OBJECTIVE:To develop an expert consensus on kidney deficiency syndrome(KDS)in pregnant women and construct a validated self-reported KDS Patient-Reported Measures Pregnancy Scale(KDS-PRMs-Pregnancy Scale)for early ide...OBJECTIVE:To develop an expert consensus on kidney deficiency syndrome(KDS)in pregnant women and construct a validated self-reported KDS Patient-Reported Measures Pregnancy Scale(KDS-PRMs-Pregnancy Scale)for early identification and management.METHODS:The study was conducted in three phases.First,a comprehensive review of Traditional Chinese Medicine(TCM)literature and diagnostic criteria was performed,generating initial KDS symptoms for pregnancy.Second,a two-round Delphi survey,involving 21 experts from TCM,obstetrics,and gynaecology,assessed importance,relevance,and appropriateness of the items.Third,a psychometric evaluation was conducted,including exploratory factor analysis and internal consistency assessment.RESULTS:In the first Delphi round,19 items were flagged for revision or removal due to expert variability,with 12 items deemed irrelevant.In the second round,consensus was reached,resulting in a 25-item scale.After psychometric evaluation,seven items were removed due to poor factor loadings,leaving an 18-item scale.Three factors—physiological discomfort,fatigue&weakness,and excretion abnormalities—accounted for 78.4%of the variance.The final scale demonstrated excellent internal consistency(Cronbach's alpha=0.959).CONCLUSION:The validated 18-item KDS-PRMsPregnancy Scale is a reliable tool for assessing KDS in pregnant women.Future research should focus on validation in diverse populations and exploring its predictive validity for pregnancy outcomes.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
Objective To develop a quality appraisal tool for case reports in traditional Chinese medicine(TCM)based on their characteristics.Methods An extensive literature search was conducted in Chinese Biomedical Literature D...Objective To develop a quality appraisal tool for case reports in traditional Chinese medicine(TCM)based on their characteristics.Methods An extensive literature search was conducted in Chinese Biomedical Literature Database(CBM),China National Knowledge Infrastructure(CNKI),and China Science and Technology Journal Database(CSTJ),focusing on expert consensus statements and check-lists for TCM case reports.Relevant items were extracted,and a Delphi method involving 34 experts was used in two rounds to rate each item on a 5-point Likert scale.Items were screened based on measures of central tendency and coordination(including total score,mean score,percentage of items rated as unimportant,and coefficient of variation).The weighted average method was used to determine item weights and construct the appraisal tool.Internal consistency was assessed using Cronbach’sαcoefficient.The finalized tool was pilot-tested by two reviewers independently appraising 20 case reports,with an additional four reviewers evaluating 5 of these cases to compare inter-rater consistency.Results A total of 9513 articles were retrieved,and 96 items from 25 articles were extracted.After two rounds of the Delphi method,27 items across 10 domains were retained.The Cron-bach’sαcoefficient was 0.72 in the first round(acceptable range),and 0.96 in the second round,indicating strong internal consistency.The tool was piloted by six reviewers,achieving a kappa value of 0.663 and a Kendall’s coefficient of concordance of 0.845,demonstrating high consistency among reviewers.Conclusion The developed TCM case report quality appraisal tool,consisting of 27 items in 10 domains,offers a scientific and reliable means of assessing the quality of TCM case reports.The tool showed high consistency and practical utility,and its application is expected to en-hance the standardization,scientific rigor,and evidence quality of TCM case reports,facilitat-ing the integration of traditional medical knowledge with modern evidence-based standards.展开更多
目的构建重症创伤伤员体外膜肺氧合(ECMO)转运方案,为重症创伤伤员ECMO转运提供参考。方法基于循证原则检索建库至2024年9月16日ProVation MD、BMJ Best Practice、UpToDate、英国国家卫生与临床优化研究所、国际指南协作网、美国国立...目的构建重症创伤伤员体外膜肺氧合(ECMO)转运方案,为重症创伤伤员ECMO转运提供参考。方法基于循证原则检索建库至2024年9月16日ProVation MD、BMJ Best Practice、UpToDate、英国国家卫生与临床优化研究所、国际指南协作网、美国国立指南库、WHO、Embase、Cochrane Library、PubMed、Web of Science、CKNI、中国生物医学数据库、维普数据库、万方数据库、医脉通等网站或数据库形成范围综述并构建重症创伤伤员ECMO转运方案初稿。通过2轮Delphi专家咨询法对18名专家函询,小组讨论后形成重症创伤伤员ECMO转运方案终稿。结果共纳入16篇文献,形成了包含人力分工、注意事项等在内的7项一级条目、20项二级条目、67项三级条目的重症创伤伤员ECMO转运方案。2轮函询的有效回收率均为94.4%,专家的权威系数均为0.94,专家意见的Kendall协调系数分别为0.310和0.489(P均<0.01)。结论本研究基于范围综述和Delphi法构建重症创伤伤员ECMO转运方案,形成了以重症创伤ECMO转运的常用模式、工具载体、人力分工、准备工作、监测、注意事项、交接核查为主题的转运方案,对重症创伤伤员具有较强的针对性与临床应用价值,可以为重症创伤伤员ECMO转运提供参考。展开更多
