Efficient methods for screening populations for undiagnosed atrial fibrillation (AF) are needed to reduce its associated mortality, morbidity, and costs. The use of digital technologies, including wearable sensors and large health record data sets allowing for targeted outreach toward individuals at increased risk for AF, might allow for unprecedented opportunities for effective, economical screening. The trial's primary objective is to determine, in a real-world setting, whether using wearable sensors in a risk-targeted screening population can diagnose asymptomatic AF more effectively than routine care. Additional key objectives include (1) exploring 2 rhythm-monitoring strategies-electrocardiogram-based and exploratory pulse wave-based-for detection of new AF, and (2) comparing long-term clinical and resource outcomes among groups. In all, 2,100 Aetna members will be randomized 1:1 to either immediate or delayed monitoring, in which a wearable patch will capture a single-lead electrocardiogram during the first and last 2 weeks of a 4-month period beginning immediately or 4 months after enrollment, respectively. An observational, risk factor-matched control group (n = 4,000) will be developed from members who did not receive an invitation to participate. The primary end point is the incidence of new AF in the immediate- vs delayed-monitoring arms at the end of the 4-month monitoring period. Additional efficacy and safety end points will be captured at 1 and 3 years. The results of this digital medicine trial might benefit a substantial proportion of the population by helping identify and refine screening methods for undiagnosed AF.
Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.