Multifactor predictive model in patients with myocardial infarction based on modern biomarkers

Abstract

Objective To study the prognostic role of current serum biomarkers in patients with myocardial infarction (MI) by constructing a multifactorial model for prediction of cardiovascular complications (CVC) in remote MI. Acute coronary syndrome is a major cause of death and disability in the Russian Federation. Introduction of current biomarkers, such as N-terminal pro-brain natriuretic peptide, stimulating growth factor (ST2), and centraxin-2 (Pentraxin, Ptx-3), provides more possibilities for diagnostics and calculation of risk for CVC.Materials and Methods Concentrations of biomarkers were measured in 180 patients with MI (mean age, 61.4±1.7) upon admission. At one year, specific and composite endpoints were determined (MI, acute cerebrovascular disease, admission for CVD, and cardiovascular death). Based on this information, a prognostic model for subsequent events was developed.Results A mathematical model was created for computing the development of a composite endpoint. In this model, the biomarkers NT-proBNP, Ptx-3 and, to a lesser extent, ST2 demonstrated their prognostic significance in diagnosis of CVC with a sensitivity of 78.79 % and specificity of 86.67 % (area under the curve, AUC 0.73).Conclusion In patients with remote MI, the biomarkers NT-proBNP, ST2, and Ptx-3 improve prediction of CVC.