Polluted Air from Canadian Wildfires and Cardiopulmonary Disease in the Eastern US
Bibliographic record
Abstract
Importance: Intense wildfires affecting residential populations are increasingly frequent. However, the adverse cardiopulmonary consequences to patients from remote wildfire smoke exposure is uncertain. Objective: To investigate the association between wildfire smoke originating in Western Canadian provinces with cardiopulmonary disease burden in sociodemographically heterogenous populations in the Eastern US. Design, Setting, and Participants: This case-only study used International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes for cardiopulmonary diseases extracted from the University of Maryland Medical System in June 2023 vs June 2018 and June 2019. Data were analyzed from September 2023 to September 2024. Exposures: High air pollution episodes where the concentration of particulate matter with aerodynamic diameter below 2.5 μm (PM2.5) exceeded the toxic National Ambient Air Quality Standard (35 μg/m3) (referred to as "hotspot days") on contiguous days. Main Outcomes and Measures: The number of patients with inpatient, ambulatory, and emergency department clinical encounters during assigned hotspot days in June 2023 compared with matching days in June of control years. Adjustments for covariates for comparisons between groups were made with χ2 tests and multivariable logistic regression. Results: Statewide air quality analysis identified June 6-8 and 28-30 as 6 hotspot days with an increase in PM2.5 by 9.4-fold and 7.4-fold, respectively, in Baltimore City compared with all other days in 2023. After adjusting for calendar days across years, the cohort included 2339 cardiopulmonary clinical encounters in June 2023 (mean [SD] age, 68 [15] years; 1098 female [46.9%]; 710 Black [30.4%], 1528 White [65.3%]) and 3609 encounters in June 2018-2019 (mean [SD] age, 65 [15] years; 1690 female [46.8%]; 1181 Black [32.7%], 2269 White [62.9%]). The proportion of clinical encounters occurring during hotspot days in June 2023 was 588 of 2339 days (25.1%) vs 806 of 3609 days (22.3%) in control years (χ2 = 6.07; P = .01), with an adjusted odds ratio (aOR) of 1.18 (95% CI, 1.03-1.34; P = .02). Restricting this analysis to cardiac diseases, there was a 20% increase in adjusted odds for a clinical encounter (aOR, 1.20; 95% CI, 1.01-1.42; P = .04). Patients with cardiopulmonary encounters on hotspot days had greater socioeconomic advantage vs control years by ADI score (mean [SD] score, 39.1 [21.1] vs 41.0 [23.7]; P = .05). Conclusions and Relevance: In this case-only study of a large medical system, we identified an increased cardiopulmonary disease burden for residents of Maryland that was likely associated with contemporaneous wildfire smoke-based infiltration of polluted or toxic air originating from Western Canada up to 2100 miles remotely.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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".