T-wave morphology in long-QT syndrome

Poster Session 1 / Journal of Electrocardiology 42 (2009) 607–613 However, it is uncertain whether ST-T changes can be accurately evaluated by the portable ECG devices. The aim of this study was to examine the accuracy of evaluation of ST-T changes, as compared with the standard 12-lead ECG. Methods: Seventy-one patients who have indicated any ST-T changes by the standard 12-lead ECG were examined. We recorded ECG by Omron's monitoring device (HCG-801) at each equivalent location of V1 to V6 for 30 seconds. We compared the ECG recorded by HCG-801 with almost simultaneously recorded 12-lead ECG. Results: HCG-801 recorded ECG clear enough for physicians to diagnose in all patients. The concordance rate of ST-T changes between 12-lead ECG and HCG-801 was approximately 56%, if V4 lead was selected for the detection of ST-T changes. However, the concordance rate has improved up to 82%, if V5 lead was selected for the detection of ST-T changes. Conclusions: Most of the ST-T changes detected by 12-lead ECG can be accurately evaluated by HCG-801, if the V5 lead was selected for the detection of ST-T changes. Our results suggest that the evaluation of ST-T changes by compact portable ECG monitors could be reliable, even if a single lead were used. doi:10.1016/j.jelectrocard.2009.08.024

Design and validation of a pacing-spike removal algorithm for paced frequency domain analysis Sami Torbey, MSc, Damian P. Redfearn, MD, MRCPI, Selim Aki, PhD, (Queen's University, Kingston, Ontario, Canada) Introduction: There is evidence to support the importance of frequency domain analysis of the signal-averaged P wave for the study of atrial electrophysiology. However, the introduction of a pacing spike renders any frequency domain analysis useless, as the amplitude of the spike overshadows that of the P wave itself. As such, the pacing spike largely dominates the energy in all frequency bands. To mitigate this, we have developed a semiautomated pacing-spike removal algorithm and we seek to validate it in this study. Methods: We recorded 10-minute paced and unpaced electrocardiograms, both before and after the administration of Flecainide (1 mg/kg) and averaged the P waves in all recordings. The algorithm simply consisted of connecting by a straight line the onset and offset of the pacing spike as determined visually. We then correlated the energy values for the 20- to 40Hz and 40- to 150-Hz frequency bands of the paced signals before and after applying our pacing-spike removal algorithm with the corresponding normal sinus rhythm recordings. Results: Nine patients were recruited; 2 were excluded due to excessive noise levels in the recordings. Median energy reduced nonsignificantly after Flecainide. Correlation coefficients between sinus P wave and paced P waves with and without utilization of the spike removal algorithm are shown in Table 1. The values we obtained show that the frequency band analysis correlated best with native sinus beats after the pacing spike was removed. The treated signals also showed an acceptable correlation with their normal sinus rhythm counterparts for both cohorts and both frequency bands despite the small sample size, whereas the untreated signals did not show any significant correlation. As such, we conclude that our pacing-spike removal

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Table 1 Correlation of energies per frequency band between paced and normal sinus rhythm signals

Paced after spike removal Paced before spike removal

r P r P

Pre-Flecainide

Post-Flecainide

P20-40

P40-150

P20-40

P40-150

0.71 0.08 0.76 0.04

0.8 0.03 -0.43 0.33

0.86 0.01 -0.16 0.73

0.64 0.12 0.27 0.55

r = Pearson correlation coefficient with P value for significance at α 20 below. algorithm enables accurate frequency domain–paced signal-averaged Pwave analysis. doi:10.1016/j.jelectrocard.2009.08.025

T-wave morphology in long-QT syndrome Esben Vedel-Larsen,a Christian Haarmark, a Claus Graff, b Mads P. Andersen, b Egon Toft, b Johannes J. Struijk, b Jorgen Kanters, a ( aLaboratory of Experimental Cardiology, Dept. of Biomedical Sciences, Copenhagen N, Denmark; bDepartment of Health Science and Technology, Aalborg University, Aalborg, Denmark) Background: Congenital long-QT syndrome (LQTS) is characterized by prolongation of the QT interval and changes in T-wave morphology. Different variations of LQTS differ in clinical courses, and genotyping is thus useful for risk stratification. Specific T-wave morphologies are associated with specific genotypes, and a quantification of T-wave morphology could be used as a fast way of genotyping in a clinical setting. The aim of this study was to develop a classification of LQTS based on the Morphology Combination Score and the Fridericia-corrected QT interval (QTcF) for surface electrocardiogram (ECG) genotyping of LQTS. Methods: Median ECGs from 28 patients KvLQT1 (LQT1) and 48 HERG (LQT2) patients, as well as, respectively, 28 and 48 healthy subjects matched to the LQTS patients in age and sex, were used in the study. To avoid the influence of infantile T waves, only subjects older than 13 years were included. The morphology combined score (MCS) (flatness + notches + asymmetry) and QTcF were calculated for each subject. The classification of KvLQT1, HERG, or healthy were done with a discriminant analysis using a mixture of gaussians. The gaussian mixture allows taking the different variances in the classification groups into account. The patients were then classified with the discriminant analysis using MCS and QTcF into KvLQT1 versus HERG and LQTS versus normal. Results: MCS classified LQTS with satisfactory results (sensitivity of 86% and specificity of 89%), and LQT2 could be distinguished from LQT1 (sensitivity of 82% and specificity of 96%). Conclusion: T-wave morphology can be used for ECG genotyping of LQTS. doi:10.1016/j.jelectrocard.2009.08.026