中医大师熊继波通过数据挖掘治疗关节痛综合征的用药经验

Q3 Medicine
Deng Wenxiang , Zhang Jidong , Zhang Wenan , He Qinghu
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The main patterns of AS included the damp heat, phlegm stasis, and neck arthralgia. The most commonly used herbs for AS were Chuanniuxi (Cyathulae Radix), Huangbo (Phellodendri Chinensis Cortex), Cangzhu (Atractylodis Rhizoma), Qinjiao (Gentianae Macrophyllae Radix), Gancao (Glycyrrhizae Radix et Rhizoma), Huangqi (Astragali Radix), and Chuanxiong (Chuanxiong Rhizoma). The most common effect of the herbs was “promoting blood circulation and removing blood stasis”, followed by “supplementing deficiency (Qi supplementing, blood supplementing, and Yang supplementing)”, and “dispelling wind and dampness”. The data were analyzed with the support ≥ 15% and confidence = 100%, and after de-duplication, five second-order association rules, 39 third-order association rules, 39 fourth-order association rules, and two fifth-order association rules were identified. 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引用次数: 0

摘要

目的通过数据挖掘,检验和传播中医大师熊继波在诊断和治疗关节痛综合征(AS)方面的用药经验和团体方剂。方法收集熊继波教授2014年1月1日至2018年12月31日的门诊病例资料,以及2019年12月出版的《真正的名医——熊继波临床病案1》中记录的病例资料。从患者数据中收集的五个变量分别是中医诊断信息、中西医诊断、证候、治疗和处方。用Excel将采集的数据建立数据库。利用Python环境,建立熊继波教授定制的AS诊疗改进自然语言处理(NLP)模型,对数据进行预处理,并对词云进行分析。基于中医传承计算平台(V3.0)和RStudio (V4.0.3)对AS病例进行频率分析、关联规则分析、聚类分析和可视化分析。结果从病例数据库中共收集到熊继波教授的病历610份。经数据筛选标准共纳入103份病历,其中处方187次(45种),中草药1506次(125种)。主要相关经络为肝、脾、肾经络。使用最多的中草药的性质以温、平、冷为主,而草药的味道以苦、辣、甜为主。AS的主要证型为湿热、痰瘀、颈痛。AS最常用的草药是川牛溪、黄柏、苍术、秦椒、甘草、黄芪和川芎。这些草药最常见的功效是“活血化瘀”,其次是“补虚(补气、补血、补阳)”和“祛风祛湿”。对数据进行支持度≥15%、置信度= 100%的分析,重复数据删除后,识别出5条二阶关联规则、39条三阶关联规则、39条四阶关联规则和2条五阶关联规则。各排序前的关联规则为“苍术(白术)→黄柏(黄柏皮)”、“苍术(白术)+川牛溪(黄柏皮)→黄柏(黄柏皮)”、“川牛溪(苍术)+当归(当归)+甘草(龙胆)→秦椒(龙胆)”和“川牛溪(苍术)+当归(当归)+甘草(甘草)+黄柏”分别为黄柏(黄柏皮)→秦椒(龙胆科)。对前30种药材进行聚类分析,得到5个聚类。中草药以燥湿、补气、活血为主。AS的主要处方为二苗散(),葛根姜黄散()和黄芪重藤饮()。核心方剂包括苍术、川牛溪、甘草、黄柏、木瓜、秦椒、当归、薏苡仁等。结论清热湿、通络止痛、益气活血是熊继波教授治疗AS最常用的方法。此外,定制化的NLP模型可以提高中医数据挖掘的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traditional Chinese medicine Master XIONG Jibo’s medication experience in treating arthralgia syndrome through data mining

Objective

This study aimed to examine and propagate the medication experience and group formula of traditional Chinese medicine (TCM) Master XIONG Jibo in diagnosing and treating arthralgia syndrome (AS) through data mining.

