Heart failure with reduced ejection fraction (HFrEF) remains a significant challenge in cardiology, necessitating continued exploration into both therapeutic strategies and safety profiles. Recent advancements in medicinal and technological realms have introduced novel treatments, such as Sodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) and intravenous digoxin, alongside sophisticated predictive models that illuminate both the adequacy and precautionary aspects of these medical interventions..
This Research Topic is dedicated to explore deeply these emerging insights and refined methodologies in the treatment and management of HFrF. We encourage the submission of original research, reviews, and meta-analyses that focus on the following areas:
• The use of artificial intelligence and machine learning to predict therapeutic outcomes in HFrEF.
• Detailed evaluations of drug efficacy and safety in diverse populations.
• Comparative studies addressing different therapeutic strategies for HFrEF.
• Clinical trials exploring novel agents and their mechanisms in the context of heart failure.
• Integration of echocardiographic and other diagnostic tools in predicting treatment responses.
Contributors are invited to provide further insights into how these advanced methodologies and therapeutic strategies can improve the management and prognosis of patients with HFrEF. By advancing our understanding through rigorous clinical research and innovative approaches, this Research Topic aims to foster better clinical practices and tailored treatment pathways for patients suffering from this debilitating condition.
Heart failure with reduced ejection fraction (HFrEF) remains a significant challenge in cardiology, necessitating continued exploration into both therapeutic strategies and safety profiles. Recent advancements in medicinal and technological realms have introduced novel treatments, such as Sodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) and intravenous digoxin, alongside sophisticated predictive models that illuminate both the adequacy and precautionary aspects of these medical interventions..
This Research Topic is dedicated to explore deeply these emerging insights and refined methodologies in the treatment and management of HFrF. We encourage the submission of original research, reviews, and meta-analyses that focus on the following areas:
• The use of artificial intelligence and machine learning to predict therapeutic outcomes in HFrEF.
• Detailed evaluations of drug efficacy and safety in diverse populations.
• Comparative studies addressing different therapeutic strategies for HFrEF.
• Clinical trials exploring novel agents and their mechanisms in the context of heart failure.
• Integration of echocardiographic and other diagnostic tools in predicting treatment responses.
Contributors are invited to provide further insights into how these advanced methodologies and therapeutic strategies can improve the management and prognosis of patients with HFrEF. By advancing our understanding through rigorous clinical research and innovative approaches, this Research Topic aims to foster better clinical practices and tailored treatment pathways for patients suffering from this debilitating condition.