摘要
目的基于数据挖掘庄礼兴教授治疗腰痛病取穴规律,为针灸治疗腰痛病提供参考。方法收集庄礼兴教授针灸治疗腰痛患者98例,并对符合纳入标准病例中的处方穴位进行统计,运用SPSSStatistics21.0及SPSSmodeler14.1软件对腧穴的频数、频率、聚类规则和关联法则进行分析。结果共纳入穴位处方98条,涉及腧穴29个,取穴以关元俞、大肠俞、腰骶督脉排针、委中为主,归经以足太阳膀胱经、足少阳胆经、督脉为主,治疗以电针+火罐、火针交替为主。对穴位聚类分析,可形成5个聚类组合。通过关联规则分析,共得穴对规则6条、配穴症状关联规则9条。结论通过对庄礼兴教授临床治疗腰痛病取穴进行聚类及关联分析,展现了其辨经取穴治疗腰痛病的临证思想。
Objective Using data mining techniques to summarize the rules of occupants of low back pain and to provide references for acupuncture treatment of low back pain from Professor Zhuang Lixing′s law of selecting acupoints.Methods 98 cases of patients with low back pain treated with acupuncture by Professor Zhuang Lixing were collected,and the prescribed acupoints in the included standard cases were counted.SPSS Statistics 21.0 and SPSS modeler 14.1 were used to analyze the frequency,frequency,clustering rules and association rules of acupoints.analysis.Results A total of 98 acupoint prescriptions were included,involving 29 acupoints.The main points were Guanyuanshu,Dachangshu,lumbosacral governor channel acupuncture,and Weizhong.Mainly pulse,the treatment is mainly electroacupuncture+cupping,fire acupuncture alternately.For cluster analysis of acupoints,5 cluster combinations can be formed.Through the analysis of association rules,there are 6 rules for acupoints pairing and 9 association rules for symptom matching.Conclusion Through clustering and correlation analysis of Professor Zhuang Lixing′s clinical treatment,we can conclude the academic thoughts of acupoints selection through differentiation of symptoms and signs.
作者
黄慧仪
罗楷文
于珺
庄锦源
庄礼兴
HUANG Hui-yi;LUO Kai-wen;YU Jun;ZHUANG Jin-yuan;ZHUANG Li-xing(Clinical School of Acupuncture&Moxibustion and Rehabilitation,Guangzhou University of Chinese Medicine,Guangzhou guangdong 510405;Acupuncture Rehabilitation Center,The First Affiliated Hospital of Guangzhou University of Chinese Medicine,Guangzhou guangdong 510405)
出处
《世界中西医结合杂志》
2020年第8期1396-1399,共4页
World Journal of Integrated Traditional and Western Medicine
基金
庄礼兴广东省名中医传承工作室(粤中医办函[2018]5号)。
关键词
腰痛病
数据挖掘
聚类分析
关联分析
Low Back Pain
Data Mining
Cluster Analysis
Association Rule Analysis