Specialists from the Petrozavodsk State University Medical Institute, collaborating with the IT company K-Sky LLC, a Skolkovo Foundation resident and the developer of the Webiomed platform, have developed a mathematical model aimed at predicting the progression of asymptomatic carotid atherosclerosis in individuals who are overweight or obese. This information was shared with socialbites.ca by the Russian Ministry of Education and Science.
Obesity and overweight are among the most prevalent risk factors driving cardiovascular diseases across the globe. In Russia, a cardiovascular risk assessment system based on commonly used risk scales, including SCORE, is employed as part of primary prevention. Yet, the predictive power of this tool is limited, particularly when there are low cardiovascular risk values at baseline.
Atherosclerosis involves the build-up of cholesterol within the walls of arteries. It often presents without noticeable symptoms, but its presence helps categorize a person with no prior cardiovascular disease into a high or very high cardiovascular risk group. This underscores the necessity for new diagnostic approaches.
One such approach is the newly developed mathematical model designed to confirm the atherosclerotic process in the carotid arteries. The model relies on data collected from around 2.9 million patients who were examined or treated within Russia. The extensive dataset adds depth to the model’s capability to identify subtle signals associated with early arterial disease.
Methods that estimate the probability of asymptomatic carotid atherosclerosis using machine learning have demonstrated strong predictive performance, with reported accuracy in the range of seventy-five to ninety-eight percent. This level of discrimination suggests substantial potential for improving risk stratification beyond traditional tools.
According to Mark Druzhilov, a member of the Department of Infectious Diseases and Epidemiology, integrating this mathematical model into the diagnostic workflow could meaningfully increase the likelihood that a patient is directed to ultrasound examination of the brachiocephalic arteries as part of a broader risk stratification strategy for individuals who initially present with low baseline cardiovascular risk according to SCORE. The aim is to optimize diagnostic precision while mindful of the overall cost of care.
Looking ahead, researchers intend to refine these tools further to predict the risk of thromboembolic, atherothrombotic, and hemorrhagic complications. Achieving improvements in predictive accuracy for these outcomes could contribute to reductions in mortality related to cardiovascular diseases, particularly among populations with higher body weight and related risk factors.