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Updated: Jan 9, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
The changing landscape of heart failure: translating management into the modern era
Cristina Madaudo1, Wasyla Ibrahim2, Daniela Noakes3
1British Heart Foundation Centre of Research Excellence, School of Cardiovascular Medicine, Faculty of Life Science, King's College London, London, UK; Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, Cardiology Unit, University of Palermo, University Hospital P. Giaccone, 90127, Palermo, Italy.
Abstract:
Heart failure (HF) is a complex clinical syndrome associated with high morbidity and mortality, accounting for approximately 2 % of total healthcare expenditures. Despite advances in pharmacological and device-based therapies, HF continues to affect over 70 million people globally, with an increasing prevalence driven by an aging population. The classification remains imperfect due to the pathophysiological complexity of the syndrome. Recent attention has focused on aetiological characterisation, particularly in non-ischaemic cardiomyopathies, where genetic testing may provide diagnostic, prognostic, and therapeutic insights. Left ventricular reverse remodeling (LVRR) and the recognition of HF with improved ejection fraction (HFimpEF) have highlighted the dynamic nature of HF and the importance of continued therapy despite apparent recovery. Guideline-directed medical therapy (GDMT), based on four foundational drug classes for HFrEF, has demonstrated significant benefit, yet its implementation remains suboptimal. For HFpEF, all effective drugs have however failed to reduce mortality. Device therapy, including implantable cardioverter-defibrillators (ICDs), cardiac resynchronisation therapy (CRT) and valve replacement offers additional benefit in select patients and may facilitate optimisation of medical therapy. New avenues such as multiomic profiling, gene therapy, and artificial intelligence (AI) are expanding our ability to phenotype HF, predict disease progression, and personalize treatment strategies. This viewpoint summarises the current understanding of HF, with an emphasis on the classification, aetiology, phenotypes and evidence-based management including newer therapies and their scope of use across the spectrum of LVEF.
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