might suppress autoantibody production and ameliorate arthritis by enhancing the Treg and Tfr cells [##REF##35148177##39##, ##REF##32711255##40##]. However, there are numerous gut microbiotas and their metabolites in RA, whether other gut microbiotas and metabolites are involved in the pathogenesis of RA, and how their relationship with Treg cells, especially Tfr cells, still needs further systematic research. Thus, it is necessary to find the disease biomarkers of RA from the numerous gut microbiotas and their metabolites and to analyze their relationship with Treg and Tfr cells, which is the focus of our study.</p>", "<p id=\"Par41\">Therefore, we performed the study to explore the association of gut microbiotas and their metabolites with the immune tolerance mediated by Tfr cells in RA. First, we assessed the immune tolerance status in RA by detecting the expression of Th17, Treg, Tfr, and Tfh cells in the peripheral blood via modified flow cytometry. And then, considering that the detection of gut microbiota and metabolites in stool samples is an ideal method to study the direct correlation between gut microbiotas and their metabolites, we identified the characteristics of gut microbiotas and their metabolites in RA by the combination of 16S rDNA sequencing and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS)-based untargeted metabolomic profiling. Subsequently, we explored the association of gut microbiotas and their metabolites with the immune tolerance mediated by circulating Tfr cells. The results of our study aimed to provide a novel insight into the pathogenesis of RA from the perspective of gut microbiota-metabolite-immune tolerance.</p>" ]
[ "<title>Materials and methods</title>", "<title>Study population and data</title>", "<p id=\"Par42\">This study recruited new-onset RA patients who were admitted to the Second Hospital of Shanxi Medical University between January 2022 and June 2022. Participants should meet the criteria of the 2010 ACR/EULAR classification and diagnosis criteria for RA and should not receive any steroid, disease-modifying antirheumatic drugs (DMARDs), or biological agents for at least 3 months. Healthy volunteers with no history of autoimmune diseases or abnormal clinical indicators were included as healthy controls (HCs). Several exclusion criteria were applied to both the new-onset RA patients and HCs as follows: (i) recent use of antibiotics and microecological agents within 8 weeks; (ii) suffered from malignant tumors, severe infections, or serious cardiovascular system diseases; (iii) suffered from inflammatory bowel disease and other diseases that may seriously affect the gut microbiotas and their metabolites; (iv) a history of gastrointestinal surgery. In accordance with these criteria, the final cohort comprised a total of 32 new-onset RA patients and 17 HCs. This study was carried out under the principles outlined in the Declaration of Helsinki and received approval from the Ethics Committee of the Second Hospital of Shanxi Medical University (Approval (2021) YX No. (250)). All participants provided written informed consent.</p>", "<p id=\"Par43\">Stool samples from HCs and new-onset patients with RA were collected and preserved at a temperature of − 80 °C for subsequent processing. Blood samples from each participant were also processed upon collection to determine the expression of Th17, Treg, Tfr, and Tfh cells in peripheral blood. Additionally, demographic data, clinical data [including the tenderness joint count (TJC), swollen joint count (SJC), and disease activity score 28(DAS28)] as well as laboratory tests [including erythrocyte sedimentation rate (ESR, mm/h), anti-CCP (U/ml), rheumatoid factor (RF)-Ig M(U/ml) and RF-Ig G(U/ml)] were acquired for analysis.</p>", "<title>The detection of Th17, Treg, Tfr and Tfh cells</title>", "<p id=\"Par44\">Peripheral blood samples were collected in heparin anticoagulation tubes for the assessment of circulating Th17, Treg, Tfr, and Tfh cells by modified flow cytometry. A representative flow cytometry figure is illustrated in Additional file ##SUPPL##0##1##: Fig. S1. The specific details of the experimental procedures were in the “Methods” section of Additional file ##SUPPL##0##1##.</p>", "<title>The analysis of gut microbiota and fecal metabolite</title>", "<p id=\"Par45\">Considering the susceptibility of gut microbiotas and their metabolites to diverse influences such as medication and dietary habits, meticulous consideration was given to mitigate potential biases. Therefore, participants were all from Shanxi Province to ensure dietary comparability and refrained from medication for at least 8 weeks before sample collection. The gut microbiotas and their metabolites were assessed by the combination of 16S rDNA sequencing and UPLC-MS-based untargeted metabolomic profiling. Further details were in the “Methods” section of Additional file ##SUPPL##0##1##.</p>", "<title>Statistical analysis</title>", "<p id=\"Par46\">The analysis of the demographic data, clinical data, and laboratory tests was under IBM SPSS 25.0. The normally distributed continuous variables were presented as mean ± standard deviation (SD) and analyzed by the independent samples <italic>t</italic>-test. While the nonparametric variables were presented as median (Q1, Q3) and were analyzed by the Mann–Whitney <italic>U</italic> test. Categorical variables were described by ratio or percentage and were assessed by the chi-square (<italic>χ</italic><sup>2</sup>) or Fisher’s exact tests. All <italic>P</italic>-values were two-tailed and statistical significance was defined as <italic>P</italic> &lt; 0.05.</p>" ]
[ "<title>Results</title>", "<title>Characteristics of participants</title>", "<p id=\"Par47\">There were 23 females and 9 males among the 32 new-onset RA patients with an average age of 56.78 ± 11.69 years. And 13 females and 4 males were included in 17 HCs with an average age of 51.94 ± 13.03 years. No significant disparities were observed in terms of gender (<italic>P</italic> = 0.729) or age (<italic>P</italic> = 0.735) between the new-onset RA patients and the HCs. The summary of demographic data, clinical data, and laboratory tests of new-onset RA patients and HCs is presented in Table ##TAB##0##1##.\n</p>", "<title>Reduced Treg and Tfr cells in RA were associated with the disease</title>", "<p id=\"Par48\">The comparison of circulating Th17, Treg, Tfr, and Tfh cells between RA and HCs is summarized in Fig. ##FIG##0##1## and Additional file ##SUPPL##0##1##: Table S1.</p>", "<p id=\"Par49\">Compared with HCs, new-onset RA patients had a lower number of Treg cells [20.605(15.633,33.415) cells/µl <italic>vs.</italic> 35.700(23.360,59.855) cells/µl, <italic>P</italic> = 0.004] and a lower number of c-Tfr cells [7.690(1.700,15.202) cells/µl <italic>vs.</italic> 14.519 (8.979,28.602) cells/µl, <italic>P</italic> = 0.008] resulting in a higher ratio of c-Tfh/c-Tfr [7.822(3.546,26.824) <italic>vs.</italic> 1.916(0.684,4.483), <italic>P</italic> &lt; 0.001], and they also had a lower percentage of c-Tfr cells [1.332(0.282,2.224) % <italic>vs.</italic> 2.097(1.143,3.130) %, <italic>P</italic> = 0.032] but a higher percentage of c-Tfh cells [8.955 (5.580,13.550) % <italic>vs.</italic> 2.750(0.923,12.965) %, <italic>P</italic> = 0.044]. Considering that most Tfr cells are derived from thymic-derived FoxP3 + Treg cells (natural Treg, nTreg) [##REF##21785430##13##–##REF##21785433##15##], our study analyzed the correlation between the number of Treg cells and Tfr cells in the new-onset RA patients, and the results showed that the two were correlated positively, supporting that there was a direct relationship between the two cells in RA (Additional file ##SUPPL##0##1##: Fig. S2).</p>", "<p id=\"Par50\">The correlation heatmap of Th17, Treg, Tfr, and Tfh cells with the clinical indicators of RA was conducted (Fig. ##FIG##1##2##). The number of Treg cells was related to ESR, TJC, SJC, DAS28, and anti-CCP negatively, while the percentage of Treg cells was only related to anti-CCP negatively. The level of c-Tfr cells was negatively associated with ESR, DAS28, anti-CCP, RF-IgG, and RF-IgM. The number of c-Tfh cells was negatively associated with RF-IgG. In summary, the reduced Treg and Tfr cells in RA were associated with the disease activity and the production of autoantibodies of RA.</p>", "<title>Relationship between gut microbiota and RA</title>", "<p id=\"Par51\">The adequacy of sequencing information from gut microbiota profiles was confirmed by the rarefaction curve based on observed species (Fig. ##FIG##2##3##A). There were 3698 and 2140 feature data obtained by the DADA2 algorithm from the new-onset RA patients and HCs, and 995 feature data were shared by the new-onset RA patients and HCs (Fig. ##FIG##2##3##B). Analysis of α diversity indicated that species richness and evenness of gut microbiota were similar between new-onset RA patients and HCs (Additional file ##SUPPL##0##1##: Fig. S3). Meanwhile, the β diversity analysis evaluated by the principal coordinate analysis (PCoA) score and the <italic>P</italic> value obtained from the analysis of similarities (ANOSIM) (R = 0.104,<italic> P</italic> = 0.039) showed the composition of gut microbiota had significant differences between new-onset RA patients and HCs (Fig. ##FIG##2##3##C).</p>", "<p id=\"Par52\">Given that many identified gut microbiotas were not classified at the species level, we mainly focused on the genus level. We compared the differences in the composition of gut microbiota among the top 30 at the phylum and genus level between RA and HCs (Fig. ##FIG##2##3##D, E). There were three significantly different gut microbiotas at the phylum level and seven gut microbiotas at the genus level (Additional file ##SUPPL##0##1##: Table S2).</p>", "<p id=\"Par53\">A total of 21 gut microbiotas from phylum to genus levels were recognized as differential gut microbiota between the RA and HCs by linear discriminant analysis (LDA) effect size (LDA &gt; 3, <italic>P</italic> &lt; 0.05) (Fig. ##FIG##3##4##A, B). The correlation heatmap of the 21 differential gut microbiotas and the clinical indicators of RA revealed that the upregulated gut microbiota in RA such as <italic>Ruminococcus 2</italic> was positively correlated with ESR, TJC, SJC, DAS28, and anti-CCP, while the downregulated gut microbiota such as <italic>Lachnospira</italic> was negatively associated with RF-IgG (Fig. ##FIG##3##4##C). Furthermore, <italic>Ruminococcus 2</italic> was identified as the potential gut microbiota biomarker of RA via receiver operating characteristic (ROC) curve analysis for it yielded the highest area under curve (AUC) of the curve [AUC = 0.782, 95% confidence interval (CI) = 0.636–0.929,<italic> P</italic> = 0.001] (Fig. ##FIG##3##4##D).</p>", "<title>Relationship between altered metabolites and RA</title>", "<p id=\"Par54\">The stool samples of 17 new-onset RA patients and 13 HCs were selected randomly to analyze metabolites by UPLC-MS-based untargeted metabolomic profiling.</p>", "<p id=\"Par55\">Multivariate statistical analysis was to identify the differential metabolites between the RA and HCs by the projections to latent structures discriminant analysis (PLS-DA) model. It showed that the metabolites between RA and HC were separated by differences in both the positive and negative ion modes. And the permutation test of the PLS-DA model with positive and negative ion modes indicated that the PLS-DA model had a good prediction and explanation ability without overfitting phenomenon (Additional file ##SUPPL##0##1##: Fig. S4). It indicated the significant differences in metabolites between new-onset RA and HCs. A total of 61 differential metabolites were recognized including 34 metabolites upregulated and 27 metabolites downregulated compared to HCs according to the conditions of differential metabolites (fold change ≥ 2 or ≤ 0.5, VIP &gt; 1 and <italic>P</italic> &lt; 0.05) (Fig. ##FIG##4##5##A, B).</p>", "<p id=\"Par56\">Among the top twenty pathways identified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the differentially abundant metabolites, there were only four pathways closely related to RA. It included biosynthesis of unsaturated fatty acids (<italic>P</italic> &lt; 0.001), arginine biosynthesis (<italic>P</italic> = 0.012), and tryptophan metabolism (<italic>P</italic> = 0.012), as well as alanine, aspartate and glutamate metabolism (<italic>P</italic> = 0.004) (Fig. ##FIG##5##6##A). Within these altered pathways, eleven differentially abundant metabolites were identified including eight abundant in new-onset RA patients while three abundant in HCs (Additional file ##SUPPL##0##1##: Table S3).</p>", "<p id=\"Par57\">A correlation heatmap demonstrated the connections between the eleven differentially abundant metabolites and the indicators of RA (Fig. ##FIG##5##6##B). It showed that the increased arachidonic acid was positively correlated with ESR, TJC, DAS28, and anti-CCP, the increased n-acetyl-l-glutamate was positively correlated with ESR, the increased 3-methyldioxyindole was positively associated with TJC, the increased n-acetyl-l-glutamate was positively associated with RF-IgG, and the increased stearic acid was positively associated with SJC. The above indicated that the differential metabolites in RA were associated with the progression of the disease. And arachidonic acid was identified as the potential metabolite biomarker of RA via ROC curve analysis (AUC = 0.724, 95% CI = 0.595–0.909, <italic>P</italic> = 0.038) (Fig. ##FIG##5##6##C).</p>", "<title>Altered gut microbiotas and their metabolites in RA were associated with Tfr cells</title>", "<p id=\"Par58\">To investigate the interactions between gut microbiotas and their metabolites related to RA, we subsequently assessed the correlations between the 21 differential gut microbiotas and 11 metabolites detected in RA by Spearman’s correlation analysis. The correlation network of the interactions between them showed arachidonic acid was the core metabolite as it was positively associated with six gut microbiotas enriched in RA including <italic>Ruminococcus 2</italic>, <italic>Staphylococcus</italic>, <italic>Staphylococcaceae</italic>, <italic>Bacillales</italic>, <italic>Lactobacillus</italic>, and <italic>Lactobacillaceae</italic> (r &gt; 0.5, <italic>P</italic> &lt; 0.05, Fig. ##FIG##6##7##A). It indicated that the altered metabolites seemed to be correlated with the gut microbiota dysbiosis in RA.</p>", "<p id=\"Par59\">To further elucidate the relationship of altered gut microbiotas and their metabolites in RA with Treg and Tfr cells, a correlation heatmap was performed (Fig. ##FIG##6##7##B). In terms of gut microbiota, the increased <italic>Ruminococcus 2</italic> was negatively correlated with the reduced number of Treg and c-Tfr cells but positively associated with the ratio of Th17/Treg. As for the metabolites, the increased arachidonic acid involved in the biosynthesis of unsaturated fatty acid pathway was negatively associated with the reduced level of Treg and c-Tfr cells, and the increased 3-methyldioxyindole involved in the tryptophan metabolism pathway was negatively associated with the reduced Treg and Tfr cells.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par60\">Circulating Tfr cells play a role in maintaining immune tolerance, and the reduced Tfr cell may contribute to the breakdown of immune tolerance to participate in the progression of RA. However, the upstream mechanism of regulating Tfr cell-mediated immune tolerance remains unclear. Numerous studies have shown that gut microbiota dysbiosis and altered metabolites are closely related to the development of RA [##REF##34670873##35##, ##REF##35145919##36##], which may be caused by the interactions of gut microbiotas and their metabolites with the immune system. It still lacks systematic studies on the relationship between gut microbiota dysbiosis and altered metabolites with the Tfr cell-mediated immune tolerance in RA. Our study was the first to investigate the association of gut microbiotas and their metabolites with the immune tolerance mediated by Tfr cells in new-onset RA. The results of our study revealed the following characteristics of the new-onset patients with RA: (i) The reduced Treg and Tfr cells in RA were associated with the disease activity and the over-production of autoantibodies. (ii) Gut microbiota dysbiosis (especially at the genus levels) and altered gut microbiota-derived metabolites exhibited in new-onset RA patients were related to the disease. (iii) <italic>Ruminococcus 2</italic> as well as arachidonic acid might be the potential biomarkers of RA. (iv) Gut microbiota interacted with their metabolites, and gut microbiota dysbiosis as well as the altered metabolites in RA were associated with the breakdown of immune tolerance mediated by reduced Tfr cells. The association between gut microbiotas and their metabolites with immune tolerance mediated by Tfr cells we pointed out may participate in RA, which provided a theoretical basis for further exploring the effect of specific gut microbiota and its metabolites on Tfr cells.</p>", "<p id=\"Par61\">Early work suggested that the activated CD4 + CD25 + CD69 − Treg cells were able to gain the expression of CXCR5 and migrate to the B-cell follicle to suppress B-cell responses [##REF##15578096##41##, ##REF##16177055##42##], which revealed the relationship between Treg cells and another new type of cells in lymphoid follicular. And then, three independent groups defined them as Tfr cells (CXCR5 + PD-1 + BCL6 + FoxP3 + cells), which originated de novo from thymic-derived FoxP3 + Treg precursors requiring multiple stimulations [##REF##21785430##13##–##REF##21785433##15##]. Increasing data highlighted the significance of Treg and Tfr cells in maintaining immune tolerance, especially Tfr cells, which exert an essential effect on regulating antibody production as the subsets of Treg cells via suppressing Tfh cells and B cells in GCs [##REF##31477921##16##]. Considering the difficulties of getting organ tissues from humans for clinical investigations, the circulating Tfr and Tfh cells are always discussed in regulating immune tolerance, which may be derived from GCs and have similar phenotypes and function to GC-Tfh and GC-Tfh cells [##REF##31289377##43##]. By analyzing the expression of circulating Th17, Treg, Tfr, and Tfh cells, our study found that in the new-onset patients with RA, the ratio of Tfh/Tfr was aberrant, and Treg and c-Tfr cells were reduced and associated with the disease activity and the abnormal autoantibodies of RA negatively, but the expressions of Th17 and c-Tfh cells were not increased significantly. The results were consistent with the previous studies [##REF##35925523##9##, ##REF##30284646##18##–##REF##30157931##20##] and supported the previous spot that the immune tolerance breakdown mediated by reduced Treg and Tfr cells participated in the progression of RA rather than the over-immune response. Interestingly, our study found that both Treg and Tfr cells were decreased in RA and were related to disease activity and antibody production of RA, but Treg cells were mainly related to disease activity while Tfr cells were mainly related to antibody production specifically. The above might suggest that the function of Treg cells and Tfr cells in regulating antibody production and maintaining immune tolerance was different despite that Tfr cells were derived from Treg cells. The role of Tfr cells in the early stage of RA, even Pre-RA, needs further exploration.</p>", "<p id=\"Par62\">The interactions between gut microbiotas and their metabolites with the host are important in health and disease, especially the role of gut microbiotas and their metabolites in RA is the focus of our research. Our study revealed that gut microbiota was dysbiosis in new-onset RA patients. Especially the increased <italic>Ruminococcus 2</italic>, one of the predominant gut microbiotas in RA, exhibited a positive correlation with disease activity and autoantibody production. And <italic>Ruminococcus 2</italic> might be the potential biomarker of RA. Notably, our study found that <italic>Lachnospira</italic> was recognized as one of the 21 differential gut microbiotas from phylum to genus levels between RA and HCs, and it was downregulated in new-onset RA patients and negatively associated with RF-IgG of RA. <italic>Lachnospira</italic> is mainly present in the gut of most healthy individuals and may be a potential probiotic involved in the metabolism of a variety of carbohydrates. A two-sample Mendelian randomization study of the causal effects between gut microbiome and systemic lupus erythematosus (SLE) showed that <italic>Lachnospira</italic> was negatively correlated with the risk of SLE [##REF##34557183##44##]. Although our study found the reduced <italic>Lachnospira</italic> in RA was only related to RF-IgG negatively, it still suggested that the reduced <italic>Lachnospira</italic> might promote RA, and the supplementation of it may be a potential treatment for RA. Of course, it still needs further exploration. Additionally, our results also showed that the gut microbiota-derived metabolites involved in the biosynthesis of unsaturated fatty acids, arginine biosynthesis, and tryptophan metabolism as well as alanine, aspartate, and glutamate metabolism were altered in RA, which was consistent with the prior studies [##REF##34670873##35##, ##REF##35145919##36##, ##REF##37219936##45##]. We found that the altered metabolites involved in the biosynthesis of unsaturated fatty acids and tryptophan metabolism pathways were associated with the progression of RA. Especially, the increased arachidonic acid in RA showed positive correlations with disease activity and autoantibody production. And it exhibited good discrimination in distinguishing RA and HCs as the potential biomarker value of RA. In brief, the above supported that gut microbiota dysbiosis and altered metabolites in RA were associated with the development of RA.</p>", "<p id=\"Par63\">Gut microbiotas and their metabolites are the vital bridge of the gut-joint axis to contribute to the pathogenesis of RA [##UREF##3##26##, ##REF##32968241##34##, ##REF##36275747##46##], but the mechanism remains unclear. Exploring the mechanism of RA triggered by gut microbiotas and their metabolites through the gut-joint axis has great significance. The trafficking of activated pro-inflammatory immune cells from the gut to joints has been thought to be one of the main mechanisms of driving the RA onset through the gut-joint axis [##REF##35945456##37##, ##REF##27096318##38##]. T cells in the synovium of patients with RA have been found to express the gut-homing receptor αEβ7 integrin supporting the viewpoint that the trafficking of mucosa-derived immune cells (such as mucosal-associated invariant T cells, Th17 cells, γδT cells, Tfh cells, and so on) from gut to joints [##REF##35945456##37##, ##REF##27096318##38##]. Gut-residing segmented filamentous bacteria (SFB) was found to promote autoimmune arthritis in K/BxN mouse models via the migration of Tfh cells and Th17 cells suggesting the interactions of gut microbiota and effector T cells contribute to the development of RA [##REF##26783341##47##, ##REF##28810929##48##]. Meanwhile, it is worth noting that the gut microbiotas and their metabolites may also contribute to the pathogenesis of RA by regulating Treg and Tfr cell-mediated immune tolerance through the gut-joint axis.</p>", "<p id=\"Par64\">The interactions between gut microbiotas and Treg cells have attracted extensive attention, which is important in establishing intestinal immune tolerance. On the one hand, gut microbiotas could regulate the function and expression of Treg cells by influencing the Treg cell-modulatory activity (such as transforming growth factor-β) directly or controlling signals coming from epithelial cells, dendritic cells, or other Treg cell-regulating cells indirectly [##REF##31235962##49##, ##REF##37316560##50##]. On the other hand, Treg cells exert the effect in establishing intestinal immune homeostasis by inducing the tolerance to symbiotic flora and the host defense against intestinal pathogens, and gut microbial-specific Treg cells have been confirmed to be the essential cells to induce intestinal immune tolerance [##REF##36070798##51##–##REF##36071167##53##]. The effects of gut microbiotas on Treg cells are also researched in RA. The association of gut microbiota dysbiosis and reduced Treg cells in RA patients has been observed [##REF##33506059##54##, ##REF##35185845##55##]. And the animal experiments also confirmed that gut microbiotas and their metabolites affected Treg cells [##REF##24721570##56##–##REF##34079556##58##]. The reduced <italic>Bacteroides fragilis</italic> in collagen-induced arthritis (CIA) mice inhibited the differentiation of CD4 + T cells into Treg cells, while the colonization of <italic>Bacteroides fragilis</italic> in germ-free mice promoted the proliferation of Treg cells and the production of anti-inflammatory cytokines [##REF##24721570##56##, ##REF##20566854##57##]. <italic>Lactobacillus casei</italic> CCFM1074 strain also upregulated the number of Treg cells in the CIA mouse model [##REF##34079556##58##]. In addition, as one of the most abundant gut microbiota-derived metabolites, SCFAs could also regulate the Treg cell-mediated immune tolerance by upregulating the expression of Foxp3 in Treg cells and enhancing the ability of dendritic cells to induce differentiation of Treg cells [##REF##34801681##59##, ##REF##29411774##60##]. Butyrate as the component of SCFA, it has been found that patients with RA lacked the butyrate-producing species and the supplementation of dietary butyrate could exert anti-inflammatory effects to ameliorate RA by promoting Treg cells while suppressing effector T cells and osteoclasts [##REF##35148177##39##]. The above evidence suggests that gut microbiota dysbiosis and altered metabolites may contribute to RA by influencing immune tolerance mediated via Treg cells, which seems to be one of the mechanisms of the gut-joint axis. Tfr cells are largely derived from Treg cells; therefore, Tfr cells are also the potential targets for gut microbiotas and their metabolites to regulate immune tolerance in patients with RA. However, few studies have revealed the relationship of gut microbiotas and their metabolites with Tfr cells directly. Although there had been some studies finding that arthritis induced by SFB was associated with the reduced expression of cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) on the surface of Tfr cells [##REF##33462137##61##] and microbiota-derived butyrate could suppress the development of autoimmune arthritis by enhancing the histone acetylation of Tfr cell to promote their differentiation [##REF##32711255##40##], the effects of gut microbiotas and their metabolites on Tfr cells still value the in-depth study in the future, especially to explore the role of other microbiotas and metabolites on regulating Tfr cells to participate in RA. Our study was the first to investigate the association of gut microbiotas and their metabolites with immune tolerance mediated by Tfr cells and found that gut microbiota dysbiosis and altered metabolites were related to the reduced Treg and Tfr cells. Specifically, the increased <italic>Ruminococcus 2</italic>, the increased arachidonic acid involved in the biosynthesis of unsaturated fatty acid pathway and the increased 3-methyldioxyindole involved in the tryptophan metabolism pathway exhibited negative correlations with the reduced Treg and Tfr cells. It meant that RA patients with altered gut microbiotas and their metabolites were more likely to exhibit impaired immune tolerance mediated by reduced Tfr cells. Therefore, we suspected that the association of altered gut microbiotas and their metabolites in RA with the breakdown of immune tolerance mediated by the reduced Tfr cells was involved in the development of RA.</p>", "<p id=\"Par65\"><italic>Ruminococcus</italic> is a kind of common commensal gut microbiota present in healthy individuals with low abundance, and the increase of it would directly lead to the disruption of intestinal barrier function [##REF##31182571##62##], which may be involved in the pathogenesis of autoimmune diseases. Some studies have shown that <italic>Ruminococcus</italic> was elevated in SLE [##REF##30782585##63##] and spondyloarthropathies [##REF##28606969##64##]. <italic>Ruminococcus</italic> was also found to be positively correlated with RF-IgA and anti-CCP antibodies and the disease activity of RA [##REF##31709198##65##, ##UREF##4##66##]. And the deletion of T-cell death-associated gene 8 (TDAG8) was found to significantly reduce local mucosal inflammation and relieve the disease severity of RA by decreasing the abundance of proinflammation-related <italic>Ruminococcus</italic> [##UREF##5##67##], which both suggested the important role of <italic>Ruminococcus</italic> in RA. Here, we focused on <italic>Ruminococcus 2</italic>, which was one of the abundant gut microbiotas detected in RA and was associated with the progression of RA. The role of <italic>Ruminococcus 2</italic> in RA has not been well-studied. Only one study has found that <italic>Ruminococcus 2</italic> was more abundant in RA patients with lower Treg cells indicating that <italic>Ruminococcus 2</italic> was associated with Treg cells in RA [##REF##33506059##54##]. And even fewer studies about <italic>Ruminococcus 2</italic> and Tfr cells. Based on our results, we hypothesized that individuals with specific compositions of gut microbiota such as increased <italic>Ruminococcus 2</italic> might be more susceptible to RA by reducing Tfr cells to destroy immune tolerance. Arachidonic acid, a polyunsaturated fatty acid, is an important inflammatory mediator in exerting regulatory effects as the direct precursor of various bioactive lipid mediators [##UREF##6##68##] and active substances such as prostaglandin E2, prostaglandin I2, and thromboxane A2 [##REF##36238558##69##]. A recent study of the serum metabolites in Pre-RA showed that arachidonic acid was enriched in the Pre-RA group [##REF##37219936##45##], and there also had been some studies about the role of arachidonic acid in RA [##REF##33568645##70##, ##REF##36162242##71##]. It showed that arachidonic acid could regulate calcium signaling in the T cells of patients with RA to promote synovial inflammation [##REF##33568645##70##]. And further study showed that <italic>Ershiwuwei Lvxue Pill</italic> (ELP), a prescription of Tibetan medicine, could alleviate cartilage and bone injury by regulating host metabolites such as arachidonic acid [##REF##36162242##71##]. The results of our study supported that arachidonic acid was the core metabolite of gut microbiota and the increase of it was associated with reduced Treg and Tfr cells. We suspected that the increased arachidonic acid in RA patients may be mainly caused by the gut microbiota dysbiosis, and it promoted the conversion of the immune balance towards autoimmunity to contribute to RA, which is related to the breakdown of immune tolerance mediated by reduced Tfr cells. In addition, our study showed that <italic>Ruminococcus 2</italic> and arachidonic acid were positively related with each other and they were both associated with the symptoms of arthritis as the potential biomarker of RA. The increased <italic>Ruminococcus 2</italic> might aggravate arthritis and pain by promoting the production of arachidonic acid to further generate the active substances including prostaglandin.</p>", "<p id=\"Par66\">Additionally, tryptophan metabolism could exert effects in regulating the immune system, and it has also been confirmed that the abnormal tryptophan metabolism was related to autoimmune disease [##REF##30557125##72##–##UREF##8##74##]. There are three main metabolic pathways for tryptophan, and nearly 90% of tryptophan is metabolized by indoleamine-2,3-dioxygenase (IDO) to produce intermediate metabolite kynurenine [##REF##30760888##75##]. And CD4 + CD25 − T cells can be transformed into Foxp3 + CD4 + CD25 + Treg cells through IDO-mediated tryptophan metabolism suggesting the role of tryptophan metabolism in regulating immune tolerance [##REF##29254698##76##]. Gut microbiota participates in tryptophan metabolism directly or indirectly, and gut microbiota-derived tryptophan metabolites were found to be associated with autoimmune arthritis [##REF##30557125##72##, ##UREF##7##73##]. IDO is highly expressed in intestinal epithelial cells, which may be affected by gut microbiota to further influence tryptophan metabolism and the transformation of Treg cells [##REF##30619249##77##]. The interactions between gut microbiota and tryptophan metabolism may regulate Treg cell-mediated immune tolerance, but the effect on Tfr cells remains unclear. Considering that Tfr cells was differentiated from Treg cells, the tryptophan metabolism affected by gut microbiota might also regulate Tfr cells, which needed further exploration. Our study suggested that there was an altered distribution of fecal tryptophan metabolites of new-onset RA and they were correlated with the arthritis symptoms and the reduced Treg and Tfr cells. It provided support for exploring the effect of tryptophan metabolism on immune cells, especially Tfr cells, in RA. However, the exact effect of tryptophan metabolism on Tfr cells needs further exploration.</p>", "<p id=\"Par67\">Our result elucidated that gut microbiotas and their metabolites were potential disease markers for RA, and there was a correlation between them with Treg and Tfr cells. The influence of gut microbiota, especially their metabolites, on immune cells is still a frontier of immunomicroecology. The effects of gut microbiota-derived metabolites including SCFAs, bile acids, and tryptophan and its derivatives on Treg cells have been demonstrated, and previous studies have also found that SCFA affected Tfr cells. Our study highlighted the association of the biosynthetic unsaturated fatty acid pathway and the tryptophan metabolic pathway with Tfr cells, which provided valuable insights for exploring the effect of other metabolites on the immune tolerance of RA in the future, especially tryptophan metabolism. Understanding these relationships may help to develop the potential therapeutic strategies targeted at modulating gut microbiotas and their metabolites to restore immune tolerance and improve RA management. However, there were some limits in our study. Firstly, the sample sizes were small and limited to a single center, which may affect the generalizability of the results. Larger and multi-center studies are needed to further verify the results, and it was also necessary to enroll in the different stages of RA (including pre-clinical RA, RA transition, early RA, and established RA) to further explore the characteristics of gut microbiotas and their metabolites during the progression of RA. Secondly, as an observational study, our study only demonstrated the relationship of gut microbiotas and their metabolites with Tfr cells in RA instead of the causality, it is necessary to conduct the vitro experiments to elucidate the causal relationship between them and identify whether the gut microbiotas and their metabolites contribute to the pathogenesis of RA by influencing Tfr cells as one of the mechanisms involved in the gut-joint axis. Finally, further studies are necessary to confirm the specific biological significance underlying these differences in the identified metabolites in RA, for example targeting the metabolism of tryptophan and unsaturated fatty acids may have significance in exploring the pathogenesis of RA.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par68\">Our study revealed that gut microbiota dysbiosis and altered metabolites were associated with the breakdown of immune tolerance mediated by reduced Tfr cells in RA. Based on it, we hypothesized that the altered gut microbiotas and their metabolites might result in the breakdown of immune tolerance by affecting Tfr cells. This finding highlighted the importance of gut microbiotas and their metabolites in the gut-joint axis. It also provides a foundation for further investigations into the potential role of gut microbiotas and their metabolites on Tfr cell-mediated immune tolerance in RA from the perspective of microecology-metabolism-immune. This could help us to better understand the pathogenesis of RA and develop new treatments for the disease.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">Patients with rheumatoid arthritis (RA) showed impaired immune tolerance characterized by reduced follicular regulatory T (Tfr) cells, and they also exhibited altered gut microbiotas and their metabolites in RA. However, the association of gut microbiotas and their metabolites with the immune tolerance mediated by Tfr cells in RA remains unclear.</p>", "<title>Methods</title>", "<p id=\"Par2\">Peripheral blood and stool samples were collected from 32 new-onset RA patients and 17 healthy controls (HCs) in the Second Hospital of Shanxi Medical University between January 2022 and June 2022. The peripheral blood was used to detect the circulating regulatory T (Treg), helper T(Th)17, Tfr, and follicular helper T (Tfh) cells by modified flow cytometry. The stool samples were used to analyze the gut microbiotas and their metabolites via 16S rDNA sequencing and metabolomic profiling. We aimed to characterize the gut microbiotas and their metabolites in RA and identified their association with Tfr cell-mediated immune tolerance.</p>", "<title>Results</title>", "<p id=\"Par3\">The new-onset RA demonstrated reduced Treg and Tfr cells, associated with the disease activity and autoantibodies. There were significant differences in gut microbiotas between the two groups as the results of β diversity analysis (<italic>P</italic> = 0.039) including 21 differential gut microbiotas from the phylum to genus levels. In which, <italic>Ruminococcus 2</italic> was associated with the disease activity and autoantibodies of RA, and it was identified as the potential biomarker of RA [area under curve (AUC) = 0.782, 95% confidence interval (CI) = 0.636–0.929,<italic> P</italic> = 0.001]. Eleven differential metabolites were identified and participated in four main pathways related to RA. Arachidonic acid might be the potential biomarker of RA (AUC = 0.724, 95% CI = 0.595–0.909, <italic>P</italic> = 0.038), and it was the core metabolite as the positive association with six gut microbiotas enriched in RA. The reduced Tfr cells were associated with the altered gut microbiotas and their metabolites including the <italic>Ruminococcus 2</italic>, the arachidonic acid involved in the biosynthesis of unsaturated fatty acid pathway and the 3-methyldioxyindole involved in the tryptophan metabolism pathway.