关键词: 抽动障碍, 用药规律, 数据挖掘, 王素梅

Abstract: Objective To study the medication law of Professor Wang Sumei in the treatment of tic disorders (TD) based on data mining technology in order to provide ideas for the clinical treatment of TD. Methods Professor Wang Sumei's TCM prescription data for TD were collected, and the Famous Veteran Chinese Medicine Practitioner Clinical Diagnosis Information Collection System was used to carry out data mining on the selected TCM prescriptions, including drug frequency, efficacy, property, taste and meridian, complex network analysis and so on.Results Through collection and screening, a total of 1 500 case histories were included. The top 5 symptom frequencies of TD were blinking, babbling, shrugging, neck-twisting and frowning. Spleen deficiency and liver hyperactivity was the main type of syndrome. The top 5 herbal medicines were Divaricate saposhniovia root, Fineleaf schizonepeta herb, Pawpaw, Eriocaulon buergerianum, Japanese Clubmoss Herb. As for the efficacy of drugs, anti-wind medicines were used most frequently followed by painkillers and liver-calming medicines. The medicines were mainly warm in property, followed by mild and cold; they mainly pungent in taste, followed by bitter and sweet; they functioned mainly in the liver meridian, followed by the lung and spleen meridians. The drugs with efficacy of clinical control and apparent efficacy in this study were mainly Divaricate saposhniovia root, Fineleaf schizonepeta herb, Eriocaulon buergerianum, Tangerine peel, Pinellia ternata, Pawpaw, etc.Conclusion Professor Wang Sumei believes that the pathogenesis of TD is spleen deficiency and phlegm aggregation as well as liver hyperactivity and wind movement. The disease is mainly in liver and spleen, and the treatment is mainly to strengthen spleen and calm liver, stop wind and dredge collaterals, which can provide some reference for the clinical treatment of TD.

Key words:

Tic disorders, Medication law, Data mining, Wang Sumei