João Carlos Moron Saes Braga et al. Jorge Eduardo Assef Fabio Villaça Guimarães Filho Raphael Aparecido Barreto da Silva
Abstract
Heart failure (HF) is a serious public health issue that impacts the mortality and morbidity of the global population. The prevalence of heart failure with preserved ejection fraction (HFpEF) is clearly increasing, associated with population aging, obesity, sedentary lifestyle, and cardiometabolic diseases. It is one of the most urgent diagnostic and therapeutic challenges nowadays. Additionally, the obesity phenotype of HFpEF may be associated with HF and occurs as a result of several mechanisms that are deleterious to cardiac function, including the direct action of epicardial adipose tissue (EAT), causing direct restraint of the pericardium and ventricular interdependence, with significant hemodynamic repercussions, decline in functional capacity, and a worse prognosis. The estimation of ventricular-arterial coupling (VAC) in a non-invasive manner by echocardiography allows a better understanding of the interaction between the heart and the arterial system by monitoring hemodynamic changes, which can guide medical therapy and have an impact on prognosis. Although these tools and parameters are promising, new technologies, such as artificial intelligence and machine learning, must be used to enable the applicability of VAC in clinical practice. Further studies are key to standardizing new methods and values in this context.