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Peer-reviewedCC BY-NC 4.0Anatolian Journal of Cardiology

A Comparative Study of Cardiovascular Risk Calculation Systems and the New PREVENT Model

  • Yasemin Atıcı1
  • Makbule Beyza Şen2
  • Doğan Yücel1
  1. 1Department of Medical Biochemistry, Faculty of Medicine, Lokman Hekim University, Ankara, Türkiye
  2. 2Department of Biochemistry, Faculty of Pharmacy, Lokman Hekim University, Ankara, Türkiye
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Abstract

Background:: Cardiovascular diseases (CVD) are a largely preventable cause of death worldwide. There are many risk factors that influence CVD, some of which are modifiable 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.

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Cite

BibTeXRIS
BibTeX
@article{atıcı2026comparative,
  title = {{A Comparative Study of Cardiovascular Risk Calculation Systems and the New PREVENT Model}},
  author = {Yasemin Atıcı and Makbule Beyza Şen and Doğan Yücel},
  journal = {Anatolian Journal of Cardiology},
  year = {2026},
  month = jul,
  doi = {10.14744/anatoljcardiol.2026.6049},
  url = {https://doi.org/10.14744/anatoljcardiol.2026.6049},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - A Comparative Study of Cardiovascular Risk Calculation Systems and the New PREVENT Model
AU  - Yasemin Atıcı
AU  - Makbule Beyza Şen
AU  - Doğan Yücel
PY  - 2026
DA  - 2026/07/21
JO  - Anatolian Journal of Cardiology
DO  - 10.14744/anatoljcardiol.2026.6049
UR  - https://doi.org/10.14744/anatoljcardiol.2026.6049
AB  - Background:: Cardiovascular diseases (CVD) are a largely preventable cause of death worldwide. There are many risk factors that influence CVD, some of which are modifiable 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.
SN  - 2149-2263
SN  - 2149-2271
ER  -