Affiliation:
1. Pacific State Medical University; Vladivostok Clinical Hospital No. 1
2. Pacific State Medical University
3. Vladivostok State University of Economics and Service, Institute of Information Technologies
Abstract
The research purpose: development of a mathematical model for predicting the risk of carotid atherosclerosis in young adults 30-49 years old of Slavic and Korean ethnicity.Materials and methods. 136 conditionally healthy people of Slavic (n-84) and Korean ethnicity (n-52) were evaluated. The survey was conducted according to the design of ESSE-RF study. A carotid arteries duplex scan has been conducted. The predictive model was developed using the logistic regression method.Results. Ethnic groups did not differ among themselves in terms of age, smoking prevalence and gender (p > 0.05). In KEG increased levels of apoB containing lipoproteins was revealed (level non-HDL-C in KEG was 5,0 ± 1,1 mmol/l versus 4.0 ± 0.9 mmol/l in SEG (p < 0,001), HDL and apoA did not differ between groups (p > 0,05).The prevalence atherosclerosis of the CA was 28.6% in SEG and 32.7% in KEG (p > 0,05). In average KEG had more pronounced atherosclerotic process in the CAthe total percentage of stenosis in the SEG 40 [20; 50] % vs 51 [29; 59] % in KEG, p =0,044, and the average % of stenoses is 22.5 [20; 25] % versus 25.5 [24.6; 29] % respectively, p = 0.029.Binary logistic regression method was used for developing a predictive model for determine the risk of developing carotid atherosclerosis, the area under the ROC curve was 0.848 ± 0.040 with 95% CI: 0.769–0.927. The model was statistically significant, p < 0,001.Conclusion. Above referenced model makes it possible to evaluate with high accuracy the risk of developing carotid atherosclerosis on a standard dispensary appointment basis.
Reference15 articles.
1. Cardiovascular prevention 2017. National guidelines. Russian Journal of Cardiology. 2018;(6):7-122. (In Russ.) https://doi.org/10.15829/1560-4071-2018-6-7-122
2. Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Bäck M, Benetos A, Biffi A, Boavida JM, Capodanno D, Cosyns B, Crawford C, Davos CH, Desormais I, Di Angelantonio E, Franco OH, Halvorsen S, Hobbs FDR, Hollander M, Jankowska EA, Michal M, Sacco S, Sattar N, Tokgozoglu L, Tonstad S, Tsioufis KP, van Dis I, van Gelder IC, Wanner C, Williams B; ESC National Cardiac Societies; ESC Scientific Document Group. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021 Sep 7;42(34):3227-3337. https://doi.org/10.1093/eurheartj/ehab484
3. Кухарчук В.В., Ежов М.В., Сергиенко И.В. и др. Диагностика и коррекция нарушений липидного обмена с целью профилактики и лечения атеросклероза. Российские рекомендации, VII пересмотр. Атеросклероз и дислипидемии. 2020;1(38):7-42. https://doi.org:10.34687/2219-8202. JAD.2020.01.0002
4. SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J. 2021 Jul 1;42(25):2439-2454. https://doi.org/10.1093/eurheartj/ehab309
5. Boytsov SA, Chazov EI, Shlyahto EV, et al. Scientific-organizational committee of the project ESSЕ-RF. Epidemiology of cardiovascular diseases in various regions of Russia (ESSE-RF). Justification and design of the study. Preventive medicine. 2013;16(6):25-34