Multifactorial Prognostication of Remote Outcomes in Patients With Non-ST Elevation Acute Coronary Syndrome

Abstract

Creation of a mathematical nonlinear regression model for prognostication of 1 year outcomes after non-ST elevation acute coronary syndrome (NSTE ACS) for optimization of rehabilitation, secondary prevention, and personalized approach to treatment. We included in this study 135 patients with confirmed NSTE ACS (mean age 59.1±6.1 years, 94 men and 41 women) admitted to hospital No 1 in Novosibirsk during 2010. During hospitalization and 1 year after discharge these patients received standard medical therapy. All patients underwent clinical and instrumental examination which included electrocardiography, echocardiography, Holter ECG monitoring. Program of clinical investigation also included determination of levels of inflammatory cytokines and molecular genetic studies. Effect of each of studied parameters on the probability of unfavorable one year prognosis was assessed by methods of correlation and factor analysis. The constructed mathematical model of multifactor prognostication of 1 year unfavorable or favorable outcomes after NSTE ACS included patient's age in years, presence of tachycardia at admission, Killip class >II, life-threatening paroxysmal tachyarrhythmias, as well as serum concentration of high-sensitivity C-reactive protein and CT genotype of a polymorphic variant rs1376251 of TAS2R50 gene. The use of the proposed model of multivariate prognostication of 1 year outcomes of NSTE ACS allows to improve the accuracy of events prediction, as it is based on data from Russian patients and takes into account the activity of subclinical inflammation and genotype of the patient. The model is simple to use and allows to personalize secondary prevention, which will facilitate lowering of total cardiovascular risk in these patients.