Ambient Ultrafine Particulate Matter and Clinical Outcomes in Fibrotic Interstitial Lung Disease
Bibliographic record
Abstract
Abstract Rationale Particulate matter with an aerodynamic diameter ≤2.5 μm is associated with adverse outcomes in fibrotic interstitial lung disease (fILD), but the impact of ultrafine particulates (UFPs; aerodynamic diameter ≤100 nm) remains unknown. Objective To evaluate UFP associations with clinical outcomes in fILD. Methods We conducted a multicenter, prospective cohort study enrolling patients with fILD from the University of Pittsburgh Dorothy P. and Richard P. Simmons Center and the Pulmonary Fibrosis Foundation Patient Registry (PFF-PR). Using a national-scale UFP model, we linked exposures using three approaches in the Simmons cohort (residential address geocoordinates, ZIP code centroid geocoordinates, and ZIP code average) and two in the PFF-PR for which only five-digit ZIP code was available (ZIP code centroid and ZIP code average). We tested UFP associations with transplantation-free survival using multivariable Cox proportional-hazards models, baseline percentage predicted FVC and Dl CO using multivariable linear regressions, and decline in FVC and Dl CO using linear mixed models adjusting for age, sex, smoking, race, socioeconomic status, site, particulate matter with an aerodynamic diameter ≤2.5, and nitrogen dioxide. Measurements and Main Results Annual mean outdoor UFP concentrations for 2017 were estimated for 1,416 Simmons and 1,919 PFF-PR patients. Increased UFP concentration was associated with transplantation-free survival in fully adjusted Simmons residential address models (hazard ratio, 1.08 per 1,000 particles/cm3 [95% confidence interval, 1.01–1.15]; P = 0.02) but not PFF-PR models, which used less precise linkage approaches. Higher UFP exposure was associated with lower baseline FVC and more rapid FVC decline in the Simmons registry. Conclusions Increased UFP exposure was associated with transplantation-free survival and lung function in the cohort with precise residential location linkage. This work highlights the need for more robust regulatory networks to study the health effects of UFPs nationwide.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".