Cardiac Telemetry Improves AF Detection Following Stroke

To test the technology, U-M researchers conducted a prospective, observational study that analyzed data from 265 ischemic stroke and transient ischemic attack (TIA) patients between April 2017 and January 2018. Atrial fibrillation (AF) episodes lasting more than 30 seconds were identified through review of electrocardiomatrix matrices by a non-cardiologist.

The electrocardiomatrix results were then compared with AF identified directly by a cardiologist through standard telemetry. The results revealed that electrocardiomatrix successfully identified AF in 260 (98%) of cases. The positive predictive value of electrocardiomatrix compared with the clinical documentation was 86% overall, and 100% among a subset of patients with no history of AF. For the five false-positive and five false-negative cases, expert overview disagreed with the clinical documentation and confirmed the electrocardiomatrix-based diagnosis. The study was published on July 1, 2019, in Stroke.

“Electrocardiomatrix goes further than standard cardiac telemetry by examining large amounts of telemetry data in a way that's so detailed it's impractical for individual clinicians to attempt,” said senior author and electrocardiomatrix co-inventor Jimo Borjigin, PhD, of the department of molecular and integrative physiology at U-M Medical School. “Importantly, the electrocardiomatrix identification method was highly accurate for the 212 patients who did not have a history of AF. This group is most clinically relevant, because of the importance of determining whether stroke patients have previously undetected AF.”

“After a stroke, neurologists are tasked with identifying which risk factors may have contributed in order to do everything possible to prevent another event. That makes detecting irregular heartbeat an urgent concern for these patients,” said lead author professor of neurology Devin Brown, MD. “As a physician can't reasonably review every single heartbeat, current monitoring technology flags heart rates that are too high. More accurate identification of AF should translate into more strokes prevented.”

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