Article(id=1242141943929581632, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242141088937485147, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2024.05.00467, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1698249600000, receivedDateStr=2023-10-26, revisedDate=1719676800000, revisedDateStr=2024-06-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1734105600000, onlineDateStr=2024-12-14, pubDate=1731427200000, pubDateStr=2024-11-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1734105600000, onlineIssueDateStr=2024-12-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774079317311, creator=sys-migrate, updateTime=1774079317311, updator=sys-migrate, issue=Issue{id=1242141088937485147, tenantId=1146029695717560320, journalId=1146031591421210625, year='2024', volume='42', issue='21', pageStart='1', pageEnd='188', issueExtLink='null', onlineDate='null', pubDate='1731427200000', pubDateStr='2024-11-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=null, issueType=-1, specialIssue=null, createTime=1774079113466, creator='sys-migrate', updateTime=1774079113466, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=94, endPage=101, ext={EN=ArticleExt(id=1242141948375543920, articleId=1242141943929581632, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Preliminary exploration of real world study and prescription validation based on traditional Chinese medicine clinical data of constipation, columnId=1242141098387252106, journalTitle=Science & Technology Review, columnName=Exclusive: The paradigm and application of clinical research in traditional Chinese medicine, runingTitle=null, highlight=null, articleAbstract=With the rapid advancement of medical informatization, clinical diagnostic and treatment data are becoming extensively available, providing a solid foundation for real world study.This study focuses on prescription compatibility patterns of constipation patients who have received traditional Chinese medicine (TCM) treatment at Yueyang Hospital of Integrated Traditional Chinese and Western Medicine affiliated to Shanghai University of Traditional Chinese Medicine over a 4-year period.Analyzing TCM prescription data from 16,416 constipation patients, the study aims to identify distinctive prescription patterns unique to the hospital.The identified core prescription is validated through randomized double-blind placebo-controlled trials and network pharmacology analysis.Clinical research demonstrates an overall effective rate of 77.78% for the core prescription, significantly surpassing the placebo group (33.33%).Network pharmacology analysis indicates that the core prescription may modulate biological pathways, including calcium ion signaling, MAPK signaling, cholinergic synapses, and GABAergic synapses.The results suggest that knowledge discovery techniques based on clinical data can uncover novel constipation treatments (Houpo, Laifuzi, Roucongrong, and Dafupi) that represent the hospital's characteristics and differ from commonly used traditional formulations.This study explores a research paradigm for summarizing clinical experience and provides a pathway for clinical knowledge discovery based on big data., authors=NI Yucheng¹, ZHU Xi¹, PAN Sizhe¹, ZHU Yu'nan¹, LIU Hua¹, LI Jiacheng², authorsList=NI Yucheng, ZHU Xi, PAN Sizhe, ZHU Yu'nan, LIU Hua, LI Jiacheng, authorCompany=1. Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China;
2. Nanjing University of Chinese Medicine Affiliated Suzhou Hospital of Traditional Chinese Medicine, Suzhou 215009, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242141947754786914, articleId=1242141943929581632, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=基于便秘中医临床数据的真实世界研究及处方验证, columnId=1242141097774883713, journalTitle=科技导报, columnName=专题：中医临床研究的范式与应用, runingTitle=null, highlight=null, articleAbstract=以上海中医药大学附属岳阳中西医结合医院4年内全体接受中医治疗的便秘患者处方配伍规律为研究对象，从16416例便秘患者的中医方药数据中挖掘医院特色的处方规律，并对核心处方从随机双盲安慰剂对照试验和网络药理学分析2方面进行验证。临床研究证明核心处方总有效率为77.78%，明显优于安慰剂组（33.33%）。网络药理学分析发现核心处方可能通过钙离子信号通路、MAPK信号通路、胆碱能突触和GABA能突触这4条通路发挥调控作用。结果表明，基于临床数据的知识发现技术能够挖掘出代表医院特征，与传统常用方剂不同的便秘治疗新处方（厚朴、莱菔子、肉苁蓉和大腹皮），为临床经验总结提供了一种研究模式的探索，为基于大数据的临床知识发现提供了一种路径。, authors=倪昱橙¹, 朱溪¹, 潘思哲¹, 朱雨楠¹, 刘华¹, 李家诚², authorsList=倪昱橙, 朱溪, 潘思哲, 朱雨楠, 刘华, 李家诚, authorCompany=1. 上海中医药大学附属岳阳中西医结合医院, 上海 200437;
2. 南京中医药大学苏州附属医院, 苏州 215009, correspAuthors=null, authorNote=倪昱橙，住院医师，研究方向为中医药防治肛肠疾病，电子信箱：nyczyy@126.com；刘华（通信作者），主任医师，研究方向为中医药防治肛肠疾病，电子信箱：yyliuhua@126.com；李家诚（共同通信作者），住院医师，研究方向为中西医结合防治肛肠疾病，电子信箱：lijiacheng@njucm.edu.cn, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=rsO1v1MkMsflBc1RAecO1Q==, pdfFileSize=2765550, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=上海医学创新发展基金会“未来计划”项目（WL-YBXN-2022002K）；上海市2022年度“科技创新行动计划”生物医药科技支撑专项（22S21901100）；上海市高级中西医结合人才培养项目（ZYSNXD012-RC-ZXY012）；上海中医药大学研究生创新创业能力培养项目（Y2020071）)}, authors=null, keywords=[Keyword(id=1242141946827842472, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242141943929581632, language=CN, orderNo=1, keyword=临床数据挖掘), 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