Phenotyping in heart failure with preserved ejection fraction: A key to find effective treatment

Abstract

Heart failure with preserved ejection fraction (HFpEF) is an increasingly widespread medical condition, with excessive morbidity and mortality. Recently, for the first time in HFpEF, a reduction in the primary composite outcome of cardiovascular death or HF hospitalization was shown with empagliflozin. The failure of previous clinical trials in HFpEF might have resulted from suboptimal patient selection and inclusion of patients without "true" or clinically significant HFpEF. Another important factor might be the heterogeneity of HFpEF, and thus there is a growing interest in HFpEF phenotyping. This phenotyping can be based on clinical presentation (e.g., subtypes with predominant atrial fibrillation, obesity, pulmonary hypertension and right ventricular failure, coronary artery disease (CAD), or noncardiac comorbidities), but also on HFpEF etiology. Specific therapies, such as tafamidis in transthyretin-related amyloidosis (ATTR) or mavacamten in hypertrophic cardiomyopathy, have demonstrated their efficacy. However, pathomechanisms leading to the development of different phenotypes of HFpEF seem more complex and subtle. Machine learning and neural network models might help identify specific subgroups within the HFpEF population that either cluster patients with similar genetic, biochemical, echocardiographic or clinical characteristics, or respond similarly to a given treatment. Herein, we review different approaches to HFpEF phenotyping and present some distinct HFpEF subtypes.

Extent of coronary atherosclerosis is associated with deterioration of left ventricular global longitudinal strain in patients with preserved ejection fraction undergoing coronary computed tomography angiography

“…Previous studies have demonstrated that HFpEF includes multiple etiologies of heart failure. Phenotyping of the disease according to etiology can provide further insights into the pathophysiology and management of HFpEF [16] . Furthermore, our study consisted of patients with normal weight/overweight rather than obese patients who are well known to have HFpEF [33] .…”

“…Finally, CMD, especially HFpEF, was not assessed as a potent cause of subclinical HF in the present study. CMD can account for up to two-thirds of symptomatic ischemic heart disease patients without epicardial coronary artery stenosis [16] . Löffler et al demonstrated that HFpEF patients had a higher prevalence of CMD and diffuse fibrosis with decreased exercise tolerance than healthy controls, although LVGLS tended to be higher in the latter [34] .…”

“…Coronary computed tomography angiography (CCTA) is widely used in clinical practice as a first-line test for symptomatic or asymptomatic patients at risk of obstructive CAD, allowing noninvasive assessment of CAD severity and extent [11] . In addition, CCTA enables the quantification of epicardial adipose tissue (EAT) volume, which is closely related to the development of CAD, atrial fibrillation, and heart failure, with or without preserved LV ejection fraction (LVEF) [12] , [13] , [14] , [15] , [16] . Recent clinical studies have demonstrated that EAT volume is associated with CAD severity and coronary microvascular dysfunction (CMD) [17] .…”

Personalized Management for Heart Failure with Preserved Ejection Fraction

“…LCA relies on a probabilistic model to describe the distribution of data, which is used to derive clusters from the data based on the probabilities that certain cases belong to certain latent classes, and relies less on a distance measure to find the clusters. Overall, these techniques offer promising tools and research approaches to identify sub-phenotypes of diseases such as HFpEF and can help to improve diagnosis, treatment, and prognosis from multiple dimensions, including clinical data, biomarkers, or imaging studies [ 7 , 13 , 23 , 26 , 27 , 28 , 29 , 30 , 31 , 32 ]. Herein, we listed several key landmark studies unraveling AI-based learning and phenotyping among the HFpEF population.…”

“…Additionally, imaging can exclude alternative diagnoses that mimic HFpEF, such as hypertrophic cardiomyopathy, primary valvular heart disease, cardiac amyloidosis, and pericardial disease. While two-dimensional (2-D) transthoracic echocardiography is the most commonly used imaging modality, advanced imaging techniques, including cardiac magnetic resonance imaging and 2-D speckle tracking echocardiography, are used to identify distinct HFpEF phenotypes based on left ventricular structure and function [ 13 , 23 , 28 , 29 , 30 , 31 , 32 , 35 ]. Compared with standard 2-D echocardiography, three-dimensional (3-D) echocardiography provides a more reliable and reproducible evaluation of cardiac chamber volumes, mass, and shape, which are highly correlated with cardiac magnetic resonance imaging (CMR) [ 36 ].…”