Integrating Conventional and Emerging Approaches in Cardiovascular Risk Assessment and Management.

Abstract

Cardiovascular diseases (CVDs) remain the leading cause of global mortality, and the burden is rising fastest in low- and middle-income countries (LMICs). Conventional risk calculators, such as Framingham and Systematic Coronary Risk Evaluation (SCORE), incorporate age, blood pressure, cholesterol, diabetes and smoking, yet they underperform in populations that differ from their derivation cohorts and leave substantial residual risk unexplained. This narrative review evaluates traditional risk factors alongside emerging tools, including coronary artery calcium (CAC) scoring, polygenic risk scores (PRS) and inflammatory biomarkers such as high-sensitivity C-reactive protein (hsCRP) and interleukin-6. It examines the contribution of lifestyle and environmental exposures-chronic stress, physical inactivity, and air pollution-to inflammatory and atherogenic pathways and considers the role of imaging, molecular biomarkers, and artificial intelligence (AI)-assisted algorithms in risk stratification. Management strategies combining pharmacological therapy (statins, antihypertensives and antidiabetic agents) with individualised de-escalation, lifestyle modification and precision medicine are summarised. Rather than describing each tool in isolation, this review compares them directly on incremental predictive value, cost, infrastructure requirements, equity implications and readiness for routine implementation, and proposes a stepwise pathway for integrating them into cardiovascular risk assessment. Particular attention is given to feasibility in resource-constrained health systems, where most of the global CVD burden now falls. We conclude that the near-term public health gain lies less in broad adoption of novel tests than in their selective use where they change management, coupled with stronger delivery of established, low-cost preventive care.