Depressive symptoms predict future simple disease activity index scores and simple disease activity index remission in a prospective cohort of patients with early inflammatory polyarthritis
Bibliographic record
Abstract
OBJECTIVE: To determine whether depressive symptoms assessed in treated patients with early inflammatory polyarthritis (EPA) influence disease activity during follow-up. METHODS: Consecutively recruited EPA patients were actively treated to remission. Simple disease activity index (SDAI) and Center for Epidemiologic Studies Depression Scale (CES-D) scores were calculated at inclusion and up to 42 months into disease. SDAI scores were log-transformed to compute univariate and multivariate linear regressions. Parametric interval-censored Kaplan-Meier and survival regressions using Weibull distribution were used to assess time to and predictors of SDAI remission. RESULTS: A total of 275 EPA patients were recruited at a median of 4 months into disease. In multivariate linear regression models, accounting for baseline demographic, clinical, serological and functional variables and 12-month inflammation markers, CES-D scores at 12 months into disease were correlated (r(2) = 0.14) with subsequent SDAI scores. Patients with 12-month high CES-D (≥19; suggestive of depression) had a lower proportion of SDAI remission (31.3% vs 84.3%; P < 0.001) and reached SDAI remission less rapidly [hazard ratio = 0.25 (95% CI 0.12, 0.53); P < 0.001]. CONCLUSION: Each follow-up SDAI correlated significantly with 12-month depressive symptoms, a median of 7 months after initiation of treatment. CES-D scores suggestive of depression at 12 months were strongly correlated with delay and failure to reach remission later on. Depressive symptoms in treated EPA patients represent important clinical issues with long-term association with disease activity. Interventions to alleviate persistent depressive symptoms in treated EPA warrant careful evaluation of their potential to improve disease remission rates.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".