Ambient Air Pollution and Daily Emergency Department Visits for Headache in Ottawa, Canada
Bibliographic record
Abstract
BACKGROUND: No extensive studies exist on the relation between ambient air pollution and health outcomes such as migraine or headache. From other side, existing publications indicated that air pollutants can trigger migraine or headache. OBJECTIVE: To examine associations between emergency department (ED) visits for headache and environmental conditions: ambient air pollution concentrations adjusted for weather factors (atmospheric pressure, temperature, and relative humidity). DESIGN AND METHODS: This is a time-series study of 8012 ED visits for headache (International Classification for Diseases ninth revision: 784) recorded at an Ottawa hospital between 1992 and 2000. The generalized linear mixed models technique is used to model relation between daily counts of ED visits for headache and ambient air pollutants (gases: sulphur dioxide [SO(2)], nitrogen dioxide [NO(2)], carbon monoxide [CO]). The counts of visits for all patients, male and female patients, are analyzed separately. RESULTS: The percentage increase in daily ED visits for headache was 4.2% (95% CI: 0.2, 6.4) and 4.9% (95% CI: 1.2, 8.8) for 1-day and 2-day lagged exposure to SO(2) for an increase in the interquartile range (IQR, IQR = 3.9 ppb). The positive statistically significant associations were also observed for exposure to NO(2) and CO for all and male ED visits for headache. CONCLUSIONS: Presented findings provide support for the hypothesis that ED visits for headache are related to ambient air pollution.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".