PAllidal versus SubThalamic deep brain Stimulation for Cervical Dystonia (PASTS-CD): study protocol for a multicentre randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Deep brain stimulation (DBS) has been validated as a safe and effective treatment for refractory cervical dystonia (CD). Globus pallidus internus (GPi) and subthalamic nucleus (STN) are the two main stimulating targets. However, there has been no prospective study to clarify which target is the better DBS candidate for CD. The objective of this trial is to compare directly the efficacy and safety of GPi-DBS and STN-DBS, thereby instructing the selection of DBS target in clinical practice. METHODS AND ANALYSIS: This multicentre, prospective, randomised, controlled study plans to enrol 98 refractory CD patients. Eligible CD patients will be randomly allocated to GPi-DBS group or STN-DBS group, with the DBS electrodes implanted into the posteroventral portion of GPi or the dorsolateral portion of STN, respectively. The primary outcome will be the improvement of symptomatic severity, measured by the changes in the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) severity subscale and the Tsui scale at 3 months, 6 months and 12 months after surgery. The secondary outcomes include the improvement of the TWSTRS-disability subscale, TWSTRS-pain subscale, quality of life, mental and cognitive condition, as well as the differences in stimulation parameters and adverse effects. In addition, this study intends to identify certain predictors of DBS efficacy for CD. ETHICS AND DISSEMINATION: The trial has been approved by the Medical Ethics Committee of Chinese PLA General Hospital (S2022-613-01). The results of this study will be published in international peer-reviewed journals and shared in professional medical conferences. TRIAL REGISTRATION NUMBER: NCT05715138.
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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 | 0.032 | 0.027 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.073 | 0.012 |
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".