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基于数据挖掘分析"温阳化积法"治疗膜性肾病

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目的:基于数据挖掘分析"温阳化积法"治疗膜性肾病的用药规律。方法:以北京中医药大学东直门医院2021年1月至2022年8月门诊治疗的420例膜性肾病患者作为研究对象,对所有患者的首诊处方均进行统计分析,使用SPSS Modeler 18。0软件进行药物频数分析,利用熵层次聚类方法分析方剂组方规律,采用Aprior算法进行药物关联规则分析,采用组间连接的聚类分析方法分析处方中核心药物组合。结果:共计收集659份首诊处方,累计收集药物129味,使用频率≥2%的高频药物38味,其中使用频率超过90%的中药为附子、茯苓、麻黄、炙甘草,使用频率在60%~89%的中药为麸炒白术、干姜、大枣、桂枝、防己、赤小豆、黄芪、泽泻、葫芦巴。其主要为温里药、解表药、补虚药、利水渗湿药等。出现频率在50%以上的中药组合分别为麻黄、附子,附子、干姜,防己、黄芪,防己、茯苓,附子、防己等。药物组合关联规则分析中,置信度前3位依次为:麻黄,附子-防己;附子,茯苓-黄芪;黄芪,麻黄-防己。采用组间连接的聚类分析方法分析核心药物组合结果发现,共得到12大类。高频药物聚类得到4个聚类方。结论:通过数据挖掘探究刘宝利治疗膜性肾病的用药规律,在温阳化积基础上结合解表、补虚、利水渗湿等治法,对于临床治疗膜性肾病的具有一定的参考意义。
Analysis of the"Warm Yang and Accumulation Method"in the Treatment of Membranous Nephropathy Based on Data Mining
Objective:To analyze the medication rule in the treatment of membranous nephropathy with"warm Yang and accumulation method"based on data mining.Methods:A total of 420 patients with membranous nephropathy treated in the outpatient department of Dongzhimen Hospital,Beijing University of Chinese Medicine from January 2021 to August 2022 were selected as the research subjects.Statistical analysis was conducted on the initial prescriptions of all patients.SPSS Modeler 18.0 software was used for drug frequency analysis,entropy level clustering method was used to analyze the formula composition rules,and Aprior algorithm was used for drug association rule analysis.Using cluster analysis method with inter group connections to analyze core drug combinations in prescriptions.Results:A total of 659 initial diagnosis prescriptions were collected,with a total of 129 drugs collected.38 high-frequency drugs with a usage frequency of≥2%were used.Among them,traditional Chinese medicines ingredients with a usage frequency of over 90%were Fuzi(Aconiti Radix Lateralis Praeparata),Fuling(Poria),Mahuang(Ephedrae Herba),and Zhigancao(Glycyrrhizae Radix cum Liquido Fricta).The traditional Chinese medicines ingredients with a usage frequency of 60%to 89%were Fuchaobaizhu(Atractylodis Macrocephalae Rhizoma Stir-fried with Bran),Ganjiang(Zingiberis Rhizoma),Dazao(Jujubae Fructus),Guizhi(Cinnamomi Ramulus),Fangji(Stephaniae Tetrandrae Radix),Chixiaodou(Phaseoli Semen),Huangqi(Astragali Radix),Zexie(Alismatis Rhizoma),and Huluba(Trigonellae Semen).It mainly consists of warm internal medicine,surface relieving medicine,tonifying deficiency medicine,diuretic and dampness absorb ing medicine,etc.The ingredients of traditional Chinese medicine combinations with a frequency of over 50%were Mahuang(Ephedrae Herba)and Fuzi(Aconiti Radix Lateralis Praeparata),Fuzi(Aconiti Radix Lateralis Praeparata)and Ganjiang(Zingiberis Rhizoma),Fangji(Stephaniae Tetrandrae Radix)and Huangqi(Astragali Radix)and Fangji(Stephaniae Tetrandrae Radix),Fuling(Poria)and Fuzi(Aconiti Radix Lateralis Praeparata),Fangji(Stephaniae Tetrandrae Radix),and etc.In the analysis of drug combination association rules,the top three confidence levels were:Mahuang(Ephedrae Herba),Fuzi(Aconiti Radix Lateralis Praeparata)-Fangji(Stephaniae Tetrandrae Radix);Fuzi(Aconiti Radix Lateralis Praeparata),Fuling(Poria)-Huangqi(Astragali Radix);Huangqi(Astragali Radix),Mahuang(Ephedrae Herba)-Fangji(Stephaniae Tetrandrae Radix).The results of core drug combinations were analyzed by cluster analysis method of inter-group linkage,and a total of 12 categories were obtained.Four clustering formulas were obtained from high-frequency drug clustering.Conclusion:According to the medication patterns of LIU Baoli in the treatment of membranous nephropathy through data mining,combined with methods such as relieving external symptoms,tonifying deficiency,and promoting diuresis and dampness on the basis of warm Yang and accumulation method,it has certain reference significance for the clinical treatment of membranous nephropathy.

membranous nephropathywarm Yang and accumulation methodmedication patternsdata miningLIU Baoli

纪利梅、李靖、刘宝利、李仁武

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北京中医药大学东直门医院,北京 100007

北京中医医院顺义医院,北京 101300

首都医科大学附属北京中医医院,北京 100010

膜性肾病 温阳化积法 用药规律 数据挖掘 刘宝利

北京市属医院科研培育计划项目

PZ2022024

2024

中医药导报
湖南省中医药学会 湖南省中医管理局

中医药导报

CSTPCD
影响因子:0.952
ISSN:1672-951X
年,卷(期):2024.30(1)
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