Association of Cardiac Biomarkers With Cardiovascular Outcomes in Patients With Psoriatic Arthritis and Psoriasis: A Longitudinal Cohort Study
Bibliographic record
Abstract
OBJECTIVE: In patients with psoriatic disease (PsD), we determined whether cardiac troponin I (cTnI) and N-terminal pro-brain natriuretic peptide (NT-proBNP) were associated with carotid plaque burden and the development of cardiovascular events independent of the Framingham Risk Score (FRS). METHODS: Among 1,000 patients with PsD, carotid total plaque area (TPA) was measured in 358 participants at baseline. Cardiac troponin I and NT-proBNP were measured using automated clinical assays. The association between cardiac biomarkers and carotid atherosclerosis was assessed by multivariable regression after adjusting for cardiovascular risk factors. Improvement in the prediction of cardiovascular events beyond the FRS was tested using measures of risk discrimination and reclassification. RESULTS: In univariate analyses, cTnI (β coefficient 0.52 [95% confidence interval (95% CI) 0.3, 0.74], P < 0.001) and NT-proBNP (β coefficient 0.24 [95% CI 0.1, 0.39], P < 0.001) were associated with TPA. After adjusting for cardiovascular risk factors, the association remained statistically significant for cTnI (adjusted β coefficient 0.21 [95% CI 0, 0.41], P = 0.047) but not for NT-proBNP (P = 0.21). Among the 1,000 patients with PsD assessed for cardiovascular risk prediction, 64 patients had incident cardiovascular events. When comparing a base model (with the FRS alone) to expanded models (with the FRS plus cardiac biomarkers), there was no improvement in predictive performance. CONCLUSION: In patients with PsD, cTnI may reflect the burden of atherosclerosis, independent of traditional cardiovascular risk factors. Cardiac troponin I and NT-proBNP are associated with incident cardiovascular events independent of the FRS, but further study of their role in cardiovascular risk stratification is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".