基于数据挖掘分析含白芍中成药的组方规律
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篇名: 基于数据挖掘分析含白芍中成药的组方规律
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摘要: 目的:分析含白芍中成药的组方规律,为白芍的现代临床应用及新药开发提供依据。方法:收集《中药成方制剂》和2015年版《中国药典》中含白芍的中成药处方,采用中医传承辅助平台V 2.5中描述性统计、关联规则分析等数据挖掘方法,统计含白芍中成药处方中的药材频次及其性味归经、主治疾病与证候分布、核心药材组合(设置支持度分别为10%、20%、30%,置信度为0.9),并对常见的主治疾病及主治证候(设置支持度为20%、30%、40%,置信度为0.9)进行组方规律分析。结果:共统计含白芍中成药处方600个,涉及中药673味。含白芍中成药处方中所含中药的药性主要为温性,其次为寒性、平性;药味主要为甘味,其次为苦味、辛味;主要归脾、肝、心经。主治疾病165种(如月经失调、痛经、眩晕),主治证候159种(如气血两虚证、气滞血瘀证、肝肾亏虚证)。当支持度为30%、置信度为0.9时,含白芍中成药处方的核心药材组合20个(如甘草-白芍、当归-白芍、白芍-茯苓),药材间关联规则19条。当支持度为40%、置信度为0.9时,含白芍中成药治疗月经失调的核心药材有8种(如白芍、香附、当归等),治疗眩晕的核心药材有9种(如白芍、熟地黄、当归等),治疗气血两虚证的核心药材有9种(如白芍、白术、茯苓等),治疗气滞血瘀证的核心药材有10种(如白芍、木香、甘草等)。结论:本研究通过数据挖掘分析了含白芍中成药的主治病证、配伍特点和组方规律,可为白芍的现代临床应用和新药开发提供依据。
ABSTRACT: OBJECTIVE: To analyze the formulation regularity of Chinese patent medicines containing Paeonia lactiflora, and to provide evidence for modern clinical application and R&D of P. lactiflora. METHODS: The formulations of Chinese patent medicine containing P. lactiflora were collected from Chinese Materia Medica Preparation and 2015 edition of Chinese Pharmacopeia. Statistical analysis was performed on the frequency of medicinal material, channel tropism, distribution of attending syndromes and attending diseases, core medicine combination (support degrees were set as 10%, 20%, 30% and confidence degree was 0.9) by using data mining methods such as descriptive statistics and association rule analysis in TCM Inheritance System V 2.5; the formulation regularity of common attending syndromes and attending diseases (support degrees were set as 20%, 30%, 40% and confidence degree was 0.9) was analyzed. RESULTS: A total of 600 Chinese patent medicine formulations contained P. lactiflora, involving 673 ingredients. The main medicinal properties in Chinese patent medicines containing P. lactiflora were warm, followed by cold and neutral. The main medicinal flavor was sweet, followed by bitter and pungent. The main channel tropism was spleen, liver and heart channel. There were 165 kinds of main treatment diseases (menstrual disorder, dysmenorrhea, dizziness) and 159 main treatment syndromes (insufficiency of qi and blood, qi stagnation and blood stasis, liver and kidney deficiency). Under the condition of 30% support degree and 0.9 confidence degree, there were 20 core combination of Chinese patent medicine formulations containing P. lactiflora (Glycyrrhiza uralensis-P. lactiflora, Angelica sinensis-P. lactiflora, P. lactiflora-Poria cocos) and 19 association rules among drugs. Under the condition of 40% support degree and 0.9 confidence degree, there were 8 core medicines in Chinese patent medicines containing P. lactiflora for menstrual disorders (such as P. lactiflora, Cyperus rotundus, A. sinensis), 9 core medicines for dizziness (such as P. lactiflora, Rehmannia glutinosa, A. sinensis), 9 core medicines for qi and blood deficiency (such as P. lactiflora, Atractylodes macrocephala, P. cocos), and 10 core medicines for qi stagnation and blood stasis syndrome (such as P. lactiflora, Aucklandia lappa, G. uralensis). CONCLUSIONS: In this study, data mining was used to analysis the main symptoms, compatibility characteristics and formulation rules of Chinese patent medicines containing P. lactiflora, which can provide a basis for the modern clinical application and new drug development of P. lactiflora.
期刊: 2019年第30卷第19期
作者: 黄远程,蒋凯林,朱朝阳,廖柳,林煜翔,梁怀枫,李培武,刘凤斌
AUTHORS: HUANG Yuancheng,JIANG Kailin,ZHU Chaoyang,LIAO Liu,LIN Yuxiang,LIANG Huaifeng,LI Peiwu,LIU Fengbin
关键字: 白芍;数据挖掘;中医传承辅助平台V2.5;组方规律;主治疾病
KEYWORDS: Paeonia lactilora; Data mining; TCM Inheritance System V 2.5; Formulation regularity; Main treatment disease
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