ArticleMovement disorders clinical practice2023
The Role of Levodopa Challenge in Predicting the Outcome of Subthalamic Deep Brain Stimulation.
Article in Movement disorders clinical practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive Models for Motor Outcomes From Deep Brain Stimulation in Parkinson's Disease: A Systematic Review.The European journal of neuroscience · 2026Pooled it
- Linking Invasive and Noninvasive Brain Stimulation in Parkinson's Disease: A Randomized Trial.Movement disorders : official journal of the Movement Disorder Society · 2024Trial
- Risk-Benefit Considerations in Deep Brain Stimulation Discontinuation for Late-Stage Parkinson's Disease.Movement disorders clinical practice · 2026Article
- Entrainment of cortical gamma oscillations predicts improved bradykinesia and dyskinesia in Parkinson's disease.medRxiv : the preprint server for health sciences · 2026Article
- Technical Feasibility of Quantitative Susceptibility Mapping Radiomics for Predicting Deep Brain Stimulation Outcomes in Parkinson Disease.Neurosurgery · 2026Article
- Survival after Subthalamic Deep Brain Stimulation for Parkinson's Disease: 25-Year Experience from a Single Center.Movement disorders clinical practice · 2026Article
- Video-based machine learning models for predicting deep brain stimulation outcomes in Parkinson's disease patients.NPJ Parkinson's disease · 2026Article
- Consensus expert recommendations for referral of Parkinson's disease patients for deep brain stimulation surgery.NPJ Parkinson's disease · 2026Review
- Development and validation of a clinical prediction model for first fall in early Parkinson's disease: a study of two fall-naive cohorts.Frontiers in aging neuroscience · 2026Article
- Differentiating effects of levodopa and subthalamic nucleus deep brain stimulation on motor features in Parkinson disease.Clinical parkinsonism & related disorders · 2026Article
- Subthalamic beta peak power ratio as an electrophysiological marker for deep brain stimulation contact selection in Parkinson's disease.Neurological research and practice · 2025Article
- Preoperative network activity predicts the response to subthalamic DBS for Parkinson's disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Article
- Functional Connectivity and Volumetrics Improve Outcome Prediction for Deep Brain Stimulation in Parkinson's Disease.Movement disorders clinical practice · 2025Article
- Identifying Poor Responders to STN DBS in Parkinson Disease: The Role of Rapid Disease Progression in the First Year in Optimal Responders to Levodopa.European journal of neurology · 2025Article
- Preoperative structural networks based on DTI predicts initial subthalamic nucleus stimulation outcome in parkinson's disease.Scientific reports · 2025Article
- Patient, target, device, and program selection for DBS in Parkinson's disease: advancing toward precision care.NPJ Parkinson's disease · 2025Review
- Are there Predictors for the Effects of Subthalamic Versus Thalamic Lesions for the Treatment of Parkinsonian Tremor?Movement disorders : official journal of the Movement Disorder Society · 2025Article
- Patient Selection in Deep Brain Stimulation: A Role for Transcranial Direct Current Stimulation to Enhance the Levodopa Challenge?Annals of clinical and translational neurology · 2025Article
- The Application of Machine Learning to Predict Clinical Outcomes of Deep Brain Stimulation in Parkinson's Disease: A Systematic Review.Medical journal of the Islamic Republic of Iran · 2025Review
- Individual Structural Covariance Network Predicts Long-Term Motor Improvement in Parkinson Disease with Subthalamic Nucleus Deep Brain Stimulation.AJNR. American journal of neuroradiology · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective and evidence-based treatment for idiopathic Parkinson's disease (iPD). A minority of patients does not sufficiently benefit from STN-DBS. Objective: The predictive validity of the levodopa challenge for individual patients is analyzed. Methods: Data from patients assessed with a preoperative Levodopa-test and a follow-up examination (mean ± standard deviation: 9.15 months ±3.39) from Kiel (n = 253), Berlin (n = 78) and Toronto (n = 98) were studied. Insufficient DBS outcome was defined as an overall UPDRS-III reduction <33% compared to UPDRS-III in med-off at baseline or alternatively if the minimal clinically important improvement of 5 points was not reached. Single UPDRS-items and sub-scores were dichotomized. Following exploratory analysis, we trained supervised regression- and classification models for outcome prediction. Results: Data analysis confirmed significant correlation between the absolute UPDRS-III reduction during Levodopa challenge and after stimulation. But individual improvement was inaccurately predicted with a large range of up to 30 UPDRS III points. Further analysis identified preoperative UPDRS-III/med-off-scores and preoperative Levodopa-improvement as most influential factors. The models for UPDRS-III and sub-scores improvement achieved comparably low accuracy. Conclusions: With large prediction intervals, the Levodopa challenge use for patient counseling is limited, though remains important for excluding non-responders to Levodopa. Despite these deficiencies, the current practice of patient selection is highly successful and builds not only on the Levodopa challenge. However, more specific motor tasks and further paraclinical tools for prediction need to be developed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.