Algorithm for non-invasive diagnosis of obliterating coronary atherosclerosis based on imaging and laboratory markers

Aim . Using the ultrasound characteristics of the carotid and femoral arteries and a number of laboratory blood parameters, develop an algorithm for non-invasive diagnosis of coronary atherosclerosis. Material and methods . The study included 216 patients (53% men) aged 24-87 years (mean age, 61,5±10,73 years) who were admitted and examined in the hospital of the National Medical Research Center for Therapy and Preventive Medicine in the period of 2016-2019. All patients underwent diagnostic coronary angiography, duplex carotid and femoral ultrasound and biochemical blood tests. In accordance with coronary angiography, 3 groups of patients were formed: 1) without coronary atherosclerosis, 2) with subclinical and 3) severe coronary atherosclerosis, the examination results of which formed the basis of the developed diagnostic algorithm. Results . A stepwise algorithm for non-invasive detection of coronary atherosclerosis has been developed, which includes biochemical blood tests at stage I (glucose, high-sensitivity C-reactive protein, creatinine and adiponectin), a visual scale (VS) at stage II, a combination of clinical and paraclinical parameters (Celermajer test and left atrium antero-­posterior diameter) at stage III and allows to identify patients with varying degrees of coronary onvolvement (including subclinical). The sequential passage of algorithm steps by the patient increases the detection rate of coronary atherosclerosis of any degree by 12,2 times, and by 13,8 times in case of severe involvement. Conclusion . To rationale the use of a combined panel of available investigations, presented as a stepwise diagnostic algorithm, the proposed algorithm should be validated on an independent cohort or in prospective observation of the initial cohort of patients.