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

Abstract

Background: 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.

Methods: 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.

Results: 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 burden <0.044 hours/day (91% vs. 14%; both P<0.05).

Conclusions: Daily snapshot ECG monitoring over 365 days detects half of patients who developed AT/AF as detected by CIED, and shorter intervals of monitoring detected fewer AT/AF patients. The detection rate was associated with individual CHADS2 score and AT/AF burden.

Trial registration: ClinicalTrials.gov NCT00279981.

Conflict of interest statement

Competing Interests: The authors have the following interests: The original TRENDS Study was sponsored by Medtronic, Inc. Dr. ED received funding from Medtronic for participation as investigators for the TRENDS Study. PZ and JK are employees and stockholders of Medtronic. Drs. YY, PG, and DLJ have nothing to disclose. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

Figures

Fig 1. Histogram of the patient’s AT/AF burden (n = 370).

AT/AF burden was defined as the amount of time spent in AT/AF on a given day. Average AT/AF burden per day over the monitoring period (A), maximum daily AT/AF burden, defined as the single day with maximal burden over the monitoring period (B), and the percentage of days over the monitoring period that the patient experienced AT/AF (C) were determined for each of the 370 patients in the primary analysis and are shown as a histogram. Each bar in Fig 1A and 1B indicates the proportion of individuals who were assigned into the corresponding group divided by 1-hour interval of the aggregated AT/AF events among 370 patients. For example, the bar of 6 hours/day in Fig 1A indicates that the proportion of patients with an average AT/AF burden between 5 to 6 hours/day among the 370 patients was 0.5%.