Diastolic heart failure: 20 years later. Сurrent issues of pathoge­nesis, diagnosis and treatment of heart failure with preserved LVEF

Abstract

Relevant aspects of the pathogenesis, diagnosis, And treatment of heart failure with preserved LV EFThis review analyzes results of studies of the recent decade that focus on epidemiology, mechanisms of development, diagnostic methods, and treatments of heart failure with preserved ejection fraction (HFpEF). As expected, the prevalence of HFpEF continues to increase due to the growing contribution of comorbidities to the structure of causes for chronic heart failure (CHF), such as arterial hypertension with left ventricular hypertrophy, obesity, chronic kidney disease, as well as due to ageing of the population and decreased contributions of ischemic heart disease and myocardial infarction. Concomitant diseases are a source of low-intensity microvascular inflammation, which is currently assigned a role of a trigger mechanism eventually provoking energy deficiency, disorders of cardiomyocyte relaxation, and diffuse myocardial fibrosis. Both these processes lead to increased heart muscle rigidity and abnormally high left ventricular filling pressure (LVFP). High LVFP is associated with the development of pulmonary venous congestion and impairment of alveolar blood oxygenation, which form the clinical picture of HFpEF. Detecting high LVEF with tissue Doppler echocardiography by the E / e’ value became the instrumental basis for the HFpEF diagnostics. Recognition of inflammation and fibrosis as the key pathogenetic factors marked the main vector of modern therapy for HFpEF (anti-inflammatory and antifibrotic). The best implementation of this vector became possible with the advent of drugs from the class of angiotensin receptor and neprilysin inhibitors (ARNI), sodium-glucose cotransporter type 2 (SGLT2) inhibitors, and aldosterone antagonists. However, the efficacy of such treatments is evident only with the LV EF <60-65% while at higher values, the efficacy substantially decreases. This limitation may result from the heterogenous nature of the disease and requires more advanced methods for verification of HFpEF clinical phenotypes. Among such methods, transcriptomic, metabolomic, and proteomic approaches are considered. With the use of capabilities of the “machine learning” and the artificial intelligence, these approaches can become a new frontier in research to represent an important step towards personalized medicine for patients with HFpEF.