Determinants for worsening in systemic autoimmune rheumatic disease-associated interstitial lung disease: a systematic review and meta-analysis of cohort studies
Bibliographic record
Abstract
Background To identify risk factors for progression, acute exacerbation (AE), and the development of rapidly progressive interstitial lung disease (RP-ILD) in Systemic autoimmune rheumatic disease-associated interstitial lung disease (SARD-ILD). Methods We systematically searched PubMed, EMBASE, Scopus, the Cochrane Library, and Web of Science databases to identify eligible cohort studies up until January 01, 2024. Two reviewers independently screened the literature and extracted data. We employed the Newcastle-Ottawa Scale (NOS) to assess study quality and performed meta-analyses using STATA software. Results This review included 50 studies. For progression, 28 studies were included, four significant risk factors were identified: male (OR = 1.97, 95% CI 1.26–3.08, p < 0.001), UIP patterns on HRCT (OR = 1.94, 95% CI 1.48–2.54, p < 0.001), extensive lung involvement (OR = 2.15, 95% CI 1.66–2.80, p < 0.001), and age (OR = 1.07, 95% CI 1.05–1.10, p < 0.001); and 11 potential risk factors. Seven studies were included in AE, and three potential risk factors were highlighted: FVC, UIP patterns on HRCT, and smoking history. In RP-ILD, 15 studies were included. Three risk factors were determined: High CRP (OR = 2.45, 95% CI 1.87–3.21, p < 0.001), Ro-52 positivity (OR = 5.35, 95% CI 3.46–8.29, p < 0.001), and MDA5 antibodies (OR = 2.09, 95% CI 1.47–2.95, p < 0.001); along with 10 potential risk factors. Conclusion Our meta-analysis identified male sex, UIP pattern on HRCT, extensive lung involvement, and advanced age as significant risk factors for the progression of SARD-ILD. High CRP, Ro-52 positivity, and MDA5 antibodies were significant risk factors for developing of RP-ILD in patients with IIM. We also discovered several potential risk factors that may be associated with the progression of SARD-ILD and acute exacerbation, as well as the occurrence of RP-ILD in IIM patients. Systematic review registration https://www.crd.york.ac.uk/prospero/ .
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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 | 0.019 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".