Validation of device algorithm to differentiate pacemaker-mediated tachycardia from tachycardia due to atrial tracking. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Current cardiac devices cannot always differentiate between pacemaker-mediated tachycardia (PMT) and tracking of sinus or atrial tachycardia. We previously derived a novel algorithm for distinguishing the 2 mechanisms based on the specific termination response to postventricular atrial refractory period extension, atrial rates, and changes in atrial electrogram morphology. OBJECTIVE: The purpose of this study was to evaluate how this algorithm would have performed in a clinical setting based on previously recorded PMT events. METHODS: We applied our algorithm to a database of 122 de-identified stored electrograms that were classified as PMT by 43 remotely monitored devices. RESULTS: Of the 122 events stored as "PMT," 3 episodes were excluded because the device recording was consistent with atrial fibrillation. Of the remaining 119 episodes, our algorithm was able to correctly reclassify 92 events (77%) as tracking of sinus or atrial tachycardia rather than true PMT. The VAV response following postventricular atrial refractory period extension, which is specific to tracking of atrial or sinus tachycardia, was seen in 72% of these cases. Changes in atrial rate and atrial electrogram morphology were able to reclassify the remainder of episodes. Finally, we observed that 12 of 83 episodes (14%) misclassified as PMT in cardiac resynchronization devices resulted in loss of cardiac biventricular pacing. CONCLUSION: Applying a novel diagnostic algorithm to current cardiac devices improves the proper diagnosis of true PMT rather than tracking of atrial or sinus tachycardia. Enhanced accuracy of diagnosis reduces the likelihood of inappropriate clinical decisions.

publication date

  • April 19, 2016

Research

keywords

  • Algorithms
  • Atrial Fibrillation
  • Heart Atria
  • Pacemaker, Artificial
  • Tachycardia

Identity

Scopus Document Identifier

  • 84971634710

Digital Object Identifier (DOI)

  • 10.1016/j.hrthm.2016.04.011

PubMed ID

  • 27108937

Additional Document Info

volume

  • 13

issue

  • 8