P.038 Impact of Disease Severity on Presentation Subtype and OnabotulinumtoxinA Utilization in Patients with Cervical Dystonia in the CD PROBE Completer Population
Bibliographic record
Abstract
Background: The impact of cervical dystonia (CD) severity on presentation subtype and onabotulinumtoxinA utilization was examined in the completer population from CD PROBE (CD Patient Registry for Observation of BOTOX® Efficacy). Methods: In this multicenter, prospective, observational registry, patients with CD were treated with onabotulinumtoxinA according to injectors’ standard of care. Completers were patients that completed all 3 treatment sessions and had accompanying data. Results: Of N=1046 patients enrolled, n=350 were completers. Completers were on average 57.3 years old, 74.9% female, 94.6% white, and 60.6% toxin-naïve. Baseline severity was mild in 32.6%, moderate in 54.3%, and severe in 13.1%. Torticollis was the most common presentation at baseline (mild: 44.7%, moderate: 55.8%, severe: 63.0%), followed by laterocollis (mild: 42.1%, moderate: 32.6%, severe: 26.1%). Median onabotulinumtoxinA dose increased over time; 160U–200U for torticollis and 170U–200U for laterocollis. For all severities, median total dose increased from injection 1 to injection 3 (mild: 138U–165U, moderate: 183U–200U, severe: 200U–285U). Eighty-one patients (23.1%) reported 139 treatment-related adverse events. There were no treatment-related serious adverse eventsand no new safety signals. Conclusions: CD severity impacted presentation subtype frequency and onabotulinumtoxinA utilization in CD PROBE, with higher and tailored dosing observed over time and with increasing disease severity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".