Factors affecting the health-related quality of life of patients with cervical dystonia and the impact of botulinum toxin type A injections.
Bibliographic record
Abstract
The purpose of this study was to analyze the health-related quality of life (HRQL) of patients with cervical dystonia (CD) and the impact of botulinum toxin A (BTX-A) therapy in these patients. The authors recruited 101 patients with CD, all previously treated with BTX-A. Both before and 4 weeks after injection of BTX-A the patients were assessed using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS), a Visual Analogue Scale for pain (VAS: 0-100%), the Short Form 36 health survey questionnaire (SF-36), and the Montgomery-Asberg Depression Rating Scale (MADRS). A control group of 84 healthy volunteers was also evaluated. The patients? baseline SF-36 scores were worse in all the domains when compared with those of the controls. Depression was found in 47.5% of the patients. Improvements were noticed 4 weeks after the single BTX-A injections in all the SF-36 domains, and in the VAS, TWSTRS and MADRS scores. The TWSTRS results did not correlate with any of the SF-36 subscores. Stepwise backward regression analysis revealed depression as the main predictor of poor HRQL, as well as female sex, poor financial situation, and living alone. On contrary, longer treatment with BTX-A was associated with better scores. Cervical dystonia has a marked impact on HRQL and treatment with BTX-A injections has a beneficial effect, seen both in objective and in subjective measures. Depression in CD patients is a main predictor of worse HRQL.
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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) | 0.000 | 0.000 |
| 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".