全国名中医丁书文益气活血解毒法治疗心房颤动的处方用药规律挖掘  

Data Mining on the Prescription Pattern of Atrial Fibrillation Treated by the Method of Benefiting Qi and Activating Blood Circulation and Detoxificating Blood Based on Prescriptions of Ding Shuwen-A National Famous Traditional Chinese Medicine Master

作　　者：郇家铭 王宁 李运伦 焦华琛[4] 周雪忠 王怡斐[4] Huan Jiaming;Wang Ning;Li Yunlun;Jiao Huachen;Zhou Xuezhong;Wang Yifei(School of Traditional Chinese Medicine,Shandong University of Traditional Chinese Medicine,Jinan 250014,China;School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China;First School of Clinical Medicine,Shandong University of Traditional Chinese Medicine,Jinan 250014,China;The Affiliated Hospital of Shandong University of Traditional Chinese Medicine,Jinan 250014,China)

机构地区：[1]山东中医药大学中医学院,济南250014 [2]北京交通大学计算机与信息技术学院医学智能研究所,北京100044 [3]山东中医药大学第一临床医学院,济南250014 [4]山东中医药大学附属医院,济南250014

出　　处：《世界科学技术-中医药现代化》2020年第12期4094-4102,共9页Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology

基　　金：国家科学技术部重点研发计划(2017YFC1703502):中医临床科研信息共享系统的研发与实施,负责人:杨杰;国家科学技术部重点研发计划(2017YFC1703506):中医药大数据挖掘研究与创新应用,负责人:于剑;国家中医药管理局国中医药办人教函(【2018】119号):丁书文全国名中医工作室建设项目,负责人:李运伦。

摘　　要：目的丁书文教授创新性地提出了心系疾病热毒学说,运用益气活血解毒法治疗房颤疗效显著。本研究以丁教授多年的处方数据为基础,探讨丁教授益气活血解毒法治疗房颤的用药规律。方法收集来自山东中医药大学附属医院门诊系统的丁书文教授处方数据,筛选出治疗房颤的372个处方,采用关联规则、点式互信息、复杂网络等数据挖掘方法对丁教授的药物配伍和处方进行分析。结果本研究利用复杂网络分析方法获得了丁教授治疗房颤的核心处方,提示益气活血解毒法是其主要治则治法;利用处方相似性和社团分析方法,获得15组类方,其中3种类方与丁教授总结的三大治法高度符合;为探寻丁教授清热解毒配伍特点,结合关联规则和点式互信息算法,获得了10个丁教授清热解毒配伍药对。结论数据挖掘技术提供了名医处方数据分析与提炼的可行方法,对丁教授经验的传承和临床应用提供直接可靠的依据。Objective Professor Ding Shuwen innovatively proposed the theory of heat toxin in cardiac diseases, andused the method of benefiting qi, activating blood and detoxifying blood to treat atrial fibrillation with remarkableefficacy. This study was conducted to investigate the medication pattern of Prof. Ding’ s method of benefiting qi,invigorating and detoxifying blood in the treatment of atrial fibrillation based on his prescription data for previous years.Methods The prescription data of Professor Ding from the outpatient system of the Affiliated Hospital of ShandongUniversity of Traditional Chinese Medicine were collected, 372 prescriptions for the treatment of atrial fibrillation werescreened, and data mining methods such as association rules, pointwise mutual information, and complex networks wereused to analyze Prof. Ding’s formulas and prescriptions. Results In this study, the core prescriptions of Professor Dingfor the treatment of atrial fibrillation were obtained by using complex network analysis, suggesting that the method ofbenefiting qi and activating blood circulation to detoxify the blood was his main treatment method;15 groups of classicalprescriptions were obtained by using prescription similarity and association analysis, among which 3 classicalprescriptions were highly consistent with the 3 major treatments summarized by Professor Ding;to explore thecharacteristics of Professor Ding’s heat-clearing and detoxifying combinations, 10 pairs of Professor Ding’s heat-clearingand detoxifying combinations were obtained by combining association rules and pointwise mutual information algorithm.Conclusion Data mining provides a feasible method for analyzing the prescription data of famous traditional Chinesemedicine masters. Using data mining technology to process and analyze Professor Ding’s prescription data can providereliable evidence for Professor Ding’s experience inheritance and clinical application.

关 键 词：丁书文 心房颤动 益气活血解毒 数据挖掘 复杂网络 核心药物组合 快速模块性优化 

分 类 号：R289.9[医药卫生—方剂学]