Open Access

Atrial fibrillation detection by the subcutaneous defibrillator: real-world clinical performances and implications from a multicentre study

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Date: 23 August 2020
Journal: EP Europace Journal , Volume 22 , Issue 11 , Pages 1628 - 1634
Authors: P. Ollitrault , P. Jacon , N. Auquier , L. Champ-Rigot , M. Ben Kilani , F. Vandevelde , A. Pellissier , V. Ferchaud , D. Legallois , P. Defaye , F. Anselme , P. Milliez

ESC Journals

AbstractAims

No data exist concerning the clinical performances of the subcutaneous implantable cardioverter-defibrillator (S-ICD) atrial fibrillation (AF) detection algorithm. We aimed to study the performances and implications of the latter in a ‘real-world’ setting.

Methods and results

Between July 2017 and August 2019, 155 consecutive S-ICD recipients were included. Endpoint of the study was the incidence of de novo or recurrent AF using a combined on-site and remote-monitoring follow-up approach. After a mean follow-up of 13 ± 8 months, 2531 AF alerts were generated for 55 patients. A blinded analysis of the 1950 subcutaneous electrocardiograms available was performed. Among them 47% were true AF, 23% were premature atrial contractions or non-sustained AF, 29% were premature ventricular contractions or non-sustained ventricular tachycardia, and 1% were misdetection. Fourteen percent (21/155) patients had at least one correct diagnosis of AF by the S-ICD algorithm. One patient presented symptomatic paroxysmal AF not diagnosed by the S-ICD algorithm (false negative patient). Patient-based sensitivity, specificity, positive, and negative predictive values were respectively 95%, 74%, 38%, and 99%. Among patients with at least one correct diagnosis of AF, 38% (8/21) had subsequent clinical implications (anticoagulation initiation or rhythm control therapies).

Conclusion

The S-ICD AF detection algorithm yields a high sensitivity for AF diagnosis. Low specificity and positive predictive value contribute to a high remote monitoring-notification workload and underline the necessity of a manual analysis. Atrial fibrillation diagnosis by the S-ICD AF detection algorithm might lead to significant therapeutic adjustments.

About the contributors

Pierre Ollitrault

Role: Author

Peggy Jacon

Role: Author

Nathanaël Auquier

Role: Author