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

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.

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