Geographic Differences in Pain Perception in Patients with Cervical Dystonia (P1.033)
Bibliographic record
Abstract
Objectives: To explore geographic differences (US versus Europe versus rest of world [ROW]) in subjective pain perception in patients with cervical dystonia (CD) being treated with botulinum neurotoxin type A and compare it with objective ratings of disability and disease severity. Background: Cervical pain is a common feature of CD, and is often a key contributor to patient disability. The Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) includes a pain subscale in addition to separate ratings of severity and disability. Methods: Meta-analyses were conducted on baseline data from two observational international studies (INTEREST IN CD1 & 2) and one US registry (ANCHOR-CD). Results: Baseline descriptive data are presented for 1624 subjects (US n=297, Europe [18 countries] n=948, ROW [16 countries] n=379) with primary CD. Meta-analyses showed that US subjects had higher TWSTRS Total scores (mean ±SD: 35.1 ±13.0 vs. 32.7 ±12.3 & 33.3 ±13.3, respectively) and indicated that this geographic difference was primarily driven by higher patient-rated TWSTRS pain scores (8.4 ±5.3 vs. 6.0 ±4.7 & 6.9 ±5.1, respectively). By contrast, patient-rated disability scores (10.2 ±6.6, 9.8 ±6.1 & 9.5 ±6.6, respectively) and physician-rated TWSTRS severity scores (16.5 ±5.0, 16.9 ±5.4 & 16.9 ±5.5, respectively) were similar between regions. Conclusions: These observational data suggest that US patients report higher levels of pain than patients from Europe or ROW when using the TWSTRS pain subscale. Despite the close associations between pain and disability, there was no clear difference in ratings of disability between regions, indicating that the difference may be related to the perception and reporting of pain rather than its impact on daily life.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".