Performance of a New Leadless Implantable Cardiac Monitor in Detecting and Quantifying Atrial Fibrillation Results of the XPECT Trial

• DOI: 10.1161/circep.109.877852
• Publication Date: 2010-02-17T05:13:50Z
• Authors: Gerhard Hindricks; Evgueny Pokushalov; Lubos Urban; Milos Taborsky; Karl-Heinz Kuck; Dmitry Lebedev; Guido Rieger; Helmut Pürerfellner
• Keywords: Adult; Aged, 80 and over; Male; Reproducibility of Results; Middle Aged; Sensitivity and Specificity; Electrodes, Implanted; 3. Good health; Electrocardiography; 03 medical and health sciences; 0302 clinical medicine; Predictive Value of Tests; Reference Values; Atrial Fibrillation; Electrocardiography, Ambulatory; Humans; Female; Prospective Studies; Algorithms; Aged; Monitoring, Physiologic

Background—

Current methods for detecting atrial fibrillation (AF) have limited diagnostic yield. Continuous monitoring with automatic arrhythmia detection and classification may improve detection of symptomatic and asymptomatic AF and subsequent patient treatment. The study purpose was to quantify the performance of the first implantable leadless cardiac monitor (ICM) with dedicated AF detection capabilities.

Methods and Results—

Patients (n=247) with an implanted ICM (Reveal XT, Medtronic Inc, Minneapolis, Minn) who were likely to present with paroxysmal AF were selected. A special Holter device stored 46 hours of subcutaneously recorded ECG, ICM markers, and 2 surface ECG leads. The ICM automatic arrhythmia classification was compared with the core laboratory classification of the surface ECG. Of the 206 analyzable Holter recordings collected, 76 (37%) contained at least 1 episode of core laboratory classified AF. The sensitivity, specificity, positive predictive value, and negative predictive value for identifying patients with any AF were 96.1%, 85.4%, 79.3%, and 97.4%, respectively. The AF burden measured with the ICM was very well correlated with the reference value derived from the Holter (Pearson coefficient=0.97). The overall accuracy of the ICM for detecting AF was 98.5%.

Conclusions—

In this ICM validation study, the dedicated AF detection algorithm reliably detected the presence or absence of AF and the AF burden was accurately quantified. The ICM is a promising new diagnostic and monitoring tool for the clinician to treat AF patients independently of symptoms. Long-term studies are needed to evaluate the clinical benefits of the technology.

Clinical Trial Registration—

clinicaltrials.gov Identifier NCT00680927.