Latent class analysis reveals a novel phenotype of heart failure that spans the left ventricular ejection fraction range

Abstract Background It is increasingly evident that heart failure (HF) represents a heterogenous syndrome rather than a single clinical entity. The elusiveness of effective therapies for heart failure with preserved ejection fraction (HFpEF) has led to a consensus that our current, unidimensional construct of HF using only left ventricular ejection fraction (LVEF) does not adequately capture the multiplicity of the disease states. The ability to harmonize echocardiographic data from multiple sources has enabled use of unsupervised cluster-based analysis to identify multidimensional cardiac structural phenotypes. Purpose To identify cardiac structural phenotypes of HF across the LVEF spectrum. Methods We harmonized echocardiographic data from eight randomized clinical HF trials (ESCAPE, EXACT-HF, FIGHT, I-PRESERVE, NEAT-HFpEF, RELAX, STICH and TOPCAT), which included both HFrEF and HFpEF populations (total n=4223 echocardiograms). These studies collectively spanned the years 2000 through 2015 and represent a balanced LVEF distribution. Latent class analysis (LCA) was performed iteratively to identify predominant structural phenotypes using LVEF, RV function, LV end diastolic volume, LV mass index, eccentricity, mitral valve deceleration time, and lateral E/e’ ratio. Results LCA identified 4 echocardiographic phenotypes. Three phenotypes skewed toward either high or low EF, but one phenotype demonstrated a relatively even distribution of patients with HFrEF, heart failure with mildly reduced ejection fraction (HFmrEF) and HFpEF (36.0%, 21.4% and 42.7%, respectively). Patients in this phenotype had preserved RV function and left ventricular hypertrophy (97%), of which 56.8% had concentric and 43.2% eccentric LVH. E/e’ was normal in 63% of subjects. A vast majority (91%) of patients had recent-onset HF (diagnosed within the past year). There were no remarkable distinguishing comorbidities. Notable differences in biomarker profile included higher levels of troponin I, cyclic GMP and lower levels of neurohormones (aldosterone, endothelin-1, dopamine, and norepinephrine) than the other phenotypes. Conclusions This is the first cluster-based analysis to identify a quantitative structural HF phenotype of HF that is not distinguished by LVEF. While the underlying pathophysiology is unclear, most patients have recent onset HF and biomarker profiles with relatively low neurohormone activity. These features may reflect a distinct pathophysiology that could indicate a specific, targeted intervention.