Approach to the Evaluation and Management of Interstitial Lung Abnormalities: An Official American Thoracic Society Clinical Statement
Bibliographic record
Abstract
Abstract Background There is growing interest in identifying early stages of interstitial lung disease (ILD) to improve patient outcomes. This document reviews updated evidence on interstitial lung abnormalities (ILAs); provides suggestions for screening, evaluation, and management; proposes criteria for distinguishing ILAs from ILD; and identifies research priorities. Methods A committee of clinical and methodology experts met by video conference to define ILAs and ILD by consensus and voted on 11 prespecified questions after reviewing synthesized evidence from a systematic literature search. Agreement of ≥70% was required to approve each suggestion. Results ILA is defined as nondependent bilateral parenchymal abnormalities on computed tomography, including ground-glass opacities or reticulations, lung distortion, traction bronchiectasis, and/or honeycombing involving ≥5% of a lung zone. The updated definition removes the prior exclusion of high-risk populations. ILD is distinguished from ILAs by symptoms (dyspnea/cough) attributable to an interstitial process, abnormal or declining lung function, fibrotic (honeycombing and/or reticulation with traction bronchiectasis involving ≥5% of total lung volume) or progressive imaging abnormalities, and/or specific fibrotic ILD patterns on imaging or pathology. Suggestions include ILA/ILD assessment on imaging acquired for lung cancer screening, screening adults with connective tissue disease and first-degree relatives of patients with familial pulmonary fibrosis, assessing baseline symptoms and pulmonary function among those with ILAs, and monitoring ILAs with chest computed tomography every 2–3 years. Conclusions This document presents a comprehensive literature review of ILAs with updates to the Fleischner Society ILA definition, establishes a working ILD definition, and provides evidence-based suggestions for ILA evaluation and management.
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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 | 0.030 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".