Even during COVID-19, cardiovascular disease poses the heaviest burden on communities with high rates of
morbidity, disability and mortality. According to current data, its prevalence in Europe – 4%, in developed countries
– 1-2%, and in Georgia – 6%. It is the most common cause of hospitalization and is characterized by a severe
prognosis. 2-17% of patients – within the first hospitalization, and more than 50% – die within 5 years after diagnosis.
The trend of decreasing morbidity, hospitalization and mortality rates due to heart failure in Georgia in 2017-2021
is determined by the effects of high prevalence of COVID-19 and overlapping clinical outcomes. However, in the
context of the incidence of other categories of cardiovascular disease, with almost unchanged hospitalization and
slightly reduced mortality rates, the country’s epidemiological model should consider other influencing trends –
systemic elements of disease management, effectiveness of clinical processes, and treatment approaches.
The increasing risks of heart failure with age in more than half of patients are associated with the seven or more
comorbid conditions, which significantly aggravates the prognosis of the disease and, conversely, heart failure
creates a predisposition to multiple comorbidities. For these reasons, heart failure due to the particularly increased
risk of aggravation and death in cases of COVID-19 belongs to the group of fatal comorbidities. Neuroendocrine
activation, dysregulation of vascular mechanisms, dysmetabolism, inflammation, and fibrotic regeneration are even
considered as shared pathogenetic relationships.
Population aging trends, obesity and diabetes have a significant negative impact on myocardial metabolism, disease
outcomes, and the effectiveness of drug treatment, and significantly aggravate the burden of heart failure. Despite
the grow of risks, the mechanisms by which they correlates with heart failure outcome have not been sufficiently
examined. This condition significantly reduces the ability to identify and predict treatment approaches tailored to
risk groups.