The association between air pollution and the incidence of idiopathic pulmonary fibrosis in Northern Italy
Bibliographic record
Abstract
Acute exacerbations and worsening of idiopathic pulmonary fibrosis (IPF) have been associated with exposure to ozone (O 3 ), nitrogen dioxide (NO 2 ) and particulate matter, but chronic exposure to air pollution might also affect the incidence of IPF. We investigated the association between chronic exposure to NO 2 , O 3 and particulate matter with an aerodynamic diameter <10 μm (PM 10 ) and IPF incidence in Northern Italy between 2005 and 2010. Daily predictions of PM 10 concentrations were obtained from spatiotemporal models, and NO 2 and O 3 hourly concentrations from fixed monitoring stations. We identified areas with homogenous exposure to each pollutant. We built negative binomial models to assess the association between area-specific IPF incidence rate, estimated through administrative databases, and average overall and seasonal PM 10 , NO 2 , and 8-hour maximum O 3 concentrations. Using unadjusted models, an increment of 10 µg·m −3 in NO 2 concentration was associated with an increase between 7.93% (95% CI 0.36–16.08%) and 8.41% (95% CI −0.23–17.80%) in IPF incidence rate, depending on the season. After adjustment for potential confounders, estimated effects were similar in magnitude, but with larger confidence intervals. Although confirmatory studies are needed, our results trace a potential association between exposure to traffic pollution and the development of IPF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".