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The breakdown of immune tolerance mediated by reduced Tfr cells was associated with the altered gut microbiotas and their metabolites implying the possible mechanism of RA pathogenesis from the perspective of microecology-metabolism-immune.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s13075-023-03260-y.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We are sincerely grateful to all RA patients and healthy individuals who participated in our study.</p>", "<title>Authors’ contributions</title>", "<p>R.H.W., D.M.W., and C.H.W. conceived the study. L.Y.C., R.S., and B.C.L. collected and collated the data. R.H.W. and C.X.F. conducted the experiments. R.H.W., L.Y.C, R.S., and B.C.L. analyzed the data. R.H.W. wrote the manuscript. D.M.W., C.G., and C.H.W. provided significant revisions to the manuscript.</p>", "<title>Funding</title>", "<p>This work was supported by the National Natural Science Foundation of China (No. 81971543), Four “Batches” Innovation Project of Invigorating Medical through Science and Technology of Shanxi Province (No. 2022XM05), and Central Guidance Special Funds for Local Science and Technology Development (YDZJSX20231A061).</p>", "<title>Availability of data and materials</title>", "<p>The datasets of gut microbiota generated for this study can be found in the SRA of NCBI: <ext-link ext-link-type=\"uri\" xlink:href=\"https://www.ncbi.nlm.nih.gov/sra/\">https://www.ncbi.nlm.nih.gov/sra/</ext-link> PRJNA955157 (Temporary Submission ID: SUB13057507). The other data can be provided by the corresponding author and requests for the data should be submitted to [email protected].</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par69\">This study was conducted under the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the Second Hospital of Shanxi Medical University (Approval (2021) YX No. (250)). Written informed consent was obtained from all participants.</p>", "<title>Consent for publication</title>", "<p id=\"Par70\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par71\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>The comparisons in the expressions of CD4 + T, Th17, Treg, c-Tfr, and c-Tfh cells between patients with RA and HCs. The number of Th17 and c-Tfh cells as well as the ratio of Th17/Treg cells was not changed between RA and HCs, while the number of Treg and c-Tfr cells was reduced in new-onset RA patients. And the ratio of c-Tfh/c-Tfr cells was increased in new-onset RA patients. The new-onset patients with RA had a higher percentage of c-Tfh cells but a lower percentage of c-Tfr cells than those in HCs. <bold>A</bold> The comparison in the number of CD4+ T cells. <bold>B</bold> The comparison in the number of Th17 cells. <bold>C</bold> The comparison in the percent of Th17 cells. <bold>D</bold> The comparison in the number of Treg cells. <bold>E</bold> The comparison in the percent of Treg cells. <bold>F</bold> The comparison in the number of c-Tfr cells. <bold>G</bold> The comparison in the percent of c-Tfr cells. <bold>H</bold> The comparison in the number of c-Tfh cells. <bold>I</bold> The comparison in the percent of c-Tfh cells. <bold>J</bold> The comparison in the ratio of Th17/Treg. <bold>K</bold> The comparison in the ratio of c-Tfh/c-Tfr. (Th17: helper T 17 cells; Treg: regulatory T cells; Tfr: follicular regulatory T cells; Tfh: follicular helper T cells; RA: rheumatoid arthritis; HCs: healthy controls)</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>The correlation heatmap of the expression of Th17, Treg, Tfr, and Tfh cells with the clinical indicators of RA. (Th17: helper T 17 cells; Treg: regulatory T cells; Tfr: follicular regulatory T cells; Tfh: follicular helper T cells; RA: rheumatoid arthritis; HCs: healthy controls; ESR: erythrocyte sedimentation rate; TJC: tenderness joint count; SJC: swollen joint count; DAS28: disease activity score 28; anti-CCP: anti-cyclic peptide containing citrulline; RF: rheumatoid factor)</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>The overview of gut microbiota in new-onset RA patients and HCs. <bold>A</bold> The sequencing depth of the gut microbiota. The curve of each sample was nearly smooth, indicating that there was sufficient sequencing information from these samples in the RA and HCs. <bold>B</bold> The number of feature data in RA and HCs. <bold>C</bold> The β diversity analysis evaluated by principal coordinate analysis (PCoA) score showed that the composition of gut microbiota was significantly different between RA and HCs. <bold>D</bold> The relative abundance of gut microbiota at the phylum level in RA and HCs. <bold>E</bold> The relative abundance of gut microbiota at the genus level in RA and HCs. (RA: rheumatoid arthritis; HCs: healthy controls)</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>The identification of the differentially abundant gut microbiota in RA and the relationship of the gut microbiota dysbiosis with RA. <bold>A</bold> The phylogenetic distribution in cladogram of differential gut microbiota between RA and HCs. <bold>B</bold> The differential gut microbiota with LDA score &gt; 4 and <italic>P</italic> &lt; 0.05 between RA and HCs, and <italic>Ruminococcus 2</italic> was the differential gut microbiota with the highest LDA score at the genus level in RA. <bold>C</bold> The correlation heatmap of the differentially abundant gut microbiota and the disease activity of RA. <bold>D</bold> The ROC curve of biomarker analysis for <italic>Ruminococcus 2.</italic> (The letters c, o, f and g represent class, order, family, and genus, respectively. RA: rheumatoid arthritis; HCs: healthy controls; LDA: linear discriminant analysis; ROC: receiver operating characteristic)</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>The profiles of gut microbiota-derived metabolites between new-onset patients with RA and HCs. <bold>A</bold> The volcano plot showed the differentially altered metabolites between RA and HCs. The red plot represented the upregulated metabolites, the green plot represented the downregulated metabolites, and the gray plot represented the metabolites with no significant differences. <bold>B</bold> The heatmap of differentially abundant metabolites based on the relative abundance. (RA: rheumatoid arthritis; HCs: healthy controls)</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>The analysis of gut microbiota-derived metabolites in new-onset patients with RA. <bold>A</bold> The KEGG pathway enrichment analysis of the differentially abundant metabolites. Four pathways including biosynthesis of unsaturated fatty acids (<italic>P</italic> &lt; 0.001), arginine biosynthesis (<italic>P</italic> = 0.012), and tryptophan metabolism (<italic>P</italic> = 0.012), as well as alanine, aspartate, and glutamate metabolism (<italic>P</italic> = 0.004) were the main pathways related to RA in the top twenty pathways. <bold>B</bold> The correlation heatmap of the eleven differentially abundant metabolites involved in the four mainly altered pathway and indicators of RA. <bold>C</bold> The ROC curve of biomarker analysis for arachidonic acid. (RA: rheumatoid arthritis; HCs: healthy controls; KEGG: Kyoto Encyclopedia of Genes and Genomes; ROC: receiver operating characteristic; AUC: area under curve; CI: confidence interval)</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>The relationship among the gut microbiota, metabolites and immune cell in RA. <bold>A</bold> The correlation network graph showed the main interactions between gut microbiotas and their metabolites (Spearman’s correlation analysis, r &gt; 0.5, <italic>P</italic> &lt; 0.05). Gut microbiotas were marked in purple and metabolites were marked in red. The Solid connecting lines indicated the positive correlations between gut microbiotas and their metabolites, while dashed connecting lines indicated negative correlations between the two. Thicker lines indicated greater correlation values. It showed that arachidonic acid seemed to be the core metabolite as it was positively associated with six gut microbiotas enriched in RA including <italic>Ruminococcus 2</italic>, <italic>Staphylococcus</italic>, <italic>Staphylococcaceae</italic>, <italic>Bacillales</italic>, <italic>Lactobacillus</italic>, and <italic>Lactobacillaceae</italic>. <bold>B</bold> The correlation heatmap of altered gut microbiotas and their metabolites in RA with the expression of Th17, Treg, c-Tfr, and c-Tfh cells in new-onset RA patients. (RA: rheumatoid arthritis; Th17: helper T 17 cells; Treg: regulatory T cells; Tfr: follicular regulatory T cells; Tfh: follicular helper T cells)</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>The summary of demographic data, clinical data and laboratory tests</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">HC (<italic>n</italic> = 17)</th><th align=\"left\">New-onset RA (<italic>n</italic> = 32)</th><th align=\"left\"><italic>P</italic> value</th></tr></thead><tbody><tr><td align=\"left\" colspan=\"4\"><bold>Demographic data</bold></td></tr><tr><td align=\"left\"> Age (years)<sup>a</sup></td><td align=\"left\">51.94 ± 13.03</td><td align=\"left\">56.78 ± 11.69</td><td align=\"left\">0.753</td></tr><tr><td align=\"left\"> Sex(male/female)<sup>b</sup></td><td align=\"left\">4/13</td><td align=\"left\">9/23</td><td align=\"left\">0.729</td></tr><tr><td align=\"left\" colspan=\"4\"><bold>Clinical data</bold></td></tr><tr><td align=\"left\"> Course(months)<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">12(3,57)</td><td align=\"left\">-</td></tr><tr><td align=\"left\"> TJC<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">9(4,20)</td><td align=\"left\">-</td></tr><tr><td align=\"left\"> SJC<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">6(2,18)</td><td align=\"left\">-</td></tr><tr><td align=\"left\"> DAS28<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">5.38(4.45,6.97)</td><td align=\"left\">-</td></tr><tr><td align=\"left\" colspan=\"4\"><bold>Laboratory tests</bold></td></tr><tr><td align=\"left\"> ESR (mm/h)<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">58.50(31.00,84.50)</td><td align=\"left\">-</td></tr><tr><td align=\"left\"> Anti-CCP (U/ml)<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">124.37(56.71,223.37)</td><td align=\"left\">-</td></tr><tr><td align=\"left\"> RF-IgM (U/ml)<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">288.10(59.25,300.00)</td><td align=\"left\">-</td></tr><tr><td align=\"left\"> RF-IgG (U/ml)<sup>c</sup></td><td align=\"left\">-</td><td align=\"left\">106.30(38.2,196.20)</td><td align=\"left\">-</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><italic>Abbreviations</italic>: <italic>HC</italic> healthy control, <italic>RA</italic> rheumatoid arthritis, <italic>TJC</italic> tenderness joint count, <italic>SJC</italic> swollen joint count, <italic>DAS 28</italic> Disease Activity Score 28, <italic>ESR</italic> erythrocyte sedimentation rate, <italic>anti-CCP</italic> anti-cyclic peptide containing citrulline, <italic>RF</italic> rheumatoid factor</p><p><sup>a</sup>Results were expressed as the mean ± SD and were analyzed by independent samples <italic>t</italic>-tests</p><p><sup>b</sup>Categorical variables were described as rates and percentages and were assessed using the chi-square or Fisher’s exact tests</p><p><sup>c</sup>Results were expressed as the median (Q1, Q3) and were analyzed by Mann–Whitney <italic>U</italic> test</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"13075_2023_3260_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Methods. Table S1.</bold> The comparison in the expression of Th17, Treg, Tfr and Tfh cells in the peripheral blood between the patients with RA and HCs. <bold>Table S2.</bold> The comparison of the gut microbiotas with significant differences at the phylum and genus level between the new-onset RA patients and HCs. <bold>Table S3.</bold> The differentially abundant metabolites involved in the four mainly altered pathways. <bold>Fig. S1.</bold> The representative flow cytometry analysis of circulating Th17, Treg, Tfr and Tfh cells. (A) The circulating Th17 cells were identified as CD4+IL-17+T cells. (B) The circulating Treg cells were identified as CD4+CD25+FoxP3+T cells. (C) The circulating Tfh cells were identified as CD3+CD4+CXCR5+CD45RA-PD-1+ T cells. (D) The circulating Tfr cells were identified as CD3+CD4+ CXCR5+ CD45RA- CD25+ FoxP3+cells (Th17: helper T 17 cells; Treg: regulatory T cells; Tfr: follicular regulatory T cells; Tfh: follicular helper T cells). <bold>Fig. S2.</bold> The correlation between the number of Treg cells and Tfr cells in the new-onset RA patients. The two cells were related positively. (Treg: regulatory T cells; Tfr: follicular regulatory T cells; CI: confidence interval). <bold>Fig. S3.</bold> The α-diversity analysis of new-onset RA patients and HCs. It was assessed by (A) Chao1, (B) Observed species, (C) Shannon and (D)Simpson indicators and showed that the species richness and evenness of gut microbiota in the new-onset RA patients were similar with that in HCs. (RA: rheumatoid arthritis; HCs: healthy controls). <bold>Fig. S4.</bold> Multivariate statistical analysis of fecal metabolite profiles between the RA and HCs. (A) The PLS-DA model showed that the fecal metabolites between the RA and HC were separated by differences in the positive ion mode. (B) The validation model of the PLS-DA model in the positive ion mode indicating that the PLS-DA model had a good ability of prediction and explanation without overfitting phenomenon (Intercept of R2 = 0.8908, Intercept of Q2 = -0.3216). (C) The PLS-DA model showed that the fecal metabolites between the RA and HC were separated by differences in the negative ion mode. (D) The validation model of the PLS-DA model in the negative ion mode indicating that the PLS-DA model had a good ability of prediction and explanation without overfitting phenomenon (Intercept of R2 = 0.909, Intercept of Q2 = -0.2835). (RA: rheumatoid arthritis; HCs: healthy controls; LDA: linear discriminant analysis; PLS-DA: projections to latent structures discriminant analysis).</p></caption></media>" ]
[{"label": ["8."], "mixed-citation": ["Go E, Yoo S-J, Choi S, Sun P, Jung MK, Kwon S, et al. Peripheral blood from rheumatoid arthritis patients shows decreased Treg CD25 expression and reduced frequency of effector Treg subpopulation. Cells. 2021;10(4):801."]}, {"label": ["11."], "mixed-citation": ["Shuai Z, Zheng S, Wang K, Wang J, Leung PSC, Xu B. Reestablish immune tolerance in rheumatoid arthritis. Front Immunol. 2022;13:1012868."]}, {"label": ["23."], "mixed-citation": ["Lucchino B, Spinelli FR, Iannuccelli C, Guzzo MP, Conti F, Di Franco M. Mucosa-environment interactions in the pathogenesis of rheumatoid arthritis. Cells. 2019;8(7):700."]}, {"label": ["26."], "mixed-citation": ["Miyauchi E, Shimokawa C, Steimle A, Desai MS, Ohno H. The impact of the gut microbiome on extra-intestinal autoimmune diseases. Nat Rev Immunol. 2023;23(1):9\u201323."]}, {"label": ["66."], "mixed-citation": ["El Menofy NG, Ramadan M, Abdelbary ER, Ibrahim HG, Azzam AI, Ghit MM, et al. Bacterial compositional shifts of gut microbiomes in patients with rheumatoid arthritis in association with disease activity. Microorganisms. 2022;10(9):1820."]}, {"label": ["67."], "mixed-citation": ["Nguyen NT, Sun W-H, Chen T-H, Tsai P-C, Chen C-C, Huang S-L. Gut mucosal microbiome is perturbed in rheumatoid arthritis mice and partly restored after TDAG8 deficiency or suppression by Salicylanilide derivative. Int J Mol Sci. 2022;23(7):3527."]}, {"label": ["68."], "mixed-citation": ["Mustonen A-M, Nieminen P. Dihomo-\u03b3-linolenic acid (20:3n-6)-metabolism, derivatives, and potential significance in chronic inflammation. Int J Mol Sci. 2023;24(3):2116."]}, {"label": ["73."], "mixed-citation": ["Langan D, Perkins DJ, Vogel SN, Moudgil KD. Microbiota-derived metabolites, indole-3-aldehyde and indole-3-acetic acid, differentially modulate innate cytokines and stromal remodeling processes associated with autoimmune arthritis. Int J Mol Sci. 2021;22(4):2017."]}, {"label": ["74."], "surname": ["Choi", "Brown", "Gong", "Ge", "Zadeh", "Li"], "given-names": ["S-C", "J", "M", "Y", "M", "W"], "article-title": ["Gut microbiota dysbiosis and altered tryptophan catabolism contribute to autoimmunity in lupus-susceptible mice"], "source": ["Sci Transl Med"], "year": ["2020"], "volume": ["12"], "fpage": ["551"], "pub-id": ["10.1126/scitranslmed.aax2220"]}]
{ "acronym": [ "RA", "anti-CCP", "Pre-RA", "FoxP3", "Treg cell", "Tfr cell", "Th 17 cell", "GC", "Tfh cell", "UPLC-MS", "DMARDs", "HC", "TJC", "SJC", "DAS28", "ESR", "RF", "SD", "PCoA", "ANOSIM", "LDA", "ROC", "AUC", "CI", "PLS-DA", "KEGG", "CXCR5", "SFB", "SCFAs", "CTLA-4", "CIA", "IDO" ], "definition": [ "Rheumatoid arthritis", "Anti-cyclic peptide containing citrulline", "Pre-clinical RA", "Forkhead Box 3", "Regulatory T cell", "Follicular regulatory T cell", "Helper T 17 cell", "Germinal centers", "Follicular helper T cell", "Ultra-performance liquid chromatography-tandem mass spectrometry", "Disease-modifying antirheumatic drugs", "Healthy control", "Tenderness joint count", "Swollen joint count", "Disease activity score 28", "Erythrocyte sedimentation rate", "Rheumatoid factor", "Standard deviation", "Principal coordinate analysis", "Analysis of similarities", "Linear discriminant analysis", "Receiver operating characteristic", "Area under curve", "Confidence interval", "Projections to latent structures discriminant analysis", "Kyoto Encyclopedia of Genes and Genomes", "C-X-C chemokine receptor type 5", "Segmented filamentous bacteria", "Short-chain fatty acids", "Cytotoxic T-lymphocyte-associated protein 4", "Collagen-induced arthritis", "Indoleamine-2,3-dioxygenase" ] }
77
CC BY
no
2024-01-14 23:43:47
Arthritis Res Ther. 2024 Jan 13; 26:21
oa_package/fb/b9/PMC10787489.tar.gz
PMC10787490
0
[ "<title>Background</title>", "<p id=\"Par4\">The eye is a highly specialized sensory organ that plays critical roles in finding food, attracting mates, and evading predators for the survival and reproduction of vertebrates [##UREF##0##1##]. The vertebrate-style eye, also known as the camera-like eye, first emerged approximately 500 million years ago (Mya) in lampreys, one of the most ancient jawless fish among living vertebrate species [##UREF##1##2##–##UREF##2##4##]. Interestingly, the cornea (Cor) of the lamprey may hold key insights into the early primordial development of vertebrate eyes, as it is merely an extension of the sclera covered with transparent skin [##REF##29488315##5##]. Unlike jawless fish, sharks have immovable eyelids and a nictitating membrane, which serves different functions from those of tetrapods, primarily acting as a protective mechanism during feeding or when facing potential threats [##REF##30066959##6##, ##UREF##3##7##]. Bony fishes lack true eyelids, and their eyeballs are separated from the surrounding skin by a shallow circumferential depression between the corneal epithelium (EP) and the skin [##UREF##4##8##]. When vertebrates first colonized terrestrial environments, their ocular surface underwent further evolutionary adaptations, including the development of novel adnexa such as the lacrimal gland, movable eyelids, and eyelashes in the case of mammals. These structures provide protection for the eye, keeping the Cor clean and moist, and enabling adaptation to dry land environments [##UREF##5##9##–##REF##27124372##12##]. It is important to note that throughout the evolutionary timeline of vertebrates, the ocular surface underwent significant adaptive changes required for survival under various environmental pressures, particularly during the water-to-land transition [##UREF##6##13##].</p>", "<p id=\"Par5\">The ocular mucosa (OM) in vertebrates is a layer of mucous membrane that lines the surface of the eyeball and eyelid, providing a physical and immunologic barrier against various challenges [##REF##17264481##14##, ##REF##36362312##15##]. Interestingly, the OM of most vertebrates presents a similar structure, mainly consisting of the Cor and conjunctiva (Figure S##SUPPL##0##1##). However, jawless fish such as lampreys only have a Cor [##UREF##6##13##]. The Cor of vertebrates is composed of two main layers: the EP and the stroma (ST), with the EP featuring a stratified, non-keratinized squamous layer [##REF##29380756##16##]. Moreover, distinct populations of resident immune cells in the corneal EP, including innate lymphoid cells, Langerhans cells, mast cells, macrophages, and T cells, form a complex immune network that enables the Cor to mount prompt immune responses to different environmental challenges [##UREF##7##17##, ##REF##33717118##18##]. The conjunctiva consists of an outer stratified EP richly interspersed with goblet cells, along with an underlying loose connective tissue known as the lamina propria (LP) [##REF##15733300##19##]. In birds and mammals, lymphocytes reside on the conjunctival surface, forming a mucosa-associated lymphoid tissue (MALT) known as the conjunctiva-associated lymphoid tissue (CALT), which functions to detect antigens and contributes to the regulation of the local immune response Knop [##REF##15733300##19##, ##REF##21641931##20##]. Notably, although the Cor and the conjunctiva are anatomically close and face similar environmental challenges and stress, the immune defensive mechanisms in these tissues are distinctly different [##UREF##7##17##]. Critically, the Cor enjoys immune privilege, as its microenvironment is anti-inflammatory and immunosuppressive, thus ensuring the Cor’s transparency. On the other hand, the conjunctiva is a highly reactive tissue that can mount a potent immune response, which is important for clearing pathogens in the OM [##UREF##7##17##, ##REF##15733300##19##].</p>", "<p id=\"Par6\">Commensal microbiota and the immune system have coevolved in animals over the course of millions of years, and their interactions are dynamic and intertwined [##UREF##8##21##, ##REF##22356853##22##]. It is now widely recognized that there is a bidirectional relationship between the microbiome and the immune system. Specifically, the microbiota plays a critical role in training and developing the host immune system, whereas the immune system regulates and shapes the microbiome in various mucosal tissues [##REF##22356853##22##]. Similar to other mucosal surfaces, OM in mammals also hosts a unique microbial community. Previous studies have suggested that an imbalance in microbial homeostasis in the OM can lead to local or systemic inflammatory responses and eye diseases [##REF##23797046##23##, ##REF##33819460##24##]. Although it is known that the OM in mammals contains MALTs, which are essential for maintaining microbial homeostasis [##UREF##7##17##, ##REF##36002743##25##], very little is known regarding the evolutionary origins of OM immunity in early vertebrate species and its primordial roles in immune defense and microbiota homeostasis. Teleost fish represent the oldest bony vertebrates and lack eyelids on their ocular surfaces. Their OM may face strong challenges from aquatic environments. Given the mucosal nature and similar evolutionary forces acting on the OM in vertebrates, we hypothesized that both primitive and modern bony vertebrates have evolved similar immune mechanisms to maintain microbial homeostasis in the OM.</p>", "<p id=\"Par7\">Confirming our hypothesis, we present the first evidence that teleost fish OM possesses a well-defined MALT with structural and functional immune characteristics similar to those described in mammals and other fish species. Importantly, we demonstrate that the trout OM can mount robust antiviral immune and inflammatory responses upon viral infection, resulting in severe tissue damage to the OM epithelial layer. This damage leads to bacterial translocation and profound dysbiosis characterized by a loss of beneficial taxa and the proliferation of pathobionts, followed by a strong antibacterial response. Interestingly, correlation analysis revealed a positive correlation between most antibacterial and inflammatory genes with pathobionts, whereas a negative correlation was observed with beneficial bacteria. Furthermore, we observed a reversal of tissue damage and microbial translocation, as well as the restoration of microbiome homeostasis, accompanied by the disappearance of the inflammatory response. Overall, our findings uncover a previously unrecognized role of teleost fish OM in immune defense and maintaining microbial homeostasis, providing insights into the coevolution between microbiota and mucosal immunity in the OM that emerged in early vertebrate species.</p>" ]
[ "<title>Materials and methods</title>", "<title>Fish</title>", "<p id=\"Par24\">All experimental rainbow trout (~ 10 g, 5–6 months old) were sourced from a fish farm in Chengdu (Sichuan, China) and acclimatized in a 16 °C recirculating aquaculture system for 2 weeks. Japanese pufferfish (<italic>Takifugu rubripes</italic>), largemouth bass (<italic>Micropterus salmoides</italic>), common pleco (<italic>Hypostomus plecostomus</italic>), and common carp (<italic>Cyprinus carpio</italic>) were purchased from an aquatic product market in Wuhan (Hubei, China).</p>", "<title>IHNV infection</title>", "<p id=\"Par25\">Healthy rainbow trout were randomly divided into the control group and the infection group. Trout (infection group) were infected with a dose of 2 mL IHNV (1 × 10<sup>7</sup> TCID<sub>50</sub>) diluted in 10 L aquatic water for 4 h at 16 ℃, and trout (control group) were exposed to virus-free cell culture supernatant and treated the same as the infection group. Then, the trout from both groups were transferred into the new tanks with fresh water and kept for 30 days. Trout were anesthetized with MS-222 before sampling and tissues were collected at 0.5, 1, 4, 7, 14, 21, and 28 DPI.</p>", "<title>Light microscopy and immunofluorescence microscopy studies</title>", "<p id=\"Par26\">The ocular tissues of rainbow trout, Japanese pufferfish, largemouth bass, common pleco (<italic>Hypostomus plecostomus</italic>), and common carp were fixed overnight at 4 °C in 4% neutral buffered formalin. After fixation, the tissues were dehydrated in graded ethanol, embedded in paraffin, and sectioned into 5 μm slices. These slices were stained with H&amp;E and AB according to previously established methods [##REF##35379790##71##]. For detection of IHNV in the trout OM, the sections were incubated overnight at 4 °C with 2 μg/mL mouse anti-IHNV-<italic>N</italic> mAbs (Bio-X Diagnostics, Rochefort, Belgium), followed by 2 μg/mL Cy3 goat anti-mouse IgG for 30 min. Nuclei were stained with DAPI (Invitrogen, Carlsbad, CA, USA) for 8 min before mounting. Cytospin preparations were stained with a Wright-Giemsa stain kit (Thermo Fisher Scientific, Wilmington, DE, USA) according to the manufacturer’s instructions. All sections were observed under an Olympus BX53 microscope (Olympus, Shinjuku City, Tokyo, Japan) and captured with the CellSense Dimension software (Olympus, Shinjuku City, Tokyo, Japan).</p>", "<title>Scanning electron microscopy and transmission electron microscopy (TEM)</title>", "<p id=\"Par27\">For scanning electron microscopy, the fresh and entire ocular tissue of trout was rapidly harvested within 1–3 min using sharp scissors, followed by fixing the tissue with electron microscopy fixative for 2 h. Then the fixed tissues were rinsed with 0.1 M phosphate buffer (PB) (PH 7.4) three times for 15 min each. After that, transfer tissue blocks into 1% OsO4 in 0.1 M PB for 2 h and rinsed again three times by 0.1 M PB (PH7.4) for 15 min each. Next, the tissues were placed in 30%, 50%, 70%, 80%, 90%, 95%, 100%, 100% ethanol for 15 min each, and in isoamyl acetate for 15 min, and finally the tissues were dried in a Critical Point Dryer. Before testing, the tissue samples were sputter-coated with gold for 30 s and then scanned using scanning electron microscopy. For TEM, the tissue samples were fixed by incubated in 30%, 50%, 70%, 80%, 95%, 100%, and 100% ethanol for 20 min each, and finally in acetone twice for 15 min each. They were inserted into the embedding models and polymerized in an oven at 60 °C for 48 h. Subsequently, the resin blocks were ultrathin sliced and transferred onto the 150 meshes cuprum grids, followed by staining with 2% uranium acetate and 2.6% lead citrate for 8 min, respectively. After drying with the filer paper, the cuprum grids were transferred into the grids board to dry overnight. Finally, the cuprum grids were observed under a TEM, and images were captured at the Institute of Hydrobiology of the Chinese Academy of Sciences.</p>", "<title>Laser capture microdissection</title>", "<p id=\"Par28\">Ten-μm-thick, sagittally oriented cryosections of trout ocular tissue from the control, 4 DPI, and 28 DPI groups were prepared as described in a previous study [##REF##36426979##72##]. Briefly, the sections underwent successive immersion in 70% ethanol, ddH<sub>2</sub>O, 75%, 95%, and 100% ethanol for 30 s each, and then immersion in xylene for 5 min. The xylene was allowed to completely evaporate in a sterile fume hood. Next, using a laser capture microdissection (LCM) system, we captured the Cor, BC, and FC regions of the OM. A total of 20 cryosections per trout were used to capture the Cor, BC, and FC samples onto Arcturus Capture Macro LCM caps (Applied Biosystems, Waltham, USA). The captured samples were then immediately processed to extract total RNA using the ArcturusTM PicoPureTM RNA Isolation Kit (Applied Biosystems, Waltham, USA).</p>", "<title>RNA extraction and qPCR analysis</title>", "<p id=\"Par29\">Total RNA was extracted from trout Cor, BC, and FC using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). RNA concentration was assessed using NanoDrop® ND-2000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA), whereas integrity was determined through agarose gel electrophoresis. Subsequently, about 1 μg of total RNA was used to synthesize cDNA by the Hifair III First-Strand Synthesis System (YEASEN, Shanghai, China). The obtained cDNA was diluted to equal concentrations and used as a template for qPCR analysis. The qPCR program consisted of a first step at 95 °C for 5 min, followed by 40 cycles at 95 °C for 10 s, and 58 °C for 30 s. To determine the viral load, an IHNV plasmid standard curve was constructed, and the IHNV copy number was calculated by extrapolating the mean of each gene copy number from the standard curve. The primers used for qPCR are provided in Table S##SUPPL##0##1##.</p>", "<title>Flow cytometry analysis</title>", "<p id=\"Par30\">The proportion of bacteria in the skin, gills, gut, Cor, BC, and FC was determined through flow cytometry analysis. Briefly, the collected tissues were homogenized in sterile phosphate-buffered saline (PBS) and passed through 100 μm cell strainers (SPL Life Sciences, Gyeonggi-do, Republic of Korea). After that, the suspension was centrifuged twice at 400 × <italic>g</italic> for 6 min at 4 °C to discard cells and debris, followed by centrifugation at 16,000 × <italic>g</italic> for 10 min at 4 °C to collect the precipitation (containing bacteria). Finally, the microbiota of Cor, BC, and FC were collected and resuspended with 200 μL PBS, respectively. For bacterial count, the suspension of equal volume (10 μL) was analyzed, and the number of bacteria labeled with SYTO BC by CytoFLEX LX flow cytometer was counted (Beckman Coulter, Brea, CA, USA). To determine the proportion of lymphocytes and myeloid cells in the skin, gills, gut, Cor, BC, and FC, the tissues were homogenized in DMEM (Gibco™, Gaithersburg, MD, USA) supplemented with 1% FBS and filtered by 100 μm cell strainers. The obtained cell suspensions were layered onto a 34 to 51% Percoll (Cytiva, Uppsala, Sweden) discontinuous density gradient and centrifuged at 400 × <italic>g</italic> for 30 min at 4 °C. The leukocytes at the interface were collected and then washed with DMEM twice for 6 min each. the proportion of lymphocytes and myeloid cells was determined based on FSC and SSC signals detected by CytoFLEX LX flow cytometer (Beckman Coulter, Brea, CA, USA).</p>", "<title>Antibiotics treatment</title>", "<p id=\"Par31\">The method for antibiotics was used as previous studies reported with slightly modified [##REF##31816414##73##]. Rainbow trout were exposed to a mixture of the 6 antibiotics (including Amoxicillin crystalline, Kanamycin sulfate, Erythromycin, Enrofloxacin, oxytetracycline dihydrate, and Doxycycline hydrochloride, 25 mg/L for each antibiotic) for 4 days. Exposure solutions were renewed daily to maintain the appropriate concentration of antibiotics. To detect the microbial changes in trout OM after treatment, Cor, BC, and FC tissue were collected, weighed, and homogenized in 1 ml PBS (filtered with 0.22 μm) for coating plates to calculate the number of colonies.</p>", "<title>RNA-Seq library and data analyses</title>", "<p id=\"Par32\">The Cor, BC, and FC samples from the control group and the IHNV-infected group at 4 and 28 DPI were sent to Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China) for RNA-Seq analysis. RNA-Seq libraries were prepared and analyzed as we previously described [##REF##31645417##29##]. The prepared libraries were then sequenced using the Illumina HiSeq X Ten/NovaSeq 6000 sequencer to generate paired-end reads with a length of 150 bp. The raw reads were trimmed and quality-controlled using SeqPrep and Sickle, and the remaining clean reads were mapped to the genome assembly of <italic>Oncorhynchus mykiss</italic>. Genes were considered as the differentially expressed genes (DEGs) if false discovery rate (FDR) ≤ 0.05 and |log2 (fold-change) |≥ 1.</p>", "<title>Analysis of bacterial translocation in trout OM</title>", "<p id=\"Par33\">For microbiota detection of the trout Cor, BC, and FC, fluorescent in situ hybridization was applied as previously described [##UREF##16##74##]. Cryosections (10 µm) of ocular tissue smears from control trout were fixed in 4% PFA for 10 min and stained with Cy3-labeled EUB338 (anti-sense probe) and Cy3-labeled NONEUB oligonucleotide probes at their 5’ ends. Hybridizations were conducted in 2 × SSC/10% formamide (hybridization buffer) with 1 μg/mL of the labeled probes for 14 h at 37 °C. Subsequently, the slides were washed with hybridization buffer without probes, washing buffer (2 × SSC), and PBS each two times at 37 °C. Nuclei were stained with DAPI (Invitrogen, Carlsbad, CA, USA) for 8 min before mounting. All sections were observed under an Olympus BX53 microscope and captured with the CellSense Dimension software (Olympus, Shinjuku City, Tokyo, Japan).</p>", "<title>qPCR to determine bacterial abundance in trout tissues</title>", "<p id=\"Par34\">Total genomic DNA was isolated from Cor, BC, FC, skin, gills, and gut tissues using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). Absolute qPCR analysis was conducted to estimate the copy numbers of total bacteria using V3–V4 region-specific primers shown in Table S##SUPPL##0##1##. In brief, pMD 19-T vector containing the 16S rRNA gene V3–V4 fragments insert was prepared from recombinant DH5α Escherichia coli cells. Plasmid DNA was isolated from an overnight selective culture using HiPure Plasmid Micro Kit (OMEGA, Norcross, USA). Standard curves were generated by serial dilutions of known copy numbers of plasmids containing 16S rRNA gene V3-V4 fragments [##REF##26454867##75##]. The Ct values of the samples were extrapolated into the standard curve to calculate the copy number. qPCR was conducted in a 20-μL reaction mixture containing 10 μL 2 × SYBR Green qPCR Mix (YEASEN, Shanghai, China), 0.5 μL of each primer (10 μM), 1.0 μL of 100 ng DNA templates, and 8.0 μL of nuclease-free water. The qPCR program consisted of an initial step at 95 °C for 5 min, followed by 40 cycles at 95 °C for 10 s, and 58 °C for 30 s. All samples were analyzed in triplicate to ensure accuracy.</p>", "<title>Bacterial 16S rRNA sequencing and data analyses</title>", "<p id=\"Par35\">Purified amplicons were equimolarly pooled, and sequencing was performed using the MiSeq platform with the MiSeq Reagent Kit v3 to generate paired-end reads with a length of 250 bp (Illumina, China). Sequence data analysis was conducted using QIIME2 and R packages [##REF##31341288##76##]. Raw reads were de-multiplexed using the demux plugin and then filtered, denoised, merged, and chimera-removed by DADA2 [##REF##27214047##77##]. Based on SILVA database (Release 132), taxonomy was assigned to amplicon sequence variants (ASVs) using the classify-sklearn naïve Bayes taxonomy classifier in the feature-classifier plugin [##UREF##17##78##]. Finally, the diversity plugin was used to estimate alpha- (Chao1 and Shannon) and beta (weighted UniFrac) diversity metrics. LEfSe analysis was performed to detect differentially abundant taxa across groups using default parameters [##UREF##18##79##].</p>", "<title>Statistics</title>", "<p id=\"Par36\">Unpaired Student’s <italic>t</italic> test (Prism version 8.0; GraphPad) and one-way analysis of variance with Bonferroni correction were used to evaluate the differences between the OM sites or groups Data are expressed as mean ± SEM. All <italic>p</italic> values &lt; 0.05 were considered statistically significant.</p>" ]
