N.A. DRAGOMIRETSKAYA, A.V. TOLMACHEVA, M.V. VETLUZHSKAYA, A.A. ABRAMOVA, I.D. MEDVEDEV, A.V. BELYAKOV, V.D. CHISTYAKOVA

 I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow

 Contact details:

Dragomiretskaya N.A. — Ph. D. (medicine), Associate Professor of the Department of Faculty Therapy No. 2 of the Institute of Clinical Medicine named after N.V. Sklifosovsky

Address: 8-2 Trubetskaya Str., Moscow, Russian Federation, 119991, tel.: +7 (495) 609-14-00, e-mail: dragomiretskaya_n_a@staff.sechenov.ru

 The purpose — to develop a method for predicting the unfavorable outcomes in patients with CHFpEF and CHFmrEF based on a comprehensive assessment of routine clinical and laboratory-instrumental parameters.

Material and methods. The study included 135 patients with FC II-IV CHF and LVEF > 40% (59 men and 76 women), hospitalized at the therapeutic clinic of Clinical Hospital No. 4 of Sechenov University, who signed informed consent. The average age was 76 ± 13 years. All patients were examined in accordance with current clinical guidelines for the diagnosis and treatment of CHF. The mortality was assessed 12 months after patient inclusion in the study. Statistical processing of the results was carried out using Statistica 12.0 and Jamovi 2.3.28.

Results. The one-year mortality rate for patients with CHFpEF was 10%, for CHFunEF – 27%. The first stage of developing a prospective model consisted of selecting the most significant clinical, laboratory and instrumental indicators, namely: LDL concentration in the blood plasma, AMI and AF history, systolic blood pressure, pneumonia at the time of hospitalization, NYHA FC, EF values LV and MPAP according to echocardiography, concentration of NT-proBNP, urea and hemoglobin in blood plasma. According to multivariate analysis, NT-proBNP (OR 1.0009; 95% CI 1.00029–1.002; p = 0.002), the presence of prior AMI (OR 3.458; 95% CI 1.039–11.507; p = 0.043) and pneumonia (OR 7.198; 95% CI 2.074–24.98; p = 0.04) showed significance and were included in the logistic regression model. According to ROC analysis, the model sensitivity was 81%, specificity — 76.8%, diagnostic efficiency — 77.8%. Model AUC = 0.863.

Conclusion: Independent significant risk factors for poor prognosis in patients with CHFpEF and CHFmrEF are previous MI and pneumonia, as well as the level of NT-proBNP. The developed algorithm is a simple mechanism for assessing the individual risk of poor prognosis in patients with CHF with LVEF > 40%.

Key words: CHFpEF, CHFmrEF, multifactorial prognostic model.

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