CHENG Yanqi, CHEN Xi, WU Yuqin, et al. Analysis on rules of TCM prescriptions in treating and preventing COVID-19 based on data mining. [J]. Shanghai Journal of Traditional Chinese Medicine 54(5):32-39(2020)
DOI:
CHENG Yanqi, CHEN Xi, WU Yuqin, et al. Analysis on rules of TCM prescriptions in treating and preventing COVID-19 based on data mining. [J]. Shanghai Journal of Traditional Chinese Medicine 54(5):32-39(2020) DOI: 10.16305/j.1007-1334.2020.05.098.
Analysis on rules of TCM prescriptions in treating and preventing COVID-19 based on data mining
Objective:To analyze and summarize rules of traditional Chinese medicine (TCM) prescriptions in the prevention and treatment of non-critical coronavirus disease 2019 (COVID-19) (including mild, moderate and severe types) by data mining through multiple versions of Diagnosis and Treatment protocol for Coronavirus Disease 2019 (hereinafter referred to as “COVID-19”) Prevention and Control Program issued by the State and the health committees of all provinces, autonomous regions and municipalities directly under the Central Government and the Administration of Traditional Chinese Medicine (or medical and health management institutions). MethodsTCM prescriptions in the multiple versions of Diagnosis and Treatment Protocol for COVID-19 issued by the state and 24 provinces, autonomous regions and municipalities directly under the Central Government were retrieved. The prescription database was established after screening the source data, and the data analysis and mining were carried out by using frequency analysis, Apriori algorithm in association rules and complex system entropy clustering algorithm methods embedded in TCMISS (V2.0.1), so as to analyze the core medicinal herbs and the corresponding properties, tastes, tropisms, medication modes and generate new prescriptions. Results:①A total of 149 formulas and 146 kinds of medicinal herbs were analyzed after screening. It was found that the top 7 medicinal herbs used frequently were Gancao (Glycyrrhizae Radix), Ku Xingren (Armeniacae Semen), Mahuang (Ephedrae Herba), Chenpi (Citri Reticulatae Pericarpium), Shigao (Gypsum Fibrosum), Cangzhu (Atractylodis Rhizoma) and Huoxiang (Agastaches Herba) respectively. Most medicinal herbs have bitter taste, warm property and enter the lung, spleen, stomach and heart meridians. ②According to the preliminary analysis of association rules, the medicinal pairs were ranked from high to low in frequency, and the top three were “Ku Xingren (Armeniacae Semen) & Mahuang (Ephedrae Herba)”, “Gancao (Glycyrrhizae Radix) & Ku Xingren (Armeniacae Semen)”, and “Shigao (Gypsum Fibrosum) & Ku Xingren (Armeniacae Semen)”. ③There were 11 medicinal pairs with correlation coefficient above 0.040, such as “Mahuang (Ephedrae Herba) & Chishao (Paeoniae Radix Rubra)”, “Mahuang (Ephedrae Herba) & Baizhu (Atractylodis macrocephalae Rhizoma)” and “Mahuang (Ephedrae Herba) & Renshen (Ginseng Radix)”, etc. ④According to the analysis of prescriptions in types, San’ao decoction was used as the core formula for the treatment of mild cases together with Huoxiang Zhengqi powder, Dayuan decoction and Fangfeng Tongsheng powder. Maxing Shigan decoction, Dayuan decoction and Yinqiao Powder were used jointly for the treatment of moderate cases. The combination of Maxing Shigan decoction, Xuanbai Chengqi decoction and Sini formulas for heart resurrection was used for the treatment of severe cases. ⑤According to the complex systems entropy cluster algorithm, 14 medicinal groups containing 3 to 4 core medicinal herbs were deduced, such as “Tinglizi (Lepidii Semen), Taoren (Persicae Semen) and Baizhu (Atractylodis macrocephalae Rhizoma)”, “Tinglizi (Lepidii Semen), Dahuang (Rhei Radix et Rhizoma) and Baizhu (Atractylodis macrocephalae Rhizoma)”, “Lianqiao (Forsythiae Fructus), Jinyinhua (Lonicerae Flos) and Lugen (Phragmitis Rhizoma)”, etc; and 7 new prescriptions were generated, such as “Tinglizi (Lepidii Semen), Taoren (Persicae Semen), Baizhu (Atractylodis macrocephalae Rhizoma), Chishao (Paeoniae Radix Rubra) and Gualou (Trichosanthis Fructus)”, “Ku Xingren (Armeniacae Semen), Huangqi (Astragali Radix), Taoren (Persicae Semen), Mahuang (Ephedrae Herba) and Shigao (Gypsum Fibrosum)”, “Chenpi (Citri Reticulatae Pericarpium), Banxia (Pinelliae Rhizoma), Huoxiang (Agastaches Herba), Fuling (Poria), Dahuang (Rhei Radix et Rhizoma), Shigao (Gypsum Fibrosum) and Gualou (Trichosanthis Fructus)”, etc. Conclusion:At present, the rules of the recommended prescriptions in multiple versions of Diagnosis and Treatment Protocol for COVID-19 focus on eliminating phlegm, relieving cough and asthma, relieving exterior and regulating qi, clearing heat and resolving dampness, invigorating qi, etc., with the treatment of lung as the key and treatment of the spleen and stomach as the complementation. During the treatment period, the rules of prescriptions for the treatment of three types vary:the mild type focuses on relieving exterior and eliminating dampness, the moderate type focuses on relieving both the exterior and interior, eliminating dampness and clearing heat and the severe type focuses on purging heat and attacking interior, invigorating qi and restoring yang. The statistical analysis results are basically consistent with the consensus of experts, and some new prescription rules with potential clinical value have also been found, which can provide theoretical basis for clinical treatment and new drug development.
关键词
新型冠状病毒肺炎新型冠状病毒处方用药规律中药数据挖掘关联规则聚类算法
Keywords
COVID-19SARS-CoV-2rules of prescriptionsChinese herbal medicinedata miningassociation rulesclustering algorithm