Background Levodopa equivalent dopaminergic dose (LEDD) reduction after subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson’s disease varies widely. Identifying predictors may guide patient selection and programming. Our objectives were to identify predictors of LEDD reduction and to test whether motor improvement mediates this association. Methods Data from 144 patients treated by STN-DBS were analysed. Predictors of LEDD reduction were selected using the Boruta algorithm, a machine-learning method comparing variable importance to randomised features and then tested in a structural equation model for direct and motor-mediated effects. Results Mean LEDD reduction was 41.7% (±38.2%) and motor improvement was 48.6% (±26.7%) at 1 year. Among the four predictors identified by Boruta, lower baseline LEDD (β=0.39, p=0.001), greater axial impairment (β=−0.25, p=0.003) and higher total volume of tissue activated (β=−0.17, p=0.031) were directly associated with lower LEDD reduction, independent of motor improvement. Sensorimotor STN overlap was not directly linked to LEDD reduction but was positively associated with motor improvement (β=0.34, p=0.001), which showed a trend-level effect on LEDD reduction (β=0.16, p=0.065). The total effect of sensorimotor STN overlap on LEDD reduction was not significant. Discussion Dopaminergic dose reduction after STN-DBS is constrained by preoperative axial symptoms and stimulation spread, independently of motor improvement, while sensorimotor STN overlap improves motor symptoms but not dose reduction. Integrating motor phenotype with anatomical guidance may enhance medication management post DBS.
Lanore et al. (2026) studied this question.