P.014 OnabotulinumtoxinA-treated cervical dystonia patients report improvements in health-related quality of life in a prospective, observational study: POSTURe
Bibliographic record
Abstract
Background: The clinical benefit of onabotulinumtoxinA in cervical dystonia (CD) is proven, but its impact on health-related quality of life (HRQoL) is largely unknown. Methods: Multicentre, prospective, observational study (NCT01655862) of CD patients treated with onabotulinumtoxinA at physician discretion (maximum 9 treatments). Patient-reported HRQoL outcomes and work productivity were collected at baseline, 4- or 8-weeks post-treatment, and final visit (prior to 9th treatment). OnabotulinumtoxinA utilization was assessed. Results: 61 patients received ≥1 treatment; 74.1% completed all treatments. Average total dose/treatment was 186.9U. The splenius capitis was most frequently treated (100% patients). Average pain numeric rating scale score was significantly improved at final visit (2.1) versus baseline (4.6; p<0.001) as were CD impact profile questionnaire-58 scores across all subscales (head/neck symptoms, pain/discomfort, sleep, upper limb activities, walking, annoyance, mood, psychosocial functioning; all p<0.001). Fewer patients (16.0%) reported loss of work productivity at final visit versus baseline (48.4%). 121 AEs were reported by 67.2% patients. 62 AEs in 44.3% patients were treatment-related, the most common being neck pain (18%). One serious AE (not treatment-related) was reported by 1 patient. No new safety signals were identified. Conclusions: Long-term use of onabotulinumtoxinA is a safe, effective treatment for CD, improving HRQoL and work productivity.
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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) | 0.005 | 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".