The incidence of depression and anxiety in patients with ankylosing spondylitis: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: As awareness for the importance of mental health continues to expand in rheumatology, it is important to understand the epidemiology of psychiatric complications in ankylosing spondylitis (AS) with the ultimate goal of future prevention and improved quality of care. This study aims to review evidence on the incidence and determinants of depression and/or anxiety among patients with AS. METHODS: We searched Medline, Embase, Cochrane Database of Systematic Reviews, CINAHL Complete, and PsycINFO for full-length observational studies that involved a sample or population of patients with AS and assessed depression and/or anxiety. Primary outcomes extracted were: 1) risk estimates for depression and/or anxiety (e.g., relative risk [RR]); and 2) determinants or factors identified as independent predictors of depression and/or anxiety using multivariable regression approaches and corresponding estimates (e.g., odds ratios [OR]). Where relevant, we pooled estimates using random effects models. RESULTS: Out of 783 titles from our search strategy, we reviewed 39 manuscripts. Four studies assessed the incidence of depression and meta-analyzing reported estimates from three of these studies yielded a pooled RR of 1.51 (95% CI 1.28 to 1.79). Differences in risk of depression among men and women with AS were inconclusive, suggesting need for further study. The incidence of anxiety was comparatively less studied with only one included study reporting a hazard ratio of 1.85 (95% CI 1.37 to 2.49). Education level was a key determinant, with lower levels associated with higher odds of depression (OR 6.65; 9% CI 1.36 to 32.51) and anxiety (OR 9.31; 9% CI 1.39 to 62.19) among AS patients. CONCLUSIONS: Our systematic review and meta-analysis shows an increased risk of depression and anxiety among patients with AS. These findings suggest the importance of monitoring and care for psychiatric conditions in AS.
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.039 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".