Role of Carotid Ultrasound and Systematic Coronary Risk Evaluation Charts for the Cardiovascular Risk Stratification of Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: The assessment of the cardiovascular (CV) risk is recommended in patients with chronic inflammatory rheumatic diseases. The objectives of this study were to assess the CV risk profile in a cohort of patients with psoriatic arthritis (PsA), to determine the presence of subclinical cardiovascular disease by carotid ultrasound (US), and to study the association of CV disease to PsA characteristics. METHODS: This was a cross-sectional multicentric descriptive study. The clinical CV risk was calculated with Systematic Coronary Risk Evaluation (SCORE) charts. Common carotid US was conducted to evaluate the carotid wall intima-media thickness and the presence of atheroma plaques. Patients were reclassified upon US results. Multivariate analyses were performed to identify associations of US carotid abnormalities with the classical CV risk factors and PsA characteristics. RESULTS: The study included 176 patients with PsA. The SCORE-estimated CV risk was intermediate in 65.3% of the patients. In the US study, 32% of the patients had abnormalities, and 30.8% of the patients were upgraded and reclassified as very high risk owing to the presence of atheroma. Subclinical CV disease was associated with age and dyslipidemia but not with other risk factors. It was associated with axial disease in the subgroup with intermediate risk, and with C-reactive protein levels in patients with high risk. CONCLUSION: Many patients with PsA have clinical estimated intermediate or high risk of a fatal CV event. A carotid US study detects subclinical vascular disease and may be useful to depict the real risk. The presence of atheroma is only partially explained by the classic CV risk factors.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".