Heart Fail Rev. 2025 Dec 1;31(1):3. doi: 10.1007/s10741-025-10585-0.
ABSTRACT
Heart failure with preserved ejection fraction (HFpEF) accounts for nearly 50% of all heart failure cases and remains a significant clinical challenge. It is characterized by a complex pathophysiology involving multiple comorbidities and overlapping symptoms between heart failure and these comorbid conditions (e.g., obesity). Due to this complexity, several pharmacological treatments that have proven effective in heart failure with reduced ejection fraction (HFrEF) have failed to improve outcomes in HFpEF. More recently, mineralocorticoid receptor antagonists, sodium-glucose co-transporter 2 (SGLT2) inhibitors, and glucagon-like peptide-1 (GLP-1) receptor agonists have shown potential benefits in symptom relief and prognosis improvement in patients with HFpEF. In recent years, artificial intelligence has demonstrated the ability to identify distinct HFpEF phenotypes associated with varying risks of cardiovascular outcomes. In this context, clinicians should be able to recognize patients who require closer monitoring and more intensive follow-up. Given the frequent scarcity of healthcare resources, which can negatively impact patient management, remote monitoring may serve as a valuable tool in the follow-up of HFpEF patients. This review aims to describe and highlight these key aspects of HFpEF, with a particular focus on recent evidence and emerging strategies in disease management.
PMID:41320694 | DOI:10.1007/s10741-025-10585-0