Deep brain stimulation for severe dystonia associated with Wilson disease: A prospective multicenter meta‐analysis of an N‐of‐1 trial
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Disabling dystonia despite optimal medical treatment is common in Wilson disease (WD). No controlled study has evaluated the effect of deep brain stimulation (DBS) on dystonia related to WD. This study was undertaken to evaluate the efficacy of DBS on dystonia related to WD. METHODS: A meta-analysis of an N-of-1 prospective, randomized, double-blind, multicenter DBS study was conducted at two French WD reference centers. Main inclusion criteria were patients with WD, stabilized for at least 6 months with significant disability due to dystonia despite optimized medical treatment. The subthalamic nucleus (STN) was targeted for bradykinetic patients with tonic dystonia, and the internal globus pallidus (GPi) was chosen for patients with hyperkinetic dystonia. Each patient underwent two periods of DBS "on" and two periods of DBS "off," each lasting 4 months. The order of stimulation conditions was randomized. The primary outcome was the change in the Canadian Occupational Performance Measure Performance (COPM-P) and Satisfaction scores after each 4-month period. Secondary outcomes were changes in the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) severity and disability scores and Unified Wilson's Disease Rating Scale (UWDRS) scores. RESULTS: Between 12 May 2016 and 7 October 2022, three patients were included. Two patients received bilateral GPi DBS, and one received bilateral STN DBS. There was no change of COPM-P (p = 0.956), BFMDRS, and UWDRS scores. No serious adverse events were reported. CONCLUSIONS: STN or GPi DBS are ineffective on dystonia related to WD.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.020 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".