Algorithm for non-invasive diagnosis of obliterating coronary atherosclerosis based on imaging and laboratory markers
https://doi.org/10.15829/1728-8800-2023-3698
EDN: QWCCQD
Abstract
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.
About the Authors
O. M. Drapkina
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation
Russian Federation
Moscow
V. A. Metelskaya
National Medical Research Center for Therapy and Preventive Medicine;
Russian Medical Academy of Continuous Professional Education
Russian Federation
Russian Federation
Moscow
M. V. Dubinskaya
Filatov City Clinical Hospital № 15
Russian Federation
Russian Federation
Moscow
E. B. Yarovaya
National Medical Research Center for Therapy and Preventive Medicine;
Lomonosov Moscow State University
Russian Federation
Russian Federation
Moscow
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What is already known about the subject?
- A variety of scales, schemes and algorithms have been proposed that allow predicting the risk of occurrence and progression of atherosclerotic cardiovascular diseases in various population groups with varying degrees of probability.
- The results of clinical and paraclinical studies as independent markers showed their moderate effectiveness in verifying coronary atherosclerosis and a very low ability in detecting subclinical involvement.
What might this study add?
- The potential of using a combination of clinical and paraclinical markers to detect coronary artery atherosclerosis presence and severity was shown.
- A 5-step algorithm for non-invasive assessment of coronary atherosclerosis probability has been developed, the use of which makes it possible to differentiate patients with and without coronary atherosclerosis and stratify them depending on its severity.
Review
For citations:
Drapkina O.M., Metelskaya V.A., Dubinskaya M.V., Yarovaya E.B. Algorithm for non-invasive diagnosis of obliterating coronary atherosclerosis based on imaging and laboratory markers. Cardiovascular Therapy and Prevention. 2023;22(8):3698. (In Russ.) https://doi.org/10.15829/1728-8800-2023-3698. EDN: QWCCQD
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