Trends in Anxiety and Depression Among Individuals With Rheumatoid Arthritis: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVE: To investigate trends in depression and anxiety over 3 decades among individuals with rheumatoid arthritis (RA). METHODS: Patients with incident RA (age ≥ 18 years, meeting 1987 American College of Rheumatology criteria between 1985 and 2014) were identified using the Rochester Epidemiology Project. Individuals with RA were matched 1:1 with non-RA comparators on age, sex, and calendar year of RA incidence. Patients were followed until death, migration, or December 31, 2020. Depression and anxiety were defined using established International Classification of Diseases, 9th and 10th revision code sets. Cox models were used to compare trends in the occurrence of depression and anxiety diagnoses and cooccurring anxiety and depression by decade and RA status, adjusted for potential confounders. RESULTS: The study included 1012 individuals with RA and 1012 matched controls (mean age 55.9 years, 68.38% female). Hazard ratios (HRs) demonstrated a temporal increase in anxiety and cooccurring anxiety and depression from 2005-2014 compared to 1985-1994 for individuals both with and without RA. Persons with RA exhibited a rising occurrence of anxiety (HR 1.27, 95% CI 0.86-1.88) and concomitant anxiety and depression (HR 1.49, 95% CI 0.96-2.33) compared to controls. Trends were most pronounced in seropositive patients with RA (anxiety: HR 4.01, 95% CI 2.21-7.30). CONCLUSION: Anxiety and concomitant anxiety and depression diagnoses are elevated in individuals with RA. The increasing occurrence of anxiety and cooccurring anxiety and depression suggests rising awareness and diagnosis of these disorders. Adding to stable but high rates of depression diagnoses, individuals with RA now have evidence of a widening gap in mental health diagnoses that clinicians should address.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".