Predictors of development and forecasting models in the diagnosis of chronic heart failure against hypertension

Abstract

Annotation. Chronic heart failure (CHF) is a recognized public health problem with significant morbidity and mortality. Complementing and improving existing ones, as well as finding new methods for diagnosing and predicting the development of CHF is a promising and important area of research. The probable association between plasma concentrations of cerebral (BNP) and vascular (CNP) types of natriuretic peptides, features of clinical status and single nucleotide polymorphism of the BNP gene encoding was studied. The aim of the study was to improve the prognosis of CHF in women of Podolsk region of Ukraine aged 40-65 with hypertension by determining the range of the most important predictors of risk of CHF and creating a prognostic mathematical model for early personalized diagnosis of CHF based on carriers of polymorphic variants of the BNP gene. The survey involved 180 women aged 40-65 living in the Podolsk region of Ukraine: 67 women in the control group without signs of cardiovascular disease, 62 women with uncomplicated EH and 51 women with EH complicated by CHF. All patients were examined using general clinical, instrumental and laboratory methods. Genotyping of the BNP gene was performed by polymerase chain reaction. Plasma concentrations of BNP and CNP were determined by plate solid phase enzyme-linked immunosorbent assay. Mathematical processing was performed on a personal computer using the standard statistical package Statistica 10.0. It is established that among the predictors of the risk of heart failure in women 40-65 years with uncomplicated EH the most important role is played by: the level of plasma concentrations of BNP and CNP, overweight, burdened heredity of EH, the onset of EH up to 40 years, blood pressure, LV EF <40% and the presence of left ventricular diastolic dysfunction type of relaxation disorders. The proposed prognostic mathematical model in the form of a scheme of equations in the future can be a convenient and fast method of early individualized diagnosis of CHF, available for use in online format.