胃脘痛证候的聚类分析及因子分析研究  

Study on Syndromes of Epigastric Pain by Cluster Analysis and Factor Analysis

作　　者：唐伟[1] 张炳秀[1] 张文东[1] 马燕[1] 王欢欢[1] 

机构地区：[1]安徽省六安市中医院,安徽六安237006

出　　处：《安徽中医学院学报》2012年第6期35-37,共3页Journal of Anhui Traditional Chinese Medical College

摘　　要：目的采用聚类分析及因子分析的数据挖掘方法,对胃脘痛的中医临床证候及四诊信息进行研究。方法收集640例755诊次胃脘痛病例,记录症状、舌象和脉象等临床资料,对临床资料进行聚类分析及因子分析。结果胃脘痛临床证候可分为六类:脾胃虚寒、肝气犯胃、湿热中阻、脾胃气虚、痰湿内蕴、瘀血停胃,每一类证候对应贡献率不同的特异的四诊信息。结论胃脘痛有特异的证候分类及四诊信息,通过数据挖掘方法深入研究,对胃脘痛的规范化诊断提供了有效的数据支持,能提高辨证准确性。Objective To study the traditional Chinese medicine （TCM） syndromes of epigastric pain and their information acquired by four TCM diagnostic methods by data mining （cluster analysis and factor analysis）. Methods The clinical data （symptoms, tongue picture, pulse condition, etc. ） of 640 epigastric pain cases （755 visits） were recorded and subject to cluster analysis and factor analysis. Results The TCM syndromes of epigastric pain could be classified into deficient cold of the spleen and stomach, liver qi invading the stomach, obstruction of middle iiao by damp-heat, deficiency of spleen qi and stomach qi, phlegm-damp retention, and blood stasis of the stomach. Each syndrome corresponded to specific informa- tion acquired by four TCM diagnostic methods. Conclusion Epigastric pain has different syndrome types with specific information acquired by four TCM diagnostic methods. Cluster analysis and factor analysis can provide effective data support for standardized diagnosis of epigastric pain and improve the accuracy of syndrome differentiation.

关 键 词：胃脘痛 数据挖掘 聚类分析 因子分析 辨证分型 

分 类 号：R282.75[医药卫生—中药学]