Journal of Clinical Epidemiology最新文献

{"title":"Handling conflicts of interest concerns more than transparency","authors":"Lex M. Bouter","doi":"10.1016/j.jclinepi.2025.111801","DOIUrl":"10.1016/j.jclinepi.2025.111801","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"182 ","pages":"Article 111801"},"PeriodicalIF":7.3,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting obstetric anal sphincter injury in the first and second vaginal delivery and after a cesarean delivery: development and validation of an intrapartal model","authors":"Jennie Larsudd-Kåverud ,&nbsp;Sigvard Åkervall ,&nbsp;Mattias Molin ,&nbsp;Ida EK. Nilsson ,&nbsp;Ewout W. Steyerberg ,&nbsp;Ian Milsom ,&nbsp;Maria Gyhagen","doi":"10.1016/j.jclinepi.2025.111782","DOIUrl":"10.1016/j.jclinepi.2025.111782","url":null,"abstract":"<div><h3>Objectives</h3><div>To develop and validate prediction models for obstetric anal sphincter injury (OASI) in three birth scenarios (1st vaginal delivery, vaginal birth after cesarean section and 2nd vaginal delivery). Antenatal and intrapartal predictors were included in the models to construct a web-based, interactive, easy-to-use calculator.</div></div><div><h3>Study design and setting</h3><div>All 45 maternity units in Sweden participated in the study, with 609,916 first and second deliveries in gestational week ≥37+0 with singleton pregnancies and cephalic presentations between 2009 and 2017. The outcome was OASI, defined as a third- or fourth-degree perineal injury involving the external or internal anal sphincter muscles, or both. We analyzed the relative contribution of predictors with Nagelkerke´s R² (<em>R</em>²_N) after minimization of the Bayesian Information Criterion for the predictor selection in a logistic regression with OASI as the binary outcome. Model performance was evaluated according to overall measures, discriminative ability, and calibration, with optimism-correction by a bootstrap procedure.</div></div><div><h3>Results</h3><div>OASI occurred in 25,245 women (4.1%). There were 54 relevant, possible predictors, and 47 predictors were kept as candidates for the final models. We included 28, 40, and 46 predictors for the 3 scenarios, respectively. Infant birth weight was identified as the primary predictor, contributing 31% to 45% of the R²_N in the full prediction models, which had R²_N values of 9.3%, 7.4%, and 12.9% for each scenario. In 2-para women, obstetric information from the first birth was important at the 2nd birth, accounting for 50% of the total predictive information. A sphincter injury in the 1st vaginal delivery strongly predicted a repeat injury (<em>R</em>²_N, 40%). Vacuum delivery in the first and second vaginal delivery contributed 33 and 29% of <em>R</em>²_N, respectively. By incorporating information on fetal biometry and labor events, the performance of the models increased substantially (e.g. <em>R</em>²_N increased from 1.7 to 9.3% in the first scenario). An online calculator was developed (<span><span>www.sphinctercalc.com</span><svg><path></path></svg></span>).</div></div><div><h3>Conclusions</h3><div>Fetal birth weight is the crucial predictor of sphincter injury, supporting efforts to assess fetal biometrics through imaging techniques. This also applies to obstetric interventions, particularly vacuum delivery, provided that there are alternatives to act upon. The proposed online calculator requires further international validation and refinement before it can be widely used clinically and for women's shared decision-making.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"183 ","pages":"Article 111782"},"PeriodicalIF":7.3,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143905962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gaps in completeness of reporting and methodological quality: a metaresearch study of 139 network meta-analyses published in January 2023 using PRISMA-NMA and AMSTAR-2","authors":"Silvia Gianola ,&nbsp;Stefania Guida ,&nbsp;Gaia Ravot ,&nbsp;Carole Lunny ,&nbsp;Silvia Bargeri ,&nbsp;Greta Castellini","doi":"10.1016/j.jclinepi.2025.111783","DOIUrl":"10.1016/j.jclinepi.2025.111783","url":null,"abstract":"<div><h3>Objectives</h3><div>Network meta-analysis (NMA) is a method for comparing multiple interventions simultaneously, combining evidence to estimate and rank their relative effectiveness and safety across a network of studies. This study evaluates (i) epidemiological and descriptive characteristics, (ii) reporting completeness, and (iii) methodological quality of NMAs.</div></div><div><h3>Study Design and Setting</h3><div>In this metaresearch study (protocol at <span><span>https://osf.io/pa6dz/</span><svg><path></path></svg></span>), we searched PubMed for systematic reviews with NMAs indexed in January 2023. We extracted epidemiological and descriptive data, assessed reporting completeness using the modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for NMA, and evaluated the methodological quality using A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2).