Adoption of the PREVENT (Predicting Risk of Cardiovascular Disease EVENTs) Risk Algorithm: Potential International Implications
Authors' conclusion
PREVENT substantially reclassifies risk and has the potential to alter prevention practice patterns.
Study context
- Population
- Simulated males and females aged 40 to 75 years with and without traditional risk factors, normal eGFR (90 or 60 ml/min/1.73 m²) or abnormal eGFR (45 or 30 ml/min/1.73 m²)simulated cohort
- Exposure
- PREVENT vs standard risk algorithms
- Outcome
- Concordance and reclassification rates by risk category, emphasis on moderate risk by standard algorithms
Methodological detailssimulated cohort
- Simulated cohort
Main finding
As reported in the abstract
- PREVENT concordant with standard algorithms (moderate risk)
- 6% to 88% of simulations
- Normal eGFR: PREVENT lower risk
- 18% to 88% of simulations
- Normal eGFR: PREVENT higher risk
- 0% to 12% of simulations
- Abnormal eGFR: PREVENT lower risk
- 0% to 26% of simulations
- Abnormal eGFR: PREVENT higher risk
- 4% to 94% of simulations
Observational data: associations, not effects.
Further findings
- PREVENT showed increased risk with progressive decreases in eGFR
Original publication
Adoption of the PREVENT (Predicting Risk of Cardiovascular Disease EVENTs) Risk Algorithm: Potential International Implications. JACC Adv. Published 18 July 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →