Assessing Residual Congestion at Hospital Discharge in Adults with Acute Heart Failure Using Multiple Evaluation Methods and AI Prognostic Modeling

What this Trial Is About

Researchers are evaluating the presence of remaining fluid buildup, known as residual congestion, in patients hospitalized for acute heart failure. The study aims to assess this condition at the time of hospital discharge using multiple methods and compare how well each method predicts patient outcomes. Artificial intelligence will also be used to develop a new predictive model that may improve on standard approaches. The study involves measuring residual congestion through clinical signs such as orthopnea, jugular venous distension, and leg swelling imaging tests including non-invasive heart pressure measurements, lung ultrasound, and venous excess ultrasound scores and laboratory tests of various blood markers like NT-proBNP, hemoglobin, and others. All assessments are made at discharge to gather comprehensive data on fluid overload. Participants will be monitored for up to six months after leaving the hospital. During this time, researchers will track worsening heart failure, cardiovascular death, other heart failure events, and overall survival. The study includes regular evaluations of clinical signs, imaging, and laboratory tests to understand which evaluation methods best predict patient outcomes and to support the development of the new AI-based prognostic tool.

Evaluating Residual Congestion at Discharge in Acute Heart Failure Patients