Subclinical Atherosclerosis

The goal of this procedure-based interventional study without drugs or devices is to investigate the molecular mechanisms underlying metabolically unfavorable obesity and related clinical phenotypes, in order to identify non-invasive biomarkers capable of early prediction of metabolic syndrome, type 2 diabetes mellitus, MASLD, and cardiovascular disease in adult participants without known cardiovascular or liver disease. The main questions it aims to answer are: * What is the association between epicardial and visceral fat thickness and plasma levels of low-grade inflammatory biomarkers? * How do these parameters relate to the presence of metabolic syndrome, type 2 diabetes mellitus, MASLD, and subclinical atherosclerosis? Participants will: * Undergo a comprehensive clinical evaluation, including demographic, anthropometric, and medical history data; * Complete non-invasive diagnostic assessments, including 12-lead electrocardiogram, transthoracic echocardiography, liver elastography (FibroScan), and carotid Doppler ultrasound; * Provide peripheral venous blood samples for biochemical, cellular, and molecular analyses.

Objective: To validate the performance of the developed clinical decision support system (CDSS) for participants with lipid metabolism disorders based on a decision tree algorithm. Materials and Methods: A clinical decision support system for participants with lipid profile abnormalities will be developed using the Orbeon open-source online form creation platform based on current clinical guidelines. During the CDSS pilot implementation, the electronic medical records (EMRs) of 500 participants from the Institute of Personalized Cardiology of the Biomedical Science and Technology Park at Sechenov University will be analyzed. Retrospective data on prescribed lipid-lowering therapy extracted from the EHR will be compared with the CDSS recommendations. The accuracy of the decisions will be assessed by three independent experts based on digitized clinical and laboratory patient profiles. The primary endpoint of the study will be to determine the accuracy of the system. Results: This study will result in the development (creation) and pilot application of the CDSS program in participants with dyslipidemia in real clinical practice. Conclusion: The developed CDSS system for dyslipidemia will significantly reduce the time required for clinical decision-making and help avoid errors in the interpretation of patient data.