One Side or Two? A Systematic Review of Deep Brain Stimulation Approaches in Movement Disorders
Bibliographic record
Abstract
BACKGROUND: Deep brain stimulation (DBS) is an established treatment for movement disorders such as Parkinson's disease (PD) and essential tremor (ET). However, the decision between unilateral, staged bilateral, or simultaneous bilateral DBS remains controversial, influenced by clinical presentation, patient preferences, and economic factors. OBJECTIVE: The aim was to compare motor score improvements, adverse events (AE), incremental benefits, and progression with unilateral to bilateral procedures and the rationale for second-side surgery. METHODS: This systematic review examined studies on patients treated with unilateral or bilateral (simultaneous or staged) DBS from 1999 to 2025, focusing on outcomes, safety, and efficacy. RESULTS: In PD, unilateral DBS targeting the subthalamic nucleus (STN) or globus pallidus internus (GPi) improves motor scores by up to 37%, whereas bilateral DBS yields improvements of up to 66%. Unilateral DBS provides up to 75% improvement in contralateral symptoms but only up to 28% in ipsilateral symptoms. More than half of PD patients eventually opt for second-side surgery due to worsening symptoms. In ET, unilateral ventral intermediate nucleus (VIM) DBS improves hand tremor by up to 89%, with staged bilateral procedures offering an additional 77% to 89% improvement contralaterally. Axial tremor improves by up to 60% with unilateral VIM DBS and a further 60% after bilateral surgery. Bilateral VIM DBS is linked to more AEs, such as gait disorders and dysarthria, whereas STN and GPi DBS have comparable risks. Staged surgeries are associated with longer surgical times and increased revisions and programming. CONCLUSIONS: Individualized treatment decisions are essential, with bilateral DBS providing superior long-term outcomes for both PD and ET.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".