New Risk Calculator Shows Promise in Predicting Heart Attack Risk
TL;DR
Identify high-risk for heart attack with PREVENT risk calculator, giving advantage in tailored care and preventive treatment.
PREVENT calculator uses factors like age, blood pressure, cholesterol to estimate heart attack risk accurately.
PREVENT tool helps predict heart attack risk, enabling tailored care and preventive treatments for better patient outcomes.
Combining PREVENT scores and coronary calcium score improves risk prediction accuracy, a significant advancement in cardiovascular disease prevention.
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Researchers at New York University's Grossman School of Medicine have validated the American Heart Association's PREVENT risk calculator's ability to estimate 10-year cardiovascular disease risk with significant accuracy. The study, published in the Journal of the American Heart Association, analyzed electronic health records of 6,961 adults to assess the tool's predictive capabilities.
The PREVENT calculator evaluates heart attack risk by considering multiple factors including age, blood pressure, cholesterol, body mass index, diabetes status, social determinants of health, smoking, and kidney function. In the study, researchers found that the calculator's risk estimates directly correlated with coronary artery calcium (CAC) scores, a key indicator of potential heart disease.
Key findings revealed that 43.6% of participants had a low heart attack risk (less than 5%), while 6.2% were categorized as high-risk (more than 20%). Notably, when the PREVENT score was combined with CAC scores, risk prediction accuracy improved, allowing for more precise identification of individuals potentially requiring preventive interventions.
Dr. Morgan Grams, the study's corresponding author, emphasized the significance of these findings, suggesting that improved risk prediction enables more tailored healthcare approaches, potentially including targeted use of cholesterol-lowering medications.
While promising, researchers acknowledged study limitations, including a predominantly white participant pool and a relatively short follow-up period of 1.2 years. These constraints suggest the need for further research with more diverse populations to validate the tool's broader applicability.
Curated from NewMediaWire
