摘要
Abstract
Objective To explore and analyze the acupoint selection rule of acupoint patching in the treatment of facial paralysis based on data mining,so as to provide reference for clinical practice.Methods The literature of acupoint application in the treatment of facial paralysis in Chinese and English databases such as China National Knowledge Infrastructure(CNKI),VIP Chinese Science and Technology Journal Database(VIP),Wanfang Academic Journal Full-text Database(Wanfang),China Biomedical Literature Database(SinoMed)and PubMed was searched by subject words and keywords.Descriptive analysis,association rule analysis and cluster analysis were performed using Excel 2016,IBM SPSS Modeler 18 and SPSS 26.0 software.Results Finally,62 literatures and 38 acupoints were included.The total frequency was 311 times,and the high-frequency acupoints were Yifeng,Jiache,Dicang,Taiyang and Xiaguan.A total of 10 meridians were involved,and the commonly used meridians were the stomach meridian of foot-yangming,the sanjiao meridian of hand-shaoyang and the gall bladder channel of foot-shaoyang.Among them,30 acupoints belong to specific acupoints,and were mainly concentrated in the face,head and neck.Correlation analysis showed that there were 16 groups of acupoint combinations that met the requirements,among which"Yangbai-Sibai"had the highest confidence,"Dicang-Yangbai"had the highest support,and"Yangbai-Sibai"had the highest gain.The results of cluster analysis showed that there were 5 effective clustering groups,among which Yifeng was the key point.Conclusion Through data mining,it is found that acupoint application in the treatment of facial paralysis has the characteristics of local acupoint selection,distal acupoint selection along meridians and reuse of specific acupoints,which can provide a certain basis for clinical acupoint selection.In the future,we can study the acupoint selection of facial paralysis syndrome differentiation and staging.关键词
面瘫/穴位贴敷/选穴规律/数据挖掘Key words
Facial paralysis/Acupoint patching/Acupoint selection rule/Data mining分类
中医学
