Neighborhood Disadvantage Associations With Radiologic Features and Patterns in Fibrotic Interstitial Lung Disease
Bibliographic record
Abstract
Abstract Rationale: Higher neighborhood-level disadvantage is associated with lower baseline lung function in patients with fibrotic interstitial lung disease (fILD), but the association of disadvantage with radiologic features and patterns remains unknown. Methods: Patients with fILD enrolled in the Canadian Registry for Pulmonary Fibrosis were evaluated in standardized multi-disciplinary discussion (MDD). Expert chest radiologists blinded to clinical data evaluated baseline computed tomography scans, visually quantifying the percentage of lung parenchyma affected by honeycombing, reticulation, ground glass opacities (GGO), and hypoattenuating lung and determining the top radiologic pattern (usual interstitial pneumonia=UIP, fibrotic hypersensitivity pneumonitis=fHP, non-specific interstitial pneumonia=NSIP, “no confident pattern”). Clinical data was introduced, and a top clinical diagnosis was assigned by the radiologist and an ILD clinician. Neighborhood disadvantage was assigned to patient residential locations using the Canadian Index of Multiple Deprivation (CIMD) score and its 4 domains (residential instability, ethnocultural composition, economic dependency, situational vulnerability), with higher scores reflecting greater disadvantage. Linear models adjusted for age, sex, smoking, race, and baseline lung function evaluated associations of CIMD score with percentage of radiologic features. Multinomial models adjusting for the same covariates determined associations of CIMD score with radiologic pattern, using UIP as the reference. Results: Of 1473 patients included, the most common diagnoses were CTD-ILD (48%), IPF (29%), and fHP (16%). Higher CIMD score (range: -1.07 to 2.57) was associated with 0.62% increased honeycombing (95%CI=0.02-1.23, p=0.04, Table). Higher ethnocultural composition score (indicating neighborhoods with higher foreign-born, immigrant, minoritized, or linguistically-isolated individuals) was associated with less reticulations and increased pure GGO. Higher CIMD score was not associated with greater odds of fHP or NSIP patterns as compared with UIP, although higher ethnocultural composition score was associated with higher odds of NSIP (OR=1.18, 95%CI=1.01-1.39, p=0.04). Within patients with a top MDD diagnosis of IPF, higher total CIMD and ethnocultural scores were associated with more honeycombing. In CTD-ILD, higher residential instability was associated with more honeycombing and higher ethnocultural composition score with more hypoattenuating lung. In fHP, none of the scores were associated with worse honeycombing, reticulations, GGO, or hypoattenuating lung. Conclusions: Neighborhood disadvantage is associated with worse honeycombing, supporting prior findings that patients living in more disadvantaged areas present to tertiary ILD care with greater disease burden. Increased ethnocultural composition scores were associated with increased extent of inflammatory features in CTD-ILD and higher odds of an NSIP pattern, suggesting possible demographic, geographic, and/or genetic risk factors for this type of fILD.
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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 | 0.001 | 0.001 |
| 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".