Air pollution and emergency department visits for respiratory diseases: A multi-city case crossover study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing evidence suggests that ambient air pollution is a major risk factor for both acute and chronic respiratory disease exacerbations and emergencies. The objective of this study was to determine the association between ambient air pollutants and emergency department (ED) visits for respiratory conditions in nine districts across the province of Ontario in Canada. Health, air pollutant (PM2.5, NO2, O3, and SO2), and meteorological data were retrieved from April 2004 to December 2011. Respiratory diseases were categorized as: chronic obstructive pulmonary disease (COPD, including bronchiectasis) and acute upper respiratory diseases. A case-crossover design was used to test the associations between ED visits and ambient air pollutants, stratified by sex and season. For COPD among males, positive results were observed for NO2 with lags of 3–6 days, for PM2.5 with lags 1–8, and for SO2 with lags of 4–8 days. For COPD among females, positive results were observed for O3 with lags 2–4 days, and for SO2 among lags of 3–6 days. For upper respiratory disease emergencies among males, positive results were observed for NO2 (lags 5–8 days), for O3, (lags 0–6 days), PM2.5 (all lags), and SO2 (lag 8), and among females, positive results were observed for NO2 for lag 8 days, for O3, PM2.5 among all lags. Our study provides evidence of the associations between short-term exposure to air pollution and increased risk of ED visits for upper and lower respiratory diseases in an environment where air pollutant concentrations are relatively low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it