Interstitial lung disease in patients with anti-neutrophil cytoplasm antibody-associated vasculitis: an update on pathogenesis and treatment
Bibliographic record
Abstract
PURPOSE OF REVIEW: Interstitial lung disease (ILD) is now recognized as a common complication of anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitides (AAV), especially myeloperoxidase (MPO)-ANCA-positive AAV and microscopic polyangiitis (MPA). This review focuses on current concepts pertaining to the pathogenesis, clinical assessment, and management of AAV-ILD. RECENT FINDINGS: ILD is typically identified before or at the onset of systemic AAV, and usual interstitial pneumonia (UIP) is the most common CT pattern. MPO-ANCA production, neutrophil extracellular traps formation, reactive oxidative species production, complement activation, environmental exposures, and genetic background might play a role in the pathogenesis of AAV-ILD. Recent research has identified promising biomarkers as potential diagnostic and prognostic tools in AAV-ILD. The optimal treatment for AAV-ILD is not well defined but might rely on a combination of immunosuppression and antifibrotics, especially in patients with progressive lung fibrosis. Despite the effectiveness of current therapies for AAV, the outcome of patients with AAV-ILD remains poor. SUMMARY: ANCA screening should be considered in patients with newly diagnosed ILD. Management of AAV-ILD should be overviewed by a collaborative team comprising vasculitis experts and respirologists. VIDEO ABSTRACT: http://links.lww.com/COPM/A33.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.004 | 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".