Performance of a new atrial fibrillation detection algorithm in a miniaturized insertable cardiac monitor: Results from the Reveal LINQ Usability Study

Abstract

Background: For clinicians, confidence in atrial fibrillation (AF) episode classification is an important consideration when electing to use insertable cardiac monitors (ICMs).

Objective: The purpose of this study was to report on the improved AF detection algorithm in the Reveal LINQ ICM.

Methods: The Reveal LINQ Usability Study is a nonrandomized, prospective, multicenter trial. The ICM has been miniaturized, uses wireless telemetry for remote patient monitoring, and its AF algorithm includes a new p-wave filter. At 1 month post-device insertion, Holter monitor data were collected and annotated for true AF episodes ≥2 minutes, and performance metrics were evaluated by comparing Holter annotations with ICM detections.

Results: The study enrolled 151 patients (age 56.6 ± 12.1, male 67%). Reasons for monitoring included AF ablation or AF management in 81.5% (n = 123), syncope in 12.6% (n = 19), and other indications in 5.9% (n = 9) of patients. Of the 138 patients with an analyzable Holter recording, a total of 112 true AF episodes were identified in 38 patients (27.5%). The overall accuracy of the ICM to detect durations of AF or non-AF episodes was 99.4%, and the AF burden measured by the ICM was highly correlated with the Holter (Pearson coefficient 0.995).

Conclusion: The new AF detection algorithm in the Reveal LINQ ICM accurately detects the presence or absence of AF. Additionally, it showed high sensitivity in detecting AF duration in patients with a history of intermittent and symptomatic AF.

Keywords: Atrial fibrillation; Diagnosis; Insertable cardiac monitor; Long-term monitoring.

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