Evaluating an AI System for Detecting Heart Failure Using Electrocardiograms in Older Adults The DECISION Trial

What this Trial Is About

Heart failure HF is a common and often undiagnosed condition with serious health impacts. Early detection is crucial to improve outcomes and reduce hospital stays. This trial evaluates the Willem132 platform, an artificial intelligence AI system designed to improve heart failure detection by analyzing electrocardiograms ECGs in primary care. The study compares AI-assisted ECG interpretation to standard ECG evaluation to see if AI improves diagnosis accuracy and clinical results. Participants are randomly assigned to two groups one receives ECG analysis aided by the Willem132 AI platform, and the other undergoes standard ECG evaluation without AI support. This multicenter trial occurs at primary care centers in Spain and Sweden. The AI provides additional diagnostic information for doctors in the intervention group. Key comparisons include how well each method detects heart failure verified by echocardiograms. Participants will undergo ECG and transthoracic echocardiogram assessments, with follow-up visits about seven days after screening. The study measures the accuracy of heart failure detection, healthcare resource use, clinical outcomes, and physician satisfaction with the AI tool. The trials results aim to guide the integration of AI ECG interpretation into routine primary care to enhance early heart failure diagnosis and management. Total participation time includes initial screening and follow-up assessments within weeks after enrollment.

Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)