基于数据挖掘的糖尿病治疗中药方剂用药规律分析。
Analysis of Prescription Medication Rules of Traditional Chinese Medicine for Diabetes Treatment Based on Data Mining.
机构信息
Preventive Health Department, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China.
Preventive Health Department, Shanghai Guangzhong Street Community Health Service Center, Shanghai 201203, China.
出版信息
J Healthc Eng. 2022 Jan 31;2022:7653765. doi: 10.1155/2022/7653765. eCollection 2022.
In this study, we have used TCM medical record management platform and SAS statistical software to analyze the cases of a professor in the treatment of type 2 diabetes, in order to explore the medication rules for the treatment of type 2 diabetes, so as to enrich and optimize the diagnosis and treatment plan for type 2 diabetes based on the experience of famous doctors. Chinese medicine treatment provides more diagnosis and treatment ideas. We have collected the professor's treatment of type 2 diabetes, screened out 100 patients, from a total of 285 prescriptions, and entered them into the TCM medical record management platform. We used the TCM medical record management platform and SAS statistical software to analyze his professor's experience in the treatment of type 2 diabetes. The medication analysis is as follows: (1) frequency of medication: 285 cases that met the inclusion criteria used a total of 187 traditional Chinese medicines. Among them, Salvia miltiorrhiza was used most frequently; (2) drug frequency analysis: 285 cases met the inclusion criteria, and the four Qi were mainly cold and warm medicines. The five flavors are mainly sweet, bitter, and pungent drugs. The main meridians are the liver, spleen, and kidney; (3) drug efficacy and classification analysis: 285 cases met the inclusion criteria, and 285 cases met the inclusion criteria and the Chinese medicines involved are the most common medicines used for tonic, heat clearing, blood circulation, and stasis; (4) clustering of medications: 35 Chinese medicines with medication frequency ≥20% are divided into 11 categories. (5) Using the improved Apriori algorithm, the minimum confidence level is selected to be 0.5, data mining is conducted on all type 2 diabetes cases, and a total of 21 recipes are dug out involving 10 Chinese medicines. In this study, with the aid of the TCM medical record management platform and SAS statistical software, cluster analysis, improved Apriori algorithm, and other data mining methods were used to systematically and objectively analyze the professor's treatment of type 2 diabetes cases. The results have clinical significance and can be used for traditional Chinese medicine treatment of type 2 diabetes, which provides an objective basis and provides a certain reference for the current inheritance of traditional Chinese medical experience and summary research.
在这项研究中,我们使用了中医病历管理平台和 SAS 统计软件分析了一位教授治疗 2 型糖尿病的病例,旨在探索治疗 2 型糖尿病的用药规律,从而丰富和优化基于名医经验的 2 型糖尿病诊治方案,为中医治疗 2 型糖尿病提供更多的诊疗思路。我们收集了教授治疗 2 型糖尿病的案例,筛选出 100 例患者,共 285 张处方,录入中医病历管理平台,运用中医病历管理平台和 SAS 统计软件分析其教授治疗 2 型糖尿病的经验。用药分析如下:(1)用药频次:符合纳入标准的 285 例病例共使用中药 187 味,其中丹参使用频次最高;(2)药物频次分析:符合纳入标准的 285 例病例,四气以寒、温药为主,五味以甘、苦、辛味药为主,归经主要涉及肝、脾、肾三经;(3)药物功效分类分析:符合纳入标准的 285 例病例,涉及的中药以补虚、清热、活血、化瘀药最常用;(4)药物聚类分析:将用药频次≥20%的 35 味中药分为 11 类;(5)采用改进的 Apriori 算法,选择最小置信度为 0.5,对所有 2 型糖尿病病例进行数据挖掘,挖掘出涉及 10 味中药的共 21 首方剂。本研究借助中医病历管理平台和 SAS 统计软件,运用聚类分析、改进的 Apriori 算法等数据挖掘方法,对教授治疗 2 型糖尿病病例进行系统、客观的分析,结果具有临床意义,可用于中医治疗 2 型糖尿病,为当前中医经验的传承和总结研究提供了客观依据和一定的参考。