Methods

Data of outpatient cases of Professor XIONG Jibo were collected from January 1, 2014 to December 31, 2018, along with cases recorded in A Real Famous Traditional Chinese Medicine Doctor: XIONG Jibo's Clinical Medical Record 1, which was published in December 2019. The five variables collected from the patients’ data were TCM diagnostic information, TCM and western medicine diagnoses, syndrome, treatment, and prescription. A database was established for the collected data with Excel. Using the Python environment, a customized modified natural language processing (NLP) model for the diagnosis and treatment of AS by Professor XIONG Jibo was established to preprocess the data and to analyze the word cloud. Frequency analysis, association rule analysis, cluster analysis, and visual analysis of AS cases were performed based on the Traditional Chinese Medicine Inheritance Computing Platform (V3.0) and RStudio (V4.0.3).

Results

A total of 610 medical records of Professor XIONG Jibo were collected from the case database. A total of 103 medical records were included after data screening criteria, which comprised 187 times (45 kinds) of prescriptions and 1 506 times (125 kinds) of Chinese herbs. The main related meridians were the liver, spleen, and kidney meridians. The properties of Chinese herbs used most were mainly warm, flat, and cold, while the flavors of herbs were mainly bitter, pungent, and sweet. The main patterns of AS included the damp heat, phlegm stasis, and neck arthralgia. The most commonly used herbs for AS were Chuanniuxi (Cyathulae Radix), Huangbo (Phellodendri Chinensis Cortex), Cangzhu (Atractylodis Rhizoma), Qinjiao (Gentianae Macrophyllae Radix), Gancao (Glycyrrhizae Radix et Rhizoma), Huangqi (Astragali Radix), and Chuanxiong (Chuanxiong Rhizoma). The most common effect of the herbs was “promoting blood circulation and removing blood stasis”, followed by “supplementing deficiency (Qi supplementing, blood supplementing, and Yang supplementing)”, and “dispelling wind and dampness”. The data were analyzed with the support ≥ 15% and confidence = 100%, and after de-duplication, five second-order association rules, 39 third-order association rules, 39 fourth-order association rules, and two fifth-order association rules were identified. The top-ranking association rules of each were “Cangzhu (Atractylodis Rhizoma) → Huangbo (Phellodendri Chinensis Cortex)” “Cangzhu (Atractylodis Rhizoma) + Chuanniuxi (Cyathulae Radix) → Huangbo (Phellodendri Chinensis Cortex)” “Chuanniuxi (Cyathulae Radix) + Danggui (Angelicae Sinensis Radix) + Gancao (Glycyrrhizae Radix et Rhizoma) → Qinjiao (Gentianae Macrophyllae Radix)” and “Chuanniuxi (Cyathulae Radix) + Danggui (Angelicae Sinensis Radix) +Gancao (Glycyrrhizae Radix et Rhizoma) + Huangbo (Phellodendri Chinensis Cortex) → Qinjiao (Gentianae Macrophyllae Radix)”, respectively. Five clusters were obtained using cluster analysis of the top 30 herbs. The herbs were mainly drying dampness, supplementing Qi, and promoting blood circulation. The main prescriptions of AS were Ermiao San (二妙散), Gegen Jianghuang San (葛根姜黄散), and Huangqi Chongteng Yin (黄芪虫藤饮). The herbs of core prescription included Cangzhu (Atractylodis Rhizoma), Chuanniuxi (Cyathulae Radix), Gancao (Glycyrrhizae Radix et Rhizoma), Huangbo (Phellodendri Chinensis Cortex), Mugua (Chaenomelis Fructus), Qinjiao (Gentianae Macrophyllae Radix), Danggui (Angelicae Sinensis Radix), and Yiyiren (Coicis Semen).

Conclusion

Clearing heat and dampness, relieving collaterals and pain, and invigorating Qi and blood are the most commonly used therapies for the treatment of AS by Professor XIONG Jibo. Additionally, customized NLP model could improve the efficiency of data mining in TCM.

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来源期刊
Digital Chinese Medicine
Digital Chinese Medicine Medicine-Complementary and Alternative Medicine
CiteScore
1.80
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126
审稿时长
63 days
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