Deep brain stimulation of the subthalamic nucleus improves sleep in Parkinson disease patients: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Sleep disorders significantly affect the quality of life in Parkinson disease (PD) patients. Deep brain stimulation of the subthalamic nucleus has been reported to improve motor symptoms and decrease medication usage. However, the impact of subthalamic nucleus deep brain stimulation (STN-DBS) on sleep quality in PD patients remains to be definitively determined. This systematic review and meta-analysis, conducted following the preferred reporting items for systematic reviews and meta-analyses guidelines, aimed to clarify the effect of STN-DBS on sleep quality in PD patients. METHODS: A rigorous literature search identified 6 studies, including 1 randomized controlled trial and 5 self-controlled trials, totaling 154 patients who underwent deep brain stimulation, providing 308 pairs of data for analysis. Parkinson disease sleep scale was the primary measure of interest, while the Movement Disorder Society-sponsored revision of the unified Parkinson disease rating scale was documented in all trials. Study quality was assessed using the Newcastle-Ottawa scale. RESULTS: STN-DBS significantly improved Parkinson disease sleep scale scores (mean difference = 20.41, 95% CI: [13.03, 27.79], I² = 60.8%, P < .001), indicating enhanced sleep quality. Furthermore, a significant reduction in movement disorder society unified Parkinson disease rating scale part III scores postoperatively (mean difference = -12.59, 95% CI: [-14.70, -10.49], I² = 89.9%, P < .001) suggested improved motor function. PD medication usage was also significantly reduced postoperatively (mean difference = -314.71, 95% CI: [-468.13, -161.28], I² = 52.9%, P < .001). A sensitivity analysis confirmed the robustness of the main findings. The sample size was adequate, allowing for conclusive inferences. CONCLUSION: The present study, which comprises a comprehensive systematic review and meta-analysis, offers compelling evidence that STN-DBS can ameliorate sleep quality, augment motor function, and curtail medication consumption among individuals afflicted with PD.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".