The influence of factors on five-year outcomes after acute coronary syndrome

Abstract

Aim. To identify the factors of long-term adverse prognosis of patients with acute coronary syndrome as a result of five-year follow-up.Material and methods. The study included 280 patients with ACS hospitalized in the 1st cardiology Department of the Novosibirsk municipal CLINICAL hospital № 1 in 2010-2011. The study cohort included 145 patients with ACS (107 men and 38 women), 135 patients with ACS (93 men and 43 women). The average age of men was 56,3±5,2, women 52,1±5,3 years. The criteria of the European society of cardiology (2015, 2017) were used for the diagnosis of ACS. For five years, all patients included in the study were contacted through communication and annual medical examinations, to which patients were invited to the clinic. The examinations included the following clinical and instrumental examinations: clinical examination, electrocardiography, Holter monitoring of electrocardiogram, echocardiography, lipid profile, inflammatory cytokines and molecular genetic parameters. In the study, a mathematical model for predicting five-year outcomes Oxpt and Oxbt. Results. Five-year observation allowed using the constructed mathematical model to determine not only the place of each factor in the cardiovascular prognosis, but also to assess how the role of these prognostic markers changes over time. Conclusion. The use of a mathematical model for predicting long-term adverse outcomes of ACS allows to assess the value of specific risk factors and predictors, respectively, makes a significant contribution to the optimization of secondary prevention and personalized approach to treatment. At the same time, the influence of the identified predictors weakens in proportion to the increase in the number of years from a vascular accident. Thus, the identified risk factors have the maximum impact in the first year after ACS, in subsequent years, the role of these factors is reduced, which is probably due not only to the importance of the factors themselves, but also to the addition of other risk factors to the overall picture of the disease of patients. Nevertheless, the use of this model is necessary to solve the problem of reducing cardiovascular risk.

Keywords

• acute coronary syndrome
• myocardial infarction
• prognostic factors
• multifactorial prediction
• genetic markers