Ambient Air Pollution and Daily Emergency Department Visits for Ischemic Stroke in Edmonton, Canada
Bibliographic record
Abstract
OBJECTIVES: In this report, we examine the associations between emergency department (ED) visits for acute ischemic stroke and environmental conditions. MATERIALS AND METHODS: The study concerned 10,881 ED visits for acute ischemic stroke (ICD-9: 434, 436) recorded at Edmonton hospitals between 1992 and 2002. Generalized linear mixed models technique was applied to build the statistical models. The logarithm of daily counts of ED visits for stroke was regressed on the levels of air pollutants (CO, NO2, SO2, and O3) and two meteorological variables. The analyses were performed by (a) age: two age groups were distinguished: 20-64 years (n=2873) and 65-100 years (n=8008); (b) season (all seasons: January-December, warm: April-September, cold: October-March); and (c) gender (both, male, female). RESULTS: The results are reported as an excess risk in relation to an increase in the interquartile range (IQR) of the pollutants. In the age group 65-100 years, the excess risk for particular pollutants was as follows: for NO2-8.2% (95% CI: 0.4-16.7) for both genders, in the warm season; for SO2-9.1% (95% CI: 2.2-16.4), for males, in the warm season: for a 1-day lagged SO2-6.0% (95% CI: 0.5-11.8), for females, in the cold season. Among the patients aged 20-64 years, the excess risk for NO2 was 6.3% (95% CI: 0.2-12.8), for both genders, and all seasons; and 13.8% (95% CI: 2.1-26.7), for females, in the cold season; for a 1-day lagged O3-17.8% (95% CI: 2.2-35.6), for males, in the warm season; for a 1-day lagged SO2-10.3% (95% CI: 0.7-20.9) for females, in the cold season. CONCLUSIONS: The findings provide evidence that exposure to air pollutants is significantly associated with ED visits for acute ischemic stroke.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".