ORIGINAL RESEARCH article
Front. Aging Neurosci.
Sec. Parkinson’s Disease and Aging-related Movement Disorders
Volume 17 - 2025 | doi: 10.3389/fnagi.2025.1511845
This article is part of the Research TopicMultifactorial balance assessment, falls prevention and rehabilitationView all 12 articles
Predictive Model for the Therapeutic Effect of Bilateral Subthalamic Nucleus Deep Brain Stimulation on Freezing of Gait in Parkinson's Disease
Provisionally accepted
Qi Limuge1
Jiang Yongqiang2*- 1Inner Mongolia Medical University, Hohhot, China
- 2Inner Mongolia Third Hospital, Hohhot, China
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Background: Freezing of gait (FOG) is a major disabling symptom that affects the quality of life of patients with Parkinson’s disease (PD). To date, notions about the effects of subthalamic deep brain stimulation (STN-DBS) on FOG remain controversial. Therefore, we developed a prediction model based on the influence of bilateral deep brain stimulation (DBS) of the subthalamic nucleus (STN) on FOG in patients with PD. Methods: We collected data from 104 PD participants with FOG who underwent STN-DBS at Xuanwu Hospital between September 2017 and June 2022. The patients were divided into training set (70%; n = 68) and validation set (30%; n = 36). The selected characteristics in the LASSO regression were used in multivariate logistic regression to build the prediction model. Receiver operating characteristic (ROC) curves for the training and validation sets were constructed to verify the model efficiency. Results: Independent variables in the prediction model included Unified Parkinson’s Disease Rating Scale II (UPDRSII), UPDRSIV, Legs rigidity, Montreal Cognitive Assessment (MoCA) score, and Mini Mental State Examination (MMSE) score. The prediction model formula is as follows: Logit(y) = -1.0043 + 0.159 × UPDRSII + 0.030 × UPDRSIV - 1.726 × Legs rigidity + 0.121 × MoCA + 0.036 × MMSE. We draw the ROC curve of the training and validation sets to validate the model, the area under the ROC curve (AUC) of the internal validation was 0.869 (95% confidence interval [CI]: 0.771-0.967) and the AUC of external validation was 0.845 (95%CI：0.6526-1), the calibration plots showed good calibration. Conclusions: The model we developed can effectively assist clinicians in preoperatively assessing the efficacy of bilateral subthalamic nucleus deep brain stimulation for freezing of gait in Parkinson's disease patients, enabling the formulation of personalized treatment plans and better improving patient outcomes.
Keywords: Parkinson's disease, freezing of gait, Prediction model, Deep brain stimualtion, subthalamic nucleus
Received: 15 Oct 2024; Accepted: 29 Apr 2025.
Copyright: © 2025 Limuge and Yongqiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jiang Yongqiang, Inner Mongolia Third Hospital, Hohhot, China
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