[ "<title>Results</title>", "<title>The teleost OM shares common anatomical features with other vertebrates</title>", "<p id=\"Par8\">The eyes are the most important sensory organs for fish, and in most fish species, the eyes are positioned on the sides of their heads without eyelids, as seen in tetrapods (Fig. ##FIG##0##1##a). To examine the basic structure of the teleost eye, we stained paraffin sections of trout eyes with hematoxylin and eosin (H&amp;E) (Fig. ##FIG##0##1##b). Our findings reveal that the structure of teleost fish eyes is basically similar to that of tetrapods, including the lens, iris, sclera, retina, Cor, and conjunctiva (which can be further divided into bulbar conjunctiva (BC) and fornix conjunctiva (FC)) (Fig. ##FIG##0##1##b, c). Histological examination of the trout eyes showed that the ocular surface is covered by a mucous membrane known as the OM, primarily consisting of the Cor, BC, and FC (Fig. ##FIG##0##1##b, c). Next, we conducted histological analysis via H&amp;E (Figure S##SUPPL##0##2##, upper) and Alcian Blue (AB) (Figure S##SUPPL##0##2##, lower) staining of OMs obtained from five different teleost families (Figure S##SUPPL##0##3##): Tetraodontidae, Centrarchidae, Salmonidae, Loricariidae, and Cyprinidae. The OMs of all species examined displayed a similar overall structure, including rainbow trout (<italic>Oncorhynchus mykiss</italic>) (Figure S##SUPPL##0##2##a), Japanese pufferfish (<italic>Takifugu rubripes</italic>) (Figure S##SUPPL##0##2##b), largemouth bass (<italic>Micropterus salmoides</italic>) (Figure S##SUPPL##0##2##c), common pleco (<italic>Hypostomus plecostomus</italic>) (Figure S##SUPPL##0##2##d), and common carp (<italic>Cyprinus carpio</italic>) (Figure S##SUPPL##0##2##e). As shown in Figure S##SUPPL##0##2##, the BC and FC exhibited two typical layers, namely the EP and LP, whereas the Cor consisted of the EP and ST. Additionally, AB staining revealed a large number of goblet cells in the EP of the BC and FC, whereas these cells were not observed in the EP of the Cor. Despite some minor morphological differences of five different teleost families, the OM all harbor myeloid and lymphoid cells mainly scattered in the EP of the BC and FC, similar to teleost MALTs found in the skin, gut, nose, and gills (Figure S##SUPPL##0##2##). Interestingly, using immunofluorescence microscopy, we observed that IgT<sup>+</sup> and IgM<sup>+</sup> B cells were present mostly within the epithelial layer (data not shown) and not the lamina propria unlike in the mammalian OM where they are predominantly dispersed in the follicles and lamina propria [##REF##36002743##25##]. Transmission electron microscope (TEM) and scanning electron microscope images confirmed the AB staining results, showing the presence of goblet cells in the BC and FC, but not in the Cor. Furthermore, the OM displayed abundant microplicae and microvilli, with longer microvilli observed in the BC and FC compared to the Cor (Fig. ##FIG##0##1##d). These results highlight distinct differences in the organizational structure characteristics of the Cor, BC, and FC, suggesting the existence of different microenvironments or niches among them.</p>", "<title>Varying sites within the teleost OM harbor diverse and distinct commensal microbiota</title>", "<p id=\"Par9\">Teleost fish are known to have diverse microbial communities colonizing their mucosal surfaces [##REF##20676094##26##–##REF##31645417##29##]. Using scanning electron microscope, we observed the presence of bacteria in the Cor, BC, and FC (Fig. ##FIG##0##1##e), and the abundance of the ocular microbiome resembled that of the skin, but was lower than that of the gills and gut, as determined by qPCR analysis (Figure S##SUPPL##0##4##a). SYTO BC Green-Fluorescent Nucleic Acid staining was used to characterize the microbial distribution and composition in the Cor, BC, and FC. Here, we found that microbial abundance was highest in the FC, followed by the BC, and lowest in the Cor (Fig. ##FIG##1##2##a, b; samples without SYTO BC Green staining are shown in Figure S##SUPPL##0##4##b). Furthermore, analysis of 16S rRNA gene sequencing data confirmed the highest abundance of bacterial communities in the FC, with relatively lower abundances in the BC and Cor (Fig. ##FIG##1##2##c, d), as indicated by the Shannon and Chao1 diversity indices. These differences in the OM sites may be attributed to the Cor and BC being more exposed to water flushing, resulting in relatively less microbial colonization, whereas the FC, with its numerous folds, provides a favorable environment for microbial colonization. Principal coordinate analysis (PCoA) revealed distinct clustering patterns in the microbiome compositions of the Cor, BC, and FC (Fig. ##FIG##1##2##e). Venn diagram analysis also demonstrated marked differences in microbiota composition among the Cor, BC, and FC (Fig. ##FIG##1##2##f). Additionally, we observed lower abundance of aerobic and gram-positive bacteria in the Cor compared to the BC and FC, whereas anaerobic and gram-negative bacteria exhibited higher abundances in the Cor compared to the BC and FC. Importantly, the abundance of biofilm-forming and potentially pathogenic bacteria was higher in the FC compared to the Cor and BC (Fig. ##FIG##1##2##g), suggesting that the FC may experience stronger selection pressure from the microbial communities residing on its mucosal surface.</p>", "<title>Trout OM exhibits distinct immune characteristics in different anatomical niches</title>", "<p id=\"Par10\">To determine the presence of immune components in trout OM, we conducted flow cytometry analysis to characterize immune-related cells in the Cor, BC, and FC at steady state. Our findings revealed typical lymphocyte populations and myeloid cell populations in these OM regions (Fig. ##FIG##2##3##a), similar to other mucosal tissues such as the skin, gills, and gut (Figure S##SUPPL##0##5##). Interestingly, the percentage of lymphocytes in trout OM was comparable to that in the skin, but significantly lower than that in the gills and gut. Notably, the FC exhibited a higher proportion of lymphocytes and myeloid cells compared to the Cor and BC, suggesting a prominent immune role of the FC in trout OM (Fig. ##FIG##2##3##b, c). To further investigate the immune gene expression profile in different sites of trout OM, we dissected three regions using laser capture microdissection (LCM) (Fig. ##FIG##2##3##d) and extracted total RNA for immune gene expression analysis. Our results demonstrated that the FC had significantly higher expression levels of T cell-related markers (<italic>cd4-1</italic>, <italic>cd8α</italic>, <italic>tcrα</italic>, <italic>cd8β</italic>, <italic>cd4-2b</italic>, <italic>tcrβ</italic>, and <italic>cd4-2a</italic>), B cell-related markers (<italic>igd</italic>, <italic>igm</italic>, <italic>igt</italic>, <italic>cd80/86</italic>, and <italic>cd22</italic>), myeloid cell-related markers (<italic>ncf2</italic>, <italic>cd11b, mrc1</italic>, <italic>mpeg1</italic>, <italic>mpo</italic>, <italic>cd209</italic>, and <italic>lyz</italic>), as well as cytokines (<italic>ccr10</italic>, <italic>ccl20b</italic>, <italic>ccl9</italic>, <italic>cxcl13</italic>, and <italic>ccl25</italic>) compared to the Cor and BC (Fig. ##FIG##2##3##e). Collectively, these results indicate that trout OM constitutes a unique immune cell microenvironment and exhibits a distinct immune transcriptional profile under a steady state.</p>", "<title>The microbiome contributes to shaping the teleostocular immune environment</title>", "<p id=\"Par11\">To further evaluate whether the high abundance of microbiota residing on the ocular mucosal surface contributes to shaping its immune environment, we measured the expression level of immune-related genes in the trout OM after exposure to a mixture of antibiotics. After 4 days, we performed an initial analysis of the abundance of microbiota using plate count and qPCR (Fig. ##FIG##3##4##). Our results indicated that the number of colonies and the expression levels of 16 s rRNA V3-V4 region decreased markedly in Cor, BC, and FC tissues treated with the antibiotics compared to the control group (Fig. ##FIG##3##4##a–c). Subsequently, we detected the expression of T cell-related markers (<italic>tcrα</italic>, <italic>tcrβ</italic>, <italic>cd8α</italic>, <italic>d8β</italic>, <italic>cd4-1</italic>,), B cell-related markers (<italic>igd</italic>, <italic>igm</italic>, <italic>igt</italic>), myeloid cell-related markers (<italic>ncf2</italic>, <italic>cd11b, mpeg1</italic>, and <italic>mpo</italic>), chemokines (<italic>ccr10</italic>, <italic>ccl20b</italic>, <italic>ccl9</italic>, <italic>cxcl13</italic>, and <italic>ccl25</italic>), as well as interleukins (<italic>il1β</italic>, <italic>il8</italic>, <italic>il10b</italic>, and <italic>il6</italic>) in the OM and found the expression of these immune-related genes also decreased significantly in the antibiotics treatment group (Fig. ##FIG##3##4##d). Taken together, these findings suggest that microbiota in OM plays a crucial role in shaping the ocular immune environment.</p>", "<title>The OM of trout mounts a robust immune response upon IHNV infection</title>", "<p id=\"Par12\">We next evaluated whether the Cor, BC, and FC serve as immune sites and generate immune responses, we developed a bath infection model using IHNV and collected tissue samples at several time points (Fig. ##FIG##4##5##a). Our result showed that infected fish displayed typical symptoms such as exophthalmia and petechial hemorrhages around the eyes at 4 DPI (Fig. ##FIG##4##5##b), and approximately 44% of the fish died within 2 weeks of infection (Fig. ##FIG##4##5##c). Furthermore, the FC exhibited a higher viral load after IHNV infection compared to the Cor and BC. The viral load in all three sites peaked at 4 DPI and gradually decreased, reaching pre-challenge levels at 28 DPI (Fig. ##FIG##4##5##d). Similar results were observed in OM paraffin sections stained with an anti-IHNV-<italic>N</italic> monoclonal antibody (Figure S##SUPPL##0##6##a, b; isotype-matched control Abs as shown in Figure S##SUPPL##0##7##). Consistently, H&amp;E staining further confirmed these findings (Figure S##SUPPL##0##6##c, d). This suggests that the FC may be one of the primary targets of the virus. Taken together, our results confirm the successful establishment of an IHNV infection model in the OM of trout.</p>", "<p id=\"Par13\">Next, to assess the immune responses of trout OM, we conducted transcriptome sequencing analyses of the Cor, BC, and FC at 4 and 28 DPI. RNA-Seq analysis revealed significant modifications in a total of 2132 genes (Cor), 2677 genes (BC), and 3,281 genes (FC) at 4 DPI following IHNV infection compared to the controls. Among these genes, 1386, 1876, and 1623 were upregulated, whereas 746, 801, and 1,658 were downregulated in the Cor, BC, and FC, respectively. Similarly, at 28 DPI following IHNV infection, a total of 767 genes (Cor), 380 genes (BC), and 551 genes (FC) were significantly modified, with 378, 99, and 299 genes being upregulated, and 380, 281, and 252 genes being downregulated in the Cor, BC, and FC, respectively (Fig. ##FIG##4##5##e). Furthermore, we observed a significant upregulation of numerous immune-related genes in the Cor, BC, and FC at 4 DPI, with expression levels returning to nearly normal levels at 28 DPI (Fig. ##FIG##4##5##f). These differentially expressed genes (DEGs) were primarily enriched in gene pathways related to antiviral, antibacterial, and inflammatory responses (Fig. ##FIG##4##5##g), as well as pathways associated with pattern recognition receptors, B and T cell receptors, and chemokine signaling (Figure S##SUPPL##0##6##) at 4 DPI. Specifically, at 4 DPI, several antiviral genes (<italic>rig-i</italic>, <italic>irf3</italic>, <italic>ifni</italic>, <italic>ifn-γ</italic>, <italic>mx1</italic>, <italic>lgp2</italic>, <italic>mda5</italic>, and <italic>trim25</italic>), antibacterial genes (<italic>cmpk2</italic>, <italic>hp1</italic>, <italic>lect2</italic>, <italic>cd209</italic>, <italic>c3</italic>, <italic>lyz2</italic>, <italic>cath1</italic>, and <italic>nox1</italic>), and inflammation genes (<italic>saa</italic>, <italic>il6</italic>, <italic>il8</italic>, <italic>il10b</italic>, <italic>il1β</italic>, <italic>il18</italic>, <italic>il4r2</italic>, and <italic>il1r2</italic>) were significantly upregulated (Fig. ##FIG##4##5##h). At 28 DPI, the expression of these genes had largely returned to the pre-challenge levels (Fig. ##FIG##4##5##g, h, Figure S##SUPPL##0##8##). To further explore the immune responses of trout Cor, BC, and FC, we dissected the three regions using LCM and extracted total RNA to detect changes in immune genes. Consistent with the transcriptome results, qPCR analysis demonstrated a strong immune response in the Cor, BC, and FC at 4 DPI, as indicated by a significant increase in the expression of antiviral (<italic>rig-i</italic>, <italic>ifn-γ</italic>, <italic>mx1</italic>, <italic>mda5</italic>, and <italic>lgp2</italic>) and inflammatory genes (<italic>saa</italic>, <italic>il1β</italic>, <italic>il6</italic>, <italic>il8</italic>, and <italic>il10b</italic>). The immune response gradually returned to homeostasis at 28 DPI (Fig. ##FIG##4##5##i, j). Notably, the FC of infected trout exhibited a stronger immune response, both antiviral and inflammatory, compared to the Cor and BC (Fig. ##FIG##4##5##i, j). These findings suggest that IHNV infection elicits a stronger immune response in the trout FC, highlighting its significant role in the antiviral infection within the local OM environment.</p>", "<title>IHNV infection causes bacterial translocation in trout OM</title>", "<p id=\"Par14\">The tissue damage and antibacterial immune response triggered by IHNV infection led us to speculate whether it could disrupt microbial homeostasis. Through fluorescent in situ hybridization (FISH) analysis, we observed a significant translocation of bacteria from the mucus layer across the EP in the Cor, BC, and FC at 4 DPI compared to the control group. The number of translocated bacteria was higher in the FC, but this was substantially restored at 28 DPI (Fig. ##FIG##5##6##a, b). To further investigate whether bacterial translocation into the mucosal EP induced an antibacterial immune response in the trout OM, we analyzed the transcript levels of antibacterial genes (<italic>lyz2</italic>, <italic>hp1</italic>, <italic>cath1</italic>, <italic>c3</italic>, <italic>cd209</italic>, <italic>lect2</italic>, <italic>nox1</italic>, and <italic>cmpk2</italic>) in the Cor, BC, and FC using LCM. We observed a significant increase in these genes at 4 DPI (Fig. ##FIG##5##6##c). Consistent with the histopathological changes and inflammatory response, a stronger antibacterial immune response was observed in the FC compared to the Cor and BC (Fig. ##FIG##5##6##c). Overall, our findings demonstrate that IHNV infection may lead to secondary bacterial infection, resulting in an antibacterial immune response in trout OM.</p>", "<title>IHNV infection induces profound dysbiosis in the OM of trout</title>", "<p id=\"Par15\">To investigate the effect of IHNV infection on the microbial composition of the OM, trout Cor, BC, and FC were collected from control and IHNV-infected trout at 4 and 28 DPI for 16S rRNA sequencing analysis. The analysis of Chao 1 indices revealed a significant increase in the richness of bacterial communities in the Cor and FC at 4 DPI, whereas it remained almost unchanged in the BC (Fig. ##FIG##6##7##a). Additionally, the diversity of bacterial communities in the FC was significantly decreased at 4 DPI, but not in the Cor and BC (Fig. ##FIG##6##7##b). A circos plot was generated to visualize the changes in bacterial structure at the phylum and order levels in OM between control and infected fish (Fig. ##FIG##6##7##c, d). At the phylum level, we observed a significant increase in the abundance of Actinobacteriota, Chloroflexi, and Acidobacteriota, and a decrease in Firmicutes in the Cor at 4 DPI. In the BC, Chloroflexi and Acidobacteriota were significantly decreased. Conversely, significant changes occurred in all top six phyla in the FC. Specifically, Proteobacteria, Actinobacteriota, Chloroflexi, and Acidobacteriota increased significantly, whereas Firmicutes and Bacteroidota decreased significantly at 4 DPI (Fig. ##FIG##6##7##e). At the order level, IHNV infection resulted in a significant increase in the abundance of Rhizobiales, Micrococcales, and Ktedonobacterale, and a significant reduction in Lactobacillales and Burkholderiales in the Cor. In the BC, there was a significant decrease in the abundance of Rhizobiales and Ktedonobacterale, coupled with an increase in Pseudomonadaies at 4 DPI. Interestingly, similar changes were observed in the FC tissue at the order level, with an increase in Rhizobiales, Micrococcales, and Ktedonobacterale, and a decrease in Lactobacillales at 4 DPI (Fig. ##FIG##6##7##f).</p>", "<p id=\"Par16\">LEfSe (linear discriminant analysis effect size) analysis was conducted next to further explore the microbial biomarkers contributing to the structural changes in bacteria among the different sites (Fig. ##FIG##7##8##a–c, Figure S##SUPPL##0##9##a–c). Significant changes in bacterial composition were observed in the Cor, BC, and FC tissues at 4 DPI (Fig. ##FIG##7##8##a–c). Specifically, there was a significant increase in <italic>Aeromonas</italic> abundance in all three regions, whereas the abundance of <italic>Bosea</italic> and <italic>Lysinibacillus</italic> increased significantly in the FC at 4 DPI (Fig. ##FIG##7##8##d). Furthermore, <italic>Deinococcus</italic> abundance decreased significantly in all of the examined regions of trout OM, whereas <italic>Lactococcus</italic> and <italic>Pedobacter</italic> only decreased significantly in the Cor and FC at 4 DPI. Interestingly, the abundance of <italic>Lactococcus</italic> significantly increased at 28 DPI (Fig. ##FIG##7##8##e), possibly indicating a return to homeostasis as the dominant bacterial group. Importantly, as the inflammatory response dissipated at 28 DPI, the bacterial community composition of the trout OM exhibited minor differences compared to the control fish (Figs. ##FIG##6##7## and ##FIG##7##8##d, e, Figure S##SUPPL##0##9##a–c), suggesting a strong association between microbial imbalance in trout OM and the inflammatory response.</p>", "<title>Analysis of the correlations between the relative abundance of the disordered microbiome and immune-related genes in the OM of trout</title>", "<p id=\"Par17\">The large number of microorganisms inhabiting mucosal surfaces is closely linked to immunity [##REF##22674334##30##]. In this study, we conducted correlation analyses between the relative abundance of OM microbiota at the genus level and immune-related genes, specifically inflammation, antiviral, and antibacterial genes, using distance-based redundancy analysis (db-RDA) (Fig. ##FIG##8##9##a–c) and Spearman correlation analysis (Fig. ##FIG##8##9##d–f). Our findings revealed a strong association between OM microbiota and immune-related genes. Notably, changes in <italic>Aeromonas</italic> abundance in the three regions of trout OM were positively associated with the levels of antibacterial and inflammation genes at 4 DPI (Fig. ##FIG##8##9##a–f), suggesting that <italic>Aeromonas</italic> may be the primary contributor to the dramatic inflammatory, antiviral, and antibacterial responses in the OM. Furthermore, variations in the relative abundance of pathogenic bacteria (<italic>Bosea</italic> and <italic>Lysinibacillus</italic>) were only positively related to most immune-related genes in the FC. <italic>Bosea</italic> was significantly associated with the antiviral gene (<italic>mx1</italic>, <italic>irf3</italic>, <italic>irf9</italic>, <italic>ifn1</italic>, and <italic>mad5</italic>), antibacterial gene <italic>tlr3</italic> and inflammation genes <italic>il4r2</italic> and <italic>tsp1</italic> (Fig. ##FIG##8##9##c, f). Importantly, we found that beneficial bacteria such as <italic>Lactococcus</italic>, <italic>Deinococcus</italic>, and <italic>Pedobacter</italic> were negatively associated with most antiviral, antibacterial, and inflammation genes (Fig. ##FIG##8##9##a–f). This suggests that pathogenic bacteria may largely contribute to the expression of antiviral, antibacterial, and inflammation genes, whereas beneficial bacteria play the opposite role. Interestingly, most immune-related genes significantly associated with beneficial bacteria were observed in the Cor and FC, but not in the BC (Fig. ##FIG##8##9##d–f). These observations suggest that IHNV infection may impose various selective pressures on the microbiota of different anatomical niches, leading to unique variations in the OM microbiome. Furthermore, these data indicate that there is a cross-talk between microbiota and immunity in the trout OM.</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par18\">The eye is a functionally conserved sensory organ among vertebrates and has been subjected to similar selective forces from pathogens and mucosal microbial communities, regardless of whether the organisms are aquatic or terrestrial. Therefore, it is likely that they have evolved similar strategies to control pathogens and maintain ocular microbiota homeostasis. However, the immune roles of OMs have mainly been studied in mammals and birds, whereas little is known regarding the primordial roles of teleost OM in mucosal homeostasis. In this study, we provide the first evidence of a well-defined MALT in teleost OM and reveal its previously unrecognized role in immune defense and maintaining microbial homeostasis. This provides evolutionary insights into the potential interaction between microbiota and mucosal immunity in the OM of early vertebrates.</p>", "<p id=\"Par19\">Here, we found that the anatomical structure of teleost OM resembles that of other jawed vertebrates, primarily consisting of the Cor and conjunctiva [##REF##27612182##31##]. Since teleost fish lack eyelids, the conjunctiva can be further divided into two regions: the BC and FC, unlike sharks and tetrapods [##REF##30066959##6##, ##REF##27124372##12##], which have palpebral conjunctiva. Additionally, similar to other teleost MALTs [##UREF##9##32##], we observed the presence of a diverse microbial community in trout OM, although its abundance was significantly lower than that of the skin, gills, and gut. Our results support the notion that the diversity and abundance of bacteria are often influenced by the specific anatomical niche in which they reside [##REF##22699609##33##]. Consistent with previous findings in the mammalian OM, we observed distinct bacterial communities in different OM sites (Cor, BC, and FC), with the FC exhibiting higher microbial richness and diversity. Moreover, in terms of phenotypes such as biofilm formation and potential pathogenicity, the relative abundance of microbiota in the FC was significantly higher than in the Cor and BC, indicating that FC is subject to greater selective pressure from the microbial communities residing on its mucosal surface. Another conserved feature of teleost MALTs, similar to mammalian MALTs, is the presence of numerous leukocytes (i.e., lymphocytes and myeloid cells) [##REF##26274978##34##]. Here, we demonstrate for the first time that the teleost OM contains lymphocytes, myeloid cells, and cytokine expression, which is consistent with our previous findings in the teleost skin, gills, and gut [##REF##20676094##26##–##REF##26869478##28##]. Interestingly, we observed a higher abundance of leukocytes in the FC compared to the Cor and BC, suggesting a prominent role of the FC in trout OM immunity. Importantly, the abundance of lymphocytes at different locations strongly correlates with microbiota burden, thus highlighting the coevolutionary principles between microbiota and mucosal immunity in early vertebrate species. In mammals, the presence of microbes plays an essential role in shaping a favorable immune environment in the mucosa [##REF##33212011##35##]. Studies have shown that the use of antibiotics leads to reductions in commensal microbes and alterations in microbiota composition, which in turn can impact the innate immune defense of the host [##REF##33212011##35##–##REF##35986099##37##]. In this study, we eliminated symbiotic microbiota with antibiotics treatment and found immune-related genes were significantly reduced in the Cor, BC, and FC at OM, which is consistent with previous findings in the mice [##REF##33212011##35##], implying that microbiota is crucial in shaping the immune environment of the OM.</p>", "<p id=\"Par20\">To further assess the immune responsiveness of the teleost OM, we established an IHNV infection model in trout through bath exposure, which mimics natural infection. As expected, the infected fish exhibited typical symptoms of IHN, including exophthalmia, petechial hemorrhages around the eyes, and darkening of the skin [##REF##27287024##38##]. Furthermore, we observed a significant increase in IHNV load in the Cor, BC, and FC as early as 4 DPI, reaching near pre-challenge levels at 28 DPI. Notably, the FC showed the highest number of viral copies, whereas the Cor had very few viral copies, which was consistent with previous studies on human OM infection with SARS-CoV-2 [##REF##35231027##39##]. Importantly, these findings correlate with severe histological changes in the EP of FC, suggesting that the FC is likely the primary entry point for this virus to invade the trout eye. Additionally, transcriptome analysis revealed the immune role of trout OM and unveiled its previously unrecognized capacity to respond to viral infection. Specifically, we observed an upregulation of antiviral genes, including <italic>rig-i</italic>, <italic>mx1</italic>, <italic>ifn-γ</italic>, <italic>irf3</italic>, and <italic>mda5</italic>, which are known to be crucial for effective antiviral responses in mucosal surfaces, particularly during the early stages of infection [##REF##21187438##40##, ##REF##24886842##41##]. Moreover, the IHNV challenge led to significant upregulation of pro-inflammatory cytokines (<italic>il1β</italic>, <italic>il6</italic>, and <italic>il8</italic>), anti-inflammatory cytokines (<italic>il10b</italic>), and inflammation regulation cytokines (<italic>saa</italic>, <italic>il4r2</italic>, and <italic>il1r2</italic>) at 4 DPI, with levels returning to baseline conditions at 28 DPI. Notably, consistent with findings in mammals that the conjunctiva is a highly reactive tissue and mounts a potent immune response to external stimuli [##UREF##10##42##, ##REF##34698365##43##], we observed a stronger immune response in the trout conjunctiva compared to the Cor. Interestingly, within the conjunctiva, the FC exhibited a higher level of immune response than the BC, suggesting that the FC plays a pivotal role as an important effector site in teleost ocular mucosal immunity.</p>", "<p id=\"Par21\">In mammals, previous studies have demonstrated that the inflammatory response triggered by a primary viral infection can increase susceptibility to secondary bacterial infections and disrupt the microbial balance in the conjunctiva [##UREF##11##44##, ##UREF##12##45##]. Consistent with this finding, we observed a significant increase in the levels of bacteria translocated from the mucus layer across the OM EP upon IHNV infection, particularly in the FC. Importantly, these findings correlated with the upregulation of antibacterial genes (<italic>lyz2</italic>, <italic>hp1</italic>, <italic>cath1</italic>, <italic>c3</italic>, <italic>cd209</italic>, <italic>lect2</italic>, <italic>nox1</italic>, and <italic>cmpk2</italic>), suggesting that IHNV infection may lead to microbiota translocation and subsequent strong antibacterial response. Furthermore, 16S rRNA analysis revealed a significant increase in microbial richness in the Cor and FC at 4 DPI. Notably, we observed a decrease in OM microbial diversity in the infected trout FC, as indicated by the Simpson index, which aligns with previous studies in mammals linking microbial diversity to various disorders [##REF##34110438##46##, ##REF##32576065##47##]. Additionally, similar to the ocular microbiome of humans, our results demonstrated that the trout OM harbors a diverse array of bacterial taxa belonging to six different phyla, representing approximately 90% of all OTUs. The dominant phyla in the teleost ocular microbiome were Proteobacteria (the most abundant phylum in human ocular microbiomes), followed by Actinobacteria and Firmicutes. Interestingly, the two dominant phyla in the trout ocular microbiome, Chloroflexi, and Acidobacteriota, are widely distributed in soil and freshwater sediments, whereas their abundance in the human ocular microbiome is low [##REF##33750980##48##, ##REF##31783682##49##]. Remarkably, the abundance of the Proteobacteria phylum in the trout FC microbial community significantly increased after IHNV infection. Proteobacteria are known to include various pathogens with adherent and invasive properties that can subvert host defenses and induce pro-inflammatory responses [##REF##29422757##50##–##REF##26210164##52##]. This finding is consistent with previous observations in mammalian conjunctiva [##REF##33717118##18##]. Furthermore, we observed a significant decrease in the Firmicutes. This contributed to a reduced Firmicutes/Bacteroidetes ratio, which is known to be associated with dysbiosis and inflammatory diseases [##REF##33139627##53##]. Therefore, our study demonstrates that while the composition and structure of the ocular microbiome in bony fish differ from those in mammals, the response of the ocular microbiota to pathogens is conserved across vertebrates.</p>", "<p id=\"Par22\">Previous studies have reported that viral infections can disrupt the microbial balance and lead to ocular inflammation due to the proliferation of opportunistic pathogens [##REF##23880529##54##, ##REF##30505304##55##]. As expected, our findings show that IHNV infection in the trout OM resulted in an increase in pathogenic bacteria abundances, including <italic>Aeromonas</italic>, <italic>Lysinibacillus</italic>, and <italic>Bosea</italic>, which have been associated with ocular diseases in mammals [##REF##29422757##50##, ##REF##33549582##56##, ##REF##33359511##57##]. Among them, <italic>Aeromonas</italic> species, which are widely distributed in natural environments, can trigger proinflammatory responses in a variety of hosts, including humans, aquatic animals, livestock, and poultry, through the release of various pro-inflammatory cytokines (e.g., <italic>il-1β</italic>, <italic>il-6</italic>, <italic>il-8</italic>, <italic>il-12</italic>, and <italic>tnf-α</italic>) [##REF##10768977##58##, ##UREF##13##59##]. In addition, studies in mammals have reported that <italic>Aeromonas</italic> is capable of causing ocular infection leading to inflammation and abscesses [##REF##9646574##60##, ##UREF##14##61##]. Notably, several antiviral-related genes (<italic>irf3</italic>, <italic>mda5</italic>, and <italic>rig-i</italic>) have been identified as key players in antimicrobial immune responses and the maintenance of microbial homeostasis [##REF##36543267##62##–##REF##27108774##64##]. Therefore, <italic>Aeromonas</italic> may contribute significantly to the proinflammatory response observed in trout OM at 4 DPI after IHNV infection. Interestingly, the significant increase in <italic>Lysinibacillus</italic> and <italic>Bosea</italic> was mainly observed in the FC, which are known to exacerbate inflammatory responses in the OM [##REF##33359511##57##, ##UREF##15##65##]. Spearman’s correlation analysis further confirmed the positive correlation between the abundance of these pathogenic bacteria and the expression of antibacterial and inflammatory genes in the FC. These findings provide evidence that viral-induced microbial dysbiosis can lead to opportunistic pathogen expansion and reduction of beneficial commensals, ultimately resulting in ocular inflammation. Moreover, we observed a significant decrease in beneficial bacteria, such as <italic>Lactococcus</italic>, <italic>Pedobacter</italic>, and <italic>Deinococcus</italic>, primarily in the Cor and FC at 4 DPI. Importantly, most antiviral, antibacterial, and inflammatory genes showed a negative correlation with the abundance of <italic>Lactococcus</italic>, <italic>Deinococcus</italic>, and <italic>Pedobacter</italic>. These genera have been shown to reduce the levels of inflammatory cytokines (e.g., <italic>tnf-α</italic>, <italic>il-1β</italic>, <italic>il-6</italic>, and <italic>il-8</italic>) and play a crucial role in maintaining microbial homeostasis in the skin and gut [##REF##29230419##51##, ##REF##34865964##66##–##REF##25110521##68##]. Recent studies have highlighted the potential of probiotic administration as a therapeutic approach for the treatment of ocular inflammatory diseases to regulate microbial homeostasis [##REF##36060740##69##, ##REF##32668575##70##]. However, most of our understanding of the relationship between symbiotic microbiota and OM immunity derives from studies in mammals. Therefore, to the best of our knowledge, our findings provide the first evidence of potential cross-talk between microbiota and immunity at the OM surface in an early vertebrate species.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par23\">Our findings reveal the presence of a well-defined MALT in teleost OM and highlight the conserved principles shared by primitive and modern vertebrates in protecting mucosal sites from pathogens and maintaining microbiota homeostasis. The teleost OM exhibits a robust antiviral immune and inflammatory response upon viral infection, which is accompanied by tissue damage and bacterial translocation. Concurrently, viral-induced inflammatory responses lead to profound dysbiosis in the microbiome, which is characterized by the increase of pathobionts and a reduction of beneficial taxa in the relative abundance in OM. Furthermore, we identified a significant correlation between viral-induced immune responses and microbiome homeostasis in the FC, underscoring its key role in OM mucosal immunity and microbiota homeostasis. Overall, our findings suggest that the defense against pathogenic infections and the maintenance of microbiota homeostasis in vertebrate OM represent an ancient association that predates the emergence of tetrapods.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The visual organ plays a crucial role in sensing environmental information. However, its mucosal surfaces are constantly exposed to selective pressures from aquatic or airborne pathogens and microbial communities. Although few studies have characterized the conjunctival-associated lymphoid tissue (CALT) in the ocular mucosa (OM) of birds and mammals, little is known regarding the evolutionary origins and functions of immune defense and microbiota homeostasis of the OM in the early vertebrates.</p>", "<title>Results</title>", "<p id=\"Par2\">Our study characterized the structure of the OM microbial ecosystem in rainbow trout <italic>(Oncorhynchus mykiss</italic>) and confirmed for the first time the presence of a diffuse mucosal-associated lymphoid tissue (MALT) in fish OM. Moreover, the microbial communities residing on the ocular mucosal surface contribute to shaping its immune environment. Interestingly, following IHNV infection, we observed robust immune responses, significant tissue damage, and microbial dysbiosis in the trout OM, particularly in the fornix conjunctiva (FC), which is characterized by the increase of pathobionts and a reduction of beneficial taxa in the relative abundance in OM. Critically, we identified a significant correlation between viral-induced immune responses and microbiome homeostasis in the OM, underscoring its key role in mucosal immunity and microbiota homeostasis.</p>", "<title>Conclusions</title>", "<p id=\"Par3\">Our findings suggest that immune defense and microbiota homeostasis in OM occurred concurrently in early vertebrate species, shedding light on the coevolution between microbiota and mucosal immunity.</p>", "<p id=\"Par500\">\n</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s40168-023-01716-6.</p>", "<title>Keywords</title>" ]
