Air pollution and emergency department visits for epistaxis
Bibliographic record
Abstract
OBJECTIVES: This study aimed to evaluate the association between outdoor ambient air pollution and emergency department (ED) visits for epistaxis. DESIGN: Cross-sectional study, case-crossover design. SETTING: ED visit data were obtained for Edmonton, Alberta, Canada, for a period of 10 years starting 1 April 1992 and ending March 31st of 2002. The data on ED visits were supplied by Capital Health for the five major acute care hospitals in the Edmonton area. PARTICIPANTS: The analysis was performed for the population as a whole (N = 15 038) and split by sex: males (N = 8587) and females (N = 6451). MAIN OUTCOME MEASURES: We explored associations between ambient concentrations of air pollutants (CO, NO2 , SO2 , O3 , PM10 , PM2.5 ) lagged by 0-4 days and ED visits for epistaxis in Edmonton, Alberta, Canada. RESULTS: Odds ratios (ORs) and their 95% confidence intervals (CI) were reported for an increase in an interquartile range (IQR) of pollutant concentration. We obtained positive and statistically significant results for all patients with epistaxis; exposure to O3 with IQR = 14 ppb, OR = 1.05 (95% CI: 1.00-1.09, lag 0), and for males (age < 25 years), OR = 1.16 (1.03-1.30), lag 4; and to PM10 with IQR = 15 μg/m(3) , OR = 1.02 (1.00-1.05, lag 3). These results were stronger for older (age > 24 years) females. CONCLUSIONS: These findings suggest that there may be an association between air pollutant exposure, specifically ozone and PM10 , and the number of ED visits for epistaxis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".