1. Decision tree model based prediction of the efficacy of acupuncture in methadone maintenance treatment
- Author
-
Yu Dong, Baochao Fan, Enliang Yan, Rouhao Chen, Xiaojing Wei, Jie Zhan, Jingchun Zeng, Hao Wen, and Liming Lu
- Subjects
methadone maintenance treatment ,machine learning ,decision tree ,feature importance ,acupuncture ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
BackgroundPatients with MMT often face difficulties such as sleep disturbance, headaches, and difficulty in complete abstinence from drugs. Research has shown that acupuncture can mitigate side effects while attenuating methadone dependence. It also has a synergistic and attenuated effect on methadone maintenance treatment (MMT). Exploring the predictors of the efficacy of acupuncture intervention in MMT might help clinicians and patients promote acupuncture-assisted participation in MMT, and improve clinical treatment strategies for MMT.ObjectiveTo describe the effect of potential predictors on MMT after acupuncture intervention by building a decision-tree model of data from A Clinical Study of Acupuncture-assisted MMT.Design, setting, and participantsIn this randomized controlled trial, 135 patients with MMT underwent acupuncture at the Substance Dependence Department of Guangzhou Huiai Hospital in Guangzhou, Guangdong Province, China.InterventionA total of 135 patients were 1:1 randomly assigned to either an acupuncture plus routine care group (acupuncture plus methadone) or a routine group (methadone only) for 6 weeks, and followed up for 10 weeks. Sex, age, education level, route of previous opioid use, years of opioid use, and MMT time were recorded before the trial.Outcome measurements and statistical analysisAll analyses were based on the intention-to-treat (ITT) population. The two decision tree models used the change of methadone dosage and the VAS score for opioid desire as response variables, respectively, and the evaluation criteria were positive effect (decreased by ≥20%) and no effect (decreased by
- Published
- 2022
- Full Text
- View/download PDF