Filtering of remote monitoring alerts transmitted by cardiac implantable electronic devices and reclassification of atrial fibrillation events by a new algorithm

Abstract

Background

Cardiac implantable electronic devices (CIEDs) are an important means of atrial fibrillation (AF) detection. However, the AF burden measurements and notifications transmitted by CIEDs are not directly related to the clinical classification of paroxysmal, persistent, or permanent AF. Moreover, AF alerts are the most frequent form of notification, imposing a time-consuming review on caregivers.

Objective

The purpose of this study was to compare the incidence of standard AF burden-related notifications in remotely monitored (RM) patients with the incidence of events detected after filtering by a new proprietary algorithm implementing the standard European Society of Cardiology classification of AF.

Methods

Between 2017 and 2022, all RM patients with daily AF burden measurements available for ≥30 days and ≥1 AF burden-related alerts were enrolled at 68 medical centers. The incidence of CIED-transmitted alerts was compared to that of AF episodes detected by a new proprietary algorithm and classified as “first recorded episode of AF”, “paroxysmal AF”, “increased paroxysmal AF”, “persistent AF”, or “end of persistent AF back to paroxysmal AF or back to sinus rhythm.”

Results

Between January 2017 and September 2022, this retrospective study analyzed data from 4162 recipients of an Abbott, Biotronik, Boston Scientific, or Medtronic CIED, RM over mean follow-up of 605 ± 386 days. The algorithm broke down 67,883 AF burden-related alerts into 9728 (14.3%) clinically relevant AF events.

Conclusion

A new AF alert algorithm successfully identified clinically significant AF events in RM CIED recipients and would markedly limit the total number of transmitted alerts that require review by caregivers.