[ "<title>Supplementary Information</title>", "<p>\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>We thank Hong Liu of Shenzhen Academy of Inspection and Quarantine Sciences for providing the IHNV strain (JL14-2814, originally isolated from juvenile rainbow trout); Xue qin Liu of College of Fisheries of Huazhong Agricultural University (Wuhan, China) for the ATCC CRL-2872 EPC cell line; Yan Wang and Yuan Sun of the Institute of Hydrobiology, Chinese Academy of Sciences for the Flow Cytometry analysis procedures.</p>", "<title>Authors’ contributions</title>", "<p>W.K. and Z.X. conceived the overall project and experimental design. W.K., G.C., and J.C. performed most of the experiments, analyzed the data, and contributed to the writing of the original manuscript. J.Y. and X.W. contributed to immunofluorescence analysis and morphological detection. Z.X. contributed to the writing of the final manuscript. Z.X. conceptualized and supervised the study.</p>", "<title>Funding</title>", "<p>This work was supported by grants from the National Natural Science Foundation of China (32225050, 32073001, 32303053), the National Key R&amp;D Program of China (2022YFF1000302), and the China Postdoctoral Science Foundation (2022M713325, 2023T160671).</p>", "<title>Availability of data and materials</title>", "<p>The raw 16S RNA sequencing data and RNA-seq data have been deposited in the NCBI Sequence Read Archive under BioProject accession numbers PRJNA1006525 and PRJNA1008220, respectively.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par37\">All fish procedures were performed in accordance with the Guiding Principles for Care and Use of Laboratory Animals and were approved by the Institute of Hydrobiology, Chinese Academy of Science (permit number 2019–048).</p>", "<title>Consent for publication</title>", "<p id=\"Par38\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par39\">The authors declare that they have no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Structural characteristics in the Cor, BC, and FC of trout OM. <bold>a</bold> Trout and its eye enlargement. <bold>b</bold> H&amp;E stain of trout eye. <bold>c</bold> Schematic diagram of the existence of three distinct regions on trout OM. d TEM (upper) and scanning electron microscope (lower) of the three distinct regions of control trout OM. From left to right: Cor, BC, and FC. Red stars indicate goblet cell orifices, red arrowheads indicate goblet cells, red arrows indicate microvilli. Scale bar, 2 μm. Enlarged images shown in (d, upper) refer to control trout OM. e Scanning Electron Microscope of microorganisms in three regions of the Cor (upper), BC (middle), and FC (lower) of control trout OM. Red arrowheads indicate commensal microbiota. Scale bar, 1 μm</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Distribution characteristics of commensal microbiota in the Cor, BC, and FC of trout OM. <bold>a</bold> Representative dot plots showing the staining of bacteria on the Cor, BC, and FC with SYTO BC Green. <bold>b</bold> Microbial counts on the Cor, BC, and FC (<italic>n</italic> = 9). <bold>c</bold>, <bold>d</bold> Richness (<bold>c</bold>) and diversity (<bold>d</bold>) of bacterial community in Cor, BC, and FC of control trout OM (<italic>n</italic> = 4). Community richness and diversity were measured by Chao1 index and Shannon index, respectively. e Principal coordinate analysis (PCoA) with weighted UniFrac distance matrix for the Cor, BC, and FC microbiota community from control trout OM (<italic>n</italic> = 4). <bold>f</bold> Venn diagram showing the number of the same and different bacteria in the Cor, BC, and FC of control trout OM. <bold>g</bold> Violin plot showing the representative abundance of aerobic-, anaerobic-, facultatively anaerobic-, gram-negative-, gram-positive-, forms biofilms-, and potentially pathogenic bacteria in the Cor, BC, and FC from control trout OM (<italic>n</italic> = 4). One-way ANOVA test was used to evaluate the statistical differences. Data are presented as mean ± SEM of three biological duplicates. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Trout OM exhibits distinct immune characteristics in different anatomical niches. a Dot plots showing lymphocytes and myeloid cells in the Cor, BC, and FC of control trout OM. Giemsa staining indicates the morphology of the sorted lymphocytes and myeloid cells (right). Scale bars, 5 μm. b Percentage of lymphocytes in the Cor, BC, FC, and other fish MALTs (i.e., skin, gill, and gut) of control trout (<italic>n</italic> = 9). <bold>c</bold> Percentage of myeloid cells in the Cor, BC, FC, skin, gill, and gut of control trout (<italic>n</italic> = 9). <bold>d</bold> Schematic diagram of the distribution of microdissection in the Cor, BC, and FC of control trout OM, EP, epithelium; ST, stroma; LP, lamina propria. <bold>e</bold> Heatmap plot of qPCR test of mRNA levels of the studied immune markers in the Cor, BC, and FC of control trout OM (<italic>n</italic> = 9). Expression levels in the BC and FC were normalized to those in the Cor, which is set as 1. One-way ANOVA test was used to evaluate the statistical differences. Data are presented as mean ± SEM of three biological duplicates. **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Effects of antibiotics on OM commensal bacteria and immunity. <bold>a</bold> The culture plates from trout OM (from left to right: Cor, BC, and FC) of control fish (upper) and 4-day treated fish with antibiotics (lower), respectively. Red triangles indicate a single colony of bacteria. <bold>b</bold> Numbers of bacterial colony in control and 4-day treated fish counted from a (<italic>n</italic> = 9). <bold>c</bold> The expression of V3-V4 16S rRNA region in the Cor, BC, and FC after treatment with antibiotics. <bold>d</bold> The expression of immune-related genes in the trout Cor, BC, and FC after treatment with antibiotics. AB, antibiotics. Statistical differences were evaluated by unpaired Student’s <italic>t</italic> test. ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Infection model and transcriptome analyses of trout OM with IHNV. <bold>a</bold> Scheme of the experimental strategy. Fish were infected by bathing with IHNV, and subsequently sacrificed at 0.5, 1, 4, 7, 14, 21, and 28 DPI for tissue sample collection. <bold>b</bold> Clinical signs of trout infected by IHNV at 4 DPI with exophthalmia and petechial hemorrhages. <bold>c</bold> Cumulative survival of IHNV-infected fish and control group. Statistical differences were assessed by the Log-rank (Mantel-Cox) test. <bold>d</bold> qPCR was applied to detect IHNV-<italic>N</italic> gene copies (Log<sub>10</sub>) in the trout Cor, BC, and FC collected at 0.5, 1, 4, 7, 14, 21, and 28 DPI (<italic>n</italic> = 6). <bold>e</bold> Venn diagrams showing the overlap of up- or downregulated genes detected by RNA-seq in the trout Cor, BC, and FC at 4 or 28 DPI versus control fish. <bold>f</bold> Heatmap plot of RNA-Seq studies for changed immune genes from the Cor, BC, and FC of IHNV-infected versus control fish measured at 4 and 28 DPI. <bold>g</bold> RNA-Seq data shows altered biological processes in the trout Cor, BC, and FC at 4 and 28 DPI versus control trout. <bold>h</bold> Heatmap plot of RNA-Seq studies for changed antivirus, anti-bacteria, and inflammation genes in the trout Cor, BC, and FC at 4 and 28 DPI. <bold>i</bold>, <bold>j</bold> Representative antiviral response (<bold>i</bold>) and inflammatory response (<bold>j</bold>) genes in the Cor, BC, and FC captured by LCM for control and IHNV-infected trout, and measured by qPCR. Gene expression levels in IHNV-infected fish were normalized to those in the control group, which were set as 1 (<italic>n</italic> = 9). Statistical differences were evaluated by unpaired Student’s <italic>t</italic> test. Data are presented as mean ± SEM of three biological duplicates. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>IHNV infection leads to microbiota translocation and subsequently induces an antibacterial immune response. <bold>a</bold> Fluorescence in situ hybridization experiment to detect the bacteria in the Cor, BC, and FC paraffin-sections from 4 and 28 days infected and control trout. From left to right: Cor, BC, and FC. EP, epithelium; ST, stroma; LP, lamina propria. Bacteria were stained red with Cy5-EUB338 oligoprobe, while nuclei were stained blue with DAPI. White arrowheads indicate bacteria. Scale bars, 10 μm. <bold>b</bold> Counts of positive bacteria in the Cor, BC, and FC of the control group and IHNV-infected trout at 4 and 28 DPI (<italic>n</italic> = 9). One-way ANOVA test was used to evaluate the statistical differences. <bold>c</bold> qPCR analysis of anti-bacteria genes in the Cor, BC, and FC of control and IHNV-infected trout OM at 4 and 28 DPI. Gene expression levels in IHNV-infected trout were normalized to those in the control group, which were set as 1 (<italic>n</italic> = 9). Statistical differences were evaluated by unpaired Student’s <italic>t</italic> test. Data are presented as mean ± SEM of three biological duplicates. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig7\"><label>Fig. 7</label><caption><p>IHNV infection leads to dysbiosis of trout OM microbiota. a, b Richness and diversity of bacterial community in the Cor, BC, and FC of control and IHNV-infected fish at 4 and 28 DPI (<italic>n</italic> = 4), measured with Chao1 and Simpson index, respectively. <bold>c</bold>, <bold>d</bold> Circos plots display the corresponding abundance of samples in relation to bacterial communities at the phylum (<bold>c</bold>) and order (<bold>d</bold>) levels. e Relative abundance (%) of the top six bacteria (phylum) in the Cor, BC, and FC. f Relative abundance (%) of the top six bacteria (order) in the Cor, BC, and FC. Statistical differences were assessed by unpaired Student’s <italic>t</italic> test. Data are presented as mean ± SEM of three biological duplicates. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig8\"><label>Fig. 8</label><caption><p>Differences of bacterial taxa in Cor, BC and FC after IHNV infection. <bold>a</bold>–<bold>c</bold> Bar chart of the log-transformed LDA value of bacterial taxa found to be significantly associated with control fish and trout infected with IHNV at 4 DPI in Cor (<bold>a</bold>), BC (<bold>b</bold>), and FC (<bold>c</bold>) by LEfSe (<italic>p</italic> &lt; 0.05). <bold>d</bold> Relative abundance of the pathogenic bacteria (<italic>Aeromonas</italic>, <italic>Bosea</italic>, and <italic>Lysinibacillus</italic>) in the Cor, BC, and FC. <bold>e</bold> Relative abundance of the beneficial bacteria (<italic>Lactococcus</italic>, <italic>Pedobacter</italic>, and <italic>Deinococcus</italic>) in the Cor, BC, and FC. Statistical differences were assessed by unpaired Student’s <italic>t</italic> test. Data are presented as mean ± SEM of three biological duplicates. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001</p></caption></fig>", "<fig id=\"Fig9\"><label>Fig. 9</label><caption><p>Correlation analysis between the relative abundance of the disordered microbiota and immune-related genes. <bold>a</bold>–<bold>c</bold> RDA association analysis of the Cor (<bold>a</bold>), BC (<bold>b</bold>), and FC (<bold>c</bold>) microbial genera and immune-related genes. <bold>d</bold>–<bold>f</bold> Spearman’s correlation between 37 immune-related genes expression determined by RNA-Seq and microbiota at genus level in the Cor (<bold>d</bold>), BC (<bold>e</bold>), and FC (<bold>f</bold>). Color scale shows a negative (blue) to positive (red) correlation. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001 indicated significant correlation</p></caption></fig>" ]
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[ "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Weiguang Kong, Gaofeng Cheng, and Jiafeng Cao contributed equally to this work.</p></fn></fn-group>" ]
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[ "<media xlink:href=\"40168_2023_1716_MOESM2_ESM.mp4\" id=\"MOESM2\"><caption><p>Video Abstract</p></caption></media>", "<media xlink:href=\"40168_2023_1716_MOESM1_ESM.docx\"><caption><p><bold>Additional file 1: Figure S1.</bold> The evolution of the vertebrate ocular mucosa. a–d show the jawless fishes, cartilaginous fishes, teleost fishes, and tetrapods, respectively. <bold>Figure S2.</bold> a–e H&amp;E (upper) and AB (lower) stain of the three distinct regions of OMs from <italic>Oncorhynchus mykiss</italic> (a), <italic>Takifugu rubripes </italic>(b), <italic>Hypostomus plecostomus</italic> (c), <italic>Micropterus Salmoides</italic> (d), and <italic>Cyprinus carpio</italic> (e). From left to right: Cor, BC, and FC. EP, epithelium; ST, stroma; LP, lamina propria. Red arrowheads indicate mucus cells. Black arrowheads indicate indicate lymphocytes. Scale bar, 50 μm. <bold>Figure S3.</bold> Fish species selected from five different families for understanding of the teleost OM. <bold>Figure S4.</bold> a Real-time PCR analysis of bacteria V3-V4 16S rRNA region in the Cor, BC, FC, and other MALTs (i.e., skin, gill, and gut). DNA abundance was normalized to that of the Cor, which is set as 1 (<italic>n</italic> = 9). Statistical differences were evaluated by one-way ANOVA. Data are presented as mean ± SEM of three independent duplicates. *<italic>p</italic> &lt; 0.05, **<italic>p</italic> &lt; 0.01, ***<italic>p</italic> &lt; 0.001. b Dot plots representing the Cor, BC, and FC samples without staining of SYTO BC Green. <bold>Figure S5.</bold> Dot plots representing lymphocytes and myeloid cells in skin, gill, and gut of control trout. <bold>Figure S6.</bold> a Immunofluorescence staining of IHNV in the Cor, BC, and FC paraffin-sections from 4, and 28 days infected and control trout. From left to right: Cor, BC, and FC. EP, epithelium; ST, stroma; LP, lamina propria. IHNV were stained red with an anti-IHNV-<italic>N</italic> mAb, while nuclei were stained blue with DAPI. Scale bars, 20 μm. b Numbers of virus-infected cells were counted from a (<italic>n</italic> = 9). c H&amp;E stain of the three distinct regions of control and IHNV-infected fish OM at 4 and 28 DPI. From left to right: Cor, BC, and FC. EP, epithelium; ST, stroma; LP, lamina propria. Red arrowheads show disrupted mucosal EP with loss of continuity. Scale bar, 20 μm. d Pathology score of the Cor, BC, and FC of control and IHNV-infected trout at 4 and 28 DPI (<italic>n</italic> = 9). One-way ANOVA test was used to evaluate the statistical differences. Data are presented as mean ± SEM of three biological duplicates. ***<italic>p</italic> &lt; 0.001. <bold>Figure S7.</bold> Immunofluorescence staining of IHNV with isotype control antibodies for anti-IHNV-N with in the Cor, BC, and FC paraffin-sections. Scale bars, 20 μm. <bold>Figure S8.</bold> Altered KEGG pathways in the Cor, BC, and FC at 4 and 28 DPI versus control trout detected by RNA-Seq. <bold>Figure S9.</bold> a–c Bar chart showing the log-transformed LDA values of bacterial taxa significantly correlated with trout infected with IHNV and control group at 28 DPI in the Cor (a), BC (b), and FC (c) by LEfSe (<italic>p</italic> &lt; 0.05). <bold>Table S1.</bold> Primers used in this study.</p></caption></media>" ]
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{ "acronym": [], "definition": [] }
79
CC BY
no
2024-01-14 23:43:47
Microbiome. 2024 Jan 13; 12:10
oa_package/6d/02/PMC10787490.tar.gz
PMC10787491
0
[ "<title>Background</title>", "<p id=\"Par6\">Liver transplantation (LT) has become the standard treatment choice for patients with end-stage liver disease (ESLD) [##REF##30153225##1##]. This shift in treatment modalities emphasises the need for an enhanced focus on the long-term management of LT patients, with cerebrovascular disease emerging as a critical concern [##REF##36495912##2##, ##REF##31898413##3##]. Perioperative stroke (PS) is defined as an ischaemic or haemorrhagic cerebral event that occurs during or up to 30 days after surgery and is considered a major cerebrovascular complication in patients undergoing LT [##REF##24978064##4##]. The most common causes of PS are cardiac surgery, neurosurgery, thoracic vascular surgery and transplantation [##REF##35224865##5##]. While PS after LT is relatively rare compared to other perioperative complications [##UREF##0##6##, ##REF##32128971##7##], patients with PS tend to have worse outcomes than non-stroke patients [##REF##37034098##8##]. In particular, the mortality rate of PS patients is approximately eight times higher than that of comparable non-surgical populations, with a mortality rate of 26% [##UREF##1##9##], and tends to be worse in LT recipients. Consequently, PS places additional burdens on patients, their caregivers, and the healthcare system [##REF##35224865##5##]. Although some factors such as smoking history, kidney insufficiency, advanced age and hypertension have been suggested to be associated with PS [##UREF##1##9##], the accuracy of these factors in predicting PS incidence remains uncertain. Moreover, there is a paucity of data that specifically examine the risk factors for PS among patients undergoing LT.</p>", "<p id=\"Par7\">As a surrogate marker of insulin resistance (IR), the triglyceride-glucose (TyG) index is derived from the fasting blood glucose (FBG) and triglycerides (TG) [##REF##19067533##10##] and provides a means for accessing the status of both lipids with glucose. The TyG index not only proves to be cost-effective and reproducible but also demonstrates better predictive value than FBG or TG alone [##REF##36451149##11##]. Growing evidence indicates a close association between the TyG index and an elevated risk of adverse cardiovascular events in both the general population [##REF##26683265##12##, ##REF##32993633##13##] and high-risk patient cohorts, such as those with hypertension [##REF##35155598##14##] and critically ill patients [##REF##35804386##15##]. IR is characterised by reduced insulin sensitivity in peripheral tissues and contributes to many metabolic abnormalities associated with critical illnesses [##REF##11681813##16##]. IR also plays an important role in the pathophysiology of microangiopathy, macroangiopathy, neuropathy, and organ failure in critically ill patients [##REF##10953019##17##]. Previous evidence have revealed that critically ill patients experienced severe IR after intensive care unit (ICU) admission, which correlated with their severity rather than their diagnoses [##REF##17161218##18##]. Patients undergoing LT often experience ESLD [##REF##37208107##19##], leading to severe disturbances in lipid metabolism and glucose status [##REF##30901133##20##], with prolonged perioperative intensive care in ICU. Published studies have suggested that TG, diabetes, and IR could be potential risk factors for PS [##REF##33411913##21##, ##REF##17301301##22##]. Consequently, recognising and addressing perioperative IR in LT recipients is crucial for preventing and managing postoperative cardiovascular complications.</p>", "<p id=\"Par8\">Numerous studies have shown that the TyG index is capable of predicting the recurrence and morbidity of strokes [##REF##36451149##11##, ##REF##36510223##23##] and that all-cause mortality tends to increase significantly when the TyG index is elevated [##REF##36639637##24##]. However, it remains unclear whether this association persists in LT recipients. Therefore, this study aimed to explore whether the TyG index could be a potential predictor in LT recipients and assist in identifying individuals at high risk of PS and all-cause mortality for healthcare management and perioperative decision-making.</p>" ]
[ "<title>Methods</title>", "<title>Study design, setting and population</title>", "<p id=\"Par9\">The retrospective cohort study examined the perioperative data of patients who underwent LT retrieved from a perioperative database platform and an electronic health record system at a university-affiliated medical centre between January 2015 and January 2021. Inclusion criteria included: (1) age &gt; 18 years and (2) allogeneic LT. Exclusion criteria encompassed: (1) missing perioperative data, (2) insufficient TG and FBG data before LT, (3) loss to follow-up, (4) insufficient diagnostic information on stroke, (5) a history of stroke, (6) simultaneous kidney and liver transplantations, and (7) secondary LT. Ultimately, 780 patients were enrolled in this study and divided into three groups according to the tertiles of the TyG index (Fig. ##FIG##0##1##).</p>", "<p id=\"Par10\">\n\n</p>", "<p id=\"Par11\">This study was approved by the Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University [27 July 2022, No. (2019)02-609-04]) and was granted exemption from the need for informed consent owing to its retrospective design. This study adhered to the guidelines outlined in the STROBE statement and the Declaration of Helsinki. All the LT recipients included in the study were formally registered in the China Organ Transplant Response System.</p>", "<title>Data collection</title>", "<p id=\"Par12\">Potential variables were divided into five categories: (1) demographics, such as age, sex, American Society of Anaesthesiologists (ASA) classification, body mass index (BMI), smoking, alcoholism, and history of previous surgery; (2) comorbidities, including hypertension, diabetes, respiratory diseases, pulmonary hypertension, renal insufficiency, hypersplenism, cirrhosis, hepatitis B, hepatitis C, and liver cancer; (3) treatments, including haemodialysis, plasma exchange (PE), and mechanical ventilation (MV); (4) laboratory indicators, including white blood cell (WBC), platelets, red blood cell (RBC), aspartate aminotransferase (AST), alanine aminotransferase (ALT), albumin, blood urea nitrogen (BUN), serum creatinine (SCr), international normalised ratio (INR), prothrombin time (PT), FBG, TG, amylase, ammonia, etc.; (5) admission severity of illness scores, including the Model for End-Stage Liver Disease Score (MELD), Child-Pugh score, and the Sepsis-related Organ Failure Assessment Score (SOFA); (6) intraoperative indicators, including emergency surgery, day or night surgery, surgery technique, surgery duration, anhepatic phase duration, massive transfusion, massive blood loss, urinary oliguria, and cardiac arrest. Notably, the TG index was calculated using the formula ln (fasting TG (mg/dl) × FBG (mg/dl])/2 [##REF##37312120##25##].</p>", "<title>Clinical outcomes and follow-up</title>", "<p id=\"Par13\">The primary outcome was the first occurrence of postoperative stroke. The secondary outcomes were the individual endpoints of all-cause mortality, defined as death from any cause during the postoperative hospitalisation period and at one year and three years after LT.</p>", "<p id=\"Par14\">The diagnosis of stroke was confirmed through a comprehensive medical review of imaging reports, and each patient underwent evaluation based on World Health Organization criteria by a certified neurologist without prior access to their medical records [##REF##33411913##21##, ##UREF##2##26##]. Follow-up visits were scheduled for one year and three years post-LT. At each follow-up visit, details on postoperative anti-rejection therapy and survival status were recorded. In instances where direct contact with the patient was unattainable, telephone interviews were conducted with relatives or caregivers. However, if the patients’ relatives could not be contacted, the patients were considered lost to follow-up and documented in the electronic tracking system.</p>", "<title>Statistical analysis</title>", "<p id=\"Par15\">The normality of continuous parameters was assessed by Kolmogorov-Smirnov test. Depending on the data distributions, continuous variables are presented as mean ± SD or median (interquartile range), while categorical variables are expressed as number (proportion). Continuous variables were analysed using the t-test if they exhibited a normal distribution, while the Kruskal-Wallis test was used for non-normal distributions. The categorical variables were analyzed using chi-square test or Fisher’s exact test. For missing values in the original dataset (Supplementary Table ##SUPPL##0##1##, Additional File 1), no categorical variables were identified as missing, and all continuous variables missing at moderate rates (&lt; 10%) were replaced by multiple imputations using the R software. The Kaplan-Meier method was employed to assess the incidence of survival endpoints, and differences based on the TyG index were determined using the log-rank test.</p>", "<p id=\"Par16\">Binary logistic regression was performed to evaluate risk factors and calculate odds ratios (OR) and 95% confidence intervals (CI) between the TyG index and post-LT stroke. Cox proportional hazard models were then used to estimate the hazard ratio (HR) and 95% CI between the TyG index and all-cause death after LT. Confounders included baseline characteristics selected by <italic>P</italic>-value &lt; 0.05 in the univariate analysis and <italic>P</italic>-value &lt; 0.01 in the additional binary logistic regression. Additionally, variables associated with aetiology and prognosis based on recent studies were also included in the multivariate models [##REF##33411913##21##, ##REF##31234757##27##, ##REF##25027142##28##], and the variance inflation factor (VIF) was used as a measure of multicollinearity for all covariates in the multivariate models.</p>", "<p id=\"Par17\">Four models were systematically constructed for analysis: an unadjusted model; model 1, adjusted for sex, age, BMI, and ASA; model 2, adjusted for sex, age, BMI, ASA, hypertension, diabetes, renal insufficiency, HE, MELD score, haemodialysis, HB, WBC, and platelet count; and model 3, adjusted for sex, age, BMI, ASA, diabetes, hypertension, renal insufficiency, HE, MELD score, haemodialysis, HB, WBC, platelet count, day-or-night surgery, surgery duration, intraoperative massive transfusion, massive blood loss, urinary oliguria, and cardiac arrest. Additionally, a restricted cubic spline (RCS) regression model with four knots (5th, 35th, 65th, and 95th) was used to flexibly model possible nonlinear associations between the TyG index and stroke.</p>", "<p id=\"Par18\">The TyG index was categorised into three groups (the first group was used as the reference group) and modelled as a continuous variable in the analyses. <italic>P</italic>-values for the trends were calculated based on the TyG index for each group. To determine the effectiveness of the TyG index as a prognostic indicator, stratified analyses were performed based on sex, hypertension, diabetes, renal insufficiency, hypersplenism, previous surgery, and day or night surgery. Likelihood ratio tests were conducted to examine interactions between the TyG index and the variables utilized for stratification.</p>", "<p id=\"Par19\">Several sensitivity analyses were conducted to validate the robustness of the current results. First, to explore the potential impact of imputation strategies, we repeated the missing value processing using a dataset without imputation and another dataset where imputation involved using the median (for numeric characteristics) or mode (for categorical characteristics). Second, to remove bias from excessively outdated medical records, we excluded patients who underwent LT before 2016. Third, we excluded patients with a history of smoking or alcohol consumption at baseline. Fourth, patients with a preoperative diagnosis of hepatic encephalopathy were excluded. Finally, to avoid the potential influence of surgery-related confounders on the outcomes, we excluded patients who did not undergo piggyback LT.</p>", "<p id=\"Par20\">A two-sided <italic>P</italic>-value &lt; 0.05 was defined as statistical significance. All analyses were performed using the R software (version 4.2.0).</p>" ]
[ "<title>Results</title>", "<p id=\"Par21\">The enrollment flowchart is presented in Fig. ##FIG##0##1##. A total of 780 patients who underwent LT were eventually included in this study. The median age of the included patients was 49 (42–56) years, and 680 (87.18%) were male. The median TyG index for all included patients was 8.23 (7.78–8.72). The incidence of stroke after LT was 5.38%, and the in-hospital, 1-year, and 3-year mortality rates were 5.54%, 13.21%, and 15.77%, respectively (Table ##TAB##0##1##).</p>", "<p id=\"Par22\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par38\">In this study, we evaluated the association between the TyG index and PS as well as the all-cause mortality in patients who underwent LT. The main findings were as follows: (1) LT recipients presented with a significantly high incidence of PS (up to 5.38%), and an increased TyG index level was associated with a higher risk of post-LT stroke. This finding remained robust even after adjusting for confounding variables. (2) The TyG index was similarly associated with all-cause mortality in LT recipients. (3) Further investigation of the TyG index and perioperative complications of LT indicated that it may be closely associated with the development and progression of perioperative renal insufficiency. Taken together, our results extend the application of the TyG index to LT-related cerebrovascular complications and demonstrate its potential importance as a simple risk predictor to improve risk stratification and perioperative decision-making.</p>", "<p id=\"Par39\">Previous studies have reported the incidence of PS in LT recipients ranging from 2 to 5% [##REF##37034098##8##, ##REF##14610116##29##, ##REF##9884245##30##], which is generally consistent with the findings of our study. In recent years, the TyG index has gained recognition beyond its initial application in diabetes, showing value in various diseases such as metabolic disorders, cardiovascular diseases, atherosclerotic diseases and even COVID-19 [##REF##32587566##31##–##REF##35779467##33##]. In our study, we identified the TyG index as a novel independent risk factor for post-LT stroke after adjusting for confounders. This finding is in line with previous epidemiological studies showing that the TyG index is predictive of stroke in individuals without diabetes mellitus [##REF##36609319##34##]. In a cohort study, Wang et al. [##REF##33602208##35##] demonstrated a 1.45-fold increased risk of ischaemic stroke among patients in the upper quartile of the TyG index. Similarly, another meta-analysis of over 5 million participants suggested that the TyG index was independently associated with a 1.3-fold increased risk of stroke [##REF##33812373##36##]. Moreover, there is a robust association between the TyG index and poor prognosis in critically ill patients, as demonstrated in several cross-sectional and retrospective studies [##REF##35804386##15##, ##REF##36639637##24##, ##REF##37312120##25##]. Subsequent research has revealed that with each unit increase in the TyG index, the likelihood of in-hospital mortality increases by approximately 30–50% [##REF##35804386##15##, ##REF##37312120##25##, ##REF##37940931##32##]. In the current study, we observed that for each unit increase in the TyG index, the risks of in-hospital, 1-year, and 3-year mortality in LT recipients increased by 67.9%, 34.9%, and 41.5%, respectively. These results are generally consistent with those of previous research, indicating a strong association between an elevated TyG index and increased mortality in patients undergoing LT. It is noteworthy that LT recipients exhibit relatively increased in-hospital mortality compared to critically ill patients. This may be attributed to the complicated surgery, prolonged operation time, ischaemia-reperfusion injury, and perioperative infection experienced by LT patients [##REF##36495912##2##, ##REF##33675318##37##]. Hence, regular monitoring of the TyG index has a potential utility in perioperative practice.</p>", "<p id=\"Par40\">In the subgroup analysis, a consistent and independent association between the TyG index and post-LT stroke was observed in male participants. This finding is partially in line with previous research where the correlation between the TyG index and poor outcomes seemed to be more pronounced in male patients than in females [##REF##37891651##38##]. It is interesting to note that none of the interaction tests performed in these studies reached statistical significance, which is consistent with our results. These results suggest that the influence of sex on the relationship between the TyG index and adverse events may not be clinically significant. Additionally, subgroup analysis showed that the TyG index and post-LT stroke were independently correlated in patients without diabetes or hypertension, without a significant interaction (<italic>P</italic> for interaction = 0.113, 0.631, respectively). These results are similar to previous studies and demonstrate that the prognostic-predictive value of the TyG index was independent of hypertension and diabetes mellitus [##REF##37891651##38##, ##REF##31941513##39##]. Moreover, an association between the TyG index and stroke was not observed in patients with hypersplenism and previous surgery, which could be attributed to the fact that hypersplenism and previous surgery are traditionally recognised as unfavourable risk factors associated with PS. Further stratification analysis reduced the sample size, potentially explaining the lack of significant results when patients without renal insufficiency were included. In the sensitivity analysis, the relationship between post-LT stroke and TyG index level was consistent with the core binary logistic regression analysis results after excluding patients with seven different conditions. All these results collectively demonstrate the stability and reliability of the findings of our study.</p>", "<p id=\"Par41\">\nFurthermore, we investigated the correlation between the TyG index and several perioperative complications which may be associated with LT. Our study found no relationship between the TyG index and postoperative pulmonary complications (PPCs) in LT recipients. Conversely, previous studies have found that high TyG index levels are associated with an increased incidence of chronic lung disease, respiratory symptoms, and reduced lung function, as well as an increased incidence of other infection-related diseases [##REF##37940931##32##, ##REF##33839084##40##]. Possible reasons for this difference include anti-rejection therapy in LT recipients, which may lead to differences in the underlying mechanism of PPCS compared with the non-operated population. Multicentre studies with large sample sizes are needed to investigate the potential association between the TyG index and lung disease. We also identified a potential correlation between a higher TyG index and the occurrence of AKI and hepatorenal syndrome in patients who underwent LT. Patients in the high TyG index group were more likely to receive postoperative haemodialysis treatment. Our study is partially consistent with a previous multicentre cohort study [##REF##37891651##38##] that demonstrated that high TyG index levels correlate with an increased risk of adverse prognosis among patients with end-stage renal disease. This surprising result provides further evidence for the relationship between the TyG index and the pathophysiology and prognosis of various renal diseases.</p>", "<p id=\"Par42\">\nThe biological mechanisms underlying the association between the TyG index and the occurrence and prognosis of stroke remain unclear. One possible pathway is the IR, a widely demonstrated response to critical illness rather than being disease-specific [##REF##17161218##18##]. This close association could be explained by the relationship between ESLD severity and IR status, as assessed using the TyG index. Macrovascular disease, neuropathy, and organ failure are strongly associated with IR [##REF##35804386##15##], which may ultimately lead to further deterioration in critically ill patients, including LT recipients with ESLD. Secondly, it has been widely demonstrated that IR is associated with endothelial dysfunction, oxidative stress, cardiovascular remodelling, coagulation imbalance, and inflammatory response [##REF##31684945##41##–##REF##30170598##43##], all of which are substantial contributors to the deterioration of LT recipients with ESLD. Third, glycometabolic disorders (GD) associated with IR also occur among critically ill patients without prior diabetes [##REF##11794168##44##], and this pathophysiological condition can also be detected in patients with ESLD [##REF##11794168##44##]. GD can lead to tissue acidosis, reactive oxygen species production, and inflammatory cell infiltration, resulting in severe structural tissue damage, which may partly explain the high risk of PS in LT recipients. Finally, individuals suffering from ESLD are typically associated with a variety of metabolic abnormalities, including IR, malnutrition, osteopenia, hypogonadism associated with IGF-I deficiency [##REF##21733081##45##]. Therefore, disturbances in platelet fuction resulting from these reasons may contribute to the pathogenesis of stroke [##REF##33880941##46##, ##REF##19336637##47##]. However, despite these mechanisms explaining our findings to some extent, it is necessary to validate the causal relationship between the TyG index and cerebrovascular events in future prospective studies with larger sample sizes.</p>", "<p id=\"Par43\">\nThe present study confirmed that the TyG index could be used as an effective predictor of post-LT stroke among LT recipients and is independently associated with the risk of all-cause mortality. However, this study has some limitations that must be acknowledged. First, this was a single-centre retrospective analysis based on an observational study design; therefore, definitive causality could not be established. Multivariate-adjusted regression and subgroup analyses were performed to verify the robustness of the main outcomes. Further studies are needed to investigate whether interventions based on the TyG index have a positive impact on preventing stroke after LT and improving clinical prognosis. Second, we were unable to assess dynamic changes in the index during the perioperative period. Previous studies conducted repeated measurements of the TyG index at specified intervals and found that an index reflecting cumulative exposure to TyG outperformed a single measurement in risk prediction [##REF##35505313##48##]. Therefore, the application of the TyG index at baseline, calculated prior to surgery, may be less robust.</p>" ]
[ "<title>Conclusions</title>", "<p id=\"Par44\">\nOur study extended the applicability of the TyG index to LT recipients and demonstrated the potential applicability of the TyG index as an indicator for the risk stratification of PS and all-cause mortality among these patients. Consequently, monitoring the TyG index may improve risk stratification and guide perioperative management. However, further investigation is needed to evaluate whether improved management of the TyG index can provide a better clinical prognosis.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">The triglyceride-glucose (TyG) index, identified as a reliable indicator of insulin resistance (IR), was reported to be associated with stroke recurrence and morbidity in the general population and critically ill patients. However, the relationship in liver transplantation (LT) recipients remains unknown. This study aimed to investigate the correlation between the TyG index and post-LT stroke along with all-cause mortality and further assess the influence of IR on the LT recipients’ prognosis.</p>", "<title>Methods</title>", "<p id=\"Par2\">The retrospective cohort study enrolled 959 patients who underwent LT at a university-based medical centre between January 2015 and January 2021. The participants were divided into three groups according to their TyG index tertiles. The primary outcome was post-LT stroke. Multivariate logistic regression, COX proportional hazards regression, and restricted cubic spline RCS were used to examine the association between the TyG index and outcomes in LT recipients.</p>", "<title>Results</title>", "<p id=\"Par3\">With a median TyG index of 8.23 (7.78–8.72), 780 (87.18% males) patients were eventually included. The incidence of post-LT stroke was 5.38%, and the in-hospital, 1-year, and 3-year mortality rates were 5.54%, 13.21%, and 15.77%, respectively. Multivariate regression analysis showed an independent association between the TyG index and an increased risk of post-LT stroke [adjusted odds ratio (aOR), 3.398 (95% confidence interval [CI]: 1.371–8.426) <italic>P</italic> = 0. 008], in-hospital mortality [adjusted hazard ratio (aHR), 2.326 (95% CI: 1.089–4.931) <italic>P</italic> = 0.025], 1-year mortality [aHR, 1.668 (95% CI: 1.024–2.717) <italic>P</italic> = 0.039], and 3-year mortality [aHR, 1.837 (95% CI: 1.445–2.950) <italic>P</italic> = 0.012]. Additional RCS analysis also suggested a linear increase in the risk of postoperative stroke with elevated TyG index (<italic>P</italic> for nonlinearity = 0.480).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">The TyG index may be a valuable and reliable indicator for assessing stroke risk and all-cause mortality in patients undergoing LT, suggesting its potential relevance in improving risk stratification during the peri-LT period.</p>", "<title>Supplementary Information</title>", "<p>The online version contains supplementary material available at 10.1186/s12933-023-02113-x.</p>", "<title>Keywords</title>" ]
