An app researchers designed for the Apple Watch allows patients to transmit electrocardiograms to a central processing center, where analysis driven by artificial intelligence (AI) can detect left ventricular (LV) dysfunction with a promising degree of accuracy.
The technology is envisioned as an easy, inexpensive way to extend routine LV functional monitoring, without clinic visits or potentially costly imaging, to vastly more people with high-risk conditions than would otherwise be practical.
The approach could be especially useful, for example, in the frail elderly, patients with hypertension or diabetes, or patients who are being treated with cardiotoxic chemotherapy agents, observed Zachi I. Attia, MSEE, PhD, an AI engineer at the Mayo Clinic, Rochester, Minnesota.
"This is a great way to keep monitoring and testing patients who are at higher risk," Attia told theheart.org | Medscape Cardiology. "We can imagine them getting an ECG every day by the watch, which will allow us to monitor them much more efficiently."
The processing system for Apple Watch single-lead tracings, obtained in sinus rhythm, had been adapted from a neural network trained to look for signs of LV dysfunction in more discerning 12-lead ECGs.
Applied to 421 patients with recent, clinically indicated echocardiograms for comparison, the app-based technique identified 13 of the 16 with ejection fractions of 40% or lower, for a predictive accuracy of almost 88% based on area-under-the curve (AUC) assessment.
