基于数据挖掘的缺血性中风中医处方用药规律研究

来源:用户上传      作者:黄辛迪 丁长松 苏�⒑� 周德生 涂海军

　　 摘要：目的 基于稻萃诰蚣际醴治鲅芯俊吨蟹绮×挤酱笕》治疗缺血性中风用药规律。方法 遴选《中风病良方大全》治疗缺血性中风处方，对数据进行规范化处理，构建缺血性中风处方数据库;并借助Python数据分析对用药频次、药性频次分布、药物功效类别的频次及分布进行统计，应用Apriori关联规则算法等进行数据挖掘，构建高频药对药组关联组合模型，探索其用药趋向性和核心药物。结果 遴选948首治疗缺血性中风处方，共845味药材9616次总用频次。挖掘前50味高频常用药材，使用频次前10位的中药依次为川芎、甘草、当归、丹参、黄芪、地龙、红花、赤芍、石菖蒲、牛膝，川芎，其中以温32.8%、平27.2%、寒性26.1%为主，以甘48.7%、苦41.2%、辛味38.1%为主，以肝68.3%、脾40.5%、心经36.7%为主，用药功效中以补虚药25.29%、活血化瘀药23.14%、平肝息风药14.79%为主;基于用药药性属性，高频用药聚类得到8大类。当满足最小支持度5%且最小置信度60%时，关联规则分析结果得到药对关联规则18条，其中置信度前3位的药对规则为远志→石菖蒲、陈皮→半夏、红花→川芎;关联规则分析结果得到药对主要3味关联药组20条，其中置信度前3位的药对规则为桃仁+地龙→红花+桃仁 赤芍→红花、桃仁+当归→红花。结论 中医治疗缺血性中风辨证用药以补气补血、滋阴活血、化痰行气为法。基于数据挖掘技术分析缺血性中风用药规律，对于临床用药指导与应用具有重要价值。
　　关键词：数据挖掘;缺血性中风;Apriori 算法;关联规则;用药规律
　　中图分类号：R743.3 文献标志码：A 文章编号：1007-2349（2022）01-0023-06
　　Research on TCM Prescription Medication Rules of Ischemic Stroke Based on Data Mining
　　HUANG Xin-di1， DING Chang-song1， SU Qi-hou1， ZHOU De-sheng1， TU Hai-jun1
　　（1. School of Information Science and Engineering， Hunan University of Traditional Chinese Medicine， Changsha， 410208， China; 2. Hunan University of Traditional Chinese Medicine， Changsha， 410208， China; 3. The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine， Changsha， 410208， China; 4. School of Biology， Hunan University， Changsha， 410208， China）
　　【Abstract】Objective： To analyze and study the medication rules of the treatment of ischemic stroke in A Complete Collection of Effective Prescription for Stroke by basing on data mining technology. Methods： The prescriptions for the treatment of ischemic stroke in the collection were selected to standardize data processing， and construct a database of ischemic stroke prescription. By using Python data analysis， the frequency of medication， the frequency distribution of drug properties and the frequency and distribution of drug efficacy categories were made statistically and by using Apriori association rule algorithm， the data mining was conducted to build a high-frequency drug-to-drug group association combination model and explore its drug trend and core drugs. Results： The first 948 prescriptions for the treatment of ischemic stroke were selected， and 845 medicinal materials were used with a total frequency of 9616 times. The top 50 high-frequency and commonly used medicinal materials were excavated. The top 10 used Chinese medicines were Ligustici， Licorice， Angelica， Salvia， Astragalus， Earthworm， Safflower， Red Peony， Acorus tatarinowii and Achyranthes bidentata， among which the warm property was 32.8， mild-nature 27.2%， cold 26.1%， mainly sweet 48.7%， bitter 41.2%， pungent 38.1%， and mainly for liver 68.3%， spleen 40.5% and heart meridian 36.7%. The efficacy of the medicine was 25.29 % of deficiency-tonic， 23.14% of activating blood and removing blood stasis drugs and 14.79% of calming liver and dispelling wind drugs. Based on the properties of the medications， the high-frequency medications clustered into 8 categories. When the minimum support degree was 5% and the minimum confidence degree was 60%， the association rule analysis results obtained 18 drug pair association rules， among which the top 3 drug pair rules of the confidence were Polygala→Acorus tatarinowii， Tangerine Peel→ Pinellia， Safflower→Ligustici. The association rule analysis results showed that there were 20 drug pairs related to the main 3 flavor drug groups， among which the top 3 drug pair rules of the confidence level were peach kernel + earthworm→safflower + peach kernel， red peony→safflower， peach kernel + angelica→safflower. Conclusion： The TCM treatment of ischemic stroke is based on the methods of invigorating qi and blood， nourishing yin and promoting blood circulation， resolving phlegm and promoting qi. The study is of great value for clinical medication guidance and application.
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