[ "<title>Baseline characteristics</title>", "<p id=\"Par23\">A comparison of the baseline characteristics of patients with and without post-LT stroke is shown in Table ##TAB##0##1## and Supplementary Table ##SUPPL##0##2## (Additional File 2). The demographic characteristics did not differ significantly between patients with and without post-LT stroke (<italic>P</italic> &gt; 0.05). However, individuals in the stroke group exhibited higher MELD scores; an increased prevalence of alcoholic liver disease, preoperative fever, renal insufficiency, diabetes, and HE; and higher values of WBC, FBG, ALT, IBIL, and SCr. Moreover, mechanical ventilation (MV), haemodialysis, plasma exchange (PE), night surgery, donation after circulatory death (DCD) grafts, intraoperative massive transfusion, massive blood loss, urinary oliguria, and cardiac arrest were significantly associated with post-LT stroke (<italic>P</italic> &lt; 0.05). Specifically, the TyG index level was significantly elevated in the stroke group compared to the non-stroke group [8.68 (8.14–9.02) vs. 8.21 (7.76–8.69), <italic>P</italic> &lt; 0.001].</p>", "<p id=\"Par24\">The baseline characteristics of LT recipients according to the TyG index tertiles are shown in Table ##TAB##1##2##. All three groups were classified according to TyG index levels [tertile (T)1: (&lt; 7.92), T2: (7.92–8.53), T3: (&gt; 8.53)], with median TyG index levels of 7.62 (7.34–7.77), 8.23 (8.08–8.37), and 8.96 (8.72–9.34), respectively. Notably, with the increase in TyG index levels, patients tended to be older, had a history of diabetes, had higher severity of MELD scores, higher levels of haemoglobin, WBC, and platelets; and a higher incidence of intraoperative urinary oliguria compared to the lower group (<italic>P</italic> &lt; 0.05). In contrast, the percentage of individuals receiving massive transfusions during surgery exhibited a lower TyG index (<italic>P</italic> &lt; 0.05).</p>", "<p id=\"Par25\">\n\n</p>", "<title>Correlation between the TyG index and primary outcome</title>", "<p id=\"Par26\">Supplementary Table ##SUPPL##0##3## (Additional File 3) shows the results of logistic regression for the risk of stroke among patients who underwent LT. Independent variables for binary logistic regression included variables that showed significance in the univariate analysis (<italic>P</italic> &lt; 0.05), as well as factors derived from clinical experience and previous research that were thought to influence the occurrence of postoperative stroke. The results show that age, ASA classification, MELD scores, diabetes, TYG index, haemoglobin level, WBC, platelets, night surgery, intraoperative massive transfusion, massive blood loss, and cardiac arrest were influential factors (<italic>P</italic> &lt; 0.01).</p>", "<p id=\"Par27\">An additional logistic regression model was used to investigate the correlation between the TyG index and post-LT stroke. When utilised as a continuous variable, the TyG index level emerged a significant risk factor for post-LT stroke in the unadjusted model [OR, 1.919 (95% CI: 1.280–2.875) <italic>P</italic> = 0.001], partially adjusted model 1 [adjusted OR (aOR), 1.915 (95% CI: 1. 227–2.986) <italic>P</italic> = 0.004], partially adjusted model 2 [aOR, 1.905 (95% CI: 1.183–3.066) <italic>P</italic> = 0.008], and fully adjusted model 3 [aOR, 1.899 (95% CI: 1.180–3.055) <italic>P</italic> = 0.007]. In the context of a nominal variable, it was observed that, compared with patients in the reference group (T1), patients in the high TyG index group (T3) showed a significantly increased risk of post-LT stroke in all four established logistic regression models, as indicated by the following results: unadjusted model [OR, 3. 204 (95% CI: 1.412–7.273), <italic>P</italic> = 0.005], partially adjusted model 1 [aOR, 3.055 (95% CI: 1.330–7.019), <italic>P</italic> = 0.008], partially adjusted model 2 [aOR, 3.348 (95% CI: 1.410–7.952), <italic>P</italic> = 0.006], and fully adjusted model 3 [aOR, 3.398 (95% CI: 1.371–8.426), <italic>P</italic> = 0.008]. There was also a trend of increasing risk with the TyG index (Table ##TAB##2##3##), as shown by the results of the trend test (<italic>P</italic> for trend = 0.012). The RCS regression model (Fig. ##FIG##1##2##) illustrated a linearly increasing relationship between the TyG index and the risk of post-LT stroke (<italic>P</italic> for nonlinearity = 0.480). Additionally, the RCS curve identified an inflexion point at TyG = 8.18, which represented a critical point in the relationship between TyG and post-LT stroke.</p>", "<p id=\"Par28\">\n\n</p>", "<p id=\"Par29\">\n\n</p>", "<p id=\"Par30\">The VIF of the confounding factors in the multivariate logistic regression models were all &lt; 2 according to collinearity diagnostics, indicating no multicollinearity among the covariates in the models (Supplementary Table ##SUPPL##0##4##, Additional File 4), and all confounders were defined or interpreted in Supplementary Table ##SUPPL##0##5##&gt; (Additional File 5).</p>", "<title>Correlation between the TyG index and secondary outcomes</title>", "<p id=\"Par31\">The Cox proportional hazards regression was employed for evaluating the association between the TyG index level and all-cause mortality following LT. In comparison to patients in T1, those in the T3 group exhibited a higher risk of in-hospital death [adjusted HR (aHR), 2.326 (95% CI: 1.089–4.931), <italic>P</italic> = 0.025], 1-year follow-up [aHR, 1.668 (95% CI: 1.024–2.717), <italic>P</italic> = 0.039], and 3-year follow-up [aHR, 1.837 (95% CI: 1.445–2.950), <italic>P</italic> = 0.012] after fully adjusting for potential confounders (Table ##TAB##2##3##). The results of the trend test (Table ##TAB##2##3##) also showed a similar tendency, indicating that the risk of hospital mortality, 1-year mortality, and 3-year mortality exhibited an upward trajectory according to the tertiles of the TyG index (<italic>P</italic> for trend = 0.018, 0.029, and 0.016, respectively).</p>", "<p id=\"Par32\">Kaplan-Meier survival analysis (Fig. ##FIG##2##3##) was utilized to assess the occurrence of all-cause mortality among T1-T3 groups categorized by the TyG index levels. It was observed that patients with a higher TyG index had a significantly increased incidence of all-cause mortality during hospitalisation as well as at the 1-year and 3-year follow-up periods (Log-rank <italic>P</italic> = 0.038, 0.029, and 0.012, respectively).</p>", "<p id=\"Par33\">\n\n</p>", "<title>Subgroup and sensitivity analysis</title>", "<p id=\"Par34\">The TyG index risk stratification value for the primary outcome was further analysed in several subgroups, including sex, hypertension, diabetes, renal insufficiency, hypersplenism, previous surgery, and surgery duration (Fig. ##FIG##3##4##). The TyG index exhibited a significant association with a higher risk of postoperative stroke in the subgroups of male [aOR, 1.812 (95% CI: (1.134–2.893)], those without hypertension [aOR, 1.989 (95% CI: (1.275–3.102)], those without diabetes [aOR, 2.529 (95% CI: (1.440–4.442)], those with renal insufficiency [aOR, 4.235 (95% CI: (1.959–9.156)], those without hypersplenism [aOR, 2.889 (95% CI: (1.524–5.477)], those without previous surgery [aOR, 2.007 (95% CI: (1.275–3.160)] and those who underwent LT at night [aOR, 2.838 (95% CI: (1.349–5.971)] (all <italic>P</italic> &lt; 0.05). Interestingly, the TyG index appears to exhibit a more pronounced predicting value [aOR (95% CI)] among patients without previous surgery [2.007 (1.275–3.160) vs. 1.925 (0.579–6.403), <italic>P</italic> for interaction = 0.042].</p>", "<p id=\"Par35\">\n\n</p>", "<p id=\"Par36\">Furthermore, a series of sensitivity analyses were carried out to evaluate the robustness and reliability of our primary results, as shown in Supplementary Table ##SUPPL##0##6## (Additional File 6). First, the results remained robust when using both non-imputed and imputed original datasets, and the TyG index level remained significantly associated with the risk of post-LT stroke in the fully adjusted models (aOR = 2.026, 2.005, respectively). Second, after excluding patients who underwent LT before 2016, our study demonstrated a significant association between the TyG index and the occurrence of post-LT stroke, as evidenced by the unadjusted and fully adjusted models (aOR = 2.002 and 1.955, respectively). Moreover, the results of the analysis, after excluding those patients with smoking history (aOR = 2.427), alcohol consumption (aOR = 2.137), hepatic encephalopathy (aOR = 2.581), and those who did not receive piggyback liver transplantation (aOR = 1.924), were consistent with the main results.</p>", "<title>Other postoperative relevant outcomes</title>", "<p id=\"Par37\">As the T3 group demonstrated a greater association with adverse clinical outcomes, we compared the differences in several relevant post-LT outcomes and complications between T3 and T1–T2 (Supplementary Table ##SUPPL##0##7##, Additional File 7). Compared to the patients in T1–T2 groups, those in the T3 group had a higher demand for haemodialysis treatment (22.57% vs. 43.22%, <italic>P</italic> &lt; 0.001), higher hospitalisation costs (294967.9 vs. 324448.1, <italic>P</italic> = 0.001), and longer postoperative ICU stay (3.40 vs. 2.80, <italic>P</italic> = 0.013). Moreover, patients with higher TyG index were associated with more postoperative complications, including a higher incidence of AKI (61.67% vs. 50.52%, <italic>P</italic> = 0.005) and hepatorenal syndrome (6.56% vs. 1.92%, <italic>P</italic> = 0.005).</p>", "<title>Electronic supplementary material</title>", "<p>Below is the link to the electronic supplementary material.</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>", "<p>\n\n</p>" ]
[ "<title>Acknowledgements</title>", "<p>None.</p>", "<title>Author contributions</title>", "<p>ZD, CC and ZH: conceptualization, methodology; ZD, YT: data cleaning, statistical analysis, visualization; ZD, CC: manuscript writing; ZD, MG, YT, CC and ZH: manuscript reviewing and editing.</p>", "<title>Funding</title>", "<p>This study was supported partly by the the Joint Funds of the National Natural Science Foundation of China (No. U22A20276), Science and Technology Planning Project of Guangdong Province - Regional Innovation Capacity and Support System Construction (No. 2023B110006), Science and Technology Program of Guangzhou, China (No. 202201020429), “Five and five” Project of the Third Affiliated Hospital of Sun Yat-Sen University (No. 2023WW501), and Young Talent Support Project of Guangzhou Association for Science and Technology (Grant No. QT20220101257).</p>", "<title>Data availability</title>", "<p>The original data supporting the results obtained are available from the corresponding author with reasonable ethical research demands.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par46\">This study protocol was granted approval by the Ethical Committee of the Third Affiliated Hospital of Sun Yat-sen University [No. (2019)02-609-04]. Since the data were anonymized before receiving by the researchers, the requirement of informed consent was waived by the Ethnic Committee.</p>", "<title>Consent for publication</title>", "<p id=\"Par47\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par45\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Patient inclusion and exclusion criteria flowchart. FBG fasting blood glucose, TyG triglyceride-glucose</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Restricted cubic spline regression analysis of TyG index with postoperative stroke. The heavy central lines in the graph depict the estimated adjusted odds ratios, while the light dotted lines indicate the corresponding 95% confidence intervals. The TyG index 8.18 was chosen as the reference level and is represented by the vertical dotted lines. TyG triglyceride-glucose, CI confidence intervals</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Kaplan–Meier event curves for all-cause death. Kaplan-Meier curves representing the cumulative probability of all-cause death according to groups in hospital (<bold>A</bold>), 1 year (<bold>B</bold>), and 3 years (<bold>C</bold>). Footnote TyG index quartiles: T1 (&lt; 7.92), T2 (7.92–8.53), T3 (&gt; 8.53)</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Forest plots of fully adjusted odds ratio for the postopeartive stroke in different subgroups. OR, odds ratio; CI, confidence interval</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Key baseline clinical characteristics of patients with stratification by stroke</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">All (N = 780)</th><th align=\"left\">Non-Stroke (N = 738)</th><th align=\"left\">Stroke (N = 42)</th><th align=\"left\">\n<italic>P-value</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"left\">49.00 (42.00–56.00)</td><td align=\"left\">49.00 (41.25–55.75)</td><td align=\"left\">52.00 (42.50–61.00)</td><td align=\"left\">0.094</td></tr><tr><td align=\"left\">Sex (male)</td><td align=\"left\">680 (87.18%)</td><td align=\"left\">643 (87.1%)</td><td align=\"left\">37 (88.1%)</td><td align=\"left\">0.855</td></tr><tr><td align=\"left\">BMI</td><td align=\"left\">22.70 (21.00-24.42)</td><td align=\"left\">22.70 (20.92–24.37)</td><td align=\"left\">22.50 (21.22–24.78)</td><td align=\"left\">0.856</td></tr><tr><td align=\"left\">ASA</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">II</td><td align=\"left\">71 (9.10%)</td><td align=\"left\">70 (9.5%)</td><td align=\"left\">1 (2.4%)</td><td align=\"left\"/></tr><tr><td align=\"left\">III</td><td align=\"left\">706 (90.51%)</td><td align=\"left\">668 (90.5%)</td><td align=\"left\">38 (90.5%)</td><td align=\"left\"/></tr><tr><td align=\"left\">IV</td><td align=\"left\">3 (0.38%)</td><td align=\"left\">0 (0.0%)</td><td align=\"left\">3 (7.1%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Smoking</td><td align=\"left\">243 (31.15%)</td><td align=\"left\">225 (30.5%)</td><td align=\"left\">18 (42.9%)</td><td align=\"left\">0.092</td></tr><tr><td align=\"left\">Alcoholism</td><td align=\"left\">200 (25.64%)</td><td align=\"left\">184 (24.9%)</td><td align=\"left\">16 (38.1%)</td><td align=\"left\">0.057</td></tr><tr><td align=\"left\">Drug abuse</td><td align=\"left\">4 (0.51%)</td><td align=\"left\">4 (0.5%)</td><td align=\"left\">0 (0.0%)</td><td align=\"left\">0.632</td></tr><tr><td align=\"left\">Previous surgery</td><td align=\"left\">53 (6.79%)</td><td align=\"left\">49 (6.6%)</td><td align=\"left\">4 (9.5%)</td><td align=\"left\">0.47</td></tr><tr><td align=\"left\">Child Pugh score</td><td align=\"left\">10.00 (8.00–11.00)</td><td align=\"left\">10.00 (8.00–11.00)</td><td align=\"left\">10.00 (9.00–11.00)</td><td align=\"left\">\n<bold>0.035</bold>\n</td></tr><tr><td align=\"left\">SOFA</td><td align=\"left\">11.00 (9.00–13.00)</td><td align=\"left\">11.00 (9.00–13.00)</td><td align=\"left\">12.00 (10.25-14.00)</td><td align=\"left\">\n<bold>0.042</bold>\n</td></tr><tr><td align=\"left\">MELD</td><td align=\"left\">23.00 (22.00–34.00)</td><td align=\"left\">22.00 (22.00–34.00)</td><td align=\"left\">31.50 (23.25–39.50)</td><td align=\"left\">\n<bold>0.001</bold>\n</td></tr><tr><td align=\"left\">Comorbidities</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Alcoholic liver disease</td><td align=\"left\">55 (7.05%)</td><td align=\"left\">48 (6.5%)</td><td align=\"left\">7 (16.7%)</td><td align=\"left\">\n<bold>0.012</bold>\n</td></tr><tr><td align=\"left\">Cirrhosis</td><td align=\"left\">642 (82.31%)</td><td align=\"left\">617 (83.6%)</td><td align=\"left\">25 (59.5%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Portal hypertension</td><td align=\"left\">426 (54.62%)</td><td align=\"left\">411 (55.7%)</td><td align=\"left\">15 (35.7%)</td><td align=\"left\">\n<bold>0.011</bold>\n</td></tr><tr><td align=\"left\">Hypersplenism</td><td align=\"left\">416 (53.33%)</td><td align=\"left\">404 (54.7%)</td><td align=\"left\">12 (28.6%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Fever</td><td align=\"left\">95 (12.18%)</td><td align=\"left\">85 (11.5%)</td><td align=\"left\">10 (23.8%)</td><td align=\"left\">\n<bold>0.018</bold>\n</td></tr><tr><td align=\"left\">Renal insufficiency</td><td align=\"left\">207 (26.54%)</td><td align=\"left\">191 (25.9%)</td><td align=\"left\">16 (38.1%)</td><td align=\"left\">\n<bold>0.081</bold>\n</td></tr><tr><td align=\"left\">Diabetes</td><td align=\"left\">109 (13.97%)</td><td align=\"left\">98 (13.3%)</td><td align=\"left\">11 (26.2%)</td><td align=\"left\">\n<bold>0.019</bold>\n</td></tr><tr><td align=\"left\">Hypertension</td><td align=\"left\">67 (8.59%)</td><td align=\"left\">63 (8.5%)</td><td align=\"left\">4 (9.5%)</td><td align=\"left\">0.824</td></tr><tr><td align=\"left\">HE</td><td align=\"left\">156 (20.00%)</td><td align=\"left\">140 (19.0%)</td><td align=\"left\">16 (38.1%)</td><td align=\"left\">\n<bold>0.003</bold>\n</td></tr><tr><td align=\"left\">\n<bold>Treatments</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Mechanical ventilation</td><td align=\"left\">60 (7.69%)</td><td align=\"left\">53 (7.2%)</td><td align=\"left\">7 (16.7%)</td><td align=\"left\">\n<bold>0.025</bold>\n</td></tr><tr><td align=\"left\">Hemodialysis</td><td align=\"left\">230 (29.49%)</td><td align=\"left\">205 (27.8%)</td><td align=\"left\">25 (59.5%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">PE</td><td align=\"left\">170 (21.79%)</td><td align=\"left\">151 (20.5%)</td><td align=\"left\">19 (45.2%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">\n<bold>Laboratory tests</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">TYG index</td><td align=\"left\">8.23 (7.78–8.72)</td><td align=\"left\">8.21 (7.76–8.69)</td><td align=\"left\">8.68 (8.14–9.02)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Hemoglobin (g/L)</td><td align=\"left\">101.00 (83.00-122.00)</td><td align=\"left\">102.00 (83.00-122.57)</td><td align=\"left\">90.14 (75.25-106.25)</td><td align=\"left\">\n<bold>0.003</bold>\n</td></tr><tr><td align=\"left\">WBC (10<sup>9</sup>/L)</td><td align=\"left\">5.39 (3.58–8.76)</td><td align=\"left\">5.29 (3.55–8.55)</td><td align=\"left\">8.18 (3.96–11.82)</td><td align=\"left\">\n<bold>0.015</bold>\n</td></tr><tr><td align=\"left\">Platelet (10<sup>9</sup>/L)</td><td align=\"left\">72.52 (46.00-122.00)</td><td align=\"left\">73.00 (47.00-123.75)</td><td align=\"left\">58.50 (40.00–99.00)</td><td align=\"left\">0.063</td></tr><tr><td align=\"left\">FBG (mmol/L)</td><td align=\"left\">5.00 (4.22–6.43)</td><td align=\"left\">4.96 (4.20–6.27)</td><td align=\"left\">6.81 (4.75–10.04)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">TC (mmol/L)</td><td align=\"left\">3.03 (2.08–3.93)</td><td align=\"left\">3.06 (2.10-4.00)</td><td align=\"left\">2.46 (1.90–3.41)</td><td align=\"left\">\n<bold>0.01</bold>\n</td></tr><tr><td align=\"left\">HDL (mmol/L)</td><td align=\"left\">0.47 (0.15–0.91)</td><td align=\"left\">0.48 (0.15–0.93)</td><td align=\"left\">0.34 (0.13–0.60)</td><td align=\"left\">\n<bold>0.02</bold>\n</td></tr><tr><td align=\"left\">FIB (g/L)</td><td align=\"left\">1.59 (1.05–2.65)</td><td align=\"left\">1.62 (1.07–2.67)</td><td align=\"left\">1.27 (0.82–1.89)</td><td align=\"left\">\n<bold>0.004</bold>\n</td></tr><tr><td align=\"left\">ALT (U/L)</td><td align=\"left\">54.90 (27.00-116.00)</td><td align=\"left\">54.00 (27.00-116.00)</td><td align=\"left\">83.85 (29.25-119.75)</td><td align=\"left\">\n<bold>0.005</bold>\n</td></tr><tr><td align=\"left\">IBIL (µmol/L)</td><td align=\"left\">38.83 (10.80-137.99)</td><td align=\"left\">36.40 (10.50-132.62)</td><td align=\"left\">111.60 (25.02–188.40)</td><td align=\"left\">\n<bold>0.026</bold>\n</td></tr><tr><td align=\"left\">SCr (µmol/L)</td><td align=\"left\">73.00 (60.00–92.00)</td><td align=\"left\">73.00 (60.00–91.00)</td><td align=\"left\">73.50 (59.50-148.75)</td><td align=\"left\">\n<bold>0.013</bold>\n</td></tr><tr><td align=\"left\" colspan=\"2\">\n<bold>Intraoperative indicators</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Night surgery</td><td align=\"left\">276 (35.38%)</td><td align=\"left\">251 (34.0%)</td><td align=\"left\">25 (59.5%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Surgery duration</td><td align=\"left\">521.00 (470.00-580.00)</td><td align=\"left\">520.00 (470.00-580.00)</td><td align=\"left\">532.50 (486.00-622.25)</td><td align=\"left\">0.174</td></tr><tr><td align=\"left\">Donor type</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">\n<bold>0.005</bold>\n</td></tr><tr><td align=\"left\">DBD</td><td align=\"left\">471 (60.38%)</td><td align=\"left\">453 (61.4%)</td><td align=\"left\">18 (42.9%)</td><td align=\"left\"/></tr><tr><td align=\"left\">DCD</td><td align=\"left\">301 (38.59%)</td><td align=\"left\">279 (37.8%)</td><td align=\"left\">22 (52.4%)</td><td align=\"left\"/></tr><tr><td align=\"left\">DBCD</td><td align=\"left\">8 (1.03%)</td><td align=\"left\">6 (0.8%)</td><td align=\"left\">2 (4.8%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Massive transfusion</td><td align=\"left\">231 (29.62%)</td><td align=\"left\">210 (28.5%)</td><td align=\"left\">21 (50.0%)</td><td align=\"left\">\n<bold>0.003</bold>\n</td></tr><tr><td align=\"left\">Massive blood losing</td><td align=\"left\">37 (4.74%)</td><td align=\"left\">30 (4.1%)</td><td align=\"left\">7 (16.7%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Urinary oliguria</td><td align=\"left\">32 (4.10%)</td><td align=\"left\">25 (3.4%)</td><td align=\"left\">7 (16.7%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Cardiac arrest</td><td align=\"left\">16 (2.036%)</td><td align=\"left\">13 (1.762%)</td><td align=\"left\">3 (7.143%)</td><td align=\"left\">\n<bold>0.017</bold>\n</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Baseline clinical characteristics and outcomes of patients categorized by TyG index<sup>a</sup></p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\"/><th align=\"left\">All (N = 780)</th><th align=\"left\">T1 (N = 259)</th><th align=\"left\">T2 (N = 262)</th><th align=\"left\">T3 (N = 259)</th><th align=\"left\">\n<italic>P-value</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Age (years)</td><td align=\"left\">49.00 (42.00–56.00)</td><td align=\"left\">46.00 (39.00–53.00)</td><td align=\"left\">50.00 (43.25-56.00)</td><td align=\"left\">50.00 (42.00–57.00)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Sex (male)</td><td align=\"left\">680 (87.18%)</td><td align=\"left\">228 (88.03%)</td><td align=\"left\">225 (85.88%)</td><td align=\"left\">227 (87.64%)</td><td align=\"left\">0.735</td></tr><tr><td align=\"left\">BMI</td><td align=\"left\">22.70 (21.00-24.42)</td><td align=\"left\">22.50 (20.80–24.20)</td><td align=\"left\">22.57 (20.83–24.37)</td><td align=\"left\">23.00 (21.15–24.70)</td><td align=\"left\">0.142</td></tr><tr><td align=\"left\">ASA</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">\n<bold>0.005</bold>\n</td></tr><tr><td align=\"left\">II</td><td align=\"left\">71 (9.10%)</td><td align=\"left\">13 (5.02%)</td><td align=\"left\">29 (11.07%)</td><td align=\"left\">29 (11.20%)</td><td align=\"left\"/></tr><tr><td align=\"left\">III</td><td align=\"left\">706 (90.51%)</td><td align=\"left\">246 (94.98%)</td><td align=\"left\">233 (88.93%)</td><td align=\"left\">227 (87.64%)</td><td align=\"left\"/></tr><tr><td align=\"left\">IV</td><td align=\"left\">3 (0.38%)</td><td align=\"left\">0 (0.00%)</td><td align=\"left\">0 (0.00%)</td><td align=\"left\">3 (1.16%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Previous surgery</td><td align=\"left\">53 (6.79%)</td><td align=\"left\">21 (8.11%)</td><td align=\"left\">15 (5.73%)</td><td align=\"left\">17 (6.56%)</td><td align=\"left\">0.549</td></tr><tr><td align=\"left\">MELD</td><td align=\"left\">23.00 (22.00–34.00)</td><td align=\"left\">22.00 (22.00-34.50)</td><td align=\"left\">22.00 (22.00–30.00)</td><td align=\"left\">29.00 (22.00-36.50)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Renal insufficiency</td><td align=\"left\">207 (26.54%)</td><td align=\"left\">76 (29.34%)</td><td align=\"left\">62 (23.66%)</td><td align=\"left\">69 (26.64%)</td><td align=\"left\">0.340</td></tr><tr><td align=\"left\">Diabetes</td><td align=\"left\">109 (13.97%)</td><td align=\"left\">15 (5.79%)</td><td align=\"left\">40 (15.27%)</td><td align=\"left\">54 (20.85%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Hypertension</td><td align=\"left\">67 (8.59%)</td><td align=\"left\">18 (6.95%)</td><td align=\"left\">27 (10.31%)</td><td align=\"left\">22 (8.49%)</td><td align=\"left\">0.392</td></tr><tr><td align=\"left\">HE</td><td align=\"left\">156 (20.00%)</td><td align=\"left\">54 (20.85%)</td><td align=\"left\">46 (17.56%)</td><td align=\"left\">56 (21.62%)</td><td align=\"left\">0.468</td></tr><tr><td align=\"left\">Hemodialysis</td><td align=\"left\">230 (29.49%)</td><td align=\"left\">80 (30.89%)</td><td align=\"left\">70 (26.72%)</td><td align=\"left\">80 (30.89%)</td><td align=\"left\">0.483</td></tr><tr><td align=\"left\">TYG index</td><td align=\"left\">8.23 (7.78–8.72)</td><td align=\"left\">7.62 (7.34–7.77)</td><td align=\"left\">8.23 (8.08–8.37)</td><td align=\"left\">8.96 (8.72–9.34)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Hemoglobin (g/L)</td><td align=\"left\">101.00 (83.00-122.00)</td><td align=\"left\">91.00 (78.00-108.00)</td><td align=\"left\">108.00 (87.00-124.00)</td><td align=\"left\">107.00 (85.00-132.03)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">WBC (10<sup>9</sup>/L)</td><td align=\"left\">5.39 (3.58–8.76)</td><td align=\"left\">4.83 (3.04–7.79)</td><td align=\"left\">4.96 (3.52–8.19)</td><td align=\"left\">6.52 (4.27–10.15)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Platelet (10<sup>9</sup>/L)</td><td align=\"left\">72.52 (46.00-122.00)</td><td align=\"left\">61.00 (39.50–90.00)</td><td align=\"left\">74.00 (49.00-126.75)</td><td align=\"left\">92.00 (52.00-146.50)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Day-or-Night surgery</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.841</td></tr><tr><td align=\"left\">Day</td><td align=\"left\">504 (64.62%)</td><td align=\"left\">171 (66.02%)</td><td align=\"left\">168 (64.12%)</td><td align=\"left\">165 (63.71%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Night</td><td align=\"left\">276 (35.38%)</td><td align=\"left\">88 (33.98%)</td><td align=\"left\">94 (35.88%)</td><td align=\"left\">94 (36.29%)</td><td align=\"left\"/></tr><tr><td align=\"left\">Surgery duration</td><td align=\"left\">521.00 (470.00-580.00)</td><td align=\"left\">530.00 (480.00-585.00)</td><td align=\"left\">515.00 (465.00-570.00)</td><td align=\"left\">520.00 (469.50–585.00)</td><td align=\"left\">0.145</td></tr><tr><td align=\"left\">Massive transfusion</td><td align=\"left\">231 (29.62%)</td><td align=\"left\">102 (39.38%)</td><td align=\"left\">61 (23.28%)</td><td align=\"left\">68 (26.25%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Massive blood losing</td><td align=\"left\">37 (4.74%)</td><td align=\"left\">18 (6.95%)</td><td align=\"left\">7 (2.67%)</td><td align=\"left\">12 (4.63%)</td><td align=\"left\">0.071</td></tr><tr><td align=\"left\">Urinary oliguria</td><td align=\"left\">32 (4.10%)</td><td align=\"left\">9 (3.47%)</td><td align=\"left\">7 (2.67%)</td><td align=\"left\">16 (6.18%)</td><td align=\"left\">0.108</td></tr><tr><td align=\"left\">Cardiac arrest</td><td align=\"left\">16 (2.04%)</td><td align=\"left\">6 (2.32%)</td><td align=\"left\">7 (2.67%)</td><td align=\"left\">3 (1.16%)</td><td align=\"left\">0.445</td></tr><tr><td align=\"left\">\n<bold>Outcomes</bold>\n</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">Stroke</td><td align=\"left\">42 (5.38%)</td><td align=\"left\">8 (3.09%)</td><td align=\"left\">10 (3.82%)</td><td align=\"left\">24 (9.27%)</td><td align=\"left\">\n<bold>&lt; 0.001</bold>\n</td></tr><tr><td align=\"left\">Hospital morality</td><td align=\"left\">43 (5.54%)</td><td align=\"left\">11 (4.31%)</td><td align=\"left\">11 (4.20%)</td><td align=\"left\">21 (8.11%)</td><td align=\"left\">\n<bold>0.027</bold>\n</td></tr><tr><td align=\"left\">1-year morality</td><td align=\"left\">103 (13.21%)</td><td align=\"left\">31 (11.97%)</td><td align=\"left\">28 (10.69%)</td><td align=\"left\">44 (16.99%)</td><td align=\"left\">\n<bold>0.028</bold>\n</td></tr><tr><td align=\"left\">3-year morality</td><td align=\"left\">123 (15.77%)</td><td align=\"left\">35 (13.51%)</td><td align=\"left\">36 (13.74%)</td><td align=\"left\">52 (20.08%)</td><td align=\"left\">\n<bold>0.020</bold>\n</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Association between quartiles of TyG<sup>a</sup> index with risk of stroke and all-cause mortality</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Outcomes</th><th align=\"left\" rowspan=\"2\">TyG<sup>a</sup> index</th><th align=\"left\" rowspan=\"2\">Event N (%)</th><th align=\"left\" colspan=\"2\">Unadjusted</th><th align=\"left\"/><th align=\"left\" colspan=\"2\">Model 1<sup>b</sup></th><th align=\"left\"/><th align=\"left\" colspan=\"2\">Model 2<sup>c</sup></th><th align=\"left\"/><th align=\"left\" colspan=\"2\">Model 3<sup>d</sup></th></tr><tr><th align=\"left\">OR/HR (95% CI)</th><th align=\"left\">\n<italic>P-value</italic>\n</th><th align=\"left\"/><th align=\"left\">OR/HR (95% CI)</th><th align=\"left\">\n<italic>P-value</italic>\n</th><th align=\"left\"/><th align=\"left\">OR/HR (95% CI)</th><th align=\"left\">\n<italic>P-value</italic>\n</th><th align=\"left\"/><th align=\"left\">OR/HR (95% CI)</th><th align=\"left\">\n<italic>P-value</italic>\n</th></tr></thead><tbody><tr><td align=\"left\">Storke</td><td align=\"left\">continuous</td><td align=\"left\">-</td><td align=\"left\">1.919 (1.280–2.875)</td><td align=\"left\">0.001</td><td align=\"left\"/><td align=\"left\">1.915 (1.227–2.986)</td><td align=\"left\">0.004</td><td align=\"left\"/><td align=\"left\">1.905 (1.183–3.066)</td><td align=\"left\">0.008</td><td align=\"left\"/><td align=\"left\">1.899 (1.180–3.055)</td><td align=\"left\">0.007</td></tr><tr><td align=\"left\"/><td align=\"left\">T1</td><td align=\"left\">8 (3.10)</td><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td></tr><tr><td align=\"left\"/><td align=\"left\">T2</td><td align=\"left\">10 (3.81)</td><td align=\"left\">1.245 (0.483–3.206)</td><td align=\"left\">0.649</td><td align=\"left\"/><td align=\"left\">1.171 (0.449–3.058)</td><td align=\"left\">0.747</td><td align=\"left\"/><td align=\"left\">1.328 (0.494–3.572)</td><td align=\"left\">0.574</td><td align=\"left\"/><td align=\"left\">1.583 (0.577–4.538)</td><td align=\"left\">0.375</td></tr><tr><td align=\"left\"/><td align=\"left\">T3</td><td align=\"left\">24 (9.26)</td><td align=\"left\">3.204 (1.412–7.273)</td><td align=\"left\">0.005</td><td align=\"left\"/><td align=\"left\">3.055 (1.330–7.019)</td><td align=\"left\">0.008</td><td align=\"left\"/><td align=\"left\">3.348 (1.410–7.952)</td><td align=\"left\">0.006</td><td align=\"left\"/><td align=\"left\">3.398 (1.371–8.426)</td><td align=\"left\">0.008</td></tr><tr><td align=\"left\"/><td align=\"left\"><italic>P</italic> for trend</td><td align=\"left\"/><td align=\"left\">0.003</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.011</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.015</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.012</td><td align=\"left\"/></tr><tr><td align=\"left\">Inhospital mortality</td><td align=\"left\">continuous</td><td align=\"left\">-</td><td align=\"left\">1.624 (1.103–2.392)</td><td align=\"left\">0.014</td><td align=\"left\"/><td align=\"left\">1.660 (1.126–2.446)</td><td align=\"left\">0.011</td><td align=\"left\"/><td align=\"left\">1.665 (1.129–2.453)</td><td align=\"left\">0.010</td><td align=\"left\"/><td align=\"left\">1.679 (1.136–2.484)</td><td align=\"left\">0.009</td></tr><tr><td align=\"left\"/><td align=\"left\">T1</td><td align=\"left\">11 (4.31)</td><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td></tr><tr><td align=\"left\"/><td align=\"left\">T2</td><td align=\"left\">11 (4.20)</td><td align=\"left\">1.088 (0.462–2.561)</td><td align=\"left\">0.847</td><td align=\"left\"/><td align=\"left\">1.143 (0.481–2.719)</td><td align=\"left\">0.761</td><td align=\"left\"/><td align=\"left\">1.137 (0.479–2.695)</td><td align=\"left\">0.772</td><td align=\"left\"/><td align=\"left\">1.075 (0.446–2.589)</td><td align=\"left\">0.873</td></tr><tr><td align=\"left\"/><td align=\"left\">T3</td><td align=\"left\">21 (8.11)</td><td align=\"left\">2.232 (1.057–4.714)</td><td align=\"left\">0.033</td><td align=\"left\"/><td align=\"left\">2.244 (1.051–4.792)</td><td align=\"left\">0.036</td><td align=\"left\"/><td align=\"left\">2.309 (1.086–4.911)</td><td align=\"left\">0.029</td><td align=\"left\"/><td align=\"left\">2.326 (1.089–4.931)</td><td align=\"left\">0.025</td></tr><tr><td align=\"left\"/><td align=\"left\"><italic>P</italic> for trend</td><td align=\"left\"/><td align=\"left\">0.025</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.038</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.030</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.018</td><td align=\"left\"/></tr><tr><td align=\"left\">1-year mortality</td><td align=\"left\">continuous</td><td align=\"left\">-</td><td align=\"left\">1.318 (1.019–1.706)</td><td align=\"left\">0.035</td><td align=\"left\"/><td align=\"left\">1.325 (1.026–1.709)</td><td align=\"left\">0.031</td><td align=\"left\"/><td align=\"left\">1.348 (1.023–1.775)</td><td align=\"left\">0.033</td><td align=\"left\"/><td align=\"left\">1.349 (1.021–1.784)</td><td align=\"left\">0.035</td></tr><tr><td align=\"left\"/><td align=\"left\">T1</td><td align=\"left\">31 (11.97)</td><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td></tr><tr><td align=\"left\"/><td align=\"left\">T2</td><td align=\"left\">28 (10.69)</td><td align=\"left\">0.941 (0.561–1.583)</td><td align=\"left\">0.821</td><td align=\"left\"/><td align=\"left\">0.986 (0.582–1.673)</td><td align=\"left\">0.735</td><td align=\"left\"/><td align=\"left\">1.053 (0.616–1.801)</td><td align=\"left\">0.851</td><td align=\"left\"/><td align=\"left\">1.021 (0.595–1.756)</td><td align=\"left\">0.757</td></tr><tr><td align=\"left\"/><td align=\"left\">T3</td><td align=\"left\">44 (16.99)</td><td align=\"left\">1.631 (1.025–2.595)</td><td align=\"left\">0.039</td><td align=\"left\"/><td align=\"left\">1.646 (1.029–2.633)</td><td align=\"left\">0.037</td><td align=\"left\"/><td align=\"left\">1.664 (1.022–2.711)</td><td align=\"left\">0.040</td><td align=\"left\"/><td align=\"left\">1.668 (1.024–2.717)</td><td align=\"left\">0.039</td></tr><tr><td align=\"left\"/><td align=\"left\"><italic>P</italic> for trend</td><td align=\"left\"/><td align=\"left\">0.028</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.026</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.024</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.029</td><td align=\"left\"/></tr><tr><td align=\"left\">3-year mortality</td><td align=\"left\">continuous</td><td align=\"left\">-</td><td align=\"left\">1.464 (1.143–1.874)</td><td align=\"left\">0.002</td><td align=\"left\"/><td align=\"left\">1.428 (1.103–1.849)</td><td align=\"left\">0.007</td><td align=\"left\"/><td align=\"left\">1.419 (1.078–1.868)</td><td align=\"left\">0.013</td><td align=\"left\"/><td align=\"left\">1.415 (1.074–1.866)</td><td align=\"left\">0.014</td></tr><tr><td align=\"left\"/><td align=\"left\">T1</td><td align=\"left\">35 (13.51)</td><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td><td align=\"left\"/><td align=\"left\">Ref.</td><td align=\"left\">-</td></tr><tr><td align=\"left\"/><td align=\"left\">T2</td><td align=\"left\">36 (13.74)</td><td align=\"left\">1.101 (0.684–1.772)</td><td align=\"left\">0.693</td><td align=\"left\"/><td align=\"left\">1.066 (0.657–1.727)</td><td align=\"left\">0.796</td><td align=\"left\"/><td align=\"left\">1.138 (0.693–1.869)</td><td align=\"left\">0.609</td><td align=\"left\"/><td align=\"left\">1.295 (0.783–2.143)</td><td align=\"left\">0.314</td></tr><tr><td align=\"left\"/><td align=\"left\">T3</td><td align=\"left\">52 (20.08)</td><td align=\"left\">1.784 (1.154–2.758)</td><td align=\"left\">0.009</td><td align=\"left\"/><td align=\"left\">1.654 (1.058–2.586)</td><td align=\"left\">0.021</td><td align=\"left\"/><td align=\"left\">1.721 (1.075–2.755)</td><td align=\"left\">0.020</td><td align=\"left\"/><td align=\"left\">1.837 (1.445–2.950)</td><td align=\"left\">0.012</td></tr><tr><td align=\"left\"/><td align=\"left\"><italic>P</italic> for trend</td><td align=\"left\"/><td align=\"left\">0.006</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.015</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.013</td><td align=\"left\"/><td align=\"left\"/><td align=\"left\">0.016</td><td align=\"left\"/></tr></tbody></table></table-wrap>" ]
[]
[]
[]
[]
[]
[ "<supplementary-material content-type=\"local-data\" id=\"MOESM1\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM2\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM3\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM4\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM5\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM6\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM7\"></supplementary-material>", "<supplementary-material content-type=\"local-data\" id=\"MOESM8\"></supplementary-material>" ]
