基于数据挖掘治疗宫颈高危型HPV感染的用药规律OA

Objective To explore the rule of drug use in treating high-risk cervical human papilloma virus(HPV)infection by using data mining method.Methods Medical records and prescriptions of patients with high-risk HPV infection treated at Wang Jin Outpatient Department of Lishui Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University from January 1,2021 to December 1,2022 were collected.SPSS Modeler 18.0 and SPSS 25.0 were used for drug use frequency,association rules,clustering and other data analysis.Results A total of 100 prescriptions were included,involving a total of 162 Chinese materia medicas,with a total of 1445 times of Chinese materia medicas.The drugs with the highest frequency of use were mainly tonic drugs,antipyretic drugs,regulating vital energy drugs and tranquillizing drugs.Complex network analysis showed that there were close correlation among hedyotis,dried tangerine peel,immature tangerine peel,silktree albizia bark and buffalo horn.Three potential new prescriptions were explored.Conclusion The disease was mostly caused by deficiency in origin and excess in pathological products,and the treatment was to treat both symptoms and root causes,and to attack and supplement,with the treatment of clearing heat and removing toxicity,eliminating dampness,benefiting qi for activating blood circulation and nourishing yin,supplemented by nourishing heart for tranquillization.