Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide.

Many forms of cardiovascular disease, such as atherosclerosis, can progress silently without causing noticeable symptoms in the early stages. This asymptomatic phase allows the disease to advance without detection until it reaches a more advanced stage or manifests as a clinical event (e.g., heart attack, stroke).

Cardiovascular disease often develops over many years as a result of the accumulation of modifiable risk factors such as hypertension, dyslipidemia, diabetes, obesity, smoking, physical inactivity, and unhealthy diet. These risk factors may go unrecognized or unaddressed until they contribute to the development of overt CVD.

This is why early detection is so critical. Routine screening may miss early states of cardiovascular disease.  For example, exercise stress testing will often be negative until there is already significant atherosclerotic disease.

The earlier you can detect signs of atherosclerotic heart disease, the more likely you can slow down progression of disease or in some cases regression of disease.

Advanced strategies for cardiovascular disease (CVD) screening involve a comprehensive approach that takes into account both traditional risk factors and emerging technologies. Here are some advanced strategies for CVD screening:

• Advanced Lipid Testing: Beyond traditional lipid panels (total cholesterol, LDL cholesterol, HDL cholesterol, and triglycerides), advanced lipid testing assesses additional lipid parameters such as apolipoprotein B (apoB), lipoprotein(a) [Lp(a)], and small dense LDL particles. These tests provide a more comprehensive evaluation of lipid-related cardiovascular risk.
• High-Sensitivity C-Reactive Protein (hs-CRP) Testing: hs-CRP is a marker of inflammation that has been associated with increased cardiovascular risk. Measuring hs-CRP levels can help identify individuals at higher risk of CVD, particularly those with low or moderate traditional risk factors.
• Coronary Artery Calcium (CAC) Scoring: CAC scoring using non-invasive imaging techniques like computed tomography (CT) measures the amount of calcified plaque in the coronary arteries. High CAC scores indicate a greater burden of atherosclerosis and are associated with increased risk of coronary events. CAC scoring provides additional risk stratification beyond traditional risk factors.
• Carotid Intima-Media Thickness (CIMT) Measurement: CIMT measurement uses ultrasound to assess the thickness of the carotid artery wall, which can indicate the presence of atherosclerosis. Increased CIMT is associated with higher cardiovascular risk, and it can be used for risk stratification in asymptomatic individuals.
• Genetic Testing: Genetic testing can identify specific genetic variants associated with cardiovascular risk, such as familial hypercholesterolemia, ApoE or other genetic lipid disorders. Understanding an individual’s genetic predisposition to CVD can help tailor preventive strategies and treatment approaches.
• Advanced Imaging Techniques: Advanced imaging modalities like cardiac magnetic resonance imaging (MRI) and coronary CT angiography can provide detailed anatomical and functional information about the heart and coronary arteries, allowing for more precise risk assessment in certain populations.
• Machine Learning and Artificial Intelligence: Machine learning algorithms can analyze large datasets to identify patterns and predictors of cardiovascular risk more accurately than traditional risk calculators. Incorporating artificial intelligence into risk assessment models may improve risk stratification and personalize treatment decisions.
• Metabolomics and Proteomics: Metabolomics and proteomics technologies analyze metabolites and proteins in biological samples to identify biomarkers associated with cardiovascular risk. These omics approaches can provide insights into underlying metabolic pathways and pathophysiological mechanisms of CVD.
• Mobile Health (mHealth) and Wearable Devices: Utilizing mobile health applications and wearable devices that monitor physiological parameters such as heart rate, blood pressure, and physical activity levels can provide real-time data for assessing cardiovascular health and guiding lifestyle interventions.
• Integration of Multimodal Data: Integrating data from multiple advanced screening modalities, including clinical, imaging, genetic, and biomarker data, into comprehensive risk assessment algorithms can enhance risk prediction accuracy and facilitate personalized preventive strategies.