Rockville, Md. (November 25, 2020)—Atrial fibrillation is the most frequent arrhythmia in both equine and human athletes. In this study, researchers investigated whether the arrhythmogenic substrate—the preexisting condition that causes arrhythmia—present between the episodes of paroxysmal atrial fibrillation (PAF) can be detected using restitution analysis of normal sinus-rhythm electrocardiograms (ECG). In this case, ECG readings were taken during routine clinical work in horses with PAF.
The data compiled in this research article suggest horses and humans have similar heart rate ranges. The study also points out the potential of a simple machine learning algorithm that allows for diagnostic markers, which are more difficult to quantify using conventional techniques. The researchers concluded that 3D ECG testing can potentially be used as a metric of an automated method for screening of PAF.
Read the full article, “ECG restitution analysis and machine learning to detect paroxysmal atrial fibrillation: insight from the equine athlete as a model for human athletes,” published ahead of print in Function. Contact the APS Communications Office or call 301.634.7314 to schedule an interview with a member of the research team.