</div></div><div><h3>Results</h3><div>Among the 139 NMAs, 77% were published in specialty journals (median journal impact factor [JIF] 4), and 52% originated from China. Reporting completeness and methodological quality were generally of a medium quality, with the median NMAs fulfilling 71% of the modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Network Meta-Analyses (PRISMA-NMA) and 63% of the AMSTAR-2 criteria. Items such as “network geometry” for modified PRISMA-NMA (15%) and “list of excluded studies” for AMSTAR-2 (12%) were frequently unfulfilled. Better reporting and methodological quality were associated with registered protocol, non-Chinese country, higher JIF, and larger author teams.</div></div><div><h3>Conclusion</h3><div>We highlight gaps in both reporting and methodological quality in NMAs. We recommend future authors to plan and conduct NMAs within a large author team that includes statistical experts and to strictly adhere to reporting and methodological quality standards. More attention should be given to the reporting of network geometry and documenting the list of excluded studies.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"183 ","pages":"Article 111783"},"PeriodicalIF":7.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reporting the involvement of patients and caregivers in identifying and designing healthcare interventions: the IDEAS framework","authors":"Javier Recabarren Silva ,&nbsp;Rebecca Wu ,&nbsp;Nicole Scholes-Robertson ,&nbsp;Anastasia Hughes ,&nbsp;Anita van Zwieten ,&nbsp;Germaine Wong ,&nbsp;Amanda Sluiter ,&nbsp;Andrea K. Viecelli ,&nbsp;Jonathan C. Craig ,&nbsp;Stephen McDonald ,&nbsp;David J. Tunnicliffe ,&nbsp;Armando Teixeira-Pinto ,&nbsp;Siah Kim ,&nbsp;Carmel M. Hawley ,&nbsp;Allison Jaure","doi":"10.1016/j.jclinepi.2025.111784","DOIUrl":"10.1016/j.jclinepi.2025.111784","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background and Objective&lt;/h3&gt;&lt;div&gt;Patient and caregiver involvement can optimize the relevance and uptake of research. However, there is little guidance on approaches for reporting the involvement of patients and caregivers in the identification and design of health care interventions. This study aims to develop a reporting framework for involving patients and caregivers in identifying and designing health care interventions to improve transparency in the approaches used.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;Electronic literature databases were extensively searched for guidelines, frameworks, reviews, and primary studies that reported patient and caregiver involvement in interventions; studies identified up to April 2024 were identified. A comprehensive list of reporting items was inductively developed. The IDEntifying And designing healthcare interventionS (IDEAS) framework was piloted with a diverse range of primary studies that reported patient and caregiver involvement in interventions.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Nineteen secondary studies (eg, guidelines, frameworks, and reviews) and 41 primary studies were used to develop the reporting items for the IDEAS framework. The IDEAS framework includes 14 reporting items that cover five domains: purpose (ie, role of patients or caregivers, type and scope of interventions, criteria considered eg, acceptability, feasibility); theory or framework used; population (ie, inclusion criteria, identification and selection, and characteristics); mode of involvement (ie, process of involvement, frequency, duration, and reimbursement); and output and impact. Each reporting item includes a descriptor and examples.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;The IDEAS framework can help ensure transparency in describing the process of reporting patients and caregivers in identifying and designing health care interventions. Ultimately, this may support the design of interventions that address the needs, preferences and priorities of patients and caregivers.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Plain Language Summary&lt;/h3&gt;&lt;div&gt;Patient and caregiver involvement in identifying and designing health care interventions can help improve acceptability, uptake, and impact of interventions. However, there is little guidance that addresses the reporting of the involvement of patients and caregivers in developing health care interventions. We carried out a detailed search for guidelines, frameworks, and primary studies to develop the reporting of the involvement of patients and caregivers in IDEentifying And designing healthcare interventionS (IDEAS) framework. The IDEAS framework consists of 14 reporting items that cover five domains: the purpose of involvement, the theory or framework used, the population of patients and caregivers who were involved, mode of involvement (ie, process of involvement), and output and impact. The IDEAS framework can be used to describe the involvement of patients and caregivers in identifying and","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"183 ","pages":"Article 111784"},"PeriodicalIF":7.