Search papers, labs, and topics across Lattice.
This narrative review examines vascular age (VA) as a biological marker for cardiovascular disease (CVD) risk assessment, offering a more intuitive understanding of vascular health compared to chronological age. It summarizes various VA assessment methods, including arterial stiffness measurements (pulse wave velocity), vascular structure evaluations (carotid intima-media thickness, coronary artery calcium score), vascular function tests, and multifactorial risk-scoring models, while also exploring emerging AI-driven technologies. The review highlights VA's role in improving CVD risk stratification, patient communication, personalized treatments, and its application in specific populations.
Vascular age assessment may offer a more intuitive and personalized approach to cardiovascular risk stratification and patient communication compared to traditional risk factor models.
Cardiovascular disease (CVD) is the leading cause of death and disability globally, highlighting the importance of effective risk assessment and early intervention. However, traditional risk assessment models based on common risk factors have limitations, particularly for stratifying intermediate-risk individuals. Vascular age (VA), a biological marker combining multiple cardiovascular risk factors and cumulative damage to the vascular system, has gained increasing attention as a more intuitive understanding of vascular health than chronological age. This may facilitate clearer physician-patient communication, and promote lifestyle changes and treatment adherence. This review summarizes methods for assessing VA and recent clinical advances. It explains popular evaluation techniques, including those based on arterial stiffness (such as pulse wave velocity), vascular structure (e.g., carotid intima-media thickness, coronary artery calcium score), vascular function, and multifactorial risk-scoring models. Emerging technologies using artificial intelligence (e.g., deep learning) to estimate VA from photoplethysmography or retinal images are also discussed. The review highlights the role of VA in improving CVD risk stratification, improving patient communication and adherence, guiding personalized treatments, and its application to specific populations (including those with diabetes and rheumatoid arthritis). It emphasizes key concepts such as early vascular aging and supernormal vascular aging. Finally, current challenges are discussed, including the need for standardized assessment methods, establishment of reference values, and evaluation of cost-effectiveness. Future directions such as technological innovations, clinical trial designs, and practical applications are explored. By thoroughly analyzing existing evidence, this review provides a valuable reference for further research and clinical implementation of vascular age.
