Post-traumatic Cervical Dystonia: A Distinct Entity?
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: The incidence of head/neck trauma preceding cervical dystonia (CD) has been reported to be 5-21%. There are few reports comparing the clinical characteristics of patients with and without a history of injury. Our aim was to compare the clinical characteristics of idiopathic CD (CD-I) to those with onset precipitated by trauma (CD-T). METHODS: We evaluated 114 consecutive patients with CD over a 9-month period. All patients were interviewed using a detailed questionnaire and had a neurological examination. Their clinical charts were also reviewed. RESULTS: Fourteen patients (12%) had mild head/neck injury within a year preceding the onset of CD. Between the two groups (CD-I and CD-T), the gender distribution (F:M of 3:2), family history of movement disorders (32% vs. 29%), the prevalence of gestes antagonistes (65% vs. 64%), and response to botulinum toxin were similar. There were non-specific trends, including an earlier age of onset (mean ages 43.3 vs. 37.6), higher prevalence of neck pain (86% vs. 100%), head tremor (67% vs. 79%), and dystonia in other body parts (23% vs. 36%) in CD-T. CONCLUSIONS: CD-I and CD-T are clinically similar. Trauma may be a triggering factor in CD but this was only supported by non-significant trends in its earlier age of onset.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".