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This prospective, multicenter, cluster-randomized controlled study aims to evaluate the accuracy of an investigational artificial intelligence (AI) Software as a Medical Device (SaMD) designed to compute ejection fraction (EF) severity categories based on the American Society of Echocardiography's (ASE) 4-category scale. The software analyzes continuous ECG waveform data acquired by the FDA-cleared Peerbridge COR® ECG Wearable Monitor, an ambulatory patch device designed for use during daily activities. The AI software assists clinicians in cardiac evaluations by estimating EF severity, which reflects how well the heart pumps blood. In this study, EF severity determination will be made using 5-minute ECG recordings collected during a 15-minute resting period with participants seated upright. The results will be compared to EF severity obtained from an FDA-cleared, non-contrast transthoracic echocardiogram (TTE) predicate device. This comparison aims to validate the accuracy of the AI software.
It is believed that targeted SERCA2a enzyme replacement in HFrEF patients will correct defective intracellular Ca2+ hemostasis, resulting in improved cardiac contractile function and energetics which will, in turn, translate to improved clinical outcomes. Additionally, it is hypothesized that correcting SERCA2a dysfunction will also improve coronary blood flow through correction of the impaired endothelium-dependent nitric oxide-mediated vasodilatation observed in heart failure.