This review discusses the limitations of LVEF and explores alternative measures like imaging techniques and artificial intelligence in heart failure classification.
Heart failure (HF) is a multifactorial and heterogeneous syndrome with substantial epidemiological burden, high mortality, and impact on quality of life. In the context of heart failure, left ventricular ejection fraction (LVEF) has been regarded as the most important marker of systolic function and is fundamental in medical research and clinical practice. In research, LVEF has been a major inclusion criterion in most clinical trials over the past few decades. Furthermore, international heart failure guidelines rely on LVEF for the diagnosis of HF and to guide effective treatment. Additionally, our understanding of HF phenotypes and prognosis is mostly grounded in a classification based on LVEF. Nevertheless, there has been a growing debate regarding the role of LVEF in heart failure. In this context, the purpose of this review is to discuss both the advantages and contemporary relevance of LVEF in heart failure, as well as its limitations and controversies. In addition, this review aims to discuss potential alternatives and future directions in heart failure classification, such as new classification methods, alternative measurements of systolic function and imaging techniques, the HLM score, and the use of artificial intelligence and machine learning.
No takes yet. Share an insight, caveat, or question.
Freire et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: