Disability in migraine: multicountry results from the CaMEO-International study
Bibliographic record
Abstract
Background Although individual studies evaluating headache burden are available, few studies have been conducted across multiple countries using the same methodology. Design/Methods Chronic Migraine Epidemiology and Outcomes-International (CaMEO-I) was a global cross-sectional, web-based survey conducted in 2021-2022 This analysis evaluated migraine burden using the Migraine-Specific Quality of Life Questionnaire (MSQ) and the Work Productivity and Activity Impairment Questionnaire (WPAI). Results 14,492 participants respondents with migraine were included. Mean (SD) MSQ scores ranged from 57.7 (23.4) in Canada to 63.3 (21.1) in France for the role function restrictive domain, 67.6 (22.9) in Germany to 77.3 (22.7) in Japan for the role function preventive domain, and 63.9 (29.1) in the US to 69.2 (24.8) in France for the emotional function domain. Regarding WPAI, the mean (SD) percentage of work missed ranged from 4.3% (16.2) in France to 9.0% (21.7) in Germany, work impaired ranged from 31.2% (28.0) in France to 47.8% (28.6) in Japan, overall work impaired ranged from 33.5% (30.3) in France to 49.4% (29.4) in Japan, and activity impaired ranged from 39.3% (30.2) in France to 50.7% (28.4) in Japan. Conclusions Migraine is associated with substantial burden, including poor quality of life and work/activity impairment.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".