Impact of Wildfire Smoke on COPD and Asthma Exacerbation Prevalence and Lung Function
Bibliographic record
Abstract
Abstract RATIONALE: Vermont saw an increase in air pollution from Canadian wildfires during the summer of 2023 compared to previous summers. Pollutants that are present in wildfire smoke can exacerbate respiratory symptoms. Previous studies have focused on the effect of smoke exposure on exacerbations in patients with chronic obstructive pulmonary disease (COPD) and asthma. This research aims to compare the effect of wildfire exposure on both the prevalence of exacerbations and impact on lung function in patients with COPD and asthma. METHODS: Weekly exacerbation counts were selected from the electronic-medical-record based on patients receiving prednisone in the outpatient, inpatient and emergency room settings for the months of June-August 2020-2023. To determine the impact on lung function, we analyzed spirometry from patients who had spirometry at least once in the 5 years before and at least once in the year after the wildfires. Demographics included age, tobacco use, BMI and FEV1%-predicted. Disease measures included: FEV1 z-score and severity of COPD and asthma; for COPD, we also recorded Peak Index and Parameter D calculated from expiratory flow data. Pollution data (PM2.5, O3, NO2) were obtained from the EPA. For both diseases, we recorded the impact of wildfire exposure by comparing lung function before and after the wildfire season of 2023. Pollutant data was aggregated as daily mean, 3-day lag time and 7-day lag time. Statistical analysis was performed using ANOVA, Tukey's HSD and linear regression. RESULTS: 122 COPD and 206 asthma patients were identified. Mean age, BMI, tobacco pack-years and FEV1%-predicted, respectively, were: 67.3/57.6 years, 29.6/18.0 kg/m2, 18.3/1.7, and 53/84% for COPD/asthma. There was an increase in prevalence of exacerbations for both COPD and asthma following the wildfire exposure period in 2023 compared to 2020 and 2021 but not 2022 (Figure 1). There was a significant drop in FEV1 z-score for COPD Stage 3 compared to COPD Stage 1 (p=0.01), and for moderate and severe asthma compared to mild asthma (p<0.01). There was no significant change in either the peak-indexdelta or parameter Ddelta in the COPD group. There was no significant relationship between pollutants and disease measures except PM2.5 7-day lag (p=0.02, R2=0.05). CONCLUSION: Although exacerbations were not increased from the year prior in 2022, exacerbations increased compared to 2020 and 2021. FEV1 decreased in patients with GOLD 3 COPD and in patients with moderate and severe asthma, suggesting these patients are more negatively affected by smoke exposure.
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.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".