[ "<table-wrap-foot><p><italic>Note</italic>: Data were expressed as mean (standard deviation), median (interquartile range) or n (%). Bold data indicates significance at &lt; 0.05</p><p><italic>Abbreviation</italic>: BMI, body mass index; ASA, American Society of Anesthesiologists; SOFA, sequential organ failure assessment score; MELD, model for end-stage liver disease score; HE, hepatic encephalopathy; PE, plasma exchange; TyG, triglyceride-glucose index; WBC, white blood cell; TG, triglyceride; FBG, fasting blood glucose; TC, total cholesterol; HDL, high density lipoprotein; LDL, low density lipoprotein; PT, prothrombin time; INR, international normalized ratio; FIB, fibrinogen; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TBIL, total bilirubin; IBIL, indirect bilirubin; SCr, serum creatinine; BUN, blood urea nitrogen; DBD, donation after brain death; DCD, donation after circulatory death; DBCD, donation after brain death followed by circulatory death</p></table-wrap-foot>", "<table-wrap-foot><p><italic>Note</italic>: Data were expressed as mean (standard deviation), median (interquartile range) or n (%). Bold data indicates significance at &lt; 0.05</p><p><sup>a</sup>TyG index: T1 (&lt; 7.92), T2 (7.92–8.53), T3 (&gt; 8.53)</p><p><italic>Abbreviation</italic>: BMI, body mass index; ASA, American Society of Anesthesiologists; MELD, model for end-stage liver disease score; HE, hepatic encephalopathy; TyG, triglyceride-glucose index; WBC, white blood cell</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>TyG index: T1 (&lt; 7.92), T2 (7.92–8.53), T3 (&gt; 8.53)</p><p><sup>b</sup>Model 1 was adjusted for age, sex, BMI and ASA classification</p><p><sup>c</sup>Model 2 was adjusted for age, sex, BMI, ASA classification, hypertension, diabetes, renal insufficiency, HE, MELD score, hemodialysis, HB, WBC and platelet</p><p><sup>d</sup>Model 3 was adjusted for age, sex, BMI, ASA classification, hypertension, diabetes, renal insufficiency, HE, MELD score, hemodialysis, HB, WBC, platelet, day-or-night surgery, surgery duration, massive transfusion, massive blood losing, urinary oliguria and intraoperative cardiac arrest</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2113_Fig1_HTML\" id=\"d32e502\"/>", "<graphic xlink:href=\"12933_2023_2113_Fig2_HTML\" id=\"d32e2499\"/>", "<graphic xlink:href=\"12933_2023_2113_Fig3_HTML\" id=\"d32e2558\"/>", "<graphic xlink:href=\"12933_2023_2113_Fig4_HTML\" id=\"d32e2581\"/>" ]
[ "<media xlink:href=\"12933_2023_2113_MOESM1_ESM.docx\"><caption><p><bold>Supplementary Material 1: Supplementary Table 1</bold>. Overview of missing values in the original data</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM2_ESM.docx\"><caption><p><bold>Supplementary Material 2: Supplementary Table 2</bold>. All baseline clinical characteristics of patients stratified by stroke</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM3_ESM.docx\"><caption><p><bold>Supplementary Material 3: Supplementary Table 3</bold>. Binary logistic regression analysis of the factors influencing stroke of the study population</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM4_ESM.docx\"><caption><p><bold>Supplementary Material 4: Supplementary Table 4</bold>. Collinearity diagnostics by variance expansion factor (VIF)</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM5_ESM.docx\"><caption><p><bold>Supplementary Material 5: Supplementary Table 5</bold>. The definitions of confounders</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM6_ESM.docx\"><caption><p><bold>Supplementary Material 6: Supplementary Table 6</bold>. Association between TyG index and postoperative stroke in sensitivity analyses</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM7_ESM.docx\"><caption><p><bold>Supplementary Material 7: Supplementary Table 7</bold>. Postoperative relative outcomes of patients categorized by TyG index</p></caption></media>", "<media xlink:href=\"12933_2023_2113_MOESM8_ESM.docx\"><caption><p><bold>Supplementary Material 8: Supplementary Table 8</bold>. Supplementary Online Content</p></caption></media>" ]
[{"label": ["6."], "mixed-citation": ["Fagiuoli S, Colli A, Bruno R, Craxi A, Gaeta GB, Grossi P, Mondelli MU, Puoti M, Sagnelli E, Stefani S, Toniutto P, Burra P, Group AST. (2014) Management of infections pre- and post-liver transplantation: report of an AISF consensus conference. J Hepatol 60: 1075\u20131089."]}, {"label": ["9."], "mixed-citation": ["Benesch C, Glance LG, Derdeyn CP, Fleisher LA, Holloway RG, Messe SR, Mijalski C, Nelson MT, Power M, Welch BG, American Heart Association, Stroke C, Council on Arteriosclerosis T, Vascular B, Council C, Stroke N, Council on Clinical C, Council on E, Prevention., (2021) Perioperative Neurological Evaluation and Management to Lower the Risk of Acute Stroke in Patients Undergoing Noncardiac, Nonneurological Surgery: A Scientific Statement From the American Heart Association/American Stroke Association. Circulation 143: e923-e946."]}, {"label": ["26."], "mixed-citation": ["(1989) Stroke\u20131989. Recommendations on Stroke prevention, diagnosis, and therapy. Report of the WHO Task Force on Stroke and other Cerebrovascular disorders. Stroke 20: 1407\u201331."]}]
{ "acronym": [ "TyG", "IR", "LT", "RCS", "OR", "CI", "HR", "ESLD", "PS", "FBG", "TG", "ICU", "BMI", "ASA", "PE", "MV", "RBC", "WBC", "ALT", "AST", "SCr", "BUN", "INR378", "PT", "MELD", "SOFA", "VIF", "GD" ], "definition": [ "triglyceride-glucose index", "insulin resistance", "liver transplantation", "restricted cubic spline", "odds ratio", "confidence interval", "hazard ratio", "end-stage liver disease", "perioperative stroke", "fasting blood glucose", "triglycerides", "intensive care unit", "body mass index", "American Society of Anaesthesiologists", "plasma exchange", "mechanical ventilation", "red blood cell", "white blood cell", "alanine aminotransferase", "aspartate aminotransferase", "serum creatinine", "blood urea nitrogen", "international normalised ratio", "prothrombin time", "Model for End-Stage Liver Disease Score", "Sepsis-related Organ Failure Assessment Score", "variance inflation factor", "glycometabolic disorders" ] }
48
CC BY
no
2024-01-14 23:43:47
Cardiovasc Diabetol. 2024 Jan 13; 23:27
oa_package/b8/17/PMC10787491.tar.gz
PMC10787492
38217048
[ "<title>Introduction</title>", "<p id=\"Par5\"> With improved living conditions and dietary changes, the incidence of metabolic diseases such as diabetes and obesity are on the rise [##REF##29392352##1##]. Obesity can result in high cholesterol, high triglycerides, insulin resistance, increased peripheral vascular resistance, and so on, which can lead to hypertension, coronary heart disease, type II diabetes mellitus (T2DM), and an increase in the morbidity and mortality associated with these diseases [##UREF##0##2##–##UREF##2##4##]. Hyperlipidemia and diabetes have been shown to cause hearing loss, but the mechanism is still unclear [##REF##28135010##5##, ##UREF##3##6##]. Long-term metabolic disorders such as hyperlipidemia and hyperglycemia can induce oxidative stress, activate multiple apoptotic signaling pathways, and cause cell damage [##UREF##4##7##]. Endoplasmic reticulum stresses (ERS) are currently being implicated in an increasing number of studies as a factor in hearing loss [##REF##32029702##8##–##UREF##5##10##]. In the ERS process, the high expression of its marker protein 78 (glucose-regulated protein 78 (GRP78)), also known as immunoglobulin heavy chain binding protein (Bip), activates many caspase family factors, such as the high expression of caspase-12, resulting in apoptosis [##REF##26801321##11##]. In this study, we investigated the expression pattern of the GRP78 protein within the cochlea. Our study delved into a comparative and analytical exploration of the ERS mechanism underlying hearing impairment in cases involving both obesity and diabetes.</p>" ]
[ "<title>Materials and methods</title>", "<title>Experimental animals and feed</title>", "<p id=\"Par6\">The study utilized 30 healthy, four-week-old male Sprague-Dawley (SD) rats weighing between 200 and 220 g, which were supplied by the Laboratory of the School of Basic Medical Science at Henan University of Science and Technology. The rats were provided unrestricted access to water and exposed to alternating cycles of natural day and night light, maintaining a controlled environment with temperatures ranging from 20 to 25 °C and relative humidity levels between 40% and 60%. Regarding their diet, they were fed a high-glucose and high-lipid feed composed of basic feed (69.5%), cholesterol (1%), sucrose (10%), and other ingredients (19.5%).</p>", "<p id=\"Par7\">This study was conducted with approval from the Ethics Committee of The First Affiliated Hospital,and College of Clinical Medicine of Henan University of Science and Technology. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.</p>", "<title>Model establishment and grouping</title>", "<p id=\"Par8\">After one week of adaptive feeding with basic feed, the rats were randomly divided into the normal control group (NC group, <italic>n</italic> = 10) and high-fat group (HF group, <italic>n</italic> = 20). The rats were fed basic feed, high glucose feed, and high fat feed for eight weeks each. When the average body weight of the HF group exceeded 20% of the average body weight of the NC group, it was deemed that the obesity model had been successfully established. The HF group was randomly divided into the obesity group (OB group, <italic>n</italic> = 10) and diabetes group (T2DM, <italic>n</italic> = 10). A low dose of STZ (45 mg/kg) was administered intraperitoneally to the T2DM group, while the OB group and the NC group received an equivalent intraperitoneal dose of citric acid buffer. Following four weeks of being on the original diet, blood samples were drawn from the tail vein to measure fasting glucose and lipid levels. The T2DM group was successfully modeled when the blood glucose level was &gt; 11.1 mmol/L.</p>", "<title>Auditory brainstem evoked potentials</title>", "<p id=\"Par9\">The rats were intraperitoneally injected with a 2% pentobarbital sodium solution at a dosage of 45 mg/kg in a designated soundproof room. Following successful anesthesia, the rats were positioned on an anatomical table. The recording electrode was carefully positioned under the skin at the middle cranial region of both ears, and the reference electrode was placed under the skin of the pinna of the ear being measured. The rats had an earphone inserted into their external auditory canal. The auditory brainstem response (ABR) threshold of the rats was measured using an evoked potential meter (Neuro-Audio Russia) [##UREF##6##12##]. The stimulation of tone pips was superimposed 1024 times, and the frequency range of the filtering was 100–3000 Hz. The frequency of stimulation was 21 times per minute. The stimulation intensity began at 90 dB SPL, decreased gradually by 10 dB SPL, and then decreased by 5 dB SPL as the level approached the ABR threshold. The ABR threshold was determined using the wave III threshold when the resistance was less than 3 kΩ.</p>", "<title>Preparation of cochlear specimens</title>", "<p id=\"Par10\">Six cochleae were selected in each group. After inducing general anesthesia, the cochleae were carefully extracted from the sacrificed rats following decapitation. A thin needle was used to puncture open the round window membrane and the tip of the cochlea. Subsequently, four injections of 10% paraformaldehyde were administered into the cochlea’s tip using a latex dropper. Following immersion in the fixing solution overnight, the cochleae were rinsed with phosphate-buffered saline (PBS) and subjected to a two-week decalcification process using a 10% EDTA decalcification solution, with the solution being renewed every three days. After complete decalcification, the samples were routinely embedded in paraffin for subsequent tissue sectioning.</p>", "<title>HE staining [##UREF##7##13##]</title>", "<p id=\"Par11\">Sections measuring 5 μm were sliced using a microtome, followed by a 10-minute dewaxing process with xylene I, II, and III, and subsequent hydration with gradient alcohol. Hematoxylin dye solution (obtained from Beijing Soleil Technology Co., Ltd.) was added drop by drop to the wet box, and the sections were allowed to react for four minutes. They were then rinsed thoroughly with running water until no residual blue color was visible. The cells were briefly treated with a differentiation solution containing 1% hydrochloric acid alcohol for 2 to 3 s, followed by a 30-minute rinse with running water to restore their blue color. Following the hematoxylin staining process, eosin dye solution (sourced from Beijing Soleil Technology Co., Ltd.) was added drop by drop for a duration of 3 min. The sections were then dehydrated and sealed for further analysis.</p>", "<title>Immunohistochemical experiment [##UREF##8##14##, ##UREF##9##15##]</title>", "<p id=\"Par12\">After dewaxing the sections in water, 3% H2O2 was added dropwise to the sections in the dark at room temperature for 10 min, and the sections were then immersed and washed in PBS. The antigen retrieval process involved microwaving for 10 min, followed by incubation in a blocking solution comprising 5% goat serum for 30 min. After rinsing, the samples were coated with GRP78/Bip rabbit monoclonal antibody (BA2042-1, sourced from Beijing Soleil Technology Co., Ltd.) at a dilution ratio of 1:400 in PBS and left overnight at 4 °C. The following day, after rewarming, the samples were removed, rinsed, and then subjected to the dropwise addition of goat anti-rabbit IgG secondary antibody (from Beijing Soleil Technology Co., Ltd.) at a dilution ratio of 1:200 in PBS. Subsequently, the samples were placed in a 37 °C incubator for 30 min, followed by rinsing. Dropwise addition of DAB dye solution (sourced from Shanghai Epizyme Biological Medicine Co., Ltd.) was carried out under a microscope (Olympus BX41, Japan). Color development was monitored, and the reaction was terminated by rinsing the samples under running water once the color changed from colorless to yellow. Hematoxylin was then applied dropwise for counterstaining. After the color changed to blue, the sections were dehydrated and subsequently sealed for analysis.</p>", "<title>Western blot analysis of protein concentration</title>", "<p id=\"Par13\">Four rats were chosen from each group. Following decapitation, the cochlea was extracted, rinsed with PBS, and immersed in liquid nitrogen for 5 min. Subsequently, the tissue was ground, and a protein lysis buffer was added. After ultrasonic homogenization, the protein was quantified using the BCA protein quantitative method. This was followed by incubation at 95 °C for 10 min and centrifugation at 12,000 revolutions per minute (r/min) for 15 min to obtain the protein extract. The protein was placed in the blocking solution after polyacrylamide gel electrophoresis and membrane transfer, and GRP78 antibody (1:1000) and internal reference–actin (1:5000) were added after shaker incubation, followed by overnight incubation at 4 °C. After being washed three times with Tris-buffered saline with Tween (TBST) buffer, the membrane was exposed to the secondary antibody for one hour. The relative expression level of the GRP78/Bip protein was calculated using ImageProPlus5 software (relative expression level of protein = gray value of the target protein/gray value of β-actin).</p>", "<title>Statistical analysis</title>", "<p id=\"Par14\">SPSS25.0 software was used for statistical analysis. Quantitative data such as body weight, blood glucose level, and ABR threshold of rats in each group are expressed as mean ± standard deviation. One-way analysis of variance was used to compare multiple groups, and the LSD t-test was used to compare pairs of groups, with <italic>P</italic> &lt; 0.05 indicating statistically significant differences.</p>" ]
[ "<title>Results</title>", "<title>Changes in body weight and comparative analysis of blood glucose and lipid in rats</title>", "<p id=\"Par15\">By the 8th week, the average body weights of the OB and T2DM groups had exceeded 20% of that in the NC group. By the 12th week, the blood glucose level in the T2DM group exceeded 11.1 mmol/L, indicating the successful establishment of the diabetic model. At this point, the body weight of the OB group was significantly higher than that of the NC group (<italic>P</italic> &lt; 0.01), while the body weight of the T2DM group was notably lower than both the NC group and the OB group (<italic>P</italic> &lt; 0.01). The T2DM group had significantly higher fasting blood glucose, total cholesterol (TC), and triglyceride (TG) values than the NC group and the OB group, and the OB group had higher values than the NC group (Table ##TAB##0##1##). A high-glucose and high-fat diet may cause metabolic disorders in the body over time.</p>", "<p id=\"Par16\">\n</p>", "<title>Comparison and analysis of ABR thresholds in rats</title>", "<p id=\"Par19\">Compared with the NC group, the ABR thresholds in the T2DM and OB groups were statistically significant (<italic>P</italic> &lt; 0.05), while the ABR threshold in the T2DM group was statistically significant compared to the OB group. The ABR thresholds of the T2DM group were also significantly higher than those of the NC and OB groups, with the OB group exceeding the NC group (Fig. ##FIG##0##1##).</p>", "<p id=\"Par20\">\n</p>", "<title>Comparison and analysis of light microscope observation results</title>", "<p id=\"Par21\">\n<list list-type=\"order\"><list-item><p id=\"Par22\">Visually, the spiral ganglion cells in the OB group did not exhibit a significant reduction compared to the NC group. However, these cells appeared loosely arranged and disordered. Additionally, the outer hair cells in the organ of Corti displayed deformities and partial displacement. Observation of the striations revealed thicker capillary diameters, narrow lumens, and disorganized, apoptotic marginal cells (Fig. ##FIG##1##2##).</p></list-item></list></p>", "<p id=\"Par23\">\n</p>", "<p id=\"Par24\">\n<list list-type=\"simple\"><list-item><label>2. </label><p id=\"Par25\">Compared to the NC group and the OB group, the spiral ganglion cells in the T2DM group were significantly diminished, and the cells were obviously disordered in arrangement, with the cytoplasm atrophying and the nucleus enlarging. Additionally, some hair cells outside of the organ of Corti underwent apoptosis, and the number of striated cells decreased significantly. The capillary lumen shrank, and the number of marginal cells decreased considerably (Fig. ##FIG##1##2##).</p></list-item></list></p>", "<title>Comparison and analysis of experimental results of immunohistochemistry</title>", "<p id=\"Par26\">In the NC group, the expression of the GRP78 protein was either weakly positive or negative in the spiral ganglion, organ of Corti, and stria vascularis. Conversely, in the OB and T2DM groups, the protein exhibited positive expression in the cytoplasm of the spiral ganglion. Positive expression results were more significant in the T2DM group than in the OB group (Fig. ##FIG##2##3##).</p>", "<p id=\"Par27\">\n</p>", "<title>Expression of GRP78 protein in rat cochlea</title>", "<p id=\"Par28\">Image J software was used to analyze the optical density values of immunohistochemistry, including spiral ganglion, organ of Corti, and stria vascularis, of rats in each group. It was found that the darker the immunohistochemical staining, the stronger the absorbance. The optical density values of rats in the T2DM group were significantly higher than those in the OB group, and the values of the OB group were significantly higher than those of the NC group (<italic>P</italic> &lt; 0.05) (Fig. ##FIG##3##4##).</p>", "<p id=\"Par29\">\n</p>", "<title>Expression of GRP78 protein in the cochlea detected by western blot</title>", "<p id=\"Par30\">The GRP78 protein was expressed at a higher level in the T2DM group than in the OB group and the NC group, and more highly expressed in the OB group compared to the NC group. (Fig. ##FIG##4##5##) The expression of GRP78 in the OB group was significantly higher than that in the NC group (<italic>P</italic> &lt; 0.05), and the expression of GRP78 in the T2DM group was significantly higher than that in the OB group (<italic>P</italic> &lt; 0.05) (Fig. ##FIG##5##6##).</p>", "<p id=\"Par31\">\n</p>", "<p id=\"Par32\">\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par33\">The GRP78 protein is an ERS chaperone. Its expression is significantly increased under ERS, so that it combines with misfolded and unfolded proteins in the endoplasmic reticulum to restore the correct conformation of proteins and enables proteins to continue to be correctly synthesized under cell stress, maintaining the homeostasis of endoplasmic reticulum calcium and the homeostasis [##REF##10652249##16##]. Furthermore, GRP78 functions by facilitating the translocation of misfolded proteins to the endoplasmic reticulum, thereby ensuring the uninterrupted synthesis of proteins within cells experiencing stress conditions. GRP78 exists in the complex with Caspase7 and Caspase12 under normal conditions. Nevertheless, following ERS, GRP78 is dissociated from the complex and bound to the intraluminal unfolded protein, resulting in the activation and release of Caspase12 and apoptosis.</p>", "<p id=\"Par34\">Obesity and diabetes have become a worldwide epidemic as a result of the modern lifestyle. However, studies indicate that hyperlipidemia and hyperglycemia resulting from long-term obesity are closely linked to hearing loss. In this study, we simulated the natural pathogenesis of human obesity and prepared obese and diabetic rat models using a high-fat and high-glucose diet, respectively combined with STZ in order to observe the expression of GRP78 protein, a molecular chaperone of ERS, in each group of cochleae, and investigated the molecular mechanism of hyperlipidemia and diabetes on inner ear damage.</p>", "<p id=\"Par35\">The results of this study revealed that the ABR threshold of rats in the OB group was elevated. The organ of Corti, striations, and spiral ganglion exhibited more evident cell arrangement disorder, destruction, and apoptosis compared to rats in the NC group, and contained more GRP78 protein. Furthermore, numerous studies have confirmed that dyslipidemia is a risk factor for hearing loss [##REF##24378290##17##–##REF##23819577##21##]. Fuji et al. developed animal models of ERS-induced cochlear cell injury and discovered that the ERS chaperone in in cochlear cells was significantly elevated, indicating that ERS may be responsible for hearing loss [##REF##20026213##22##]. The results of this study are comparable to those of previous studies. However, additional animal experiments in this study confirmed the changes in the microstructures of inner ears with hearing loss caused by dyslipidemia and its correlation with ERS. We hypothesize that the elevated levels of blood lipids and altered hemorheology in obese rats led to increased blood viscosity and flow velocity. Consequently, this condition resulted in tissue hypoxia, triggering ERS in the spiral ganglion, organ of Corti, and striated vascular cells. Additionally, it led to the release of apoptosis-inducing factors, causing cell atrophy, degeneration, and eventual apoptosis, culminating in hearing loss. Rats in the T2DM group exhibited higher ABR thresholds compared to those in the NC and OB groups. Upon the administration of a low dose of STZ, rats in the T2DM group demonstrated significantly elevated levels of blood glucose, serum TG, and serum TC in comparison to the OB group. This observation suggests that upon transitioning to a diabetic state, obese rats experienced more severe dysfunction in lipid metabolism. In addition, the cells in the organ of Corti, striations, and spiral ganglion demonstrated more prominent cell destruction and apoptosis than those in the OB group. Strong expression of the GRP78 protein was found in the cytoplasm of the organ of Corti, striations, and spiral ganglion. In their research, Jia et al. discovered ERS in the cochlear hair cells of mice with type II diabetes [##UREF##5##10##]. Consistent with the experimental findings, ERS may increase the defect rate of cochlear outer hair cells and the hearing threshold of diabetic mice. Long-term hyperlipidemia, glucosamine pathway induced by diabetic hyperglycemia, and ERS induced by insulin resistance of macrophages are hypothesized to result from diabetes. This leads to many GRP78 proteins to separate from the complex and combine with the unfolded proteins in the cavity, resulting in the activation and release of Caspase12, as well as the disordered arrangement, destruction, and apoptosis of the organ of Corti, striations, and spiral ganglion cells in the cochlea, which ultimately leads to hearing loss. Liu et al. established the in vitro ERS model using hair cells treated with tunicamycin [##REF##34250248##23##]. The observation that alleviating ERS can mitigate sensorineural hearing loss suggests a clear association between ERS and hearing impairment. Research conducted by Oishi et al. revealed that ERS, when mitigated by XBP1, could potentially mask aminoglycoside neurotoxicity at the organismal level, including hearing loss [##REF##25973683##24##]. Increased expression of the ERS protein molecular chaperone and hearing loss have been shown to have a direct or indirect relationship, based on western blot and reverse transcription PCR analysis.</p>", "<p id=\"Par36\">This study has several limitations: (1) The limited number of experimental animals diminishes the persuasiveness of the results. (2) Due to experimental constraints, dynamic observation and comparison were not conducted, restricting the comprehensive understanding of the phenomena. (3) Detailed characterization of cochlear hair cells, particularly the basement membrane, was hindered due to equipment and resource limitations. (4) To strengthen the quantitative data, a more robust study design, such as incorporating stereological studies, is necessary for further confirmation and validation of the findings.</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par37\">Obesity and T2DM can induce ERS in cells, leading to cell apoptosis, morphological and structural changes in the cochlea, and varying degrees of hearing loss.</p>", "<p id=\"Par38\">The coexistence of hyperglycemia and hyperlipidemia results in more profound damage to cochlear cells. This discovery establishes a crucial experimental foundation for the early intervention of hearing loss stemming from diabetes and hyperlipidemia. Furthermore, it signifies the involvement of the GRP78 protein, a molecular component associated with ERS, in the mechanisms underlying hyperlipidemia-induced hearing impairment in diabetes. Consequently, these findings offer a molecular framework for the treatment of diabetes-related hearing loss. Owing to constraints related to laboratory conditions and time, we regrettably could not administer the intervention treatment to the obese and diabetic rats. Additionally, we were unable to investigate the extent of hearing recovery post-treatment and the expression of GRP78/Bip proteins in their cochlea. This limitation prevented us from providing more direct evidence in our study.</p>" ]
[ "<title>Objective</title>", "<p id=\"Par1\">This study aimed to compare and analyze the expression and significance of the GRP78 protein in cochlear cell injury induced by a high glucose and high-fat diet in obese and diabetic rats.</p>", "<title>Methods</title>", "<p id=\"Par2\">Male SD rats were randomly divided into two groups: normal (NC) and high-fat (HF) groups. The NC group was fed a standard diet for eight weeks, while the HF group received a high-glucose, high-fat diet. The HF group was further categorized into the obesity group (OB group) and the type II diabetes mellitus group (T2DM group). To induce a type II diabetes mellitus (T2DM) model, the T2DM group received an intraperitoneal injection of a small dose of STZ (45 mg/kg). After four weeks on the original diet, body weight, blood glucose, blood lipid levels, and auditory brainstem response (ABR) thresholds were measured. The cochlea was dissected, and its morphology was observed using HE staining. Immunohistochemistry and western blotting were utilized to examine the expression level of the GRP78 protein in the cochlea.</p>", "<title>Results</title>", "<p id=\"Par3\">(1) The ABR threshold demonstrated a statistically significant difference between the T2DM group and the OB group (<italic>P</italic> &lt; 0.05), as well as between the OB group and the NC group (<italic>P</italic> &lt; 0.05). (2) Based on morphological comparisons from HE-stained sections, the T2DM group exhibited the most significant alterations in the number of cells in the spiral ganglion, the organ of Corti, and the stria vascularis of the cochlea. (3) The expression level of the GRP78 protein in the cochlea was higher in the T2DM group compared to the OB group (<italic>P</italic> &lt; 0.05) and higher in the OB group compared to the NC group (<italic>P</italic> &lt; 0.05).</p>", "<title>Conclusion</title>", "<p id=\"Par4\">The findings indicate that the GRP78 protein plays a role in hearing loss caused by T2DM and hyperlipidemia. Moreover, T2DM is more likely than hyperlipidemia to be associated with hearing impairment.</p>", "<title>Keywords</title>" ]
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[ "<title>Acknowledgements</title>", "<p>We would like to acknowledge the hard and dedicated work of all the staff that implemented the intervention and evaluation components of the study.</p>", "<title>Author contributions</title>", "<p>Conception and design of the research: KX, H-PL. Acquisition of data: H-PL, Y-HW, Y-YL, M-MZ, XZ, B-WX. Analysis and interpretation of the data: H-PL, LW. Statistical analysis: KX, H-PL, Y-HW, Obtaining financing: KX , H-PL,Y-HW, Y-YL Writing of the manuscript: H-PL, M-MZ, XZ, B-WX Critical revision of the manuscript for intellectual content: KX , H-PL, LW. All authors read and approved the final draft.</p>", "<title>Funding</title>", "<p>Effect analysis of different timing of vestibular rehabilitation in patients with acute vestibular neuritis (No. LHGJ20220680).</p>", "<title>Availability of data and materials</title>", "<p>All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par39\">This study was conducted with approval from the Ethics Committee of The First Affiliated Hospital,and College of Clinical Medicine of Henan University of Science and Technology. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.</p>", "<title>Competing interests</title>", "<p id=\"Par40\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Comparison of ABR thresholds in the three groups of rats (<italic>n</italic> = 30). Number of cochleae = 20. ABR thresholds in OB group was significantly different (<italic>P</italic> &lt; 0.05) from NC group. ABR thresholds in T2DM was significantly different (<italic>P</italic> &lt; 0.05) from NC group, and OB group</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Morphological manifestations of the spiral ganglion, organ of Corti, and stria vascularis of the cochlea under a light microscope (×200).  1, 4, and 7 depict the spiral ganglion, organ of Corti, and stria vascularis in the NC group, respectively  2, 5, and 8 depict the spiral ganglion, organ of Corti, and stria vascularis in the OB group, respectively  3, 6, and 9 depict the spiral ganglion, organ of Corti, and stria vascularis in the T2DM group, respectively</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Immunohistochemical staining results of the spiral ganglion, organ of Corti, and stria vascularis of the cochlea under a light microscope (×200). <bold> A</bold>, <bold>D</bold>, and <bold>G</bold> are the staining results of the spiral ganglion, organ of Corti, and stria vascularis in the NC group, respectively; the cytoplasm was faintly stained or not stained  <bold>B</bold>, <bold>E</bold>, and <bold>H</bold> are the staining results of the spiral ganglion, organ of Corti, and stria vascularis in the OB group, respectively; the cytoplasm was stained mildly or moderately  <bold>C</bold>, <bold>F</bold>, and <bold>I</bold> are the staining results of the spiral ganglion, organ of Corti, and stria vascularis in the T2DM group, respectively; the cytoplasmic staining is significantly deep and visible, and there are significantly more brownish-yellow particles distributed at ×200</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Correlation analysis between GRP78 protein and ABR threshold. Average immunohistochemical optical density (OD) values of rats in the three groups were analyzed. OD values in OB group was significantly different (<italic>P</italic> &lt; 0.05) from NC group. OD values in T2DM was significantly different (<italic>P</italic> &lt; 0.05) from NC group, and OB group</p></caption></fig>", "<fig id=\"Fig5\"><label>Fig. 5</label><caption><p>Western blot analysis of GRP78 and β-actin protein expression in the inner ear tissues of the three groups (<italic>n</italic> = 30)</p></caption></fig>", "<fig id=\"Fig6\"><label>Fig. 6</label><caption><p>Comparison of GRP78 protein gray values in the three groups of rats (<italic>n</italic> = 30). *Indicates <italic>P</italic> &lt; 0.05 as compared with the two groups</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Body weight, blood glucose, and the lipid levels of rats in the three groups (<italic>n</italic> = 30)</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Group</th><th align=\"left\" colspan=\"3\">Weight (g)</th><th align=\"left\" rowspan=\"2\">Blood glucose level</th><th align=\"left\" colspan=\"2\">Blood lipid level (mmol/L)</th></tr><tr><th align=\"left\">Week 1</th><th align=\"left\">Week 8</th><th align=\"left\">Week 12</th><th align=\"left\">Total cholesterol</th><th align=\"left\">Total triglyceride</th></tr></thead><tbody><tr><td align=\"left\">NC group</td><td char=\"±\" align=\"char\">228.1 ± 11.06</td><td char=\"±\" align=\"char\">322.5 ± 12.59</td><td char=\"±\" align=\"char\">413.9 ± 8.06</td><td char=\"±\" align=\"char\">8.77 ± 1.44</td><td char=\"±\" align=\"char\">1.63 ± 0.26</td><td char=\"±\" align=\"char\">0.53 ± 0.22</td></tr><tr><td align=\"left\">OB group</td><td char=\"±\" align=\"char\">229.1 ± 13.03</td><td char=\"±\" align=\"char\">404.3 ± 8.31**</td><td char=\"±\" align=\"char\">512.8 ± 12.92**</td><td char=\"±\" align=\"char\">11.03 ± 1.67*</td><td char=\"±\" align=\"char\">2.02 ± 0.47*</td><td char=\"±\" align=\"char\">0.94 ± 0.55*</td></tr><tr><td align=\"left\">T2DM group</td><td char=\"±\" align=\"char\">229.5 ± 12.21</td><td char=\"±\" align=\"char\">404.6 ± 15.41**</td><td char=\"±\" align=\"char\">298.9 ± 9.55**▫▫</td><td char=\"±\" align=\"char\">19.93 ± 6.68**▫▫</td><td char=\"±\" align=\"char\">2.59 ± 0.45**▫</td><td char=\"±\" align=\"char\">1.74 ± 1.03**▫</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>*Indicates <italic>P</italic> &lt; 0.05 as compared with the NC group;</p><p>**Indicates <italic>P</italic> &lt; 0.01 as compared with the NC group</p><p>▫Indicates <italic>P</italic> &lt; 0.05 as compared with that OB group</p><p>▫▫Indicates <italic>P</italic> &lt; 0.01 as compared to OB group</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
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[{"label": ["2."], "surname": ["Wang", "Liu", "Li"], "given-names": ["K", "X", "P"], "article-title": ["Advances in molecular mechanisms for enhanced hepatic lipogenesis in insulin resistance"], "source": ["Acta Pharm Sinica"], "year": ["2020"], "volume": ["55"], "issue": ["02"], "fpage": ["189"], "lpage": ["194"], "pub-id": ["10.16438/j.0513-4870.2019-0718"]}, {"label": ["3."], "surname": ["Yang", "Wu"], "given-names": ["S", "D"], "article-title": ["The research progress of obesity and its treatment"], "source": ["Chin J New Clin Med"], "year": ["2016"], "volume": ["9"], "issue": ["04"], "fpage": ["358"], "lpage": ["362"]}, {"label": ["4."], "surname": ["Li", "Wang", "He"], "given-names": ["X", "J", "S"], "article-title": ["Effect of benign obesity on type 2 diabetes, cardiovascular events and death-23-year follow-up study"], "source": ["Chin J Endocrinol Metab"], "year": ["2020"], "volume": ["36"], "issue": ["3"], "fpage": ["207"], "lpage": ["212"], "pub-id": ["10.3760/cma.j.cn311282-20190604-00210"]}, {"label": ["6."], "surname": ["Xu", "Tan", "Peng"], "given-names": ["X", "M", "J"], "article-title": ["Large sample analysis on association between metabolic syndrome and hearing loss"], "source": ["Chin J Otol"], "year": ["2022"], "volume": ["20"], "issue": ["6"], "fpage": ["897"], "lpage": ["903"]}, {"label": ["7."], "surname": ["Wang", "Xia", "Yang"], "given-names": ["J", "Y", "C"], "article-title": ["Analysis of microRNA regulatory network in cochlear hair cells with oxidative stress injury"], "source": ["Chin J Otorhinolaryngol Head Neck Surg"], "year": ["2016"], "volume": ["51"], "issue": ["10"], "fpage": ["751"], "lpage": ["755"]}, {"label": ["10."], "surname": ["Jia", "Li", "He"], "given-names": ["Z", "F", "Q"], "article-title": ["Influence of endoplasmic reticulum stress in degeneration of cochlear hair cells in type 2 diabetic mice"], "source": ["J Jilin Univ (Medicine Edition)"], "year": ["2019"], "volume": ["45"], "issue": ["1"], "fpage": ["51"], "lpage": ["56"]}, {"label": ["12."], "mixed-citation": ["Anonymous. Listen to the brainstem response of each wave amplitude measurement, the animal experiment research. Chin Sci Magazine. 2019;17(2):9. 10.3969/j.issn.1672-2922.2019.02.008."]}, {"label": ["13."], "mixed-citation": ["Deng Hua L, Haozhao Z, Zhaohai et al. An improved HE staining method :CN201910961552.1[P].CN110686957A[2023-08-17]."]}, {"label": ["14."], "surname": ["Hong-Yan", "Jing-Mei", "Jin-Yu"], "given-names": ["W", "W", "Z"], "article-title": ["Immunohistochemical staining of bone demineralization methods"], "source": ["J Clin Exp Pathol"], "year": ["2005"], "volume": ["21"], "issue": ["3"], "fpage": ["1"], "pub-id": ["10.3969/j.issn.1001-7399.2005.03.029"]}, {"label": ["15."], "surname": ["Zhengwen", "Hongwei", "Yong"], "given-names": ["X", "L", "H"], "article-title": ["Bone demineralization technology and application in the immunohistochemical study"], "source": ["Chin J Comp Med"], "year": ["2004"], "volume": ["14"], "issue": ["3"], "fpage": ["4"], "pub-id": ["10.3969/j.iSSN.1671-7856.2004.03.015"]}]
{ "acronym": [], "definition": [] }
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2024-01-14 23:43:47
Diabetol Metab Syndr. 2024 Jan 13; 16:16
oa_package/44/a1/PMC10787492.tar.gz
PMC10787493
38216954
