Relative environmental and social disadvantage in patients with idiopathic pulmonary fibrosis
Bibliographic record
Abstract
BACKGROUND: Air pollution exposure is associated with disease severity, progression and mortality in patients with idiopathic pulmonary fibrosis (IPF). Combined impacts of environmental and socioeconomic factors on outcomes in patients with IPF are unknown. The objectives of this study were to characterise the relationships between relative environmental and social disadvantage with clinical outcomes in patients with IPF. METHODS: Patients with IPF were identified from a longitudinal database at University of California, San Francisco. Residential addresses were geocoded and linked to the CalEnviroScreen 3.0 (CES), a tool that quantifies environmental burden in California communities, combining population, environmental and pollution vulnerability into individual and composite scores (higher scores indicating greater disadvantage). Unadjusted and adjusted linear and logistic regression and Fine and Gray proportional hazards models were used. RESULTS: 603 patients were included. Higher CES was associated with lower baseline forced vital capacity ( β =-0.073, 95% CI -0.13 to -0.02; p=0.006) and diffusion capacity of the lung for carbon monoxide ( β =-0.11, 95% CI -0.16 to -0.06; p<0.001). Patients in the highest population vulnerability quartile were less likely to be on antifibrotic therapy (OR=0.33; 95% CI 0.18 to 0.60; p=0.001) at time of enrolment, compared with those in the lowest quartile. An association between CES and mortality was suggested, but sensitivity analyses demonstrated inconsistent results. Relative disadvantage of the study cohort appeared lower compared with the general population. CONCLUSIONS: Higher environmental exposures and vulnerability were associated with lower baseline lung function and lower antifibrotic use, suggesting that relative socioenvironmental disadvantage has meaningful impacts on patients with IPF.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".