Comorbidities Associated with Psoriatic Arthritis Compared with Non-psoriatic Spondyloarthritis: A Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVE: Psoriatic arthritis (PsA) is a chronic inflammatory skeletal disease associated with health concerns such as obesity, Type II diabetes, dyslipidemia, hypertension (HTN), and cardiovascular (CV) disease. The involvement of these metabolic factors in the pathogenesis, severity, and progression of PsA remains unclear. In our study, we compared comorbidities associated with PsA to those patients with related but non-PsA forms of spondyloarthritis (SpA). METHODS: The SpA database at the Rheumatology Department of University Hospitals Leuven was analyzed in a cross-sectional manner using the demographic, medical, and laboratory information of 518 patients with PsA and non-PsA SpA. The patients were grouped by their diagnosis and evaluated on the basis of sex, age, education, work status, disease duration, treatment, and type and number of comorbidities. The data were assessed using the chi-square test, Student t test, Fisher's exact test, and logistic regression, including correction for multiple testing. RESULTS: Out of the 518 patients (62.74% men, 37.25% women), 53.66% had comorbidities. The PsA group had 262 patients (mean age 58.8 yrs) and the non-PsA SpA group had 256 patients (mean age 44.9 yrs, p < 0.001). The PsA group was found to have more and multiple comorbidities compared with non-PsA SpA (p < 0.001). The CV and metabolic comorbidities were also significantly higher in the PsA group (p < 0.001). Coronary artery disease, HTN, hyperlipidemia, and metabolic syndrome showed a marked difference between the 2 groups (p < 0.05). An increased incidence of malignancy was found in PsA group (p < 0.05). CONCLUSION: Comorbidities and malignancies are increased in patients with PsA compared with non-PsA SpA, irrespective of demographic factors and type of treatment.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".