Atrial fibrillation (AF) is the most frequent cardiac arrhythmia. AF is a significant burden to healthcare professional and the society in general, with an increased risk of stroke and embolism. Its incidence varies with age from 1.7% for the youngest to 23.4% for the oldest. Moreover, AF has also an impact on patients’ mortality, increasing with age.

The use of a cardiac implantable electronic device (CIED) is not new and its relationship to AF has been widely described in the literature. It has been demonstrated that patients implanted with a dual-chamber pacemaker experienced AF in 75% of the cases and 69% of the patients had AF detected by the pacemaker despite being asymptomatic. Insertable cardiac monitors (ICMs) are a solution to record over a long period to patient’s electrocardiogram, up to several years. ICMs automatically record abnormal rhythmic episodes, such as bradycardias, tachycardias and AF. Some authors have demonstrated the good performance of such devices.

CIEDs transmit the abnormal events by remote monitoring to the manufacturer, then transfer to the physician. This amount of information can impact the workflow of the healthcare providers that are in charge to analyze them. The main limitation is the number of false positive diagnoses conducting to the classification of an event as AF when it is just an artifact or noise.

Remote monitoring (RM) is nowadays recommended to reduce the number of in-office follow-up in patients with pacemakers who have difficulties to attend in-office visits. Moreover, the RM is recommended to detect progression to clinical AF, monitor the atrial high-rate episodes and subclinical AF burden and detect changes in underlying clinical conditions. The ICM associated to RM allows an increase of the AF diagnosis by three-times compared to no-ICM use.

Implicity is committed to improving efficient and early AF detection via RM to improve patient care. Implicity latest science shows the performance of a novel algorithm to reduce by 79% the false positive rate of Medtronic ICM devices (HRS 2021). Moreover, Implicity developed a new AI-based algorithm allowing the reduction of false positive AF detection by 72% (ESC 2021). Implicity is involved in the development of new AI solutions that save healthcare professionals time and ease the workload in patient follow-up.

Jean-Luc Bonnet, PhD, Head of Clinical Affairs, Implicity