基金Supported by the National Natural Science Foundation of China:to Explore the Intergenerational Effects of Bu-Shen-Tian-Jing Therapeutic Principle on the Offspring of Hyper-Androgenic Polycystic Ovary Syndrome Based on Regulating Rhythmic Iron Death in the Ovarian Granulosa Cells Mediated by Fos Proto-OncogeneRetinoic Acid Receptor-Related Orphan Receptor A-Solute Carrier Family 7 Member 11(No.82274564)the National Natural Science Foundation of China:the Underlying Mechanism of Bu-Shen-Jian-Pi Therapeutic Principle in Regulating Ovarian Granulosa Cells Autophagy Mediated by Short-chain Fatty Acids-forkhead Box O1 Pathway and its Effects on the Development of Offspring of Polycystic Ovary Syndrome(No.82074476)the Open Fund Project of Zhejiang Key Laboratory of Maternal and Infant Health,Women’s Hospital,School of Medicine,Zhejiang University:Mediating Role of Kidney Deficiency in the Relationship between Fear of Childbirth and Delivery Modes:an Exploratory Investigation Grounded in the Classic Traditional Chinese Medicine Theories of“Fear Injuring Kidney”and“Kidney Storing Essence”(No.ZDFY2024-MI-2)。
文摘OBJECTIVE:To develop an expert consensus on kidney deficiency syndrome(KDS)in pregnant women and construct a validated self-reported KDS Patient-Reported Measures Pregnancy Scale(KDS-PRMs-Pregnancy Scale)for early identification and management.METHODS:The study was conducted in three phases.First,a comprehensive review of Traditional Chinese Medicine(TCM)literature and diagnostic criteria was performed,generating initial KDS symptoms for pregnancy.Second,a two-round Delphi survey,involving 21 experts from TCM,obstetrics,and gynaecology,assessed importance,relevance,and appropriateness of the items.Third,a psychometric evaluation was conducted,including exploratory factor analysis and internal consistency assessment.RESULTS:In the first Delphi round,19 items were flagged for revision or removal due to expert variability,with 12 items deemed irrelevant.In the second round,consensus was reached,resulting in a 25-item scale.After psychometric evaluation,seven items were removed due to poor factor loadings,leaving an 18-item scale.Three factors—physiological discomfort,fatigue&weakness,and excretion abnormalities—accounted for 78.4%of the variance.The final scale demonstrated excellent internal consistency(Cronbach's alpha=0.959).CONCLUSION:The validated 18-item KDS-PRMsPregnancy Scale is a reliable tool for assessing KDS in pregnant women.Future research should focus on validation in diverse populations and exploring its predictive validity for pregnancy outcomes.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
基金General Program of National Natural Science Foundation of China (82274412)Natural Science Foundation of Hunan Province (2020JJ4062)Science and Technology Innovation Program of Hunan Province (2020RC2061)。
文摘Objective To develop a quality appraisal tool for case reports in traditional Chinese medicine(TCM)based on their characteristics.Methods An extensive literature search was conducted in Chinese Biomedical Literature Database(CBM),China National Knowledge Infrastructure(CNKI),and China Science and Technology Journal Database(CSTJ),focusing on expert consensus statements and check-lists for TCM case reports.Relevant items were extracted,and a Delphi method involving 34 experts was used in two rounds to rate each item on a 5-point Likert scale.Items were screened based on measures of central tendency and coordination(including total score,mean score,percentage of items rated as unimportant,and coefficient of variation).The weighted average method was used to determine item weights and construct the appraisal tool.Internal consistency was assessed using Cronbach’sαcoefficient.The finalized tool was pilot-tested by two reviewers independently appraising 20 case reports,with an additional four reviewers evaluating 5 of these cases to compare inter-rater consistency.Results A total of 9513 articles were retrieved,and 96 items from 25 articles were extracted.After two rounds of the Delphi method,27 items across 10 domains were retained.The Cron-bach’sαcoefficient was 0.72 in the first round(acceptable range),and 0.96 in the second round,indicating strong internal consistency.The tool was piloted by six reviewers,achieving a kappa value of 0.663 and a Kendall’s coefficient of concordance of 0.845,demonstrating high consistency among reviewers.Conclusion The developed TCM case report quality appraisal tool,consisting of 27 items in 10 domains,offers a scientific and reliable means of assessing the quality of TCM case reports.The tool showed high consistency and practical utility,and its application is expected to en-hance the standardization,scientific rigor,and evidence quality of TCM case reports,facilitat-ing the integration of traditional medical knowledge with modern evidence-based standards.
文摘目的构建重症创伤伤员体外膜肺氧合(ECMO)转运方案,为重症创伤伤员ECMO转运提供参考。方法基于循证原则检索建库至2024年9月16日ProVation MD、BMJ Best Practice、UpToDate、英国国家卫生与临床优化研究所、国际指南协作网、美国国立指南库、WHO、Embase、Cochrane Library、PubMed、Web of Science、CKNI、中国生物医学数据库、维普数据库、万方数据库、医脉通等网站或数据库形成范围综述并构建重症创伤伤员ECMO转运方案初稿。通过2轮Delphi专家咨询法对18名专家函询,小组讨论后形成重症创伤伤员ECMO转运方案终稿。结果共纳入16篇文献,形成了包含人力分工、注意事项等在内的7项一级条目、20项二级条目、67项三级条目的重症创伤伤员ECMO转运方案。2轮函询的有效回收率均为94.4%,专家的权威系数均为0.94,专家意见的Kendall协调系数分别为0.310和0.489(P均<0.01)。结论本研究基于范围综述和Delphi法构建重症创伤伤员ECMO转运方案,形成了以重症创伤ECMO转运的常用模式、工具载体、人力分工、准备工作、监测、注意事项、交接核查为主题的转运方案,对重症创伤伤员具有较强的针对性与临床应用价值,可以为重症创伤伤员ECMO转运提供参考。
