摘要
目的基于数据挖掘技术研究古代中药复方治疗肺痨的用药规律。方法选取中华医典5.0系统中治疗肺痨的处方,利用Excel 2010软件建立肺痨处方数据库,并使用统计软件IBM SPSS Statistics 23及数据挖掘软件IBM SPSS Modeler 15.0对数据进行频数分析、聚类分析、因子分析、关联规则分析。结果共纳入749首肺痨治疗处方,中药种类合计475味,排列在前10味的高频药物分别为:甘草、人参、茯苓、当归、芍药、麦冬、生姜、白术、柴胡、生地黄。中药类别中占据前5类的是:补虚药、清热药、化痰止咳平喘药、解表药、(健脾)利湿药。高频药物间生成4个聚类分析结果,因子分析中提取12个公因子,经关联规则分析,设置最低条件支持度≥8%,最小规则置信度≥72%,提升度>1,得出关联规则8条,3味药配伍关联规则29条,4味药配伍关联规则11条。结论通过对中华医典的挖掘,客观呈现古代医家治疗肺痨的组方用药经验,为现代临床用药指导提供理论借鉴。
Objective To study the drug use of ancient Chinese herbal compound in the treatment of tuberculosis based on data mining technology.Methods The prescription of the treatment of tuberculosis in the Chinese Medical Code 5.0 system was selected,The database of tuberculosis prescription was established by using Excel 2010 software,and the frequency analysis of the data was carried out by using the statistical software IBM SPSS Statistics 23 and the data mining software IBM SPSS Modeler 15.0,Clustering analysis,the factor analysis,association rule analysis.Results A total of 749 tuberculosis treatment prescriptions were included,The total number of traditional Chinese medicines was475,the top 10 high-frequency drugs were:Licorice,Ginseng,Poria,Angelica,Peony,Mai Dong,Ginger,Atractylodes,Bupleurum,Rehmannia.The category of traditional Chinese medicine occupies the top 5 categories are:Tonic medicine,antipyretic medicine,Phlegm cough and asthma medicine,Solution medicine,and dampness medicine.4 Cluster analysis results were generated between high-frequency drugs.12 common factors were extracted from factor analysis.Through the Analysis of association rules,set the minimum condition support degree≥8%,the minimum rule confidence≥72%,the lifting degree>1,obtains the association rule 8,3 taste Drug Compatibility Association rule 29,4 flavor Medicine Compatibility Association rule 11.Conclusion The experience of the treatment of tuberculosis in ancient doctors is objectively presented,which provides reference for the guidance of modern clinical drug use.
作者
陈小丽
许光兰
赵媚
王光耀
吴红英
陈青蓝
明春玉
Chen Xiaoli;Xu Guanglan;Zhao Mei;Wang Guangyao;Wu Hongying;Chen Qinglan;Ming Chunyu(Graduate School of Guangxi University of Traditional Chinese Medicine,Nanning,530001,China;The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine,Nanning,530023,China)
出处
《世界科学技术-中医药现代化》
CSCD
北大核心
2020年第7期2285-2293,共9页
Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology
基金
国家自然科学基金委员会地区科学基金项目(81760848):清金化痰汤对AECOPD痰热郁肺型大鼠气道上皮细胞自噬作用机制的研究,负责人:许光兰
国家自然科学基金委员会地区科学基金项目(81360534):探讨JAK/STAT通路调控慢性阻塞性肺疾病急性加重期(痰热阻肺)大鼠气道炎症及清金化痰颗粒干预实验研究,负责人:许光兰
关键词
肺痨
数据挖掘
用药规律
聚类分析
Tuberculosis
Data mining
Medication rule
Cluster analysis
作者简介
通讯作者:许光兰,主任医师,硕士生导师,主要研究方向:中西医结合呼吸系统疾病的基础与临床研究。