[ "<title>Introduction</title>", "<p id=\"Par5\">Supracondylar humerus fractures (SHFs) are the most common elbow injury in children, accounting for approximately 15% of all childhood fractures [##UREF##0##1##]. According to Gartland staging, SHFs can be split into three categories [##UREF##1##2##], with extensional SHFs accounting for more than 90% of cases in children [##UREF##2##3##]. Closed reduction and percutaneous pinning(CRPP) is the classic surgical procedure for the treatment of SHF in children [##UREF##1##2##], which is a stable fixing technique, according to biomechanical studies, however there is still a risk of postoperative fracture re-displacement [##UREF##3##4##]. An earlier study found that up to 18% of postoperative fracture re-displacements with CRPP occurred [##UREF##3##4##]. One probable explanation for this is that intraoperative pin repositioning, which is always necessary even under fluoroscopic guidance, can cause a loss of the pull-out resistance of almost 50% [##UREF##4##5##]. Simultaneous multiple pin repositioning will increases radiation exposure as well as the potential of neurovascular injury [##UREF##5##6##, ##UREF##6##7##]. We developed the K-wire targeting device (Patent No. ZL 202220185369. 4) for use in pediatric CRPP surgery and assessed its clinical efficacy in order to decrease intraoperative pin repositioning.</p>" ]
[ "<title>Materials and methods</title>", "<title>Inclusion and exclusion criteria</title>", "<p id=\"Par6\">Inclusion criteria: (1) age ≤ 14 years; (2) fresh Gartland type II and type III SHF (time from injury to operation &lt; 5 days); (3) surgical method to CRPP; (4) follow-up ≥ 6 months.</p>", "<p id=\"Par7\">Exclusion criteria: (1) open SHF; (2) inability to perform normal elbow exercises; (3) preoperative severe neurovascular injury; (4) preoperative or postoperative diagnosis of a disease affecting bone development or fracture healing, such as vitamin D deficiency, severe malnutrition, malignant tumor, hypothyroidism, etc.; (5) inability to complete a full follow-up.</p>", "<title>Ethics approval statement</title>", "<p id=\"Par8\">Our study was approved by the Ethics Committee of The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University(Number: KY- 2023–130-01). All guardians of the children were informed about the purpose of the study and the study procedure and provided their informed consent.</p>", "<title>General information</title>", "<p id=\"Par9\">Retrospective analysis was performed on the clinical data of children with extensional SHF treated in our institution from June 2019 to August 2022. This study comprised 105 patients in total, with 62 males and 43 females, ages 1 to 13 (6. 055 ± 3. 215), that met the aforementioned criteria. The study group and the control group of patients were separated and Table ##TAB##0##1## displays the general facts about the two groups. In terms of gender, age, fracture type, side of injury, time from injury to surgery, and cause of injury, there were no statistically significant differences between the two groups (<italic>p</italic> &gt; 0. 05).</p>", "<title>Surgical methods</title>", "<p id=\"Par10\">All CRPP operations were performed by the same physician team. The K-wire placement guided technique for paediatric supracondylar humerus fracture reduction and fixation has been authorized for patenting under utility model innovation with patent number ZL202220185369. 4 (Fig. ##FIG##0##1##).</p>", "<title>Non-guided group:</title>", "<p id=\"Par11\">During general anesthesia, children's lens, thyroid, and gonads are shielded by lead clothes. The forearm and upper arm are secured by two stainless steel clamps, and traction is used to realign the fracture. With the aid of a steering fixation device, the two stainless steel clamps are attached to the carbon fibre rod for temporary fixation to maintain reduction of fractured end. The fracture reduction was confirmed with fluoroscopy of elbow joint anteroposterior and lateral, and if necessary, fluoroscopic medial and lateral oblique films were used to monitor the medial and lateral column reduction. If there is a considerable rotational or translations displacement, repeat the fracture reduction methods described above. The anterior–posterior displacement of the fracture can be modified by adjusting the length of the steering fixing device in respect to the carbon fiber connecting rod if the fluoroscopy only shows a slight anterior–posterior displacement. To modify the modest rotational displacement of the medial and lateral columns, one can rotate the forearm anteriorly or posteriorly by loosening the stainless steel clamp on the forearm. Two K-wires are inserted under fluoroscopic guidance at the medial and lateral condyles of the humerus once the fracture has been sufficiently reduced. The results of the fluoroscopic examination are utilised to estimate the extent of the pin entry. Determine the entrance location using fluoroscopy after first inserting the K-wire into the skin and making contact with the bone surface. The K-wire is inserted into bone by the electric drill at a slow speed until a sence of \"breakthrough\" is felt. Check the K-wire position through fluoroscopy and reposition the pin if necessary. Bend the K-wire and snip off the end of the pin after making sure the elbow joint is firmly fastened. After the surgery, immobilize the elbow joint using a polymer splint.</p>", "<title>Guided group:</title>", "<p id=\"Par12\">Preoperative attachment of the K-wire placement guided device and the auxiliary reduction and fixation device. As in the non-guided group, the fracture was realigned and temporarily immobilized. The K-wire should be fixed in the aiming sleeve, the aiming device adjusted, the pin placed outside the skin near the point of entry, the elbow joint fluoroscopically visualized in the anteroposterior and lateral position, and the point and direction of entry ultimately determined based on the fluoroscopy results. Finally, the electric drill should be connected, and the K-wires should be cross-inserted at a low speed guided by the direction of the aiming sleeve until a \"breakthrough\" is felt (Fig. ##FIG##1##2##).</p>", "<p id=\"Par13\">The polymer splint was immobilised in both groups for 3 to 4 weeks post-operatively. The timing of removing the bilateral K-wire and polymer splint was determined by the weekly reviews of post-operative x-rays. After the splint was taken off, the functional flexion and extension activities were begun.</p>", "<title>Evaluation indicator</title>", "<p id=\"Par14\">Operative time, the number of K-wires put at once, the number of intraoperative fluoroscopies, Baumann's angle, carrying angle, and fracture healing time were all noted as perioperative data. Postoperative complications included ulnar nerve injury, cubitus varus, elbow valgus deformity, pin site infection, and number of re-displacements after fixation. The Flynn elbow function score [##REF##4375679##8##], as detailed in Table ##TAB##1##2##, was utilised at the final follow-up to assess the overall excellent rate.</p>", "<title>Statistical analysis</title>", "<p id=\"Par15\">SPSS 21. 0 software was used for data analysis. The measurement data were expressed by (x̅ ± s). When the data were normally distributed, one-way ANOVA was used for inter-group comparison, LSD method was used for pairwise comparison; and paired T-test or one-way ANOVA was used for intra-group comparison. When the data are not normally distributed, the rank sum test was used. Chi-square test or Fisher accurate test was used for counting data. Rank sum test was used to compare the rank data. <italic>P</italic> &lt; 0. 05 was considered a statistically significant difference.</p>" ]
[ "<title>Results</title>", "<p id=\"Par16\">Both patient groups successfully underwent the procedure. As detailed in Table ##TAB##2##3##, while there was no statistical difference in Baumann angle or fracture healing time between the two groups (<italic>p</italic> &gt; 0. 05), there were statistically significant differences in the operation time, intraoperative fluoroscopy times, and carrying angle of the study group compared to the Non-guided group. (A typical case is shown in Fig. ##FIG##2##3##).</p>", "<title>Follow-up results</title>", "<p id=\"Par17\">All patients in both groups were followed up for 8-17 months (11. 67 ± 3. 192) months. As shown in Table ##TAB##3##4##, there was no significant difference in the excellent and good rate between the two groups in Flynn score(<italic>P</italic> &gt; 0. 05).</p>", "<title>Complications</title>", "<p id=\"Par18\">In the non-guided group, there were two cases of ulnar nerve injury, with neurological symptoms going away three days after removal of the K-wire; four cases of pin site infection, which resolved after removal of the K-wire; two cases of mild cubitus varus, which worked well and weren't treated; and four cases of postoperative fracture displacement, of which two required additional CRPP treatment. In the guided group, there were one case of ulnar nerve damage, two cases of pin site infection that cleared up after removal, and one case of postoperative fracture displacement. In neither group were there any elbow valgus abnormalities. The incidence of complications in the guided group was significantly lower than that in the non-guided group (χ<sup>2</sup> = 3. 873, <italic>p</italic> &lt; 0. 05).</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par19\">SHF is the most common fracture of the elbow joint in children. For the treatment of SHF, Gartland I can be managed with plaster fixation alone; Gartland II and III are often managed with CRPP, and open reduction and fixation are required if closed reduction fails. Moreover, it has been claimed that closed reduction and plaster fixation for Gartland II can produce outcomes comparable to those of CRPP, however there is a chance of re-displacement and cubitus varus following surgery [##UREF##7##9##, ##REF##27014946##10##]. A unilateral placement technique and a cross-placement approach are the two categories for K-wire placement in CRPP. Both methods can achieve sufficient biomechanical stability, and there is no difference between them [##UREF##8##11##]. For the fracture to remain mechanically stable and to minimize trauma, the K-wire must be placed precisely. Some researchers have used a hypodermic injection pin to guide the point and direction of K-wire insertion on unstable SHFs, which can significantly reduce the need for K-wire resets. However the technique requires the K-wire to be placed at a certain depth under the skin, which increases surgical trauma, and only works on the lateral side of the elbow, with a risk of nerve injury when applied medially [##REF##27014946##10##]. In this study, the CRPP is fitted with the self-designed and manufactured device that can help to assist in the reduction and temporarily fixate the SHF during the surgery. In addition to assisting in pin pointing the entrance site and orientation, the aiming device can also be used to realize the precise positioning of the K-wire. The study's findings revealed that the guided group's rate of K-wire placement at once was 81. 37% much higher than the non-guided group's rate of 19. 44%. The use of the device lessens harm to the soft tissue and bone near the pin site in addition to significantly reducing intraoperative reinsertion.</p>", "<p id=\"Par20\">Children and the surgeon will both be exposed to more radiation from SHFs with large displacement and difficult repositioning [##UREF##9##12##]. According to a prior research, between 30. 7 and 126 fluoroscopies were performed during the CRPP [##UREF##10##13##, ##UREF##11##14##]. In addition, when the C-arm image intensifier was used as the operating table, the radiation exposure of the elbow and neck of the patient was significantly higher [##UREF##5##6##, ##UREF##9##12##]. In multi-directional unstable SHFs, we should apply a joystick technique to assist in the reduction of the broken end of the fracture [##UREF##12##15##], which can significantly increase the likelihood that the reduction will be successful, increase the effectiveness of the procedure, and simultaneously decrease the need for fluoroscopy. Rotating the child's arm for lateral imaging usually results in loss of repositioning of these fractures due to high instability [##UREF##13##16##]. Our technology reduces needless, repetitive manual reduction procedures by providing a robust temporary fixation and fluoroscopic insertion of the elbow joint without displacement the broken end. The K-wire can be placed precisely thanks to the targeting device, which significantly lowers the likelihood that it will reset. The results of the study indicate that the number of surgical fluoroscopies was about 18, which is less than previously reported. In addition, the operator's exposure to radiation is significantly reduced by fluoroscopy because it does not require constant movement and allows for operator concealment behind a lead screen.</p>", "<p id=\"Par21\">To evaluate the reduction of the broken end of the fracture, the standard anteroposterior and true lateral views of the elbow joint are typically sufficient. The anterior humeral line, which in a normal elbow joint should travel through the middle third of the ossification center of the lateral humeral condyle, is the primary anatomical landmark evaluated on lateral films [##UREF##13##16##]. It happens frequently that the severity of a fracture is underestimated due to subpar radiographic methodology. Consequently, careful assessment of the repositioning should be performed prior to the placement of the K-wire. We recommend a fluoroscopic medial and lateral tilt view prior to K-wire placement to assess the repositioning of the medial and lateral columns of the distal humerus and to ensure that rotation is corrected. To get a better placement position and angle, a 3D model reconstruction of the distal humerus is required to identify the placement point and the range of placement angles [##UREF##6##7##]. We routinely perform preoperative 3D CT and design the K-wire placement point and angle according to the direction of the fracture line in order to obtain more stable fixation. Nonetheless, fluoroscopic intraoperative guidance and the operator's skill both play a role in the ultimate K-wire placement. At the same time, the fixation of high one-time pin placement rate increases the anti-pullout ability of K-wire [##UREF##4##5##]. According to the study's findings, the guided group had a reduced likelihood of postoperative re-displacement than the non-guided group. However, for a novice, it might be challenging to spatially comprehend the swollen child's elbow and its intricate anatomy. Placing the K-wire can also be challenging, particularly if the relocation is unstable and the surface markers are difficult to reach. The difficulty of putting the K-wire during surgery is significantly reduced by the use of repositioning fixation and aiming devices for the K-wire placement, which can be mastered by novice and experienced surgeons with simple training.</p>", "<p id=\"Par22\">Ulnar nerve damage is more likely to occur with cross pinning [##UREF##14##17##–##UREF##16##19##]. To prevent ulnar nerve damage, which surely increases surgical trauma, a minor medial incision has been utilized to expose the medial pinning point [##UREF##17##20##]. In order to protect the ulnar nerve, we locate it by palpation when soft group swelling is not immediately apparent and avoid the ulnar nerve row area when inserting the pin. However, this is not a completely safe technique [##UREF##18##21##]. Before inserting the K-wire with a low speed drill, we prefer to first puncture the skin with the tip of the K-wire and then execute blunt row stripping around the entry point with the tail of the wire. Previous studies have shown that among 1541 patients in supine position, 69 (4. 5%) suffered from a ulnar nerve injury [##UREF##19##22##], while our results show a lower ulnar nerve damage, 3 cases of 105(2. 9%).</p>" ]
[ "<title>Conclusion</title>", "<p id=\"Par23\">To summarize, the K-wire placement guided technique is straightforward and simple to learn, and it is deserving of clinical application in children with supracondylar humerus fractures to increase the rate of pin placement at once, decrease the number of intraoperative fluoroscopy, and lower the incidence of complications.</p>", "<p id=\"Par24\">Some limitations of this study should be mentioned. Firstly, this study is its retrospective design, which is more susceptible to bias than prospective study designs. Another limitation may be the short follow-up period. The average follow-up time in our study was 6 months, although this is comparable to other publications involving SCHF results. Finally, the sample size is too small. A Prospective, large-sample studies with long-term follow-up will be conducted in the future to further demonstrate its effects and values.</p>" ]
[ "<title>Background</title>", "<p id=\"Par1\">To analyze the clinical efficacy of K-wire placement guided technology in paediatric supracondylar humerus fractures.</p>", "<title>Methods</title>", "<p id=\"Par2\">A retrospective study was conducted in 105 patients who underwent closed reduction and percutaneous pinning surgeries in our hospital from June 2019 to August 2022. 54 patients treated with a assisted reduction fixation device to assist in closed reduction and percutaneous K-wire cross-fixation were allocated into the Non-guided group, and 51 patients with K-wire placement guided technology to guide K-wire placement were assigned into the Guided group. The operation duration, number of disposable K-wire placement, intraoperative fluoroscopy frequency, Baumann angle, carrying angle, fracture healing time and Flynn score of elbow joint function at the final follow-up were compared between two groups. The postoperative complications of two groups were recorded.</p>", "<title>Results</title>", "<p id=\"Par3\">There were significant differences between two groups in terms of operation duration, intraoperative fluoroscopy frequency, and disposable K-wire placement rate (<italic>p</italic> &lt; 0. 05), while no significant differences of Baumann angle, carrying angle and the fracture healing time between two groups were observed (<italic>p</italic> &gt; 0. 05). In the control group, ulnar nerve injury in 2 case, pin site infection in 4 cases, mild cubitus varus in 2 cases and loss of reduction in 4 cases were detected. In the study group, ulnar nerve injury in 1 case, pin site infection in 2 cases and loss of reduction in 1 case was observed. There was no significant difference in Flynn scores between two groups.</p>", "<title>Conclusion</title>", "<p id=\"Par4\">K-wire placement guided technology is simple and convenient. The application of K-wire placement guided technology could relatively improved disposable K-wire placement rate, shorten the intraoperative fluoroscopy frequencies and reduce complication rates<bold>.</bold></p>", "<title>Keywords</title>" ]
[]
[ "<title>Permission to reproduce material from other sources</title>", "<p id=\"Par25\"> All the data and photographs are original and no material was reproduced from other sources.</p>", "<title>Clinical trial registration</title>", "<p id=\"Par26\">This study was clinical retrospective observation research. Clinical trial registration was not needed.</p>", "<title>Authors’ contributions</title>", "<p>All authors contributed to the study conception and design. Material preparation and data collection were performed by Qirui Ding. Data and analysis were performed by Yunru GE.The collation and translation of the manuscript were performed by Ying Ding.The manuscript was written by Huan Liu and Lingzhi Li. The formulation of overarching research goals and aims were performed by Shouguo Wang and Haodong Fei.All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors, and no material support of any kind was received.</p>", "<title>Availability of data and materials</title>", "<p>The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par27\">Our study was approved by the Ethics Committee of The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University(Number: KY- 2023–130-01). All guardians of the children were informed about the purpose of the study and the study procedure and provided their informed permission.</p>", "<title>Consent for publication</title>", "<p id=\"Par28\">Patients signed informed consent regarding publishing their data and photographs.</p>", "<title>Competing interests</title>", "<p id=\"Par29\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Usage of K-wire aiming device, connection mode, and auxiliary reduction and fixation device during operation. <bold>A </bold>A metal handle can be used to adjust a clamp with a 6 mm diameter side convex column clamp that comes in three sizes: 21-44 mm, 27-51 mm, and 46-70 mm; <bold>B</bold> A self-made universal fixed concave parts that have an inner diameter of 6 mm and the clamp with a side convex column may be added to it. The top butterfly buckle can be used to tighten a carbon fibre rod or a K-wire; <bold>C</bold> Different length carbon fibre rods in the 5 mm or 6 mm range; <bold>D</bold> Self-made universal fixed convex with a convex column diameter of 6 mm that can connect to another self-made aiming component or another universal fixed concave. The bottom butterfly buckle can tighten a carbon fibre rod or a K-wire; <bold>E</bold> Self-made aiming equipment with a concave diameter of 6 mm, a self-made universal fixed convex, an aiming sleeve inner diameter of 2. 5 mm, and a side butterfly buckle that can tighten and fix the K-wire. <bold>F</bold> With the universal fastening concave connection shown in the schematic picture of the device connection, the clamp can be rotated and fixed 360 degrees; <bold>G</bold>, <bold>H</bold> A schematic showing how to operate the K-wire aiming device</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Perspective view of the use of auxiliary reset fixture and K-wire aiming device in guided group. <bold>A</bold>, <bold>B</bold> Prior to surgery, Gartland II SHF was visible in the results of anterior and lateral fluoroscopy; <bold>C</bold>, <bold>D</bold> The elbow joint was rotated while the manual reduction device was temporarily fixed. The fracture's broken end was well-reduced, as evidenced by the fluoroscopy's anterior and posterior positions as well as medial and lateral oblique positions; (F, G) Adjusting the K-wire's entry point and angle in the sagittal plane in vitro: Lateral film view; <bold>H</bold>, <bold>I</bold> Adjusting the K-wire's entry point and angle in the coronal plane in vitro:Inside oblique view; <bold>J</bold>, <bold>K</bold> The medial condylar K-wire is in the previous aiming direction, as shown in the lateral view and medial oblique film; <bold>L</bold>-<bold>N</bold> lateral K-wire was inserted in the same way; (O, P) Fluoroscopy is used to determine whether the fixation is secure once the temporary fixation has been removed</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>A Typical case of guided group. The patient had right-sided Gartland type II SHF and was a 2-year-old boy. <bold>A-D</bold> Preoperative positive X-ray and three-dimensional CT images that are positive Gartland type II SHF. <bold>E–H</bold> One day following surgery, the fracture had been successfully reduced and fixed with K-wire; <bold>I-L</bold> The fracture line had blurred three weeks after the operation, and the K-wire had been taken out</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Comparison of general data of extensional SHF between two groups of children</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\" rowspan=\"2\">Group</th><th align=\"left\" colspan=\"2\">Gender</th><th align=\"left\" rowspan=\"2\">Age, year (mean ± SD)</th><th align=\"left\" colspan=\"2\">Side</th><th align=\"left\" rowspan=\"2\">Time<sup>a</sup>, hour<break/>(mean ± SD)</th><th align=\"left\" colspan=\"2\">Gartland type</th></tr><tr><th align=\"left\">Male</th><th align=\"left\">Female</th><th align=\"left\">Left</th><th align=\"left\">Right</th><th align=\"left\">Type II</th><th align=\"left\">Type III</th></tr></thead><tbody><tr><td align=\"left\">Guided, <italic>N</italic> = 51</td><td align=\"left\">28</td><td align=\"left\">23</td><td align=\"left\">6.24 ± 3.172</td><td align=\"left\">20</td><td align=\"left\">31</td><td char=\".\" align=\"char\">48.02 ± 29.504</td><td align=\"left\">29</td><td align=\"left\">22</td></tr><tr><td align=\"left\">Non-guided, <italic>N</italic> = 54</td><td align=\"left\">34</td><td align=\"left\">20</td><td align=\"left\">5.87 ± 3.257</td><td align=\"left\">24</td><td align=\"left\">30</td><td char=\".\" align=\"char\">52.56 ± 23.141</td><td align=\"left\">35</td><td align=\"left\">19</td></tr><tr><td align=\"left\">t/χ<sup>2</sup></td><td align=\"left\" colspan=\"2\">0.705</td><td align=\"left\">0.850</td><td align=\"left\" colspan=\"2\">0.295</td><td align=\"left\">-0.873</td><td align=\"left\" colspan=\"2\">0.697</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\" colspan=\"2\">0.401</td><td align=\"left\">0.562</td><td align=\"left\" colspan=\"2\">0.587</td><td align=\"left\">0.385</td><td align=\"left\" colspan=\"2\">0.404</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>Flynn elbow function evaluation criteria</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Rating</th><th align=\"left\">Cosmetic Factor:<break/>Carrying-Angle Loss</th><th align=\"left\">Functional Factor:<break/>Motion Loss<sup>a</sup></th></tr></thead><tbody><tr><td align=\"left\">Excellent</td><td align=\"left\">0° ~ 5°</td><td align=\"left\">0° ~ 5°</td></tr><tr><td align=\"left\">Good</td><td align=\"left\">5° ~ 10°</td><td align=\"left\">5° ~ 10°</td></tr><tr><td align=\"left\">Fair</td><td align=\"left\">10° ~ 15°</td><td align=\"left\">10° ~ 15°</td></tr><tr><td align=\"left\">Poor</td><td align=\"left\"> &gt; 15°</td><td align=\"left\">10° ~ 15°</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Comparison of perioperative data and fracture healing time between two groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Group</th><th align=\"left\">Operation time<sup>a</sup>, min<sup>c</sup></th><th align=\"left\">Fluoroscopy times, time<sup>c</sup></th><th align=\"left\">Rate<sup>b</sup></th><th align=\"left\">Baumann angle<sup>c</sup></th><th align=\"left\">Carrying angle<sup>c</sup></th><th align=\"left\">Fracture healing time, week<sup>c</sup></th></tr></thead><tbody><tr><td align=\"left\">Guided, <italic>N</italic> = 51</td><td align=\"left\">31.27 ± 4.920</td><td align=\"left\">15.53 ± 2.063</td><td align=\"left\">83/19</td><td align=\"left\">72.31° ± 1.794°</td><td align=\"left\">10.00° ± 1.483°</td><td align=\"left\">3.96 ± 0.848</td></tr><tr><td align=\"left\">Non-guided, <italic>N</italic> = 54</td><td align=\"left\">38.72 ± 4.249</td><td align=\"left\">20.69 ± 2.126</td><td align=\"left\">21/87</td><td align=\"left\">72.56° ± 1.777°</td><td align=\"left\">10.17° ± 1.463°</td><td align=\"left\">4.13 ± 0.778</td></tr><tr><td align=\"left\">t/χ<sup>2</sup></td><td align=\"left\">-8.316</td><td align=\"left\">-12.600</td><td align=\"left\">80.478</td><td align=\"left\">0.828</td><td align=\"left\">0.731</td><td align=\"left\">0.403</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\"> &lt; 0.001</td><td align=\"left\">0.489</td><td align=\"left\">0.564</td><td align=\"left\">0.290</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Comparison of Flynn scores between the two groups</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Group</th><th align=\"left\">Excellent</th><th align=\"left\">Good</th><th align=\"left\">Fair</th><th align=\"left\">Poor</th><th align=\"left\">Rate<sup>a</sup></th></tr></thead><tbody><tr><td align=\"left\">Guided, <italic>N</italic> = 51</td><td align=\"left\">33</td><td align=\"left\">14</td><td align=\"left\">3</td><td align=\"left\">1</td><td char=\".\" align=\"char\">92.16%</td></tr><tr><td align=\"left\">Non-guided, <italic>N</italic> = 54</td><td align=\"left\">30</td><td align=\"left\">17</td><td align=\"left\">5</td><td align=\"left\">2</td><td char=\".\" align=\"char\">87.04%</td></tr><tr><td align=\"left\">χ<sup>2</sup></td><td align=\"left\" colspan=\"5\">0.733</td></tr><tr><td align=\"left\"><italic>P</italic> value</td><td align=\"left\" colspan=\"5\">0.392</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p><sup>a</sup>from injury to operation</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>limitation of flexion and extension of elbow joint</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>time from the auxiliary reduction device installation to the K-wire tail cutting</p><p><sup>b</sup>for needle placement one / more times</p><p><sup>c</sup>mean ± SD</p></table-wrap-foot>", "<table-wrap-foot><p><sup>a</sup>for total excellent and good rate</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn><fn><p>Huan Liu and Lingzhi Li contributed equally to this work.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12891_2023_7160_Fig1_HTML\" id=\"MO1\"/>", "<graphic xlink:href=\"12891_2023_7160_Fig2_HTML\" id=\"MO2\"/>", "<graphic xlink:href=\"12891_2023_7160_Fig3_HTML\" id=\"MO3\"/>" ]
[]
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{ "acronym": [], "definition": [] }
22
CC BY
no
2024-01-14 23:43:47
BMC Musculoskelet Disord. 2024 Jan 12; 25:56
oa_package/51/c8/PMC10787493.tar.gz
PMC10787494
0
[ "<title>Introduction</title>", "<p id=\"Par5\">Sarcopenia, which was coined in 1989, is defined as the loss of skeletal muscle mass and function [##REF##31171417##1##]. Patients with sarcopenia present with reduced exercise capacity and nutrition deficiency, leading to physical disability and deconditioning and subsequently adverse outcomes. The prevalence of sarcopenia in end-stage heart failure (HF) has been shown to be 20% higher than that in healthy subjects of the same age [##REF##23178647##2##]. Actually, there may exist a deleterious interaction between sarcopenia and HF, with the reduced peripheral perfusion in HF triggering skeletal myopathy, while skeletal muscle degradation in turn deteriorates exercise capacity and thereby results in HF-related symptoms [##REF##28436486##3##]. Recently, clinical evidence suggests that low axial thoracic skeletal muscle size is associated with the severity of HF and could predict adverse outcomes preceding overt body weight loss [##REF##32950445##4##, ##REF##36098058##5##]. Given this close relationship, sarcopenia is increasingly becoming recognized as an important abnormal body composition alteration, and evaluation of axial thoracic skeletal muscle size should be incorporated into the routine care of patients with HF [##REF##35924562##6##].</p>", "<p id=\"Par6\">Diabetes mellitus (DM) is one of the most common comorbidities in heart failure with reduced ejection fraction (HFrEF), which is present in up to 40% of these patients and portends a worse prognosis [##REF##32035890##7##, ##REF##35729555##8##]. It is necessary to better understand the potential association of sarcopenia with left ventricular (LV) remodeling and clinical outcome in patients with HFrEF and DM. However, to our knowledge, data on this issue are limited. Therefore, in this study, we aimed to (1) compare the clinical characteristics and MRI findings according to different grades of axial thoracic skeletal muscle size; (2) investigate the relationship between skeletal muscle size, LV remodeling, and plasma concentrations of natriuretic peptides; and (3) determine the prognostic significance of skeletal muscle size in diabetes patients with HFrEF.</p>" ]
[ "<title>Methods</title>", "<title>Study population</title>", "<p id=\"Par7\">The diagnosis of HFrEF was made according to the guidelines from the European Society of Cardiology (2021) [##REF##34447992##9##]. Patients were initially enrolled between June 2015 and June 2022 with the presence of symptoms and/or signs of HF, an elevated amino-terminal pro-B-type natriuretic peptide (NT-proBNP), and a reduced LV ejection fraction (LVEF ≤ 40%). Patients were excluded whenever one of the following criteria was met: (1) age younger than 18 years old; (2) a history of decompensated HF within 3 months of enrollment; (3) acute coronary syndrome; (4) severe arrhythmia; or (5) incomplete clinical or MRI information. Demographics, clinical characteristics, and laboratory measurements at baseline were collected from electronic clinical records. DM status was then defined based on the current guidelines from the European Society of Cardiology (2019) [##REF##31497854##10##]. This study was approved by the Biomedical Research Ethics Committees of West China Hospital and complied with the Declaration of Helsinki. Written informed consent was waived because of the retrospective nature of the study. All medical data were protected with full confidentiality and used only for the purpose of the present study.</p>", "<title>Cardiac MRI protocol</title>", "<p id=\"Par8\">Cardiac MRI was performed on a 3-Tesla scanner (MAGNETOM Skyra/Tim Trio; Siemens Healthcare, Erlangen, Germany) for each patient at the time of HF diagnosis for evaluating cardiac structure and function. As included in the routine cardiac MRI protocol, an axial stack of steady-state free precession (SSFP) imaging was obtained with the following parameters: temporal resolution = 224.16 ms; echo time (TE) = 1.23 ms; slice thickness = 6.0 mm; flip angle (FA) = 60°; acquisition matrix = 126 × 256 pixels; and field of view (FOV) = 340 × 255 mm<sup>2</sup>. For cine imaging, a balanced SSFP sequence was performed with the following parameters: repetition time (TR) = 2.81 ms; TE = 1.22 ms; slice thickness = 8.0 mm; FA = 40°/50°; acquisition matrix = 166 × 208 pixels; and FOV = 340 × 284 mm<sup>2</sup>. Twenty-five frames were reconstructed per breath-hold acquisition for cine images. Fifteen minutes after the administration of gadolinium-based contrast (0.2 mL/kg), late gadolinium enhancement (LGE) imaging was acquired by phase-sensitive inversion recovery sequence. The acquisition parameters were as follows: TR = 700/500 ms; TE = 1.18/1.07 ms; slice thickness = 8.0 mm; FA = 40°; acquisition matrix = 184 × 256 pixels; and FOV = 350 × 295 mm<sup>2</sup>.</p>", "<title>Cardiac MRI imaging assessment</title>", "<p id=\"Par9\">All images were analyzed using commercially available CVI<sup>42</sup> software (Circle Cardiovascular Imaging, Inc., Calgary, Alberta, Canada). Methods of axial thoracic skeletal muscle size measurements were based on the work conducted in a previous study [##REF##32950445##4##]. In brief, thoracic skeletal muscle at the level of the carina, including muscle groups of pectoralis major, pectoralis minor, serratus anterior, periscapular, paraspinal, and trapezius muscles, were manually traced bilaterally to obtain cross-sectional area (i.e., skeletal muscle size [cm<sup>2</sup>]) (Fig. ##FIG##0##1##). The carina represents the inferior termination of the trachea into the right and left main bronchi. Periscapular muscles refer to the muscle groups of latissimus dorsi, subscapularis, and infraspinatus around the scapula. Axial thoracic skeletal muscle size in each patient was standardized with adjustment of body size and further produced skeletal muscle index (SMI [cm<sup>2</sup>/m<sup>2</sup>]).</p>", "<p id=\"Par10\">\n\n</p>", "<p id=\"Par11\">For volumetric analyses, endocardial and epicardial borders were traced semiautomatically and manually corrected if needed at the LV end-diastolic and end-systolic phases in a series of short-axis images. LV function parameters, including EF, end-diastolic volume (EDV), end-systolic volume (ESV), and stroke volume (SV), were automatically calculated. LV papillary muscles were included in the LV mass (LVM) but not in the LV volume. For myocardial strain analyses, a stack of short-axis cine images combined with 4-, 2- and 3-chamber long-axis images were loaded into the feature-tracking module. We delineated LV endocardial and epicardial borders at the end-diastolic phases (reference phase) of all cine images. The software automatically traced the contours throughout the cardiac cycle. During the systolic phase, the LV shortens in the longitudinal and circumferential directions, causing negative global longitudinal peak strain (PS) and circumferential PS, whereas thickening in the radial direction causes positive global radial PS. Detection and quantification of LGE were carried out by both visual and quantitative methods using the established grayscale threshold method of six standard deviations exceeding the mean signal intensity of remote nonfibrotic myocardium.</p>", "<p id=\"Par12\">To determine the interobserver reproducibility, half of the sample size selected in a random manner was analyzed by two experienced radiologists who were blind to each other’s findings. Moreover, to determine the intraobserver reproducibility, the same study sample was reanalyzed a second time 2 weeks after the initial assessment. Reproducibility was assessed with intraclass correlation coefficients (ICCs), which ranged from 0.88 to 0.92. ICCs &gt; 0.80 indicated good reproducibility.</p>", "<title>Follow-up and outcomes</title>", "<p id=\"Par13\">The primary composite outcome was recorded as HF hospitalization, cardiovascular mortality and heart transplantation, whichever occurred first. HF hospitalization was defined as an unplanned hospitalization or an urgent hospital visit for worsening HF. Follow-up data were obtained from electronic medical records or phone calls to patients or family members. Follow-up duration was calculated as either the time from cardiac MRI to the occurrence of any endpoint or June 2023 (the last follow-up date).</p>", "<title>Statistical analysis</title>", "<p id=\"Par14\">Statistical analyses were performed using SPSS (IBM SPSS Inc., Armonk, New York, USA) and Prism (GraphPad software Inc., San Diego, California, USA). The normality of the data was determined using the Shapiro–Wilk test. Data are expressed as the means with standard deviations or medians with interquartile ranges (IQRs) for continuous variables and frequencies for categorical variables. Comparative analyses among variables stratified by tertiles of thoracic SMI were carried out according to the type of variable using one-way analysis of variance, followed by the Bonferroni’s post hoc test or its nonparametric equivalents (Kruskal–Wallis test), chi–square test or Fisher’s exact test, as appropriate. Between-group differences in thoracic SMI in patients with and without primary outcomes were assessed using unpaired t–tests or Mann–Whitney U–tests. NT-proBNP was log-transformed and analyzed in a continuous fashion. Bivariate correlations related to thoracic SMI or NT-proBNP were obtained using the Pearson method. The relationship of NT-proBNP with thoracic SMI was assessed using linear regression analysis, and the standardized betas (β) were provided. Long-term adverse outcomes were assessed using Kaplan–Meier survival analysis and compared among different tertiles of thoracic SMI using the log-rank test. Associations of thoracic SMI and its components with adverse outcomes were determined using a multivariable Cox proportional hazards model after adjusting for potential confounders. Differences with a two-tailed P value &lt; 0.05 were considered indicative of statistical significance.</p>" ]
