Relationship Between Depression and Disease Activity in United States Veterans With Early Rheumatoid Arthritis Receiving Methotrexate
Bibliographic record
Abstract
OBJECTIVE: Depression is common in patients with rheumatoid arthritis (RA), exacerbates disease activity, and may decrease response to first-line disease-modifying antirheumatic drugs. This study aimed to determine if depression affects disease activity among veterans with early RA prescribed methotrexate (MTX). METHODS: Participants included veterans enrolled in the Veterans Affairs Rheumatoid Arthritis (VARA) registry with early RA (onset < 2 yrs) prescribed MTX. Depression was assessed at enrollment using the International Classification of Diseases, 9th revision codes (296.2-296.39, 300.4, 311). Disease activity was measured using the Disease Activity Score in 28 joints (DAS28) and other core measures of RA disease activity. Propensity score weights were used to adjust depressed (n = 48) and nondepressed (n = 220) patients on baseline confounders within imputed datasets. Weighted estimating equations were used to assess standardized mean differences in disease activity between depressed and nondepressed patients at 6-month, 1-year, and 2-year follow-ups. RESULTS: The analytic sample was composed of 268 veterans with early RA prescribed MTX who were predominantly male (n = 239, 89.2%) and older (62.7 yrs, SD 10.6) than patients with RA in the general population. Adjusted estimates indicated that depression was associated with significantly higher DAS28 at 6 months (β 0.35, 95% CI 0.01-0.68) but not at the 1- or 2-year follow-up. Also, depression was associated with significantly worse pain at 6 months (β 0.39, 95% CI 0.04-0.73) and 1 year (β 0.40, 95% CI 0.04-0.75). CONCLUSION: In early RA, depression is associated with greater short-term disease activity during MTX treatment, as well as more persistent and severe pain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".