Advancements in Incident Heart Failure Risk Prediction and Screening Tools

Abstract

Heart Failure (HF) is a major cause of mortality and morbidity in the United States that carries substantial healthcare costs. Multiple risk prediction models and strategies have been developed over the past 30-years with the aim to identify those at high risk of developing HF and implement preventive therapies effectively. This review highlights recent developments in HF risk prediction tools including emerging risk factors, innovative risk prediction models, and novel screening strategies from AI to biomarkers. These developments allow for more accurate prediction but their impact on clinical outcomes remain to be investigated. Implementation of these risk models into clinical practice is a considerable challenge, but HF risk prediction tools offer a promising opportunity to improve outcomes while maintaining value.