[ "<title>Results</title>", "<title>Baseline characteristics</title>", "<p id=\"Par15\">Detailed baseline characteristics of the study population stratified by thoracic SMI are displayed in Table ##TAB##0##1##. There was no difference in age, sex, baseline blood pressure, heart rate, or history of smoking and drinking among the three groups (all P &gt; 0.05), except body mass index (BMI), which was higher in patients in the third tertile (P = 0.006). HF duration, New York Heart Association functional class, etiology of HF, and comorbidity burden with the use of relevant medications were similar across groups (all P &gt; 0.05).</p>", "<p id=\"Par16\">\n\n</p>", "<p id=\"Par17\">Patients in the first tertile had the highest level of NT‑proBNP (median, 3281 [Q1-Q3, 1645–9909] pg/mL vs. 2628 [976, 4958] pg/mL vs. 1709 [669, 3967] pg/mL; P &lt; 0.001) but the lowest estimated glomerular filtration rate (eGFR), albumin and hemoglobin levels (all P &lt; 0.05). Moreover, compared with patients in the second and third tertiles, those in the first tertile tended to have the highest levels of fasting blood glucose (P = 0.07) and glycated hemoglobin (P = 0.09).</p>", "<title>Differences in cardiac MRI findings stratified by thoracic SMI</title>", "<p id=\"Par18\">Although LV volumetric indices and LVEF were similar among the thoracic SMI tertiles, lower thoracic SMI occurred with a deteriorated magnitude of LV global PS in longitudinal (-4.2 ± 1.8% vs. -5.2 ± 2.1% vs. -6.0 ± 1.9%; P &lt; 0.001), circumferential (-6.3 ± 2.5% vs. -7.5 ± 2.9% vs. -8.4 ± 2.7%; P &lt; 0.001), and radial (8.1 ± 4.3% vs. 10.7 ± 5.5% ± 10.2 ± 4.9%; P = 0.003) components (Fig. ##FIG##1##2##). To explore the association between thoracic SMI tertiles and LV contractile function more carefully, we made subgroup analysis excluding patients with ischemic etiology. As expected, greatest deterioration of the magnitude LV global PS in longitudinal (-4.5 ± 2.1% vs. -5.6 ± 2.6% vs. -5.9 ± 1.8%; P = 0.002), circumferential (-6.5 ± 2.7% vs. -7.8 ± 3.2% vs. -7.9 ± 2.7%; P = 0.014), and radial (8.4 ± 5.3% vs. 10.7 ± 4.8% vs. 9.8 ± 5.4%; P = 0.047) components was observed in patients in the first tertile.</p>", "<p id=\"Par19\">\n\n</p>", "<p id=\"Par20\">Interestingly, concomitant with the thoracic SMI decrease, there was an increase in LVM (153.9 ± 37.2 g vs. 139.9 ± 31.5 g vs. 126.3 ± 23.1 g; P &lt; 0.001). The significant difference remained robust even when taking body size into account (92.3 ± 18.0 g/m<sup>2</sup> vs. 81.8 ± 18.3 g/m<sup>2</sup> vs. 72.8 ± 14.7 g/m<sup>2</sup>; P &lt; 0.001) (Table ##TAB##1##2##). Further Pearson analysis showed a negative correlation between thoracic SMI and LVM index (r = -0.40; P &lt; 0.001). Moreover, despite a nonsignificant distribution of myocardial scars, a higher median of scar extent in patients with LGE was observed with decreasing thoracic SMI grade (median, 27.8 [IQR, 19.3–39.7] % vs. 23.3 [16.1–31.6] % vs. 20.6 [13.6–30.8] %; P = 0.03). Mitral regurgitation occurred more frequently in patients with the lowest grade of thoracic SMI (64.2% vs. 48.1% vs. 45.7%; P = 0.04).</p>", "<p id=\"Par21\">\n\n</p>", "<title>Associations of NT-proBNP with thoracic SMI and BMI</title>", "<p id=\"Par22\">As demonstrated in Fig. ##FIG##2##3##, we found an inverse correlation between NT-proBNP and thoracic SMI (r = -0.34; P &lt; 0.001), whereas only a weak trend was obtained between NT-proBNP and BMI (r = -0.12; P = 0.06). These relationships were assessed with linear regression. In the unadjusted univariate analysis, thoracic SMI (β = -0.34; P &lt; 0.001), rather than BMI (β = -0.12; P = 0.06), was associated with NT-proBNP. In a model that adjusted for age, sex, NYHA functional class, the eGFR, LVEF and LVM index, the association between thoracic SMI and NT-proBNP remained unchanged (β = -0.25; P &lt; 0.001) but not the association with BMI (β = -0.04; P = 0.55) (Table ##TAB##2##3##).</p>", "<p id=\"Par23\">\n\n</p>", "<p id=\"Par24\">\n\n</p>", "<title>Associations of thoracic SMI and its components with clinical outcomes</title>", "<p id=\"Par25\">During a median follow-up of 33.6 months (Q1-Q3, 20.4–52.8 months), a total of 48 patients (19.8%) met one confirmed composite endpoint event. The primary composite events occurred more frequently in patients in the lowest grade of thoracic SMI (27.2% vs. 21.0% vs. 11.1%; P = 0.035). By Kaplan–Meier survival analysis, patients in the lowest tertile, indicating the lowest size of thoracic skeletal muscle, were more likely to experience the primary outcome than those in the middle and highest tertiles during follow-up (log-rank P = 0.035; Fig. ##FIG##3##4##).</p>", "<p id=\"Par26\">\n\n</p>", "<p id=\"Par27\">Patients with adverse outcomes had reduced thoracic SMI (median, 40.1 [IQR, 34.3–47.9] cm<sup>2</sup>/m<sup>2</sup> vs. 45.3 [37.3–55.0] cm<sup>2</sup>/m<sup>2</sup>; P = 0.017), pectoralis major index (11.0 [8.8–14.3] cm<sup>2</sup>/m<sup>2</sup> vs. 10.2 [8.1–12.0] cm<sup>2</sup>/m<sup>2</sup>; P = 0.019), and periscapular index (20.7 [15.0-27.3] cm<sup>2</sup>/m<sup>2</sup> vs. 17.4 [13.7–22.6] cm<sup>2</sup>/m<sup>2</sup>; P = 0.029) compared with those without adverse outcomes. Nevertheless, BMI in patients with adverse outcomes was comparable to that in patients without (24.8 ± 3.9 kg/m<sup>2</sup> vs. 24.6 ± 3.7 kg/m<sup>2</sup>; P = 0.76). Our multivariable Cox proportional hazards model showed that a higher thoracic SMI (HR: 0.96; 95% CI: 0.92–0.99; P = 0.01), pectoralis major index (HR: 0.85; 95% CI: 0.75–0.96; P &lt; 0.01), and periscapular index (HR: 0.94; 95% CI: 0.90–0.99; P = 0.02) were each independently associated with a lower risk of the primary outcome in diabetes patients with HFrEF (Table ##TAB##3##4##). However, our analysis did not yield any associations between BMI and the primary outcome in the same condition.</p>", "<p id=\"Par28\">\n\n</p>" ]
[ "<title>Discussion</title>", "<p id=\"Par29\">The present study emphasized the necessity of thoracic SMI evaluation and provided a convenient surrogate for sarcopenia with prognostic information in the routine care of diabetes patients with HFrEF. The principal findings were as follows: (1) in diabetes patients with HFrEF, a reduction in thoracic SMI was more likely to be associated with a deterioration in LV contractility, together with an increase in LVM and a heavier burden of myocardial fibrosis, leading to “nonfunctional” cardiac hypertrophy; (2) thoracic SMI, rather than BMI, was independently associated with the level of NT-proBNP; and (3) a lower thoracic SMI indicated a higher risk of adverse clinical outcomes, regardless of cardiac functional/structural measurements. Thoracic SMI and its components assessed by routine cardiac MRI could be used as a new predictor of outcomes in diabetes patients with HFrEF.</p>", "<title>Role of sarcopenia in LV remodeling</title>", "<p id=\"Par30\">The role of sarcopenia in the context of HF has recently received much attention. This change in body composition is considered a key determinant of many symptoms related to HF syndrome and is associated with poor outcomes, suggesting the detrimental effect of sarcopenia on LV remodeling in patients with chronic HF [##REF##32950445##4##, ##REF##36098058##5##, ##REF##27454614##11##–##REF##30160804##14##]. However, these studies fail to further reveal the alterations of LV structure and function in a given HF phenotype, and the possible cardiac remodeling in the condition of skeletal muscle wasting is incompletely understood. In contrast, with respect to diabetes patients with HFrEF, our data showed that those with reduced axial thoracic muscle mass were more likely to display deteriorated LV contractility despite similar LVEF. Indeed, it is believed that both sarcopenia and HF interact with each other, with the onset of one disease promoting disease progression in the other. Our findings may partially be explained by the mechanism by which hypoperfusion accompanied by LV dysfunction in HFrEF could induce skeletal myopathy, which subsequently yields increased activation of the sympathetic nervous system as well as the renin–angiotensin–aldosterone system and consequently leads to endothelial dysfunction, vasoconstriction and myocardial injury [##REF##28436486##3##, ##REF##37186680##15##–##REF##37072781##17##].</p>", "<p id=\"Par31\">Interestingly, we found that patients in the lowest tertile of thoracic SMI exhibited a higher LVM with a higher burden of myocardial fibrosis. In terms of this point, only the study by Beyer et al. reported similar findings in UK adults, which indicated an inverse correlation between the severity of sarcopenia and cardiac mass [##REF##29538386##18##]. The role of sarcopenia in the development of cardiac remodeling in HFrEF is not fully understood. Apart from the abovementioned validated mechanisms, it has also been observed that sarcopenia and HFrEF share similar proinflammatory cytokines and molecular pathways in the occurrence and persistence of myocardial inflammation, which together are sufficient to cause cardiomyocyte death and secondary myocardial fibrosis [##REF##30065268##19##–##REF##36732747##22##]. Thus, in view of the characteristics of “nonfunctional” cardiac hypertrophy accompanied by cardiac dysfunction and remarkable myocardial fibrosis, whether a sarcopenic heart exists needs further study for clarification.</p>", "<title>Prognostic ability of axial thoracic SMI</title>", "<p id=\"Par32\">The “obesity paradox” is a well-known phenomenon in established HF that describes a survival benefit in obese patients. However, for diabetes patients comorbid with HFrEF, data from multicenter studies suggested that obesity may confer no advantage at all to this patient group [##REF##20930001##23##–##REF##27312985##25##]. To date, there is no consensus on the reason why the obesity paradox is absent in diabetes patients with HFrEF. A previous report observed significantly lower sympathetic activation in obese patients than in their nonobese counterparts, but whether the positive impact of attenuated sympathetic activation in obese patients with HF is blunted by the presence of DM remains unknown [##REF##25497534##26##]. In the present study, axial thoracic SMI, but not BMI, demonstrated an independent relationship with NT-proBNP, and only a reduction in axial thoracic SMI indicated an increased risk of adverse outcomes. Based on these findings, we speculate that a superimposed and synergistic effect exerted by the coexistence of DM and sarcopenia may promote the process of adverse LV remodeling, leading to poor outcomes in HFrEF. In fact, the simple BMI measurement is unable to reflect the changes in body composition and thereby cannot separate lean mass from fat mass. Moreover, skeletal muscle wasting often occurs prior to adipose loss [##REF##32950445##4##, ##REF##30065268##19##]. In this view, the present study may help elucidate why BMI is not independently associated with survival in diabetes patients with HFrEF. Therefore, our data highlight the importance and sensitivity of skeletal muscle mass changes in relation to prognosis in this condition.</p>", "<p id=\"Par33\">Consistent with published literature, the cross-sectional size of the pectoralis major in this study was demonstrated to be an independent predictor of clinical outcomes [##REF##32950445##4##, ##REF##30755074##13##, ##REF##28912261##27##]. Moreover, our study additionally evaluated and identified the periscapular muscle groups, which were found to be the other major muscle groups with prognostic value. The possible explanation for this observation is that the wasting of these skeletal muscle groups is more reflective of physical performance, such as the maintenance of upright posture and cardio-pulmonary function, which itself is an indicator of the development of frailty. Further studies in larger and more diverse populations are needed to confirm our findings.</p>", "<title>Evaluation of axial thoracic SMI by routine cardiac MRI in clinical practice</title>", "<p id=\"Par34\">Currently, the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) recommends dual-energy X-ray absorptiometry (DEXA) as the method of choice for the evaluation of skeletal muscle quantity in clinical settings. Although this method has the advantages of being fast and low-cost, the results are susceptible to fluid status, which frequently fluctuates with HF, making it less useful in these cases [##REF##35924562##6##]. Moreover, this method has been traditionally applied in assessing skeletal muscle of the upper or lower extremities, which is more subject to deconditioning [##REF##28899988##12##, ##REF##35292039##28##]. Our methods of quantification of thoracic skeletal muscle mass suggest that it is feasible to obtain important prognostic information related to sarcopenia from routine cardiac MRI images alone without adding additional sequences. Thus, our study may provide a “one-stop” scanning protocol not only for cardiac structure and function but also for sarcopenia assessment in diabetes patients with HFrEF.</p>", "<title>Study limitations</title>", "<p id=\"Par35\">The present study had some limitations. First, we identified the prognostic ability of thoracic skeletal muscle size for diabetes patients with HFrEF based on the SMI tertile. However, the threshold for this novel predictor to define low muscle mass is currently unknown. Further studies should be conducted in HF populations to confirm the specific cutoff value of thoracic skeletal muscle size for the diagnosis of sarcopenia. Second, although our study found a novel and promising alternative for assessing reduced skeletal muscle, we did not include functional data, such as muscle strength and physical performance, which is helpful in stratification. This issue merits further investigation. Finally, we must acknowledge that due to the retrospective nature of this study, selection bias was inevitable.</p>", "<p id=\"Par36\">In conclusion, thoracic SMI, but not BMI, is independently associated with adverse outcomes in diabetes patients with HFrEF and is a surrogate of sarcopenia that can be obtained by a readily available routine cardiac MRI protocol. Our study provided a novel prognostic predictor and highlighted the necessity of assessing thoracic skeletal muscle size in diabetes patients with HFrEF. Further studies with more sample sizes are warranted to validate our findings.</p>" ]
[]
[ "<title>Background</title>", "<p id=\"Par1\">Sarcopenia is frequently found in patients with heart failure with reduced ejection fraction (HFrEF) and is associated with reduced exercise capacity, poor quality of life and adverse outcomes. Recent evidence suggests that axial thoracic skeletal muscle size could be used as a surrogate to assess sarcopenia in HFrEF. Since diabetes mellitus (DM) is one of the most common comorbidities with HFrEF, we aimed to explore the potential association of axial thoracic skeletal muscle size with left ventricular (LV) remodeling and determine its prognostic significance in this condition.</p>", "<title>Methods</title>", "<p id=\"Par2\">A total of 243 diabetes patients with HFrEF were included in this study. Bilateral axial thoracic skeletal muscle size was obtained using cardiac MRI. Patients were stratified by the tertiles of axial thoracic skeletal muscle index (SMI). LV structural and functional indices, as well as amino-terminal pro-B-type natriuretic peptide (NT-proBNP), were measured. The determinants of elevated NT-proBNP were assessed using linear regression analysis. The associations between thoracic SMI and clinical outcomes were assessed using a multivariable Cox proportional hazards model.</p>", "<title>Results</title>", "<p id=\"Par3\">Patients in the lowest tertile of thoracic SMI displayed a deterioration in LV systolic strain in three components, together with an increase in LV mass and a heavier burden of myocardial fibrosis (all P &lt; 0.05). Moreover, thoracic SMI (β = -0.25; P &lt; 0.001), rather than body mass index (β = -0.04; P = 0.55), was independently associated with the level of NT-proBNP. The median follow-up duration was 33.6 months (IQR, 20.4–52.8 months). Patients with adverse outcomes showed a lower thoracic SMI (40.1 [34.3, 47.9] cm<sup>2</sup>/m<sup>2</sup> vs. 45.3 [37.3, 55.0] cm<sup>2</sup>/m<sup>2</sup>; P &lt; 0.05) but a similar BMI (P = 0.76) compared with those without adverse outcomes. A higher thoracic SMI indicated a lower risk of adverse outcomes (hazard ratio: 0.96; 95% confidence interval: 0.92–0.99; P = 0.01).</p>", "<title>Conclusions</title>", "<p id=\"Par4\">With respect to diabetes patients with HFrEF, thoracic SMI is a novel alternative for evaluating muscle wasting in sarcopenia that can be obtained by a readily available routine cardiac MRI protocol. A reduction in thoracic skeletal muscle size predicts poor outcomes in the context of DM with HFrEF.</p>", "<title>Keywords</title>" ]
[]
[ "<title>Acknowledgements</title>", "<p>Not applicable.</p>", "<title>Author contributions</title>", "<p>K.S. and G.Z. interpreted the data and wrote the manuscript. H.F., X.M.L. and S.Q.Y. analyzed the data and gave advice on data presentation. K.S., G.Z., H.F., R.S., W.F.Y. and W.L.Q. collected the data. H.Y.X., Y.L., Y.K.G. and Z.G.Y. participated in the study design. K.S., Y.K.G. and Z.G.Y. revised the manuscript. All authors read and approved the final manuscript.</p>", "<title>Funding</title>", "<p>This study was financially supported by the National Natural Science Foundation of China (82120108015, 82371925), Science and Technology Support Program of Sichuan Province (2022NSFSC1494, 2023ZYD0100) and the 1–3–5 project for disciplines of excellence of West China Hospital, Sichuan University (ZYGD23019).</p>", "<title>Data availability</title>", "<p>The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.</p>", "<title>Declarations</title>", "<title>Ethics approval and consent to participate</title>", "<p id=\"Par39\">This study was approved by the Biomedical Research Ethics Committees of West China Hospital and was complied with the Declaration of Helsinki. Written informed consent was waived because of the retrospective nature of the study.</p>", "<title>Consent for publication</title>", "<p id=\"Par40\">Not applicable.</p>", "<title>Competing interests</title>", "<p id=\"Par38\">The authors declare no competing interests.</p>" ]
[ "<fig id=\"Fig1\"><label>Fig. 1</label><caption><p>Axial MRI image at the level of carina demonstrating the measurements of bilateral cross-sectional area of thoracic skeletal muscle</p></caption></fig>", "<fig id=\"Fig2\"><label>Fig. 2</label><caption><p>Differences of magnitude of global left ventricular systolic PS across the groups. Abbreviations: PS, peak strain. *, P value &lt; 0.017 versus patients in the second tertile. #, P value &lt; 0.017 versus patients in the first tertile</p></caption></fig>", "<fig id=\"Fig3\"><label>Fig. 3</label><caption><p>Bivariate correlations between NT-proBNP and thoracic SMI or BMI. NT-proBNP is log-transformed before being included in the Pearson’s analysis. Abbreviations: NT-proBNP, amino-terminal pro-B-type natriuretic peptide; SMI, skeletal muscle index; BMI, body mass index</p></caption></fig>", "<fig id=\"Fig4\"><label>Fig. 4</label><caption><p>Survival curves of the study cohort according to tertiles of thoracic SMI. Abbreviations: SMI, skeletal muscle index</p></caption></fig>" ]
[ "<table-wrap id=\"Tab1\"><label>Table 1</label><caption><p>Baseline characteristics of the study population according to tertiles of thoracic SMI</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">First tertile (n = 81)</th><th align=\"left\">Second tertile (n = 81)</th><th align=\"left\">Third tertile (n = 81)</th></tr></thead><tbody><tr><td align=\"left\">Age, yrs</td><td align=\"left\">57.8 ± 11.4</td><td align=\"left\">57.4 ± 10.9</td><td align=\"left\">55.7 ± 11.9</td></tr><tr><td align=\"left\">Male, n (%)</td><td align=\"left\">53 (65.4)</td><td align=\"left\">56 (69.1)</td><td align=\"left\">62 (76.5)</td></tr><tr><td align=\"left\">BMI, kg/m<sup>2</sup></td><td align=\"left\">23.7 ± 3.8</td><td align=\"left\">24.7 ± 3.8</td><td align=\"left\">25.5 ± 3.3*</td></tr><tr><td align=\"left\">SBP, mmHg</td><td align=\"left\">120.4 ± 20.9</td><td align=\"left\">118.0 ± 20.5</td><td align=\"left\">122.0 ± 20.9</td></tr><tr><td align=\"left\">DBP, mmHg</td><td align=\"left\">78.2 ± 15.9</td><td align=\"left\">77.9 ± 14.5</td><td align=\"left\">80.5 ± 14.8</td></tr><tr><td align=\"left\">HR, beats/min</td><td align=\"left\">85.9 ± 14.2</td><td align=\"left\">87.4 ± 18.3</td><td align=\"left\">85.6 ± 19.1</td></tr><tr><td align=\"left\">Smoking, n (%)</td><td align=\"left\">39 (48.1)</td><td align=\"left\">38 (46.9)</td><td align=\"left\">45 (55.6)</td></tr><tr><td align=\"left\">Drinking, n (%)</td><td align=\"left\">27 (33.3)</td><td align=\"left\">32 (39.5)</td><td align=\"left\">31 (38.3)</td></tr><tr><td align=\"left\" colspan=\"4\">HF duration, n (%)</td></tr><tr><td align=\"left\">≤ 1 yr</td><td align=\"left\">46 (56.8)</td><td align=\"left\">40 (49.4)</td><td align=\"left\">49 (60.5)</td></tr><tr><td align=\"left\">&gt; 1 and ≤ 5 yrs</td><td align=\"left\">22 (27.2)</td><td align=\"left\">21 (25.9)</td><td align=\"left\">25 (30.9)</td></tr><tr><td align=\"left\">&gt; 5 yrs</td><td align=\"left\">13 (16.0)</td><td align=\"left\">20 (24.7)</td><td align=\"left\">7 (8.6)</td></tr><tr><td align=\"left\">NYHA functional class III– IV, n (%)</td><td align=\"left\">68 (80.2)</td><td align=\"left\">60 (74.1)</td><td align=\"left\">58 (71.6)</td></tr><tr><td align=\"left\" colspan=\"4\">Etiology of HF</td></tr><tr><td align=\"left\">Ischemia</td><td align=\"left\">25 (30.9)</td><td align=\"left\">29 (35.8)</td><td align=\"left\">24 (29.6)</td></tr><tr><td align=\"left\">Cardiomyopathy</td><td align=\"left\">36 (44.4)</td><td align=\"left\">32 (39.5)</td><td align=\"left\">44 (54.3)</td></tr><tr><td align=\"left\">Other</td><td align=\"left\">20 (24.7)</td><td align=\"left\">20 (24.7)</td><td align=\"left\">13 (16.1)</td></tr><tr><td align=\"left\" colspan=\"4\">Medical history, n (%)</td></tr><tr><td align=\"left\">HT</td><td align=\"left\">38 (46.9)</td><td align=\"left\">36 (44.4)</td><td align=\"left\">43 (53.1)</td></tr><tr><td align=\"left\">AF</td><td align=\"left\">16 (19.8)</td><td align=\"left\">18 (22.2)</td><td align=\"left\">11 (13.6)</td></tr><tr><td align=\"left\">Dyslipidemia</td><td align=\"left\">28 (34.6)</td><td align=\"left\">34 (42.0)</td><td align=\"left\">33 (40.7)</td></tr><tr><td align=\"left\">LBBB</td><td align=\"left\">5 (6.3)</td><td align=\"left\">9 (11.1)</td><td align=\"left\">5 (6.3)</td></tr><tr><td align=\"left\">COPD</td><td align=\"left\">11 (13.6)</td><td align=\"left\">4 (4.9)</td><td align=\"left\">7 (8.6)</td></tr><tr><td align=\"left\">SAS</td><td align=\"left\">1 (1.2)</td><td align=\"left\">4 (4.9)</td><td align=\"left\">4 (4.9)</td></tr><tr><td align=\"left\" colspan=\"4\">Laboratory measurements</td></tr><tr><td align=\"left\">NT‑proBNP, pg/mL</td><td align=\"left\">3281 (1645, 9909)</td><td align=\"left\">2628 (976, 4958) &amp;</td><td align=\"left\">1709 (669, 3967) &amp;#</td></tr><tr><td align=\"left\">eGFR, mL/min/1.73m<sup>2</sup></td><td align=\"left\">67.5 ± 28.3</td><td align=\"left\">74.6 ± 21.5</td><td align=\"left\">77.1 ± 23.2*</td></tr><tr><td align=\"left\">FBG, mmol/L</td><td align=\"left\">8.2 (6.7, 10.5)</td><td align=\"left\">7.9 (6.5, 10.1)</td><td align=\"left\">7.3 (6.2, 9.2)</td></tr><tr><td align=\"left\">HbA1C, %</td><td align=\"left\">7.4 (6.6, 8.4)</td><td align=\"left\">7.0 (6.2, 8.0)</td><td align=\"left\">6.8 (6.3, 7.9)</td></tr><tr><td align=\"left\">Albumin, g/L</td><td align=\"left\">38.9 ± 5.3</td><td align=\"left\">41.6 ± 4.1*</td><td align=\"left\">41.7 ± 4.2*</td></tr><tr><td align=\"left\">TG, mmol/L</td><td align=\"left\">1.4 (1.0, 2.0)</td><td align=\"left\">1.6 (1.1, 2.5)</td><td align=\"left\">1.6 (1.1, 2.3)</td></tr><tr><td align=\"left\">TC, mmol/L</td><td align=\"left\">4.1 (3.5, 4.7)</td><td align=\"left\">3.9 (3.1, 4.6)</td><td align=\"left\">4.1 (3.3, 4.8)</td></tr><tr><td align=\"left\">HDL‑C, mmol/L</td><td align=\"left\">1.1 ± 0.4</td><td align=\"left\">1.0 ± 0.3</td><td align=\"left\">1.0 ± 0.3</td></tr><tr><td align=\"left\">LDL‑C, mmol/L</td><td align=\"left\">2.4 (1.9, 2.9)</td><td align=\"left\">2.2 (1.6, 2.9)</td><td align=\"left\">2.5 (1.8, 2.9)</td></tr><tr><td align=\"left\">Hemoglobin, g/L</td><td align=\"left\">132.7 ± 26.3</td><td align=\"left\">135.8 ± 22.7*</td><td align=\"left\">145.3 ± 22.3*†</td></tr><tr><td align=\"left\" colspan=\"4\">Cardiovascular medications, n (%)</td></tr><tr><td align=\"left\">Beta‑blocker</td><td align=\"left\">60 (74.1)</td><td align=\"left\">65 (80.2)</td><td align=\"left\">65 (80.2)</td></tr><tr><td align=\"left\">ACEI/ARB</td><td align=\"left\">57 (70.4)</td><td align=\"left\">63 (77.8)</td><td align=\"left\">64 (79.0)</td></tr><tr><td align=\"left\">SGLT-2i</td><td align=\"left\">27 (33.3)</td><td align=\"left\">26 (32.1)</td><td align=\"left\">30 (37.0)</td></tr><tr><td align=\"left\">Diuretics</td><td align=\"left\">68 (84.0)</td><td align=\"left\">69 (85.2)</td><td align=\"left\">67 (82.7)</td></tr><tr><td align=\"left\">ARNI</td><td align=\"left\">31 (38.3)</td><td align=\"left\">27 (33.3)</td><td align=\"left\">34 (41.9)</td></tr><tr><td align=\"left\">CCB</td><td align=\"left\">11 (13.6)</td><td align=\"left\">7 (8.6)</td><td align=\"left\">14 (17.3)</td></tr><tr><td align=\"left\"><p>Anti‑thrombotic</p><p>agents</p></td><td align=\"left\">43 (53.1)</td><td align=\"left\">45 (55.6)</td><td align=\"left\">49 (60.5)</td></tr><tr><td align=\"left\">Statins</td><td align=\"left\">38 (46.9)</td><td align=\"left\">39 (48.1)</td><td align=\"left\">41 (50.6)</td></tr><tr><td align=\"left\">Digoxin</td><td align=\"left\">20 (24.7)</td><td align=\"left\">20 (24.7)</td><td align=\"left\">8 (9.9) §λ</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab2\"><label>Table 2</label><caption><p>MRI findings of the study population according to tertiles of thoracic SMI</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">First tertile (n = 81)</th><th align=\"left\">Second tertile (n = 81)</th><th align=\"left\">Third tertile (n = 81)</th></tr></thead><tbody><tr><td align=\"left\">LVEDV, mL</td><td align=\"left\">262.8 (185.8, 339.3)</td><td align=\"left\">256.2 (176.4, 316.5)</td><td align=\"left\">260.8 (197.9, 308.3)</td></tr><tr><td align=\"left\">LVEDV index, mL/m<sup>2</sup></td><td align=\"left\">152.8 (125.7, 195.5)</td><td align=\"left\">148.4 (109.7, 185.7)</td><td align=\"left\">147.0 (123.0, 173.8)</td></tr><tr><td align=\"left\">LVESV, mL</td><td align=\"left\">199.7 (129.3, 285.5)</td><td align=\"left\">190.9 (118.7, 261.6)</td><td align=\"left\">193.8 (143.4, 239.1)</td></tr><tr><td align=\"left\">LVESV index, mL/m<sup>2</sup></td><td align=\"left\">121.7 (89.4, 163.8)</td><td align=\"left\">108.9 (71.2, 147.6)</td><td align=\"left\">111.3 (83.2, 135.4)</td></tr><tr><td align=\"left\">LVSV, mL</td><td align=\"left\">55.4 (39.4, 72.3)</td><td align=\"left\">56.3 (45.9, 77.5)</td><td align=\"left\">63.1 (47.7, 77.0)</td></tr><tr><td align=\"left\">LVSV index, mL/m<sup>2</sup></td><td align=\"left\">32.5 (24.6, 44.5)</td><td align=\"left\">35.6 (25.9, 45.4)</td><td align=\"left\">36.1 (28.4, 45.0)</td></tr><tr><td align=\"left\">LVEF, %</td><td align=\"left\">22.8 ± 8.3</td><td align=\"left\">26.9 ± 8.8</td><td align=\"left\">26.7 ± 9.1</td></tr><tr><td align=\"left\">LVM, g</td><td align=\"left\">153.9 ± 37.2</td><td align=\"left\">139.9 ± 31.5*</td><td align=\"left\">126.3 ± 23.1*†</td></tr><tr><td align=\"left\">LVM index, g/m<sup>2</sup></td><td align=\"left\">92.3 ± 18.0</td><td align=\"left\">81.8 ± 18.3*</td><td align=\"left\">72.8 ± 14.7*†</td></tr><tr><td align=\"left\">MR, n (%)</td><td align=\"left\">52 (64.2)</td><td align=\"left\">39 (48.1) §</td><td align=\"left\">37 (45.7) §</td></tr><tr><td align=\"left\">LGE present, n (%)</td><td align=\"left\">55 (67.9)</td><td align=\"left\">54 (66.7)</td><td align=\"left\">60 (74.1)</td></tr><tr><td align=\"left\">LGE size, % LVM</td><td align=\"left\">27.8 (19.3, 39.7)</td><td align=\"left\">23.3 (16.1, 31.6) &amp;</td><td align=\"left\">20.6 (13.6, 30.8) &amp;#</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab3\"><label>Table 3</label><caption><p>Linear regression analysis for factors associated with NT-proBNP</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Univariable coefficient B (one unit increase for continuous variables/yes or no for categorical variables)</th><th align=\"left\">Univariable standardized coefficient β (compare the effect estimates)</th><th align=\"left\">Multivariable coefficient B (one unit increase for continuous variables/yes or no for categorical variables)</th><th align=\"left\">Multivariable standardized coefficient β (adjusted R<sup>2</sup> = 0.31) (compare the effect estimates)</th></tr></thead><tbody><tr><td align=\"left\">Age</td><td align=\"left\">0.01</td><td align=\"left\">0.20†</td><td align=\"left\">0.004</td><td align=\"left\">0.08†</td></tr><tr><td align=\"left\">Male sex</td><td align=\"left\">-0.08</td><td align=\"left\">-0.07</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">BMI</td><td align=\"left\">-0.02</td><td align=\"left\">-0.12</td><td align=\"left\"/><td align=\"left\"/></tr><tr><td align=\"left\">NYHA functional class ≥ III</td><td align=\"left\">0.46</td><td align=\"left\">0.27†</td><td align=\"left\">0.456</td><td align=\"left\">0.25†</td></tr><tr><td align=\"left\">eGFR</td><td align=\"left\">-0.01</td><td align=\"left\">-0.39†</td><td align=\"left\">-0.007</td><td align=\"left\">-0.32†</td></tr><tr><td align=\"left\">LVEF</td><td align=\"left\">-0.01</td><td align=\"left\">-0.13†</td><td align=\"left\">-0.006</td><td align=\"left\">-0.11†</td></tr><tr><td align=\"left\">LVM index</td><td align=\"left\">0.01</td><td align=\"left\">0.31†</td><td align=\"left\">0.006</td><td align=\"left\">0.20†</td></tr><tr><td align=\"left\">Thoracic SMI</td><td align=\"left\">-0.02</td><td align=\"left\">-0.34†</td><td align=\"left\">-0.007</td><td align=\"left\">-0.25†</td></tr></tbody></table></table-wrap>", "<table-wrap id=\"Tab4\"><label>Table 4</label><caption><p>Associations of thoracic SMI and its components with primary outcomes in the study cohort</p></caption><table frame=\"hsides\" rules=\"groups\"><thead><tr><th align=\"left\">Variables</th><th align=\"left\">Patients without primary outcomes (n = 48)</th><th align=\"left\">Patients with primary outcomes (n = 195)</th><th align=\"left\">Unadjusted HR (95% CI)</th><th align=\"left\">Adjusted HR<sup>a</sup> (95% CI)</th></tr></thead><tbody><tr><td align=\"left\">Thoracic SMI, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">45.3 (37.3, 55.0)</td><td align=\"left\">40.1 (34.3, 47.9) <sup>b</sup></td><td align=\"left\">0.96 (0.94, 0.99) [0.01]</td><td align=\"left\">0.96 (0.92, 0.99) [0.01]</td></tr><tr><td align=\"left\">Pectoralis major index, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">11.0 (8.8, 14.3)</td><td align=\"left\">10.2 (8.1, 12.0) <sup>b</sup></td><td align=\"left\">0.87 (0.80, 0.95) [&lt; 0.01]</td><td align=\"left\">0.85 (0.75, 0.96) [&lt; 0.01]</td></tr><tr><td align=\"left\">pectoralis minor index, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">2.2 (1.6, 3.0)</td><td align=\"left\">2.2 (1.6, 2.7)</td><td align=\"left\">0.83 (0.61, 1.14) [0.25]</td><td align=\"left\">0.86 (0.60, 1.24) [0.42]</td></tr><tr><td align=\"left\">serratus anterior index, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">4.0 (3.3, 4.8)</td><td align=\"left\">4.0 (3.2, 4.9)</td><td align=\"left\">1.09 (0.89, 1.33) [0.40]</td><td align=\"left\">1.10 (0.90, 1.33) [0.37]</td></tr><tr><td align=\"left\">Periscapular index, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">20.7 (15.0, 27.3)</td><td align=\"left\">17.4 (13.7, 22.6) <sup>b</sup></td><td align=\"left\">0.95 (0.91, 0.99) [0.03]</td><td align=\"left\">0.94 (0.90, 0.99) [0.02]</td></tr><tr><td align=\"left\">Paraspinal index, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">4.4 ± 1.3</td><td align=\"left\">4.3 ± 1.2</td><td align=\"left\">0.89 (0.70, 1.13) [0.34]</td><td align=\"left\">0.85 (0.65, 1.12) [0.25]</td></tr><tr><td align=\"left\">Trapezius index, cm<sup>2</sup>/m<sup>2</sup></td><td align=\"left\">2.4 (2.0, 2.9)</td><td align=\"left\">2.3 (1.9, 2.8)</td><td align=\"left\">0.81 (0.53, 1.23) [0.33]</td><td align=\"left\">0.83 (0.51, 1.34) [0.44]</td></tr></tbody></table></table-wrap>" ]
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[ "<table-wrap-foot><p>Data are presented as mean ± SD, media (Q1, Q3) or number (percentage)</p><p>One-way analysis of variance test: * P-value &lt; 0.017 versus patients in the first tertile. † P-value &lt; 0.017 versus patients in the second tertile. Kruskal-Wallis test: &amp; P-value &lt; 0.05 versus patients in the first tertile. # P-value &lt; 0.05 versus patients in the second tertile. Chi-square test (Fisher’s exact test): § P-value &lt; 0.05 versus patients in the first tertile. λ P-value &lt; 0.05 versus patients in the second tertile</p><p>Abbreviations: SMI, skeletal muscle index; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate; HF, heart failure; NYHA, New York Heart Association; HT, hypertension; AF, atrial fibrillation; COPD, chronic obstructive pulmonary disease; LBBB, complete left bundle branch block; SAS, sleep apnea syndrome; NT-proBNP, amino-terminal pro-B-type natriuretic peptide; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HbA1C, glycated hemoglobin; TG, triglycerides; TC, cholesterol; HDL-C, high-density lipoprotein cholesterol content; LDL‑C, low-density lipoprotein cholesterol content. ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; SGLT-2i, sodium-glucose cotransporter-2 inhibitors; ARNI, angiotensin receptor-neprilysin inhibitor; CCB, calcium-channel blocker</p></table-wrap-foot>", "<table-wrap-foot><p>Data are presented as mean ± SD, media (Q1, Q3) or number (percentage)</p><p>One-way analysis of variance test: * P-value &lt; 0.017 versus patients in the first tertile. † P-value &lt; 0.017 versus patients in the second tertile. Kruskal-Wallis test: &amp; P-value &lt; 0.05 versus patients in the first tertile. # P-value &lt; 0.05 versus patients in the second tertile. Chi-square test (Fisher’s exact test): § P-value &lt; 0.05 versus patients in the first tertile</p><p>Abbreviations: SMI, skeletal muscle index; LVEDV, left ventricular end-diastolic volume; LVESV, left ventricular end-systolic volume; LVSV, left ventricular stroke volume; LVEF, left ventricular ejection fraction; LVM, left ventricular mass; MR, mitral regurgitation; LGE, late gadolinium enhancement</p></table-wrap-foot>", "<table-wrap-foot><p>Abbreviations: NT-proBNP, amino-terminal pro-B-type natriuretic peptide; BMI, body mass index; NYHA, New York Heart Association; eGFR, estimated glomerular filtration rate; LVEF, left ventricular ejection fraction; LVM, left ventricular mass; SMI, skeletal muscle index</p><p>† indicates P-value &lt; 0.05. NT-proBNP is log-transformed before being included in the regression analysis</p></table-wrap-foot>", "<table-wrap-foot><p>Data are presented as media (Q1, Q3) or mean ± SD. Data in brackets are P-values</p><p>Abbreviations: SMI, skeletal muscle index; HR, hazards ratio; CI, confidence interval; BMI, body mass index; SBP, systolic blood pressure; HF, heart failure; NT-proBNP, amino-terminal pro-B-type natriuretic peptide; eGFR, estimated glomerular filtration rate; SGLT-2i, sodium-glucose cotransporter-2 inhibitors; LVEF, left ventricular ejection fraction; LVM, left ventricular mass</p><p>a. Based on a multivariable Cox model adjusted for age, sex, BMI, SBP, etiology of HF (ischemic or not), NYHA functional class, NT-proBNP, eGFR, use of SGLT-2i, LVEF and LVM index</p><p>b. Mann-Whitney test: P-value &lt; 0.05</p></table-wrap-foot>", "<fn-group><fn><p><bold>Publisher’s Note</bold></p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></fn-group>" ]
[ "<graphic xlink:href=\"12933_2023_2109_Fig1_HTML\" id=\"d32e365\"/>", "<graphic xlink:href=\"12933_2023_2109_Fig2_HTML\" id=\"d32e817\"/>", "<graphic xlink:href=\"12933_2023_2109_Fig3_HTML\" id=\"d32e993\"/>", "<graphic xlink:href=\"12933_2023_2109_Fig4_HTML\" id=\"d32e1127\"/>" ]
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{ "acronym": [ "HF", "DM", "HFrEF", "LV", "NT-proBNP", "LVEF", "SSFP", "TE", "FA", "FOV", "TR", "LGE", "SMI", "EDV", "ESV", "SV", "LVM", "PS", "IQRs", "BMI", "eGFR" ], "definition": [ "heart failure", "diabetes mellitus", "heart failure with reduced ejection fraction", "left ventricular", "amino-terminal pro-B-type natriuretic peptide", "left ventricular ejection fraction", "steady-state free precession", "echo time", "flip angle", "field of view", "repetition time", "late gadolinium enhancement", "skeletal muscle index", "end-diastolic volume", "end-systolic volume", "stroke volume", "left ventricular mass", "peak strain", "interquartile ranges", "body mass index", "estimated glomerular filtration rate" ] }
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2024-01-14 23:43:47
Cardiovasc Diabetol. 2024 Jan 13; 23:28
oa_package/40/66/PMC10787494.tar.gz