gms | German Medical Science

33rd International Congress on Electrocardiology

International Society of Electrocardiology

Dynamic analysis of repolarization instability: methods and emerging applications

Meeting Abstract

  • corresponding author presenting/speaker V. Shusterman - PinMed, Inc. and University of Pittsburgh, Pittsburgh, USA
  • A. Goldberg - University of Pittsburgh, Pittsburgh, USA
  • D. Edmundowicz - University of Pittsburgh, Pittsburgh, USA
  • T. Malloy - University of Pittsburgh, Pittsburgh, USA
  • D. Housel - University of Pittsburgh, Pittsburgh, USA
  • R. L. Lux - University Utah, Salt Lake City, USA
  • D. Schwartzman - University of Pittsburgh, Pittsburgh, USA

33rd International Congress on Electrocardiology. Cologne, 28.06.-01.07.2006. Düsseldorf, Köln: German Medical Science; 2007. Doc06ice010

The electronic version of this article is the complete one and can be found online at: http://www.egms.de/en/meetings/ice2006/06ice010.shtml

Published: February 8, 2007

© 2007 Shusterman et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

Text

T-wave alternans (TWA), an index of proarrhythmic repolarization instability, has recently become a clinical tool for arrhythmia risk stratification. However, the spatial distribution of TWA and the optimal lead set for analysis of this repolarization instability are still uncertain. We hypothesized that because of the spatial heterogeneity, TWA is frequently localized in a single (anterior, lateral, or inferior) lead set and tested this hypothesis in subjects undergoing exercise stress-testing. In addition, we examined the ability of TWA determined on the root-mean-square (RMS)-curve (a robust representation of the average cardiac repolarization properties) to capture repolarization instability independent of the spatial differences (TWA-RMS).

Methods: Continuous, 1uV-resolution, 12-lead ECG was recorded in 25 patients undergoing clinically scheduled stress testing with nuclear imaging. TWA was analyzed using previously validated software. For analysis of TWA, 6 subjects with documented coronary artery disease (CAD), Group 1, were matched to CAD-free controls (Group 2) based on age, gender, EF, and maximum heart rate achieved during the test.

Results: TWA increased in a single (anterior, lateral, or inferior) lead set in 33% of the subjects, in 2 sets in 33% of the subjects, and in all 3 lead sets in 22% of the subjects. TWA-RMS increased in Group 1 (p=0.046) but not in Group 2. In Group 1, the increase in TWA-RMS occurred both in the early portion of the T-wave (between T-onset and T-peak) and in the late portion (between T-peak and T-end).

Conclusions: TWA is spatially heterogeneous and localized in <3 lead sets in 66% of the studied patients. Analysis of the spatial distribution of TWA might provide new insights into the regional irregularities of repolarization in patients with CAD. TWA measurement on the RMS-curve does not require specialized equipment, and this simple and practical screening test can be easily incorporated into a clinical practice.