Unilateral repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex in Parkinson's Disease: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) may improve motor and non-motor symptoms in Parkinson's disease (PD). This meta-analysis assessed the efficacy of 10 unilateral rTMS sessions in PD. EVIDENCE ACQUISITION: Randomized controlled trials comparing this protocol to sham stimulation in PD were systematically searched in PubMed, EMBASE, and the Cochrane Library through January 2025. Short-term outcomes were assessed immediately after treatment; long-term outcomes were measured 1-6 months later. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated using random-effects models. EVIDENCE SYNTHESIS: Seven trials were included (mean follow-up: 8.7 weeks). Long-term motor function improved significantly (UPDRS part III: MD=-4.97; 95% CI: -6.53 to -3.40; P<0.001), whereas short-term changes were non-significant. Long-term reductions in depressive symptoms were observed on the Hamilton Depression Rating Scale (MD=-2.77; 95% CI: -4.75 to -0.79; P=0.006), the Montgomery-Åsberg Depression Rating Scale (MD=-6.23; 95% CI: -9.78 to -2.68; P<0.001), and the Beck's Depression Inventory (MD=-4.41; 95% CI: -8.34 to -0.48; P=0.028). Sleep quality improved at long-term follow-up (Pittsburgh Sleep Quality Index: MD=-2.51; 95% CI: -5.33 to -0.31; P=0.081). Short-term cognitive gains were observed on the Montreal Cognitive Assessment (MD=1.70; 95% CI: 0.01 to 3.40; P=0.049). CONCLUSIONS: Ten sessions of unilateral rTMS over the DLPFC improved motor and non-motor symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".