Heart failure (HF) poses a major global health challenge with rising prevalence, significant morbidity and mortality, and substantial associated healthcare costs. With aging of the population and an increasing burden of comorbidities, the complex interplay between cardiovascular, kidney, and metabolic risk factors have been thrust into the spotlight and have broadened the traditional focus from HF treatment to an increased emphasis on prevention. In recognition of the evolving HF landscape, the American Heart Association released the PREVENT models which are comprehensive risk assessment tools that estimate 10- and 30-year risk of incident cardiovascular disease and its subtypes, including atherosclerotic cardiovascular disease (ASCVD) and, for the first time, HF. While it is an accurate risk estimation tool and represents a step forward in improving risk stratification for primary prevention of HF, there remain several limitations and unknowns like model performance across disaggregated racial and ethnic groups, the role of traditional ASCVD vs. HF-specific risk factors, HF prediction among those with known ASCVD, and the use of traditional regression techniques in lieu of potentially more powerful machine learning-based modeling approaches. Furthermore, it remains unclear how to optimize risk estimation in clinical care. The emergence of multiple novel pharmacological therapies that prevent incident HF, including sodium-glucose co-transporter 2 (SGLT2) inhibitors, glucagon-like peptide 1 (GLP1) receptor agonists, and nonsteroidal mineralocorticoid receptor antagonists (MRAs), highlights the importance of accurate HF risk prediction. To provide HF prevention with these effective but costly therapies, we must understand the optimal strategy in sequencing and combining these therapies and prioritize patients at highest risk. Such implementation requires both accurate risk stratification and a better understanding of how to communicate risk to patients and providers. This state-of-the-art review aims to provide a comprehensive overview of recent trends in HF prevention, including risk assessment, care management strategies, and emerging and novel treatments.
Keywords: Cardiovascular-Kidney-Metabolic; Heart Failure; Lifestyle; Pharmacotherapies; Prevention; Risk stratification.
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.