Increased Burden of Psychiatric Disorders in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: We estimated the incidence and prevalence of depression, anxiety disorder, bipolar disorder, and schizophrenia in a population-based cohort with rheumatoid arthritis (RA) as compared to an age-, sex-, and geographically matched cohort without RA. METHODS: Using population-based administrative health data from Manitoba, Canada, we identified persons with incident RA between 1989 and 2012, and a cohort from the general population matched 5:1 on year of birth, sex, and region of residence. We applied validated algorithms for depression, anxiety disorder, bipolar disorder, and schizophrenia to determine the annual incidence of these conditions after the diagnosis of RA, and their lifetime and annual period prevalence. We compared findings between cohorts using negative binomial regression models. RESULTS: We identified 10,206 incident cases of RA and 50,960 matched individuals. After adjustment for age, sex, socioeconomic status, region of residence, number of physician visits, and year, the incidence of depression was higher in the RA cohort over the study period (incidence rate ratio [IRR] 1.46 [95% confidence interval (95% CI) 1.35-1.58]), as was the incidence of anxiety disorder (IRR 1.24 [95% CI 1.15-1.34]) and bipolar disorder (IRR 1.21 [95% CI 1.00-1.47]). The incidence of schizophrenia did not differ between groups (IRR 0.96 [95% CI 0.61-1.50]). Incidence rates of psychiatric disorders declined minimally over time. The lifetime and annual period prevalence of depression and anxiety disorder were also higher in the RA than in the matched cohort over the study period. CONCLUSION: The incidence and prevalence of depression, anxiety disorder, and bipolar disorder are elevated in the RA population as compared to a matched population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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 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".