Emergency department visits for migraine and headache: a multi-city study
Bibliographic record
Abstract
OBJECTIVES: We set out to examine associations between ambient air pollution concentrations and emergency department (ED) visits for migraine/headache in a multi-city study. MATERIALS AND METHODS: We designed a time-series study of 64 839 ED visits for migraine (ICD-9: 346) and of 68 495 ED visits for headache (ICD-9: 784) recorded at hospitals in five different cities in Canada. The data (days) were clustered according to the hierarchical structure (location, year, month, day of week). The generalised linear mixed models technique was applied to fit the logarithm of clustered daily counts of ED visits for migraine, and separately for headache, on the levels of air pollutants, after adjusting for meteorological conditions. The analysis was performed by sex (all, male, female) and for three different seasonal periods: whole (January-December), warm (April-September), and cold (October-March). RESULTS: For female ED visits for migraine, positive associations were observed during the warm season for sulphur dioxide (SO2), and in the cold season for particulate matter (PM2.5) exposures lagged by 2-days. The percentage increase in daily visits was 4.0% (95% CI: 0.8-7.3) for SO2 mean level change of 4.6 ppb, and 4.6% (95% CI: 1.2,-8.1) for PM2.5 mean level change of 8.3 microg/m3. For male ED visits for headache, the largest association was obtained during the warm season for nitrogen dioxide (NO2), which was 13.5% (95% CI: 6.7-20.7) for same day exposure. CONCLUSIONS: Our findings support the associations between air pollutants and the number of ED visits for headache.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".