基于数据挖掘的四川南派藏医药主治疾病及用药规律的研究
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篇名: 基于数据挖掘的四川南派藏医药主治疾病及用药规律的研究
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摘要: 目的:研究四川南派藏医药的学术特色及内涵,为南派藏医药的传承和发展提供相关信息,为其中常用药材的开发利用提供参考。方法:采用中医传承辅助平台中的数据挖掘、统计分析、归纳演绎等方法,系统分析属于四川南派藏医药的藏医院中使用的672个医院制剂的品种特点、药物频次、主治疾病及其用药规律等,并采用熵层次聚类方法演化出基于核心组合药物的新方。结果:四川南派藏医药方剂中共使用了624种药物,其中植物药509种(81.67%)、矿物药61种(9.77%)、动物药54种(8.65%);使用频次>120的药物有16味,排名前3的药物为诃子(57.44%)、红花(43.15%)、木香(42.26%);主治疾病包括13类,排名前3的依次为胃病(28.13%)、肝胆疾病(12.80%)和神经疾病(11.90%)。在治疗胃病方面,主要使用诃子、红花、豆蔻、荜茇、木香、石榴子等,常用药物组合共61个,最常用的药对为荜茇-豆蔻;治疗肝胆疾病主要使用诃子、红花、波棱瓜子、獐牙菜、渣驯等,常用药物组合共64个,最常用药对为红花-诃子;治疗神经疾病主要使用肉豆蔻、诃子、木香、丁香、沉香、广枣等,常用药物组合共73个,最常用药对为诃子-肉豆蔻。采用熵层次聚类方法演化出包括紫草茸-紫草-茜草-石榴子在内的5个候选新方。结论:所得四川南派藏医药医院制剂治疗常见疾病的高频药对及基于核心组合演化出的候选新方可为治疗胃病、肝胆疾病和神经系统疾病的现代藏药新药开发提供参考。
ABSTRACT: OBJECTIVE: To study the academic characteristics and connotation of Sichuan Nanpai Tibetan medicine (SNTM), to provide relevant information for the inheritance and development of Nanpai Tibetan medicine, and to provide reference for the development and utilization of commonly used medicinal materials in SNTM. METHODS: The type characteristics, medication frequency, main treatment disease and medication rule of 672 preparations of Tibetan hospital of SNTM were analyzed by means of data mining, statistical analysis and inductive deduction methods of TCM inheritance support system (TCMISS). Based on the core combination drugs, the new prescriptions were evolved by the entropy hierarchical clustering method. RESULTS: A total of 624 medicinal materials were used in formulation of SNTM, involving 509 plant drugs (81.67%), 61 mineral drugs (9.77%) and 54 animal drugs (8.65%). There were 16 medicines with frequency>120; among them, top 3 medicines were Terminalia chebula (57.44%), Carthamus tinctorius (43.15%) and Aucklandia lappa (42.26%). Main treatment diseases involved 13 categories, and top 3 categories were gastric diseases (28.13%), hepatobiliary diseases (12.80%) and neurological diseases (11.90%). In the treatment of stomach diseases, T. chebula, C. tinctorius, Alpinia katsumadai, Piper longum, A. lappa and Punica granatum were mainly used; totally 61 commonly used drug combinations were obtained and the most commonly used combination was P. longum-A. katsumadai. In the treatment of hepatobiliary diseases, T. chebula, C. tinctorius, Herpetospermum caudigerum, Swertia bimaculata, Zhaxun were mainly used; 64 commonly used drug combinations were obtained and the most commonly used combination is T. chebula-C. tinctorius. In the treatment of neurological diseases, Myristica fragrans, T. chebula, A. lappa, Syzygium aromaticum, Aquilaria sinensis, Choerospondias axillaris were mainly used; 73 commonly used drug combinations were obtained, and the most commonly used combination was T. chebula-M. fragrans. 5 candidate new formulations had been evolved by the entropy hierarchical clustering method, involving Lacciferlacca-Lithospermum erythrorhizon-Rubia cordifolia- Punica granatum. CONCLUSIONS: Obtained high frequency drug pairs and evolved new candidate formulation based on the core combinations drugs of SNTM for commonly diseases can provide reference for the development of modern new Tibetan medicines for gastric, hepatobiliary and neurological diseases.
期刊: 2019年第30卷第19期
作者: 赵程成,徐僮,田玫瑰,杜欢,范刚,张艺
AUTHORS: ZHAO Chengcheng,XU Tong,TIAN Meigui,DU Huan,FAN Gang,ZHANG Yi
关键字: 南派藏医药;主治疾病;用药规律;中医传承辅助平台;数据挖掘
KEYWORDS: Nanpai Tibetan medicine; Main treatment diseases; Medication rule; TCM inheritance support system; Data mining
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