广州医药 ›› 2023, Vol. 54 ›› Issue (3): 72-80.DOI: 10.3969/j.issn.1000-8535.2023.03.014

• 论著 • 上一篇    下一篇

基于中药处方数据挖掘探索中医药治疗盆腔炎用药规律

谢巍1, 杨妮2   

  1. 1 柳州市妇幼保健院(柳州 545001)
    2 广西科技大学附属妇产医院,儿童医院(柳州 545001)
  • 收稿日期:2022-06-05 出版日期:2023-03-20 发布日期:2023-04-14
  • 通讯作者: 杨妮,E-mail: 642413556@qq.com
  • 基金资助:
    广西壮族自治区中医药管理局自筹经费科研课题(GZZC2020360)

Exploration on regularity of traditional Chinese medicine for pelvic inflammatory disease based on large data mining of Chinese herbal medicine prescriptions

XIE Wei1, YANG Ni2   

  1. 1 Liuzhou Maternity and Child Healthcare Hospital, Liuzhou 545001, China
    2 Affiliated Maternity Hospital and Affiliated Children's Hospital of Guangxi University of Science and Technology, Liuzhou 545001, China
  • Received:2022-06-05 Online:2023-03-20 Published:2023-04-14

摘要: 目的 探究中医药治疗盆腔炎的用药规律,为中医临床辩证用药提供借鉴。方法 采用主题词联合自由词相,全面检索CNKI、VIP、Wangfang、CBM、PubMed和EMbase、数据库及Cochrane图书馆,收集中、西药对比治疗盆腔炎的随机对照试验。严格按照纳入、排除标准挑选随机对照试验中涵盖的中药药方,采用Excel表格统计分析药方中药的四气、五味、归经和用药频率,随后利用系统聚类软件对使用频率高的中药开展关联、聚类和主成分分析。结果 本文共纳入235个随机对照试验,涉及320首中药处方,平均用药味数13.29味,使用频率前五位的药分别为延胡索、赤芍、当归、蒲公英、丹参;关联规则共得出41对高关联药对,其中包括赤芍-延胡索、莪术-三棱-败酱草等。高频率使用的前30味中药可分为五大类,获取的9个主成分分析结果与系统聚类中的结果一致。结论 本研究采用循证医学和系统聚类分析方法,剖析中医药治疗盆腔炎的用药规律,为临床用药提供参考。

关键词: 盆腔炎, 循证医学, 中医药, 聚类分析, 主成分分析

Abstract: Objective To discuss the medication regularity of traditional Chinese medicine (TCM) in the treatment of pelvic inflammatory disease, and provide new thinking for effective medication in clinical medicine. Methods Keywords combined with free word were used to comprehensively search CNKI, VIP, Wangfang, CBM, PubMed and EMbase, databases and Cochrane library to collect randomized controlled trials of comparative treatment of pelvic inflammatory disease between Chinese and Western drugs. The TCM prescriptions covered in the randomized controlled trial were selected in strict accordance with the standard inclusion and exclusion criteria. Excel was used to statistically analyze the four properties, five flavors, meridian and medication frequency of TCM prescriptions. Then, systematic clustering software was used to carry out correlation, clustering and principal component analysis for the Chinese medicines with high using frequency. Results The study included 235 randomized controlled trial and 320 prescriptions of traditional Chinese medicine were involved, the average number of herbs was 13.29, which Yanhusuo, Chishao, Danggui, Pugongying, Danshen were with top five frequency. A total of 41 drug pairs with high association were obtained by association rules, including Chishao-Yanhusuo, Eshu-Sanleng-Baijiangcao, etc. Thirty traditional Chinese medicine with high using frequency can be divided into 5 categories according to the effect. The obtained results of 9 principal component analysis were consistent with those in the system cluster. Conclusions In this study, evidence-based medicine and systematic cluster analysis were used to analyze the medication regularity of traditional Chinese medicine in the treatment of pelvic inflammatory disease, so as to provide reference for the clinical medication.

Key words: pelvic inflammatory disease, evidence-based medicine, traditional Chinese medicine, cluster detection, principal component analysis