Predictors of mortality in rheumatoid arthritis‐related interstitial lung disease
Bibliographic record
Abstract
Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) has a heterogeneous clinical presentation and disease course. Establishing prognosis for these patients is challenging. Identifying the factors that predict mortality in patients with RA-ILD could help guide management. A detailed systematic review was conducted in order to identify individual variables that predict mortality in RA-ILD. A literature review was performed using keywords and medical subject headings to identify all articles relating to the prognosis of RA-ILD. Studies were included if they identified predictors of mortality in adults with RA-ILD, were published in English, and included at least 10 patients with RA-ILD. Two authors independently reviewed each citation and extracted data from all studies meeting inclusion criteria. Any differences were then resolved by consensus. A total of 10 studies met our inclusion criteria. All were observational cohort studies of variable quality. Mean age of reported patients ranged from 55 to 69 years, and 41.7% of all patients were male. Median survival ranged from 3.2 to 8.1 years. Significant predictors of mortality on multivariate analysis were older age, male gender, lower diffusion capacity for carbon monoxide, extent of fibrosis, and the presence of usual interstitial pneumonia pattern. Mortality in RA-ILD is associated with several patient- and ILD-specific variables; however, previous studies are of low quality.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| 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) | 0.002 | 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".