基于数据挖掘的6种疼痛病方剂用药规律比较研究
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摘要
该文以数据挖掘研究和比较腹痛、头痛、胃脘痛、胁痛、心痛、腰痛6种疼痛病方剂的用药规律,以期为相关中药配伍机制研究和中药新复方开发提供参考。通过收集、整理《中医方剂大辞典》中治疗6种疼痛病的方剂共2 443首,利用Apriori关联规则算法,以置信度、提升度、支持度为指标对方剂进行数据挖掘,研究治疗不同类型疼痛的核心中药及其配伍规律。研究结果显示,各类疼痛病治疗中常用补虚药(如甘草、当归)、理气药(如木香)和活血化瘀药(如川芎),但针对不同疼痛病的用药存在一定程度的差异,如腹痛、胃脘痛中厚朴的使用频次较高,头痛中防风的使用频次较高。治疗腹痛提升度较大的潜在规则为红花→当归等,而头痛中则为黄芪→甘草等,胃脘痛中则为麦芽→陈皮等,胁痛中则为龙胆→柴胡等,腰痛中则为丁香→麝香等。研究结果显示,通过应用数据挖掘方法对6种疼痛病方剂组成进行对比研究,能有效地反映6种疼痛病用药规律的异同,并能发现潜在的中药配伍规律。
To study and compare the medication regularities of traditional Chinese medicine formulas(TCMFs) for the six kinds of pains,namely abdominal pain,headache,epigastric pain,hypochondriac pain,heartache and backache,using a data-mining approach,in order to provide reference for relevant studies for the compatibility mechanism and new compound development of related TCMFs. A total of 2 443 TCMFs for pains were collected from the Dictionary of Chinese Medicine Prescriptions,and analyzed using the Apriori algorithm based on three indicators,namely confidence,lift and support,so as to study pivotal traditional Chinese medicines(TCMs) for each pain and their compatibility regularities. The results showed that deficiency tonifying medicines(such as Glycyrrhizae Radix et Rhizoma and Angelicae Sinensis Radix),Qi-regulating medicines(like Aucklandiae Radix) and blood circulation promoting medicines(like Chuanxiong Rhizoma) were commonly used TCMs for pains. However,there were many differences between drugs for various kinds of pains. For example,Magnoliae Officinalis Cortex was used frequently for abdominal pain and epigastric pain,while Saposhnikoviae Radix was used frequently for headache. The latent association rules with significant lift included Carthami Flos → Angelicae Sinensis Radix for abdominal pain,Astragali Radix → Glycyrrhizae Radix et Rhizoma for headache,Hordei Fructus Germinatus → Citri Reticulatae Pericarpium for epigastric pain,Gentianae Radix et Rhizoma → Bupleuri Radix for hypochondriac pain,and Caryophylli Flos → Moschus for backache. This study showed that based on the TCMFs from the Dictionary of Chinese Medicine Prescriptions,the data-mining approach can reveal the differences and similarities in the use of TCMs for the six kinds of pains,and discover the latent composition regularities of relevant TCMs.
To study and compare the medication regularities of traditional Chinese medicine formulas(TCMFs) for the six kinds of pains,namely abdominal pain,headache,epigastric pain,hypochondriac pain,heartache and backache,using a data-mining approach,in order to provide reference for relevant studies for the compatibility mechanism and new compound development of related TCMFs. A total of 2 443 TCMFs for pains were collected from the Dictionary of Chinese Medicine Prescriptions,and analyzed using the Apriori algorithm based on three indicators,namely confidence,lift and support,so as to study pivotal traditional Chinese medicines(TCMs) for each pain and their compatibility regularities. The results showed that deficiency tonifying medicines(such as Glycyrrhizae Radix et Rhizoma and Angelicae Sinensis Radix),Qi-regulating medicines(like Aucklandiae Radix) and blood circulation promoting medicines(like Chuanxiong Rhizoma) were commonly used TCMs for pains. However,there were many differences between drugs for various kinds of pains. For example,Magnoliae Officinalis Cortex was used frequently for abdominal pain and epigastric pain,while Saposhnikoviae Radix was used frequently for headache. The latent association rules with significant lift included Carthami Flos → Angelicae Sinensis Radix for abdominal pain,Astragali Radix → Glycyrrhizae Radix et Rhizoma for headache,Hordei Fructus Germinatus → Citri Reticulatae Pericarpium for epigastric pain,Gentianae Radix et Rhizoma → Bupleuri Radix for hypochondriac pain,and Caryophylli Flos → Moschus for backache. This study showed that based on the TCMFs from the Dictionary of Chinese Medicine Prescriptions,the data-mining approach can reveal the differences and similarities in the use of TCMs for the six kinds of pains,and discover the latent composition regularities of relevant TCMs.
