Acute heart failure is a leading reason for emergency department visits, hospital admissions, and readmissions. Despite the high rate of hospitalization for heart failure and the high resource burden attributable to acute heart failure, limitations of clinical decisions have been demonstrated. Risk stratification methods might provide guidance to clinicians who care for patients with acute heart failure syndromes, and might improve decision-making in emergent care when decisions must be made quickly and accurately. Although many acute heart failure risk models have been developed in hospitalized cohorts to predict in-hospital mortality, there are fewer methods to enable prognostication broadly among all patients in a community-based setting. As validated predictive risk algorithms become increasingly accessible, they may be applied to select optimal therapies, determine how patients will be cared for in the emergency department, and improve decisions pertaining to patient disposition and follow-up.
Emergency department visits