The continuous heart failure spectrum: moving beyond an ejection fraction classification

Filippos Triposkiadis, Javed Butler, Francois M Abboud, Paul W Armstrong, Stamatis Adamopoulos, John J Atherton, Johannes Backs, Johann Bauersachs, Daniel Burkhoff, Robert O Bonow, Vijay K Chopra, Rudolf A de Boer, Leon de Windt, Nazha Hamdani, Gerd Hasenfuss, Stephane Heymans, Jean-Sébastien Hulot, Marvin Konstam, Richard T Lee, Wolfgang A Linke, Ida G Lunde, Alexander R Lyon, Christoph Maack, Douglas L Mann, Alexandre Mebazaa, Robert J Mentz, Petros Nihoyannopoulos, Zoltan Papp, John Parissis, Thierry Pedrazzini, Giuseppe Rosano, Jean Rouleau, Petar M Seferovic, Ajay M Shah, Randall C Starling, Carlo G Tocchetti, Jean-Noel Trochu, Thomas Thum, Faiez Zannad, Dirk L Brutsaert, Vincent F Segers, Gilles W De Keulenaer, Filippos Triposkiadis, Javed Butler, Francois M Abboud, Paul W Armstrong, Stamatis Adamopoulos, John J Atherton, Johannes Backs, Johann Bauersachs, Daniel Burkhoff, Robert O Bonow, Vijay K Chopra, Rudolf A de Boer, Leon de Windt, Nazha Hamdani, Gerd Hasenfuss, Stephane Heymans, Jean-Sébastien Hulot, Marvin Konstam, Richard T Lee, Wolfgang A Linke, Ida G Lunde, Alexander R Lyon, Christoph Maack, Douglas L Mann, Alexandre Mebazaa, Robert J Mentz, Petros Nihoyannopoulos, Zoltan Papp, John Parissis, Thierry Pedrazzini, Giuseppe Rosano, Jean Rouleau, Petar M Seferovic, Ajay M Shah, Randall C Starling, Carlo G Tocchetti, Jean-Noel Trochu, Thomas Thum, Faiez Zannad, Dirk L Brutsaert, Vincent F Segers, Gilles W De Keulenaer

Abstract

Randomized clinical trials initially used heart failure (HF) patients with low left ventricular ejection fraction (LVEF) to select study populations with high risk to enhance statistical power. However, this use of LVEF in clinical trials has led to oversimplification of the scientific view of a complex syndrome. Descriptive terms such as 'HFrEF' (HF with reduced LVEF), 'HFpEF' (HF with preserved LVEF), and more recently 'HFmrEF' (HF with mid-range LVEF), assigned on arbitrary LVEF cut-off points, have gradually arisen as separate diseases, implying distinct pathophysiologies. In this article, based on pathophysiological reasoning, we challenge the paradigm of classifying HF according to LVEF. Instead, we propose that HF is a heterogeneous syndrome in which disease progression is associated with a dynamic evolution of functional and structural changes leading to unique disease trajectories creating a spectrum of phenotypes with overlapping and distinct characteristics. Moreover, we argue that by recognizing the spectral nature of the disease a novel stratification will arise from new technologies and scientific insights that will shape the design of future trials based on deeper understanding beyond the LVEF construct alone.

Keywords: Ejection fraction; Endothelium; Heart failure; Pathophysiology.

Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2019. For permissions, please email: journals.permissions@oup.com.

Figures

Figure 1
Figure 1
Variability in left ventricular ejection fraction (EF) measurements. Bland-Altman plots for EF compared for biplane Simpson method by echocardiography and gated single-photon emission computed tomography (SPECT) (A), biplane Simpson method by echocardiography and cardiovascular magnetic resonance (CRM) (B), and SPECT and CRM (C). Modified from Ref.
Figure 2
Figure 2
Endothelial physiology: more to say than just NO. Schematic figure illustrating the putative role of endothelial cell activation and dysfunction in heart failure. Albeit too often restricted to an interaction between endothelial cells and adjacent cells through nitric oxide (NO), the physiology of the endothelium and its role in the pathophysiology of heart failure very complex. Endothelial cells have a sensing function to detect changes in the mechanical (shear stress, cyclic stretch, and compression), chemical (lactate, hypoxia, …) and neurohormonal (endothelin-1, acetylcholine, …) environment, and an effector function by the release of many bioactive factors (prostacyclin, endothelin, neuregulin, …) influencing targets cells in many different organs. When endothelial cells become dysfunctional, such as in heart failure, homeostatic balances in virtually each organ system will be affected in a pleiotropic fashion. For more detailed information, we refer the reader to Ref. ADP, adenosine diphosphate; AGE, advanced glycation end products; CTGF, connective tissue growth factor; DKK-3, Dickkopf-related protein 3; FGF, fibroblast growth factor; FST, follistatin; IL-1, interleukin-1; miR, microRNA; NO, nitric oxide; oxLDL; oxidized low density lipoproteins; PDGF, platelet-derived growth factor; ROS, reactive oxygen species; TGF, tissue growth factor; TNF, tumour necrosis factor; TSP-1, thrombospondin-1; VEGF, vascular endothelial growth factor.
Figure 3
Figure 3
Heart failure a spectrum across phenotypes. Each heart failure phenotype is the result of a patient-specific trajectory wherein the heart remodels towards concentric hypertrophy, eccentric hypertrophy, or a combination of both. The way of entry and the subsequent path of the trajectory depend on the patient’s risk factor(s), comorbidity(ies), and disease modifiers. Risk factors are disease entities that always precede the development of heart failure and are associated with an increased heart failure incidence. Comorbidities may precede or develop after heart failure and usually coexist with heart failure in groups of two or more (multi-morbidity). Modifiers are specific patient characteristics that contribute to the development of the entry phenotype and heart failure progression. Across the heart failure spectrum left ventricular ejection fraction variability relates with left ventricular end-diastolic volume in a non-linear relationship. Despite quantitative differences between the extreme left and right sides of the spectrum, there is important overlap between the phenotypes along the entire spectrum. Any subdivision of the spectrum by a single biomarker is artificial. Afib, atrial fibrillation; CAD, coronary artery disease; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; DM-II, type II diabetes mellitus; LVEDV, left ventricular end-diastolic volume; LVEF, left ventricular ejection fraction; OSAS, obstructive sleep apnoea syndromes.
Figure 4
Figure 4
Evolution of heart failure research. Phenotype-oriented research in heart failure will emerge from an updated heart failure classification recognizing phenotypes across the left ventricular ejection fraction spectrum. These may either be based on mechanisms or aetiology of disease, or from unbiased data-driven approaches (see inset). Advances in both technology and computing now provides unprecedented opportunity to understand biologic subgroups of patients to target personalized therapy that maximizes chances of benefit and minimizes chances of risks. One such scheme could be to stratify patients across the risk spectrum and study their biologic, sociologic, demographic, and other determinants in detail to describe not only prediction more accurately (to guide use of existing therapy) but also the relevant biologic pathways involved (to guide development of new therapies).

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