基于现代文献的绝经期关节炎用药规律研究  被引量:2

Rule Study of Menopausal Arthritis Based on Modern Literature

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作  者:黄彦新[1] 刘荣 

机构地区:[1]深圳平乐骨伤科医院,广东深圳518000 [2]广州中医药大学第一附属医院,广东广州510600

出  处:《新中医》2018年第1期138-142,共5页New Chinese Medicine

基  金:广东省自然科学基金项目(2014A030310051)

摘  要:目的:探讨绝经期关节炎的中医辨证用药规律。方法:检索中国知识资源总库(CNKI)、中国生物医学文献数据库(CBM)、Pub Med等数据库,收集中医辨证论治绝经期关节炎的相关文献,提取症状、处方信息构建绝经期关节炎医案数据库,采用频数分析、隐结构模型、频繁项集等数据挖掘方法,分析绝经期关节炎的辨证用药规律。结果:共纳入医案604则,得出医案中高频症状16项,建立绝经期关节炎证候隐结构模型;统计出高频处方、治法与药物,挖掘症状-药味、药味组合频繁项集各8项。结论:中医治疗绝经期关节炎多以补益气血肝肾、散寒除湿为法,常用处方以补中桂枝汤、二仙汤、红花桃仁煎为主,其相关规律可为临床治疗绝经期关节炎提供参考。Objective: To explore the administration rule of Chinese medicine in treating menopausal arthritis.Methods:China National Knowledge Infrastructure(CNKI),Chinese Biological Medical Disc(CBM),PubMed,and other databases were searched to collect related literature about the differentiation and treatment of menopausal arthritis.Symptoms and prescriptions were extracted to establish a database with cases of menopausal arthritis.Data mining methods such as frequency analysis,latent structure models,and frequent itemset were employed to analyze the administration rule of Chinese medicine in treating menopausal arthritis.Results:A total of 604 medical cases were selected into the study and 16 cases of high frequency symptoms were found in the medical cases.A latent structure model of menopausal arthritis syndrome was established.There were respectively 8 kinds being found in high frequency prescriptions,treatment and medicine,mining symptoms-flavour of medicine,and frequent itemset of flavour of medicine combination.Conclusion: The treatment of Chinese medicine for menopausal arthritis is mostly based on methods such as tonifying qi,blood,liver and kidney,as well as dispelling cold and removing dampness.Commonly used Chinese medicine prescriptions for the disease include Buzhong Guizhi tang,Erxian tang and Honghua Taoren tang.Both the aforesaid methods and prescriptions can provide references for the clinical treatment of menopausal arthritis.

关 键 词:关节炎 绝经期 用药规律 隐结构模型 频繁项集 数据挖掘 

分 类 号:R684.3[医药卫生—骨科学]

 

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