Simulation of Daily Snapshot Rhythm Monitoring to Identify Atrial Fibrillation in Continuously Monitored Patients with Stroke Risk Factors

PloS One
Yuichiro YanoPaul D Ziegler

Abstract

New technologies are diffusing into medical practice swiftly. Hand-held devices such as smartphones can record short-duration (e.g., 1-minute) ECGs, but their effectiveness in identifying patients with paroxysmal atrial fibrillation (AF) is unknown. We used data from the TRENDS study, which included 370 patients (mean age 71 years, 71% men, CHADS2 score≥1 point: mean 2.3 points) who had no documentation of atrial tachycardia (AT)/AF or antiarrhythmic or anticoagulant drug use at baseline. All were subsequently newly diagnosed with AT/AF by a cardiac implantable electronic device (CIED) over one year of follow-up. Using a computer simulation approach (5,000 repetitions), we estimated the detection rate for paroxysmal AT/AF via daily snapshot ECG monitoring over various periods, with the probability of detection equal to the percent AT/AF burden on each day. The estimated AT/AF detection rates with snapshot monitoring periods of 14, 28, 56, 112, and 365 days were 10%, 15%, 21%, 28%, and 50% respectively. The detection rate over 365 days of monitoring was higher in those with CHADS2 scores ≥2 than in those with CHADS2 scores of 1 (53% vs. 38%), and was higher in those with AT/AF burden ≥0.044 hours/day compared to those with AT/AF...Continue Reading

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Aug 10, 2018·International Journal of Stroke : Official Journal of the International Stroke Society·Tommaso Sanna
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