Lifestyle and Clinical Risk Factors for Incident Rheumatoid Arthritis-associated Interstitial Lung Disease
Bibliographic record
Abstract
OBJECTIVE: To determine the association between novel lifestyle factors on risk of rheumatoid arthritis (RA)-associated interstitial lung disease (ILD), define the threshold at which smoking increases RA-ILD risk, and calculate the degree to which known lifestyle and clinical factors predict RA-ILD. METHODS: This nested case-control study matched incident RA-ILD cases to RA non-ILD controls on age, sex, RA duration, rheumatoid factor, and time from exposure assessment to RA-ILD. Exposures included education, BMI, smoking, anticyclic citrullinated peptide antibodies, race, joint erosions, rheumatoid nodules, C-reactive protein (CRP), disease activity score, functional status, disease-modifying antirheumatic drug use, and glucocorticoid use. OR for each exposure on risk of RA-ILD were obtained from logistic regression models. Area under the curve (AUC) was calculated based on all lifestyle and clinical exposures. RESULTS: We identified 84 incident RA-ILD cases and 233 matched controls. After adjustment, obesity, high-positive CRP (≥ 10 mg/L), and poor functional status (multidimensional Health Assessment Questionnaire [MDHAQ] ≥ 1) were associated with increased risk of RA-ILD (OR 2.42, 95% CI 1.11-5.24 vs normal BMI; OR 2.61, 95% CI 1.21-5.64 vs CRP < 3 mg/L; OR 3.10, 95% CI 1.32-7.26 vs MDHAQ < 0.2). Smoking 30 pack-years or more was strongly associated with risk of RA-ILD compared to never smokers (OR 6.06, 95% CI 2.72-13.5). Together, lifestyle and clinical risk factors for RA-ILD had an AUC of 0.79 (95% CI 0.73-0.85). CONCLUSION: Obesity, CRP, functional status, and extensive smoking may be novel risk factors for RA-ILD that may be useful for RA-ILD risk assessment and prevention. The overall ability to predict RA-ILD remains modest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".