Depression Is Associated with an Increased Risk of Psoriatic Arthritis among Patients with Psoriasis: A Population-Based Study
Bibliographic record
Abstract
The factors that contribute to the development of psoriatic arthritis (PsA) among patients with psoriasis are not well known; however, systemic inflammation is believed to be important. On the basis of recent laboratory work demonstrating that major depressive disorder (MDD) is associated with increased systemic inflammation, we hypothesized that patients with psoriasis who develop MDD are at increased risk of subsequently developing PsA. We utilized The Health Improvement Network, a primary care medical records database, to identify 73,447 individuals with psoriasis. Patients were followed up to 25 years until the development of the primary outcome of PsA or the censor date. The exposure of interest was the development of MDD. Cox proportional-hazards models showed that patients with psoriasis who developed MDD were at significantly increased risk of subsequently developing PsA compared with patients who did not develop MDD, even after accounting for numerous covariates (hazard ratio 1.37, 95% confidence interval 1.05-1.80, P = 0.021). This result was maintained through numerous sensitivity analyses. These data support the hypothesis that MDD increases the risk of developing PsA among patients with psoriasis, suggesting a need for heightened prevention and management of MDD in patients with psoriasis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".