Arterial hypertension (AH) is one of the leading contributors to the development of atherosclerotic cardiovascular disease; however, traditional risk assessment scales often fail to provide an accurate estimation of individual prognosis. Coronary artery calcification (CAC), detected by computed tomography (CT), is a highly specific marker of subclinical atherosclerosis and serves as a valuable tool for personalized cardiovascular risk stratification.

Aim: to systematize and summarize current evidence from international clinical guidelines, recommendations, and scientific publications regarding the clinical use of coronary artery calcium assessment as a tool for personalized therapy and risk prediction in patients with arterial hypertension.

Materials and methods. An analysis was conducted of international clinical guidelines, recommendations, and scientific publications indexed in the scientometric databases PubMed, Scopus, Web of Science, and Google Scholar. The following keywords were used: “arterial hypertension”, “dyslipidemia”, “coronary calcification”, “cardiovascular risk stratification”, “diabetes mellitus”, “cardiac computed tomography”, “primary prevention”, “screening of asymptomatic adults”.

Results. Based on the analysis of the professional literature, the prognostic value of the calcium index (CI) has been confirmed, as well as the place of the test in modern international guidelines. The clinical applications of the CI encompass test indications, patient risk reclassification, guidance for initiating lipid-lowering therapy, and evaluation of aspirin use in primary prevention. The evolution of quantitative coronary calcium assessment methods has been reviewed, alongside technical considerations for CT scanning and specialized software-based data processing. The Agatston score has been highlighted as the standardized metric for quantifying CAC. Key advantages of the method include the absence of contrast agent requirement, low radiation exposure, and increasing availability. Acknowledged limitations of the test include inability to detect non-calcified (“soft”) plaques and limited suitability for serial monitoring of therapy efficacy. The prospects of mass screening using automated analysis of chest CT images and artificial intelligence for early detection of subclinical atherosclerosis as well as personalization of cardiovascular risk assessment with preventive measures have been proven.

Conclusions. The detection of coronary calcification in patients with hypertension is a highly specific method for identifying subclinical atherosclerotic lesions with strong prognostic value for cardiovascular risk stratification and for a personalized approach to treatment and prevention.