基于复杂网络与PCA降维和K-Means聚类探讨治疗COVID-19组方配伍特点

Research on the Compatible Features of Prescriptions in Treating COVID-19 Based on Complex Network and PCA Dimension Reduction and K-Means Algorithm Clustering

目的探讨治疗新型冠状病毒肺炎(COVID-19)处方的组方配伍规律。方法收集国家及各省市卫生健康委、中医药管理局颁布的关于疫情确立的中医药诊疗方案,以及中英文数据库中已公开发表的相关文献,整理其中治疗新型冠状病毒肺炎的方药,运用关联规则、药物复杂网络关系和基于主成分分析(PCA)降维和K-Means算法进行药物聚类,分析组方核心药物和配伍规律。结果纳入治疗方剂共639首,共涉及单味中药237味。频繁项集结果显示支持度较高的药物有甘草、杏仁、麻黄、石膏、黄芩、半夏、藿香、茯苓、陈皮、苍术、厚朴、连翘等,主要为宣降肺气药、清肺解毒药、芳香化湿药等,并形成支持度较高的药对、药组如麻黄、杏仁、石膏、黄芩配伍,茯苓、半夏、藿香、陈皮配伍等;频繁且相关结果显示,有些药对支持度不高但关联紧密,如附子、山茱萸、人参,草果、槟榔等组成的药对;复杂网络结果显示以麻黄、杏仁、石膏、甘草、黄芩为核心,与厚朴、苍术、草果、槟榔、茯苓、连翘、半夏、藿香、陈皮等形成紧密关系;聚类分析获得6类药物社团,具有清肺解毒、芳香化湿、辟秽化浊、通腑解毒祛瘀、回阳救逆、补气养阴等配伍特征。结论结合不同的数据挖掘方法可以从不同层面反映COVID-19用药与配伍特点,为中医药治疗疫病提供资料及依据。

OBJECTIVE To explore the compatible characteristics of prescriptions in treating COVID-19.METHODS The traditional Chinese Medicine(TCM)treatment programs for COVID-19 issued by the National and Provincial Health Commission and National Administration of TCM,as well as the publicly published literature of Chinese and English database documents were collected.The compatible characteristics and core herbs were analyzed by data-mining methods including association rules,complex herb network,as well as drug clustering by PCA dimension reduction and K-Means algorithm.RESULTS A total of 639 prescriptions were included,involving 237 Chinese herbs.The results of frequent itemsets showed that Chinese herbs with high support were Glycyrrhizae radix et rhizoma,Armeniacae semen amarum,Ephedrae herba,Gypsum fibrosum,Scutellariae radix,Pinelliae rhizoma,Pogostemonis herba,Poria,Citri reticulatae pericarpium,Atractylodis rhizoma,Magnoliae officinalis cortex,Forsythiae fructucs,etc.The functions were dispersing and lowering lung qi,resolving dampness with aroma,as well as clearing lung and detoxifying,etc.The herb pairs and groups with high support mainly concentrated on the compatibility among Ephedrae herba,Armeniacae semen amarum,Gypsum fibrosum and Scutellariae radix,the compatibility among Poria,Pinelliae rhizoma,Pogostemonis herba and Citri reticulatae pericarpium,etc.The frequent and relevant results showed that some Chinese herbs worked closely with each other even with low support such as herb pairs composed from Aconiti lateralis radix praeparata,Corni fructus,Ginseng radix et rhizoma,Tsaoko fructus,Arecae semen,etc.The complex network results showed that the core herbs were Glycyrrhizae radix et rhizoma,Armeniacae semen amarum,Ephedrae herba,Gypsum fibrosum and Scutellariae radix,which formed complex network relationship with Magnoliae officinalis cortex,Atractylodis rhizoma,Tsaoko fructus,Arecae semen,Poria,Forsythiae fructucs,Pinelliae rhizoma,Pogostemonis herba,Citri reticulatae pericarpium,etc.6 kinds of drug groups were gathered out with cluster analysis,which had the compatibility characteristics of clearing heat and removing toxicity in the lung,resolving dampness with aromatics,etc.CONCLSION Combined with different data mining methods,the characteristics of medication and compatibility in treating COVID-19 can be reflected from multiple angles,providing a basis for TCM in treating epidemic diseases.