Neurostimulation in cervical dystonia: effects on motor and non-motor symptoms within 5 years follow up
Bibliographic record
Abstract
Background Cervical Dystonia (CD) is a movement disorder characterised by neck muscle contractions, causing involuntary, abnormal posturing. Deep brain stimulation (‘DBS’) of the globus pallidal internus (‘GPi’) is an advanced treatment for medication-refractory patients. This study aims to (1) measure the efficacy of GPi-DBS on motor and non-motor symptoms of CD; (2) evaluate if clinical factors – such as age, disease duration and baseline disease severity – influence motor outcomes. Methods 37 idiopathic CD patients were recruited from movement disorders clinics at The Walton NHS Foundation Trust. Patients were assessed pre-operatively, 1 year, 3 years and 5 years post-operatively using three clinical scales: Toronto Western Spasmodic Torticollis Rating Scale, Hospital Anxiety and Depression Scale and EuroQuol-5D. Results Comparing baseline to 5 years follow-up (‘5Y FU’), GPi-DBS significantly improved overall motor scores by 57%, and severity, disability, and pain sub-scores by 72%, 59% and 46% respectively. Mood and quality of life (‘QoL’) did not improve significantly, and baseline clinical factors did not correlate with variability in outcomes. Conclusion GPi-DBS is an effective treatment until 5Y FU for motor symptoms in CD (severity, disability, and pain). There was limited effect on mood and QoL, and no baseline predictors of outcome were identified.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".