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基于数据挖掘分析神经根型颈椎病气滞血瘀证的用药规律

Drug use rules in cervical spondylosis of nerve root with qi stagnation and blood stasis syndrome based on data mining
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摘要 目的归纳总结中医药治疗神经根型颈椎病气滞血瘀证的用药规律。方法检索中国知网、万方数据库、PubMed数据库等,搜集近20年中药复方治疗神经根型颈椎病气滞血瘀证的相关文献,提取出具有完整中药组成的方药及其具体剂量,统计其药物频率、药量、性味归经、类别,并对高频中药进行关联规则、聚类分析。结果共纳入61篇文献,包含61个处方,102味中药。使用频次前5位的中药及其剂量分别是甘草6 g、当归15 g、川芎10 g、白芍15 g、葛根20 g。药物主要归于肝经,性味以辛温为主,功效以活血调经,缓急止痛为主。支持度>0.50、置信度>0.85的关联项集产生的关联度较高的药物组合为白芍-葛根,当归-川芎,葛根-甘草。支持度>0.10、置信度>0.60的关联项集产生的关联度较高的药物剂量组合为川芎15 g与当归15 g,川芎15 g与红花15 g,葛根30 g与甘草6 g。中药及中药剂量聚类分析显示,活血化瘀、行气止痛为该聚类中药物组合特点,其中葛根、伸筋草、丹参、当归、白芍、延胡索、桂枝、黄芪用量较大(≥15 g)。方剂及方剂剂量聚类分析显示,方剂多为以川芎-当归、桃仁-红花、白芍-甘草等为核心的药对组合,以“桃红四物汤”为代表的活血化瘀类经方应用较多。结论本研究初步总结了单味中药及中药复方治疗神经根型颈椎病气滞血瘀证的用药规律,用药重在疏肝气、调气血、化瘀滞,以活血化瘀为主要治则,行气止痛为基本大法,辅以通络、止痛、解筋舒肌,为临床运用中药治疗颈椎病提供了参考与理论依据。 Objective To summarize the medication rule of traditional Chinese medicine in treating cervical spondylosis of nerve root with qi stagnation and blood stasis syndrome.Methods The literature related to the treatment of qi stasis and blood stasis syndrome of nerve root type cervical spondylosis by TCM compound in the past 20 years were searched from China National Knowledge Infrastructure,Wanfang Database and PubMed database,and so on,and the prescriptions with complete TCM composition and their specific dosage were extracted.The drug frequency,drug dosage,nature and taste,meridian,meridial distribution were recorded,and association rules and cluster analysis were conducted on the high-frequency traditional Chinese medicine(TCM).Results A total of 61 literatures were included,including 61 prescriptions and 102 TCM drugs.The top 5 most frequently used Chinese herbs were Gancao 6 g,Danggui 15 g,Chuanxiong 10 g,Baishao 15 g,Gegen 20 g.The drugs,mainly entering the liver channel,had warm nature and pungent taste,and the main functions of promoting blood and regulating the menstrual cycle,and relieving pain.With support>0.50 and confidence>0.85,the drug combinations with high correlation were Baishao-Gegen,Danggui-Chuanxiong,Gegen-Gancao.With support>0.10 and confidence>0.60,the drug dose combinations with high correlation were Chuanxiong 15 g and Danggui 15 g,Chuanxiong 15 g and Honghua 15 g,Gegen 30 g and Gancao 6 g.The clustering analysis of TCM and TCM dose showed the efficacy was mainly promoting blood circulation and removing blood stasis,activating qi and relieving pain.The dosage of Gegen,Shenjincao,Danshen,Danggui,Baishao,Yanhusuo,Guizhi,Huangqi were higher(≥15 g).In the study of prescription and prescription dose cluster analysis,the prescription structure mainly consisted of the combinations of core drug pair,such as Chuanxiong-Danggui,Taoren-Honghua,Biashao-Gancao,and the experienced prescription functioning in activating blood circulation and removing blood stasis was represented by"Taohong Siwu Decoction".Conclusion This study initially summarizes the medication rules of single TCM and TCM combination in treating syndrome of qi stagnation and blood stasis of nerve root type cervical spondylosis.The drug use focuses on soothing liver qi,regulating qi and blood,and removing blood stasis.The treatment principle is main based on promoting blood and removing stasis,activating qi and relieving pain,supplemented by dredging collaterals,pain relief,tendon and muscle relaxation,providing reference and theoretical basis for the clinical application of TCM in the treatment of cervical spondylosis.
作者 王资涵 陈鑫 张伯滔 康然 朱垚 WANG Zihan;CHEN Xin;ZHANG Botao;KANG Ran;ZHU Yao(the Affiliated Hospital of Integrated Traditional Chinese and Western Medicine of Nanjing University of Chinese Medicine,Nanjing,Jiangsu,210000;Jiangsu Province Academy of Traditional Chinese Medicine,Nanjing,Jiangsu,210000;the First Clinical College of Nanjing University of Chinese Medicine,Nanjing,Jiangsu,210000)
出处 《实用临床医药杂志》 2023年第17期110-116,共7页 Journal of Clinical Medicine in Practice
基金 国家自然科学基金项目(81772356)。
关键词 神经根型颈椎病 气滞血瘀证 中医药 名老中医医案 数据挖掘 cervical radiculopathy syndrome of qi stagnation and blood stasis traditional chinese medicine medical records of distinguished veteran Chinese doctors data mining
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