节点文献
慢性萎缩性胃炎近10年中医文献研究
【作者】 魏玉霞;
【导师】 严季澜;
【作者基本信息】 北京中医药大学 , 中医医史文献, 2012, 博士
【摘要】 本研究借助数据库、数据挖掘等手段,以近10年国内公开发表的中医或中西医结合治疗慢性萎缩性胃炎(CAG)的期刊文献为研究对象,采用频数分析、因子分析、主成分分析、聚类分析、以及关联规则等数据挖掘方法,分别对慢性萎缩性胃炎的证素、证候规律、用药规律等不同方面及相关性进行分析处理,为归纳总结治疗慢性萎缩性胃炎的经验,做了一种尝试和探索,为理论与临床结合提供一个平台。目的:从多角度、多层次对慢性萎缩性胃炎的证候、证候要素、病机及用药规律进行数据挖掘;为完善慢性萎缩性胃炎的辨证体系作出有益探索,为临床诊治提供新的思路。方法:1.通过检索2000-2011年的中国期刊全文数据库(CNKI)及相关数据库,得到相关文献;2.进行数据预处理:对证型名称、症状名称、药物名称进行规范;3.建立数据库:通过计算机编程把原始数据库录入excel数据库;4.采用频数分析、因子分析、主成分分析、聚类分析、频繁项集、关联规则数据挖掘方法进行数据统计:(1)证型、证候要素、靶位进行频数分析;(2)对症状进行频数分析、因子分析、主成分分析、聚类分析;(3)对药物进行频数分析、因子分析、主成分分析、聚类分析;(4)运用频繁项集和关联规则对药物和药物、症状和药物进行数据挖掘;结论:1.运用数理统计方法对慢性萎缩性胃炎近10年中医文献的研究发现:慢性萎缩性胃炎辨证分型多、参考标准不统一,慢性萎缩性胃炎证候、症状、药物名称不规范等,制约了慢性萎缩性胃炎临床应用和行业交流;2.运用数理统计方法提取慢性萎缩性胃炎近10年中医文献中主要的证候要素、靶位并探索其应证组合规律;中医的证候千变万化,而证候要素、靶位相对简约,多元统计方法能够较好地展现这种复杂的组合关系3.通过对症状聚类分析,将慢性萎缩性胃炎的证候归纳为9类,即:脾胃虚弱、胃阴亏虚、肝胃不和、肝胃郁热、脾胃湿热、肝气郁滞、瘀阻胃络、脾阳虚、胃热壅盛等;4.通过对药物频数分析,发现补益药、理气药、清热药三类药物的使用频次较高,其中补气药是治疗慢性萎缩性胃炎的特异性药物;5.通过对药物聚类分析,形成慢性萎缩性胃炎的7种聚类方,从功效方面来看,包括:扶正、祛邪、扶正祛邪三类;6.通过药物与药物关联分析,发现四君子汤、二陈汤、行气活血方是医家治疗慢性萎缩性胃炎的基本方药,三者之间的配合应用构成了医家用药的一般规律。7.通过对症状与药物的关联分析,发现对于核心症状:食欲不振、嗳气胃脘胀痛、上腹饱胀,核心药物是炙甘草、茯苓、白术、党参、黄芪、陈皮。反推慢性萎缩性胃炎的证候要素为气虚、气郁,靶位为:肝、脾、胃;肝气郁滞、脾胃气虚是慢性萎缩性胃炎的基本证型。本研究的创新点:1.合理运用“证候要素”和“靶位”以及“应证组合”思路,结合数据挖掘方法对慢性萎缩性胃炎近10年期刊文献进行系统梳理,并就慢性萎缩性胃炎的证治提出新的认识;2.从文献角度、用数据挖掘方法对慢性萎缩性胃炎的证候类型、证候要素、病机、用药规律进行总结,从多层次、多角度探索慢性萎缩性胃炎的证候特征和用药规律。
【Abstract】 This study with the database, data mining, and other means, for nearly 10-year domestic public Chinese medicine or or integrated traditional Chinese and Western medicine in treatment of chronic atrophic gastritis in the literature as the research object, using frequency analysis, factor analysis, principal component analysis, cluster analysis, as well as associatedrules, data mining methods, respectively syndrome factor on the CAG, syndromes, different aspects of drug law and related analysis and processing, to summarize the treatment of CAG experience, to do an experiment and explore; for the combination of theory and clinicalprovide a platform;Objective:Using data mining method on CAG syndrome, syndrome factor, pathogenesis and drug law from different perspective;to improve the CAG syndrome differentiation system makes beneficial exploration, for clinical in prescriptions with mode of thinking and decision-making basis.Method:1.Retrieval 2000-2011 China Academic Journal (CNKI) and related databases, the relevant literature;2.Data preprocessing:check against Syndrome type name, symptoms name, name of the drug to be regulated;3.Establishment of a database:the original database input excel database through computer programming;4.Use of frequency analysis, factor analysis, principal component analysis, cluster analysis, frequent itemsets, association rules data mining methods for data mining.(1)Use of frequency analysis for Syndrome, syndrome elements, targeted to carry out frequency analysis.(2)Use of frequency analysis, frequency analysis, factor analysis, principal component analysis, cluster analysis for symptom data mining.(3)Using frequency analysis, factor analysis, principal component analysis, cluster analysis, data mining on Chinese herbal medicine.