Heart failure with preserved left ventricular ejection fraction in patients with obstructive sleep apnea syndrome: prognostic value of biomarkers.

Aim      To study the role of soluble ST2 (sST2), N-terminal pro-brain natriuretic peptide (NT-proBNP), and С-reactive protein (CRP) in patients with chronic heart failure and preserved left ventricular ejection fraction (CHF with pLVEF) and syndrome of obstructive sleep apnea (SOSA) in stratification of the risk for development of cardiovascular complications (CVC) during one month of a prospective observation.Material and methods  The study included 71 men with SOSA with an apnea/hypopnea index (AHI) >15 per hour, abdominal obesity, and arterial hypertension. Polysomnographic study and echocardiography according to a standard protocol with additional evaluation of left ventricular myocardial fractional changes and work index were performed for all patients at baseline and after 12 months of observation. Serum concentrations of sST2 , NT-proBNP, and CRP were measured at baseline by enzyme-linked immunoassay (ELISA).Results The ROC analysis showed that the cutoff point characterizing the development of CVC were sST2 concentrations ≥29.67 ng/l (area under the curve, AUC, 0.773, sensitivity 65.71 %, specificity 86.11 %; p<0.0001) while concentrations of NT-proBNP (AUC 0.619; p=0.081) and CRP (AUC 0.511; р=0.869) were not prognostic markers for the risk of CVC. According to data of the ROC analysis, all patients were divided into 2 groups based on the sST2 cutoff point: group 1 included 29 patients with ST2 ≥29.67 ng/l and group 2 included 42 patients with ST2 <29.67 ng/l. The Kaplan-Meyer analysis showed that the incidence of CVC was higher in group 1 than in group 2 (79.3 and 28.6 %, respectively, p<0.001). The regression analysis showed that adding values of AHI and left ventricular myocardial mass index (LVMMI) to sST2 in the model increased the analysis predictive significance.Conclusion      Measuring sST2 concentration may be used as a noninvasive marker for assessment of the risk of CVC development in patients with CHF with pLVEF and SOSA within 12 months of observation. Adding AHI and LVMMI values to the model increases the predictive significance of the analysis.