Short-term air pollution exposure and exacerbation events in mild to moderate COPD: a case-crossover study within the CanCOLD cohort
Bibliographic record
Abstract
Background Infections are considered as leading causes of acute exacerbations of chronic obstructive pulmonary disease (COPD). Non-infectious risk factors such as short-term air pollution exposure may play a clinically important role. We sought to estimate the relationship between short-term air pollutant exposure and exacerbations in Canadian adults living with mild to moderate COPD. Methods In this case-crossover study, exacerbations (‘symptom based’: ≥48 hours of dyspnoea/sputum volume/purulence; ‘event based’: ‘symptom based’ plus requiring antibiotics/corticosteroids or healthcare use) were collected prospectively from 449 participants with spirometry-confirmed COPD within the Canadian Cohort Obstructive Lung Disease. Daily nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), ground-level ozone (O 3 ), composite of NO 2 and O 3 (O x ), mean temperature and relative humidity estimates were obtained from national databases. Time-stratified sampling of hazard and control periods on day ‘0’ (day-of-event) and Lags (‘−1’ to ‘−6’) were compared by fitting generalised estimating equation models. All data were dichotomised into ‘warm’ (May–October) and ‘cool’ (November–April) seasons. ORs and 95% CIs were estimated per IQR increase in pollutant concentrations. Results Increased warm season ambient concentration of NO 2 was associated with symptom-based exacerbations on Lag−3 (1.14 (1.01 to 1.29), per IQR), and increased cool season ambient PM 2.5 was associated with symptom-based exacerbations on Lag−1 (1.11 (1.03 to 1.20), per IQR). There was a negative association between warm season ambient O 3 and symptom-based events on Lag−3 (0.73 (0.52 to 1.00), per IQR). Conclusions Short-term ambient NO 2 and PM 2.5 exposure were associated with increased odds of exacerbations in Canadians with mild to moderate COPD, further heightening the awareness of non-infectious triggers of COPD exacerbations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".