The Air Quality Health Index and Emergency Department Visits for Otitis Media
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to explore novel multipollutant exposure assessments using the Air Quality Health Index in relation to emergency department visits for otitis media (OM). DESIGN: This study was a retrospective analysis using information from emergency department visits for OM, air pollution, and weather databases. METHODS: For children 3 years of age or younger, there were 4,815 emergency department visits for OM over a 6-year period across hospitals in Windsor, Ontario, Canada. Both time-stratified case-crossover and nonlinear time series distributed lag analyses were applied to investigate the association between the Air Quality Health Index and visits for OM. FINDINGS: Using case-crossover analysis, there was an increase in emergency department visits with OM diagnoses 6 to 7 days postexposure to increased ozone and 3 to 4 days after exposure to increased particulate matter. For every 1 unit increase in the Air Quality Health Index, discharge diagnosis of OM increased 5% to 6% three days postexposure. Effects were stronger using the nonlinear time series analysis. The overall risk for OM, in the first 15 days after an increase in the Air Quality Health Index, was 1.22 times the risk of OM on days following no increase in exposures. CONCLUSIONS: These findings confirm that there is an association between the multipollutant Air Quality Health Index and emergency department visits for OM. The findings can be used to inform risk communication, patient education, and policy. CLINICAL RELEVANCE: Clinicians can use the Air Quality Health Index as an education and advocacy tool to promote and protect the health of those at high risk for OM to reduce exposures.
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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 | 0.003 | 0.002 |
| 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".