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143905963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Author's reply: letter to the editor regarding the paper “How the PICAR framework can benefit guideline systematic reviews: a call for greater attention”","authors":"Amy Johnston,&nbsp;Shannon E. Kelly,&nbsp;George A. Wells","doi":"10.1016/j.jclinepi.2025.111780","DOIUrl":"10.1016/j.jclinepi.2025.111780","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"182 ","pages":"Article 111780"},"PeriodicalIF":7.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143881880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sample size and geographical region predict effect heterogeneity in psychotherapy research for depression: a meta-epidemiological study","authors":"Paula Kuper ,&nbsp;Clara Miguel ,&nbsp;Pim Cuijpers ,&nbsp;Christian Apfelbacher ,&nbsp;Claudia Buntrock ,&nbsp;Eirini Karyotaki ,&nbsp;Antonia A. Sprenger ,&nbsp;Mathias Harrer","doi":"10.1016/j.jclinepi.2025.111779","DOIUrl":"10.1016/j.jclinepi.2025.111779","url":null,"abstract":"<div><h3>Objectives</h3><div>Depression is a very prevalent and burdensome disease, for which the efficacy of psychological treatments has been extensively studied in randomized controlled trials (RCTs). Meta-analytic evidence in this field is often heavily limited due to heterogeneity, meaning a broad dispersion of true treatment effects and high uncertainty when predicting future outcomes. Causes for this heterogeneity are largely unclear, and cannot be directly examined using conventional meta-analytic methods. Using newly introduced location-scale models, this study is the first to examine direct predictors of between-study heterogeneity in depression psychotherapy trials.</div></div><div><h3>Study Design and Setting</h3><div>We used a large meta-analytic database containing RCTs on the efficacy of depression psychotherapy. We included studies in all age groups, comparing psychotherapy to control conditions. Risk of bias (RoB) was assessed with the “Cochrane Collaboration Risk of Bias Tool” (Version 1). Univariate analyses were used to explore associations of study-level variables with treatment effect heterogeneity, and multimodel selection to investigate the predictive effect of all variables simultaneously.</div></div><div><h3>Results</h3><div>We included 539 RCTs with 607 comparisons, with 35% showing low overall RoB. Higher heterogeneity was found in studies with high RoB and lower sample sizes; heterogeneity varied depending on the geographical region where trials were conducted. Based on multimodel selection, the most important predictors of effect heterogeneity were geographical region, baseline sample size, and RoB. These predictors were also significant after model averaging.</div></div><div><h3>Conclusion</h3><div>Our study shows that several study-level variables predict the heterogeneity of treatment effects in psychotherapy research, and thus their predictability across different contexts. To enhance the robustness of pooled effects, meta-analysts may consider restricting their synthesis to methodologically rigorous studies only. Our findings also indicate that the assumption of constant heterogeneity in “traditional” random-effects analyses might often be violated, making sensitivity analyses imperative.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"183 ","pages":"Article 111779"},"PeriodicalIF":7.3,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing major comorbidity indices as predictors of all-cause mortality in the Veterans Affairs health care system","authors":"Hind A. Beydoun ,&nbsp;Dorota Szymkowiak ,&nbsp;May A. Beydoun ,&nbsp;Neil Nixdorff ,&nbsp;Robert Brunner ,&nbsp;Jack Tsai","doi":"10.1016/j.jclinepi.2025.111778","DOIUrl":"10.1016/j.jclinepi.2025.111778","url":null,"abstract":"<div><h3>Objectives</h3><div>The Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Index (ECI), and the Functional Comorbidity Index (FCI) are validated clinical measures of comorbidity, but direct comparisons between these measures have rarely been studied especially in high-risk patient populations, such as homeless individuals. The US Department of Veterans Affairs (VA) offers large patient samples to compare these comorbidity measures as predictors of mortality using administrative and clinical records. We examined CCI, ECI, and FCI scores among veterans seeking VA healthcare services, including those experiencing homelessness, and compared their predictive value in relation to all-cause mortality risk.</div></div><div><h3>Study Design and Setting</h3><div>Several VA databases from 2017 to 2021 were retrospectively linked, and 4,701,711 U S. veterans [308,553 with homelessness and 4,393,158 without homelessness] were evaluated over a median follow-up of 4.1 years, yielding 917,921 recorded deaths. Regression models were constructed, and Harrell's Concordance Statistic (HCS) was calculated that assessed the ability of z-transformed comorbidity scores to discriminate “high-risk” vs “low-risk” groups of patients for mortality risk, after adjustment for demographic and clinical characteristics.