Depression and anxiety in an early rheumatoid arthritis inception cohort. associations with demographic, socioeconomic and disease features
Bibliographic record
Abstract
OBJECTIVE: Depression and anxiety are not uncommon in Rheumatoid arthritis (RA). It is increasingly recognised that they are associated with high disease activity and worse disease outcomes. We aimed to examine the frequency of depression and anxiety in an early RA inception cohort and to explore associations with disease-related measures. METHODS: The Scottish Early Rheumatoid Arthritis inception cohort recruited newly diagnosed RA patients followed-up 6-monthly. Anxiety and depression were assessed using the hospital anxiety and depression scale. Associations with demographic characteristics and disease-related measures were examined at baseline, 6 months and 12 months. RESULTS: 848 RA patients were included. The prevalence of anxiety and depression at baseline was 19.0% and 12.2%, respectively. Depression and anxiety scores correlated with DAS28 at all time-points (all p<0.0001). In multivariable linear regression, anxiety score at baseline was associated with younger age and Health Assessment Questionnaire (HAQ) score. Anxiety scores at 6 months and 12 months were associated with low body mass index (BMI), baseline anxiety score and current patient global score and HAQ. Depression score at baseline was associated with younger age, being single and HAQ, while depression scores at 6 months and 12 months were associated with male gender (only at 6 months), baseline anxiety and depression scores and current patient global score, HAQ and C-reactive protein (CRP) levels. CONCLUSION: Depression and anxiety are associated with disease activity, worse functional status and other variables in early RA. There is a close relationship between CRP and depression but not anxiety.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".