(4)Use of frequent itemsets and association rules data mining on Chinese herbal medicine and Chinese herbal medicine, symptoms, and Chinese herbal medicine.Result:1.Use of mathematical statistics on the study of Chinese literature in the past decade, and found:CAG differentiation of type, reference standards are not uniform,CAG syndromes, symptoms, Chinese herbal medicine names are not standardized, which restricts the CAG clinical applications and exchange of technology2.Using the method of mathematical statistics on CAG nearly ten years literature of traditional Chinese medicine extract its main syndrome elements, targets and their combination rule; TCM syndrome has changed a lot, and syndrome factor, target relative simplicity, multivariate statistical method can better reveal the complex combinatorial relation;3.Symptom cluster analysis of CAG syndromes grouped into nine categories, namely:spleen-stomach weakness syndrome,stomach yin deficiency syndrome, syndrome of liver qi invading the stomach, syndrome of depressed liver and stomach qi transforming into fire, syndrome of dampness-heat in the spleen and stomach, syndrome of liver depression and qi stagnation, syndrome of (blood) stasis in the stomach collateral, spleen yang deficiency syndrome, stomach heat syndrome, etc.4The drug frequency analysis, found the tonic medicinal, regulating qi medicinal, heat-clearing medicinal use with high frequency, which tonify qi medicinal of CAG is nonspecific drug;5.Based on the cluster analysis of CAG Chinese herbal medicine, formed 7 kinds of clustering method, from the functional perspective, including:reinforce the healthy qi, eliminate the pathogenic fanctors, reinforce the healthy qi and eliminate the pathogenic fanctors.6.Drugs and drug association analysis and found that Decoction of Sijunzi Decoction of Er chen, moving qi and activing blood medicinal is the medicine treatment CAG basic recipe, between the three applications constitute the general laws of the physician medication.7.Associated symptoms with herbs and found that the core symptoms:torpid intake, belching, epigastric pain, epigastric fullness, the core of herbs:Zhigancao, Poria, Atractylodes, Codonopsis, Astragalus, dried tangerine peel. Therefore infer that the the CAG syndrome elements is qi deficiency and qi stagnation, target is liver and spleen; basic syndrome type of CAG is liver stagnation and spleen deficiency.Innovation of this study:1.Rational use of" syndrome factor" and the" target" and" evidence combination rule " ideas, combined with data mining methods to CAG nearly 10 years periodical literature systematically, and propose own point of view on the diagnosis and treatment of CAG.2.The CAG syndromes, syndrome factor, pathogenesis, drug law were summarized from the literature point of view, using data mining from the literature point to explore the CAG syndrome characteristics and herb law.
【Key words】 chronic gastritis; atrophic; data mining; Association rules; cluster analysis; syndrome factor;