The Risk of Developing Diabetes Mellitus in Patients with Psoriatic Arthritis: A Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence of diabetes mellitus (DM) in patients with psoriatic arthritis (PsA) in comparison with the general population and to assess whether the level of disease activity over time predicts the development of DM in these patients. METHODS: A cohort analysis was conducted in patients followed in a large PsA clinic from 1978 to 2014. The prevalence of DM in the patients was compared with the general population of Ontario, Canada, and the age-standardized prevalence ratio (SPR) was calculated. For the assessment of risk factors for DM, time-weighted arithmetic mean (AM) levels of PsA-related disease activity measures were assessed as predictors for the development of DM. Multivariable Cox proportional hazards models were used to compute HR for incident DM after controlling for potential confounders. RESULTS: A total of 1305 patients were included in the analysis. The SPR of DM in PsA compared with the general population in Ontario was 1.43 (p = 0.002). Of the 1065 patients who were included in the time-to-event analysis, 73 patients were observed to develop DM. Based on multivariable analyses, AM tender joint count (HR 1.53, 95% CI 1.08-2.18, p = 0.02) and AM erythrocyte sedimentation rate (HR 1.21, 95% CI 1.03-1.41, p = 0.02) predicted the development of DM. CONCLUSION: The prevalence of DM is higher in patients with PsA compared with the general population. Patients with elevated levels of disease activity are at higher risk of developing DM.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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 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".