[Individual coronary heart disease risk prediction as part of primary prevention]

Area of Science:

• Cardiology
• Preventive Medicine
• Medical Imaging

Context:

• Population-level interventions for traditional risk factors have advanced coronary heart disease (CHD) prevention.
• Current individual cardiovascular disease (CVD) prediction models, relying on traditional risk factors and global risk scoring, show limitations.
• A significant number of primary cardiovascular events occur in individuals with seemingly low calculated risk, including younger patients, women, and those without multiple risk factors.

Purpose:

• To evaluate the prognostic value of established global risk scoring models for individual CHD prediction.
• To assess the added value of incorporating novel risk factors into risk prediction models.
• To determine the role of cardiovascular imaging modalities in diagnosing subclinical atherosclerosis for improved risk stratification.

Summary:

• This review examines the effectiveness of standard global risk scoring models in predicting individual CHD risk.
• It explores the potential of new risk factors to enhance the accuracy of existing prediction tools.
• The review highlights the contribution of cardiovascular imaging, such as carotid ultrasound and coronary CT angiography, in identifying subclinical atherosclerosis and refining risk assessment.

Impact:

• Identifies limitations in current individual CHD risk prediction, particularly for low-risk populations.
• Suggests incorporating novel risk factors and advanced imaging techniques to improve the accuracy of cardiovascular risk assessment.
• Aims to enhance primary prevention strategies by providing more precise individual risk stratification for cardiovascular events.