Psoriatic arthritis and the association with cardiometabolic disease: a narrative review
Bibliographic record
Abstract
Psoriatic arthritis (PsA) is associated with a higher burden of cardiometabolic disorders, such as hypertension, dyslipidemia, diabetes, obesity, and cardiovascular disease (CVD), compared with the general population. These comorbidities are associated with the severity of disease, and adversely affect treatment outcomes in PsA. Comorbidities lead to increased physician visits and medications for patients and make the selection and maintenance of therapies challenging for physicians. Moreover, CVD is a leading cause of mortality in PsA. Therefore, optimal management of PsA should include not only treating the skin and joint disease, but also identifying comorbidities early, and managing them to improve long-term outcomes. Further studies are needed to understand the complex mechanisms, interactions, and trajectories of cardiometabolic comorbidities in psoriatic disease. PLAIN LANGUAGE SUMMARY: Psoriatic arthritis (PsA) is associated with a higher incidence and prevalence of cardiometabolic comorbidities compared with the general population, and higher than psoriasis and other inflammatory arthritides, such as rheumatoid arthritis and other spondyloarthritides.Obesity and hyperlipidemia are associated with an increased risk of developing PsA.Cardiometabolic comorbidities in PsA are associated with more severe disease and a lower likelihood of response to therapy.Suggested approaches to improve screening and management of CVD in PsA include education of family physicians and relevant specialists, development of mechanisms to improve communication between the rheumatologists and primary care providers, and novel models of care, including interdisciplinary cardio-rheumatology clinics.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".