</div></div><div><h3>Results</h3><div>In adjusted models, ECI (HCS: 0.76–0.77) and CCI (HCS: 0.75–0.76) were better able to discriminate “high-risk” vs “low-risk” groups than FCI (HCS: 0.72–0.75) among homeless and nonhomeless veterans. Compared to ECI and CCI, FCI was more strongly associated with homelessness.</div></div><div><h3>Conclusion</h3><div>CCI and ECI may be more predictive of all-cause mortality risk than FCI, although FCI may be a useful measure of functioning in homeless populations.</div></div><div><h3>Plain Language Summary</h3><div>The CCI, ECI, and FCI are clinical measures of comorbidity, but their direct comparisons have been limited, especially in high-risk patient populations like homeless individuals. This study examined CCI, ECI, and FCI scores among veterans seeking health care services at the US Department of Veterans Affairs and found that ECI and CCI were better at discriminating high-risk vs low-risk groups and predicting mortality among homeless and nonhomeless veterans.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"182 ","pages":"Article 111778"},"PeriodicalIF":7.3,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How should we assess trustworthiness of randomized controlled trials?","authors":"Jack Wilkinson ,&nbsp;David Tovey","doi":"10.1016/j.jclinepi.2025.111670","DOIUrl":"10.1016/j.jclinepi.2025.111670","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111670"},"PeriodicalIF":7.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to ʻMethodological systematic review recommends improvements to conduct and reporting when meta-analyzing interrupted time series studies’. Journal of Clinical Epidemiology 145 (2022) 55–69","authors":"Elizabeth Korevaar ,&nbsp;Amalia Karahalios ,&nbsp;Simon L. Turner ,&nbsp;Andrew B. Forbes ,&nbsp;Monica Taljaard ,&nbsp;Allen C. Cheng ,&nbsp;Jeremy M. Grimshaw ,&nbsp;Lisa Bero ,&nbsp;Joanne E. McKenzie","doi":"10.1016/j.jclinepi.2025.111706","DOIUrl":"10.1016/j.jclinepi.2025.111706","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111706"},"PeriodicalIF":7.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143450901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seven principles for integrating health equity considerations in the practice guideline enterprise","authors":"Omar Dewidar ,&nbsp;Andrea J. Darzi ,&nbsp;Shahab Sayfi ,&nbsp;Jordi Pardo Pardo ,&nbsp;Vivian Welch ,&nbsp;Grace C. Wright ,&nbsp;Elie A. Akl ,&nbsp;Joanne Khabsa ,&nbsp;Jennifer S. Lin ,&nbsp;Rebecca L. Morgan ,&nbsp;Kevin Pottie ,&nbsp;Janice Tufte ,&nbsp;Jana Khawandi ,&nbsp;Xiaoqin Wang ,&nbsp;Oyekola Oloyede ,&nbsp;Tamara Lotfi ,&nbsp;Xiaomei Yao ,&nbsp;Ana Carolina Pereira Nunes Pinto ,&nbsp;Yuan Chi ,&nbsp;Reem A. Mustafa ,&nbsp;Peter Tugwell","doi":"10.1016/j.jclinepi.2025.111777","DOIUrl":"10.1016/j.jclinepi.2025.111777","url":null,"abstract":"<div><h3>Background and Objectives</h3><div>Health equity aims to provide all individuals with equal and fair opportunities to achieve optimal health. Practice guidelines can play a pivotal role in advancing health equity; yet, few organizations use tools to systematically integrate health equity considerations. Thus, it is important to establish a foundation for practical tools to support the systematic integration of health equity considerations. This manuscript proposes principles for the integration of health equity considerations in the practice guideline enterprise.</div></div><div><h3>Methods</h3><div>In the process of developing an equity extension for the GIN-McMaster guideline development checklist, we established a diverse advisory group of guideline developers, patients, members of the public experiencing inequities, health equity researchers, and guideline developers. We formulated the principles informed by a methodological review of guideline handbooks and iterative discussions between working group members.</div></div><div><h3>Results</h3><div>We identified the following seven principles for integrating health equity considerations into the practice guideline enterprise: (1) articulating health equity, (2) a priori planning for considering health equity, (3) selection and engagement of individuals with lived experiences of inequities, (4) equity in evidence synthesis, (5) developing equity-informed recommendations, (6) inclusive knowledge mobilization, and (7) evaluating the impact of health equity considerations. We elaborated on the importance of the principles using published examples and mapped them to the different phases of the guideline development process.</div></div><div><h3>Conclusion</h3><div>Guideline developers should adhere to these principles in the development of guidelines and health equity guideline development and appraisal tools. These principles are the foundational concepts for developing health equity extension items for the GIN-McMaster guideline development checklist.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"182 ","pages":"Article 111777"},"PeriodicalIF":7.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}