Anatolian journal of cardiology · 2026
A Comparative Study of Cardiovascular Risk Calculation Systems and the New PREVENT Model.
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Atıcı Yasemin, Şen Makbule Beyza, Yücel Doğan
Аннотация
BACKGROUND: Cardiovascular diseases (CVD) are a largely preventable cause of death worldwide. There are many risk factors that influence CVD, some of which are modifi-able and others non-modifiable. Several systems, such as the widely used Framingham, Reynolds, and the most recently developed Predicting Risk of Cardiovascular Disease EVENTs (PREVENT), are used to calculate an individual's CVD risk based on the effects of these risk factors.
METHODS: This study compared CVD risk scores calculated using the Framingham, Reynolds, and PREVENT systems. The risk factors common to these 3 systems were determined to be age, gender, smoking status, high-density lipoprotein cholesterol, total cholesterol, and systolic blood pressure, and the effects of these risk factors on CVD risk were evaluated. The numerical risk scores obtained because of the effects of risk factors were presented comparatively in tables created based on gender and smoking status.
RESULTS: According to the results obtained, it was observed that the PREVENT system provides more individualized results by including renal, metabolic, and social markers in the calculation and provides a more detailed assessment by also considering the age of risk.
CONCLUSION: These features may enable PREVENT to classify both low- and high-risk patients more clearly. This classification of patients may contribute to changing the course of CVD, a major global disease, by enabling appropriate interventions and treatments.
METHODS: This study compared CVD risk scores calculated using the Framingham, Reynolds, and PREVENT systems. The risk factors common to these 3 systems were determined to be age, gender, smoking status, high-density lipoprotein cholesterol, total cholesterol, and systolic blood pressure, and the effects of these risk factors on CVD risk were evaluated. The numerical risk scores obtained because of the effects of risk factors were presented comparatively in tables created based on gender and smoking status.
RESULTS: According to the results obtained, it was observed that the PREVENT system provides more individualized results by including renal, metabolic, and social markers in the calculation and provides a more detailed assessment by also considering the age of risk.
CONCLUSION: These features may enable PREVENT to classify both low- and high-risk patients more clearly. This classification of patients may contribute to changing the course of CVD, a major global disease, by enabling appropriate interventions and treatments.