Air Pollution and Emergency Department Visits for Ischemic Heart Disease in Montreal, Canada
Bibliographic record
Abstract
OBJECTIVES: We examined the associations between emergency department (ED) visits for ischemic heart disease (IHD) and short-term elevations in ambient air pollutants (CO and NO(2)). MATERIALS AND METHODS: A hierarchical clusters design was used to study ED visits (n = 4979) for ischemic heart disease (ICD-9: 410-414) that occurred at a Montreal hospital between 1997 and 2002. The generalized linear mixed models technique was applied to create Poisson models for the clustered counts of ED visits for IHD. The analysis was done by gender for two age categories, all patients and patients aged over 64 years. RESULTS: The results are presented as an excess risk increase associated with the interquartile range (IQR) of daily average of the pollutant concentration. The results for NO(2) (IQR = 9.5 ppb) were 5.9% (95% CI: 2.1-9.9) for all patients and 6.2% (95% CI: 1.2-11.4) for males; for patients aged over 64: 7.1% (95% CI: 2.5-11.9) for all patients, 9.1% (95% CI: 2.8-15.7) for males, and 6.5% (95% CI: 0.7-12.7) for females (for exposure lagged by 1-day). The results for CO (IQR = 0.2 ppm): 5.4% (95% CI: 2.3-8.5) for all patients, and 7.5% (95% CI: 3.6-11.6) for males. For patients aged over 64 years, 4.9% (95% CI: 1.3-8.7) for all patients, and 7.5% (95% CI: 2.6-12.6) for males. The results show the associations for the same day exposures. CONCLUSIONS: The short-term effects of nitrogen dioxide and carbon monoxide are associated significantly with daily ED visits for ischemic heart disease. For NO(2) the associations are stronger for patients aged over 64 years. As indicated by our results, it is likely that vehicular traffic, a producer of NO(2) and CO, contributes to an increased number of ED visits for IHD.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".