Deep brain stimulation for Parkinson’s disease: meta-analysis of results of randomized trials at varying lengths of follow-up
Bibliographic record
Abstract
OBJECTIVE Deep brain stimulation (DBS) is effective in the management of patients with advanced Parkinson's disease (PD). While both the globus pallidus pars interna (GPi) and the subthalamic nucleus (STN) are accepted targets, their relative efficacy in randomized controlled trials (RCTs) has not been established beyond 12 months. The objective of this study was to conduct a meta-analysis of RCTs to compare outcomes among adults with PD undergoing DBS of GPi or STN at various time points, including 36 months of follow-up. METHODS The MEDLINE, Embase, CENTRAL, Web of Science, and CINAHL databases were searched. Registries for clinical trials, selected conference proceedings, and the table of contents for selected journals were also searched. Screens were conducted independently and in duplicate. Among the 623 studies initially identified (615 through database search, 7 through manual review of bibliographies, and 1 through a repeat screen of literature prior to submission), 19 underwent full-text review; 13 of these were included in the quantitative meta-analysis. Data were extracted independently and in duplicate. The Cochrane Collaboration tool was used to assess the risk of bias. The GRADE evidence profile tool was used to assess the quality of the evidence. Motor scores, medication dosage reduction, activities of daily living, depression, dyskinesias, and adverse events were compared. The influence of disease duration (a priori) and the proportion of male patients within a study (post hoc) were explored as potential subgroups. RESULTS Thirteen studies (6 original cohorts) were identified. No difference in motor scores or activities of daily living was identified at 36 months. Medications were significantly reduced with STN stimulation (5 studies, weighted mean difference [WMD] -365.46, 95% CI -599.48 to -131.44, p = 0.002). Beck Depression Inventory scores were significantly better with GPi stimulation (3 studies; WMD 2.53, 95% CI 0.99-4.06 p = 0.001). The motor benefits of GPi and STN DBS for PD are similar. CONCLUSIONS The motor benefits achieved with GPi and STN DBS for PD are similar. DBS of STN allows for a greater reduction of medication, but not as significant an advantage as DBS of GPi with respect to mood. This difference is sustained at 36 months. Further long-term studies are necessary.
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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 | 0.066 | 0.104 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.033 | 0.089 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".