Acute exacerbations of progressive-fibrosing interstitial lung diseases
Bibliographic record
Abstract
Acute exacerbation of interstitial lung disease (ILD) is associated with a poor prognosis and high mortality. Numerous studies have documented acute exacerbation in idiopathic pulmonary fibrosis (IPF), but less is known about these events in other ILDs that may present a progressive-fibrosing phenotype. We propose defining acute exacerbation as an acute, clinically significant respiratory deterioration, typically less than 1 month in duration, together with computerised tomography imaging showing new bilateral glass opacity and/or consolidation superimposed on a background pattern consistent with fibrosing ILDs. Drawing on observations in IPF, it is suspected that epithelial injury or proliferation and autoimmunity are risk factors for acute exacerbation in ILDs that may present a progressive-fibrosing phenotype, but further studies are required. Current acute exacerbation management strategies are based on recommendations in IPF, but no randomised controlled trials of acute exacerbation management have been performed. Although there are no formal strategies to prevent the development of acute exacerbation, possible approaches include antifibrotic drugs (such as nintedanib and pirfenidone), and minimising exposure to infection, airborne irritants and pollutants. This review discusses the current knowledge of acute exacerbation of ILDs that may present a progressive-fibrosing phenotype and acknowledges limitations of the data available.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".