This study was designed to investigate whether artificial intelligence-enabled electrocardiograms (AI-ECG) assessment of Atrial Fibrillation (AF) risk predicts cognitive decline and cerebral infracts. Participants included patients who had a sinus-rhythm ECG as well as a brain magnetic resonance imaging (MRI). To determine the AI-ECG-AF relationship with baseline cognitive dysfunction, we compare linear mixed-effects models with global and domain-specific cognitive z-scores from longitudinal neuropsychological assessments. AI-ECG-AF score was logit transformed and modeled with cubic splines. Participants in the study underwent cognitive analysis. We found that the AI-ECG-AF score correlated with worse cognition and gradual global cognition and attention decline. High AF probability by AI-ECG-AF score correlated with MRI cerebral infarcts .
Anumana Appoints Kevin Ballinger and Jean-Luc Butel to Board of Directors
