HF is a life-threatening condition in which the heart can no longer pump enough blood to the rest of the body. Symptoms of HF can include shortness of breath, nausea, fatigue, swelling of the feet or abdomen, and an irregular or rapid pulse. A critical challenge facing ED doctors is how to best manage people who come into the ED with symptoms of HF. Currently, most people evaluated for HF in the ED are admitted to the hospital; however, not all of these people are in need of such intensive treatment. It is estimated that up to 50% of HF-related hospital admissions could be avoided. Improving the ability of the ED doctor to effectively and safely manage low-risk HF patients is essential to avoid unnecessary hospitalizations. This study will gather information from ED patients at risk for HF to develop an algorithm decision tool that will predict patients' risk for inpatient or outpatient death and serious complications from HF. This decision tool will be distributed worldwide for ED use and will hopefully reduce the costs of HF care by appropriately allocating hospital resources.~This study will enroll adults admitted to the ED with possible signs of HF. While in the ED, participants will undergo a digital heart sound recording procedure, a medical record review, blood collection, and a brief cognitive assessment. Five and 30 days following the ED visit, participants will be contacted by phone or will be visited in the hospital by study staff. Information will be collected on health status and unplanned hospital or ED visits that have occurred following the initial ED visit.
People with heart failure (HF) symptoms who are seen in the emergency department (ED) are often admitted to the hospital even though it may not be necessary. This study will gather information from HF patients seen in the ED to develop a decision-making tool that will help doctors predict the risk of HF-related death or serious complications. Improving the ability of ED doctors to effectively and safely manage low-risk HF patients should lead to fewer unnecessary hospitalizations.