Serum uric acid significantly improves the accuracy of cardiovascular risk score models
Authors' conclusion
sUA significantly improves the classification accuracy of PCE and SCORE2 models. This effect is especially pronounced among normal-weight and low-risk subjects.
Study context
- Population
- Asymptomatic self-referred adults aged 40–79 years free of CVD and DM, screened annually in a preventive healthcare setting
- Participants
- 19,769 adults
- Exposure
- Pooled cohort equations (PCE) or SCORE2 with vs without high serum uric acid
- Outcome
- Composite of:
- Death
- ACS
- Stroke (excluding subjects diagnosed with metastatic cancer during follow-up)
- Follow-up
- Median 6 years
Methodological detailsMean age 50 ± 8 years; 69% men
- Mean age 50 ± 8 years; 69% men
Main finding
As reported in the abstract
Primary endpoint; classification accuracy (continuous net reclassification improvement)
Continuous net reclassification improvement
13%
P < 0.001
PCE + high serum uric acid (sUA) vs PCE
Continuous net reclassification improvement
13%
P < 0.001
SCORE2 + high sUA vs SCORE2
- Subjects reaching the study endpoint
- 1658 (8%)
- PCE, SCORE2 and high sUA independently associated with the endpoint (multivariable model)
- P < 0.001 for all
Observational data: associations, not effects.
Further findings
sUA and study endpoint by weight status (SCORE2 model, subgroup)
| HR (95% CI) | ||
|---|---|---|
| sUANormal-weight subjects | 1.3 (1.1–1.6) | |
| 0.512Hazard ratio (log scale) |
- sUA and study endpoint by weight status (SCORE2 model, subgroup): P for interaction = 0.01
sUA and study endpoint by weight status (SCORE2 model, subgroup)
- Not independently associated among overweight individuals
Model performance improvement among normal-weight and low-risk subjects (subgroup)
- Significant improvement in model performance
- 16-20%
- PCE
- P < 0.001
- SCORE2, normal-weight and low-risk respectively
- P = 0.026 and P < 0.001
Original publication
Serum uric acid significantly improves the accuracy of cardiovascular risk score models. Eur J Prev Cardiol. Published 15 November 2022. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →