2,697 publications from this institution
The aim of this study was to compare the performance of machine learning models to detect atrial fibrillation (AF) from single-lead ECGs which use either RR-intervals alone, or the entire ECG signal.Experiments were conducted using single-lead, 30-second ECG signals acquired using handheld ECG recorders from two datasets: the Computing in Cardiology (CinC) 2017 dataset (public), and the Screening for Atrial Fibrillation with ECG to Reduce Stroke (SAFER) dataset (private).The models assessed in this study were: two models which used the whole ECG signal, both of which were top-performing models from the 2017 PhysioNet / CinC Challenge; and two RR-interval-based models -a state-of-the-art model and a novel model which detects AF from a 2D representation of the differences between RR intervals.The models had AUROCs of 0.93 -0.99.The AUPRCs varied more widely, from 0.64-0.94.The novel RR-interval-based AF detection model achieved an AUPRC of 0.94 on the CinC 2017 dataset, outperforming the state-of-the-art RRinterval-based model (0.88) and the entire-signal-based models (0.68 and 0.64).This experiment demonstrated that AF detection models utilizing only RR intervals could achieve comparable performance to those utilizing the entire ECG signal.
Atrial fibrillation affects 33.5 million people worldwide and its prevalence is expected to double by 2050 because of the aging population. Atrial fibrillation confers a 5-fold higher risk of ischemic stroke compared to sinus rhythm. We present our view of the role of shared medical decision-making to combat global underutilization of oral anticoagulation for stroke prevention in atrial fibrillation patients. Oral anticoagulation underuse is widespread as it is present within atrial fibrillation patients of all risk strata and in countries across all income levels. Reasons for oral anticoagulation underuse include but are probably not limited to poor risk stratification, over-interpretation of contraindications, and discordance between physician prescription preferences and actual administration. By comparing a catastrophic event to the consequences of atrial fibrillation related strokes, it may help physicians and patients understand the negative outcomes associated with oral anticoagulation under-utilization and the magnitude to which oral anticoagulations neutralize atrial fibrillation burden.