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Europace. 2017 Oct 3. doi: 10.1093/europace/eux272. [Epub ahead of print]

Adapting detection sensitivity based on evidence of irregular sinus arrhythmia to improve atrial fibrillation detection in insertable cardiac monitors.

Author information

Department of Cardiology, Public Hospital Elisabethinen, Academic Teaching Hospital, Ordensklinikum A-4020 Linz, Fadingerstraße 1, Austria.
Department of Cardiology, Centre for Heart Rhythm Disorders, South Australian Health and Medical Research Institute, University of Adelaide and Royal Adelaide Hospital, Adelaide, South Australia 5005, Australia.
Research and Development, Cardiac Rhythm and Heart Failure, Medtronic Plc., Moundsview, MN, 55112, USA; Moundsview, MN, USA.
Arrhythmia Department and Electrophysiology Laboratory, State Research Institute of Circulation Pathology, Rechkunovskaya 15, Novosibirsk, 630055, Russia Research Institute of Circulation Pathology, Novosibirsk, Russia.
Department of Arrhythmias and Cardiac Pacing, The National Institute of Cardiovascular Diseases, Pod Kr´snou hôrkou 1, 833 48 Bratislava 37, Slovakia.
Department of Cardiology, Catharina Hospital, Michelangelolaan 2, 5623 EJ Eindhoven, The Netherlands.



Intermittent change in p-wave discernibility during periods of ectopy and sinus arrhythmia is a cause of inappropriate atrial fibrillation (AF) detection in insertable cardiac monitors (ICM). To address this, we developed and validated an enhanced AF detection algorithm.

Methods and results:

Atrial fibrillation detection in Reveal LINQ ICM uses patterns of incoherence in RR intervals and absence of P-wave evidence over a 2-min period. The enhanced algorithm includes P-wave evidence during RR irregularity as evidence of sinus arrhythmia or ectopy to adaptively optimize sensitivity for AF detection. The algorithm was developed and validated using Holter data from the XPECT and LINQ Usability studies which collected surface electrocardiogram (ECG) and continuous ICM ECG over a 24-48 h period. The algorithm detections were compared with Holter annotations, performed by multiple reviewers, to compute episode and duration detection performance. The validation dataset comprised of 3187 h of valid Holter and LINQ recordings from 138 patients, with true AF in 37 patients yielding 108 true AF episodes ≥2-min and 449 h of AF. The enhanced algorithm reduced inappropriately detected episodes by 49% and duration by 66% with <1% loss in true episodes or duration. The algorithm correctly identified 98.9% of total AF duration and 99.8% of total sinus or non-AF rhythm duration. The algorithm detected 97.2% (99.7% per-patient average) of all AF episodes ≥2-min, and 84.9% (95.3% per-patient average) of detected episodes involved AF.


An enhancement that adapts sensitivity for AF detection reduced inappropriately detected episodes and duration with minimal reduction in sensitivity.


Atrial fibrillation; Diagnosis and monitoring; Insertable cardiac monitors


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