Improving the detection of ventricular tachycardia: a smarter implantable loop recorder

Abstract

This editorial refers to ‘Tachycardia detection performance of implantable loop recorders: results from a large ‘real-life’ patient cohort and patients with induced ventricular arrhythmias’ by K. Volosin et al., on page 1215. More than a decade ago an implantable loop recorder (ILR) was launched to detect bradyarrhythmias as a cause of syncope, dizziness, and feeling unwell. It is now recognized as an indispensable tool when serial Holter recordings, long-term external event loop recording, tilt test, or an electrophysiological study fail to unmask the cause of syncope. 1 The same holds true for unexplained palpitations. In about a quarter of patients with syncope, which remains unexplained despite various diagnostic methods, ILR disclosed a bradyarrhythmic event during syncope, 2 whereas in about 10% tachyarrhythmias could be related to syncope. 3 Growing experience brought out that ILR showed a superior diagnostic power to tilt table testing and programmed electrical stimulation in unexplained syncope and dizziness, and therefore conquered a prominent diagnostic position in this condition. 4 Initially, ILR was not designed for the independent automated detection of various types of tachyarrhythmias due to the limited diagnostic programmability and the small storage capacity. A recent upgrade of diagnostic algorithms for atrial fibrillation improved the accuracy of ILR. 5 However, oversensing of myopotentials and P-waves, frequent atrial extrasystoles, and R-wave undersensing undermine its diagnostic performance in a small percentage (15%) of patients with atrial fibrillation. Remote monitoring and follow-up of the performance of implanted cardiac devices through the Internet emerged at the same time as ILR deployment. Apart from timely identification of technical failure of leads and device pacing and sensing algorithms, the detection of asymptomatic arrhythmias and true arrhythmic events related to syncope and other symptoms constituted a major diagnostic therapeutic leap forwards, leading to appropriate treatment measures. Combining remote monitoring with ILR to transmit the automated or manually stored electrocardiogram (ECG) rhythm strips to the server and thereafter to the clinic was the following logical step. Currently in the Netherlands � 11 000 patients, predominantly implantable cardioverterdefibribllator (ICD) patients, use the Medtronic CareLink server, and � 400 of them transmit ILR data. In this issue of the Journal, Volosin et al. 6 report on the diagnostic performance of tachycardia by application of new ILR diagnostic algorithms (Medtronic Reveal). The performance was tested in a large, unselected patient cohort, and secondly in an external ILR model to assess the diagnostic performance of true ventricular tachycardia (VT) and ventricular fibrillation (VF) induced during ICD insertion. Comparable with other cardiac devices, detection and diagnosis of tachycardia is solely based on interval detection and comparison, the nominal (but programmable at discretion) number of successive QRS complexes, their stability, and the onset and offset pattern of tachycardias. Fulfilling of a set of programmed parameters includes the presence of tachycardia and storage in the ILR memory with a programmable duration of the episode. Because the primary study target was correct VT and VF detection, the conventional VT and fast VT zones of the ICD programmes were applied. Conceivably, because VT cannot be discriminated from various types of supraventricular tachycardia (SVT), the diagnosed VT or fast VT could also be SVT with similar rates.