P.045 Quality of life and treatment satisfaction in onabotulinumtoxinA-treated cervical dystonia patients: multicentre, prospective, observational study, posture
Bibliographic record
Abstract
Background: Health-related quality of life (HRQoL) data is valuable, but limited. This analysis describes the impact of onabotulinumtoxinA treatment on HRQoL and level of treatment satisfaction in cervical dystonia (CD) patients. Methods: A multicenter, prospective, observational study in CD patients initiating onabotulinumtoxinA treatment (NCT01655862); ≤8 treatments administered at the physician’s discretion. Primary measures (baseline, 4/8 weeks post-treatment, and before final treatment): pain numeric rating scale (PNRS) and cervical dystonia impact profile questionnaire (CDIP-58). Secondary measures (8 weeks post-treatment): patient/physician treatment satisfaction. Results: 61 patients (31.3-86.3 years old) were enrolled (efficacy cohort); majority had moderately severe CD (77.0%) and were female (77%). CDIP-58 domain and PNRS scores decreased from baseline, with significant changes (p<.0001) by 4 weeks post-treatment 3 (mean±SD): symptoms (-18.8±16.1), daily activities (-7.2±13.7), psychosocial sequelae (-17.4±13.4), and PNRS (-1.8±3.3). Most patients (78.0% and 94.4%) felt their condition was improved and majority of physicians (68.9% and 75.0%) indicated satisfaction with patients’ responses following treatments 1 and 2, respectively. 27 patients reported 56 treatment-related adverse events (52 resolved, 4 ongoing); none were serious. Conclusions: No new safety signals were identified. Patients and physicians appear to be satisfied with onabotulinumtoxinA treatment for CD. Results suggest that onabotulinumtoxinA treatment may help improve HRQoL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".