引文
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[13]穆启运,蓝涛华,徐方方,等.正交试验优选川芎和细辛挥发油的β-环糊精微囊萃取工艺及成分分析[J].中国实验方剂学杂志,2014,20(20):1.
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[15]刘杨,张方博,唐仕欢,等.基于数据挖掘的芍药治疗心系疾病“成分-靶标-通路”分析[J].中国中药杂志,2018,43(7):1310.
[16]王敏,李宇航.从“血虚”论小柴胡汤及柴胡四物汤妇科应用[J].世界中西医结合杂志,2016,11(12):1742.
[17]郑琴,魏韶锋,熊文海,等.川芎在治疗头痛中成药中的组方应用分析[J].中草药,2013,44(19):2777.
[18]陈婷,宿树兰,钱叶飞,等.乳香-没药配伍前后汤液理化参数变化与化学成分的关联分析[J].中成药,2012,34(8):1529.
[19]王雄,吴金虎.大麦芽的研究概述[J].中药材,2010,45(9):1503.
[20]赵莹,赵瑞芝,陈有军,等.醋柴胡对龙胆苦苷在小鼠体内分布的影响[J].中国实验方剂学杂志,2015,21(17):71.
[2]唐谦,王林,朱焱. 2016年贵阳市社区中老年人慢性疼痛流行病学特征分析[J].现代预防医学,2017,44(18):3330.
[3]彭怀仁.中医方剂大辞典[M].北京:人民卫生出版社,1993.
[4] Hahsler M,Grun B,Hornik K. Arules———a computational environment for mining association rules and frequent item sets[J].J Stat Softw,2005,14(15):1.
[5]梁宜,孙晶,周杰,等.方剑乔教授从“瘀”“虚”角度辨识慢性疼痛病机[J].浙江中医药大学学报,2017,41(12):941.
[6]廖尖兵,刘淼,王文譞,等.探微慢性疼痛中医病、机、证、治思路[J].中华中医药杂志,2018,33(4):1441.
[7]张建伟,王苹.《金匮要略》对腹痛的辨治用药探析[J].天津中医药大学学报,2009,28(4):173.
[8]姚欣艳,李点,刘朝胜,等.熊继柏教授辨治头痛经验[J].中华中医药杂志,2015,30(7):2419.
[9]廖美媛,樊光辉.偏头痛的中医治疗近况[J].现代中西医结合杂志,2014,23(2):215.
[10]王娟娟,秦雪梅,高晓霞,等.杜仲化学成分、药理活性和质量控制现状研究进展[J].中草药,2017,48(15):3228.
[11]尹丹丹,杨沫,王运来,等.基于川芎内生枯草杆菌初步研究川芎中川芎嗪的来源[J].中国中药杂志,2018,43(19):3893.
[12]郭思宇,刘明平,周赛妮,等.川芎-天麻不同配比对血瘀型偏头痛大鼠药效学分析[J].中国实验方剂学杂志,2017,23(17):127.
[13]穆启运,蓝涛华,徐方方,等.正交试验优选川芎和细辛挥发油的β-环糊精微囊萃取工艺及成分分析[J].中国实验方剂学杂志,2014,20(20):1.
[14]胡志妍,齐天,杨光,等.白芷、川芎药对配伍挥发油成分的GC-MS分析[J].第二军医大学学报,2014,35(2):177.
[15]刘杨,张方博,唐仕欢,等.基于数据挖掘的芍药治疗心系疾病“成分-靶标-通路”分析[J].中国中药杂志,2018,43(7):1310.
[16]王敏,李宇航.从“血虚”论小柴胡汤及柴胡四物汤妇科应用[J].世界中西医结合杂志,2016,11(12):1742.
[17]郑琴,魏韶锋,熊文海,等.川芎在治疗头痛中成药中的组方应用分析[J].中草药,2013,44(19):2777.
[18]陈婷,宿树兰,钱叶飞,等.乳香-没药配伍前后汤液理化参数变化与化学成分的关联分析[J].中成药,2012,34(8):1529.
[19]王雄,吴金虎.大麦芽的研究概述[J].中药材,2010,45(9):1503.
[20]赵莹,赵瑞芝,陈有军,等.醋柴胡对龙胆苦苷在小鼠体内分布的影响[J].中国实验方剂学杂志,2015,21(17):71.