【摘要】 目的:利用数据挖掘技术对治疗高血压早期肾损害(EHN)的中药复方进行分析，以探讨EHN的用药规律，优化EHN的诊疗方案。方法:检索中国知网、万方、维普、中国生物医学数据库中主治疾病为EHN的中药方剂，进行用药频次、性味归经、药物用量、相关性、关联规则及聚类分析，探究EHN治疗的组方规律。结果:共纳入文献79篇，处方82首，涉及中药128味，用药频次867次。频数≥10次的中药共28味，排名前5位的中药分别为丹参、山茱萸、茯苓、山药、牛膝。四气以温、寒居多，五味以甘、苦、辛为主，归经多入肝、肾、脾经。设置关联规则支持度≥25%,置信度≥90%,提升度>1,获得17种常用药物组合。聚类分析获得3组适用于不同证型的新处方。结论:中医辨治EHN以滋阴潜阳、活血通络为主，兼以清泻虚热、化痰祛湿。通过数据挖掘技术，为临床遣方用药及新方新药研发提供参考。更多还原

【Abstract】 Objective: Data mining technology was used to analyze the traditional Chinese medicine(TCM) compounds for treating early hypertensive nephrosclerosis(EHN).Methods: TCM compounds with EHN as the main disease were searched from China National Knowledge Infrastructure(CNKI),Wanfang Data, Wipro Chinese Full-text Database of Scientific, and Technological Journals(VIP),and Chinese Biomedical Literature Service System(SinoMed).The drug frequency, property, flavors, attributive channel, drug dosage, correlation, association rules, and cluster analysis were carried out to explore the prescription formation rule of EHN treatment.Results: A total of 79 literatures were included, with 82 prescriptions, involving 128 flavors of TCM,and the frequency of medication was 867 times.There were 28 herbs with frequency≥10 times, and the top 5 herbs were radix salviae, cornus officinalis sieb, poria cocos, rhizoma dioscoreae and achyranthis bidentatae radix.The four Qi were mainly warm and cold, and the five tastes were mainly sweet, bitter and xin, which attributive the liver, kidney, and spleen channels.The association rules were set with support≥25%,confidence≥90% and lift>1 to obtain 17 combinations of commonly used drugs combinations.Three groups of new prescriptions for different syndrome types were obtained by cluster analysis.Conclusion: TCM differentiation and treatment of EHN is mainly based on nourishing Yin and suppressing Yang, promoting blood and clearing collaterals, as well as clearing vacuity and heat, promoting blood circulation for removing obstruction in collaterals, as well as clearing deficiency heat, resolving phlegm and dispelling dampness.Through data mining technology, will provide reference for clinical prescriptions and the development of new prescriptions and medicines.更多还原