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The Utility of Quantitative Body Surface Isoarea Mapping for Predicting Ventricular Tachyarrhythmias
Author(s) -
GOLDNER BRUCE G.,
HORWITZ LEORA,
KOHN NINA,
LESSER MARTIN,
EHRLICH JASON,
COHEN TODD J.,
JADONATH RAM
Publication year - 1999
Publication title -
pacing and clinical electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.686
H-Index - 101
eISSN - 1540-8159
pISSN - 0147-8389
DOI - 10.1111/j.1540-8159.1999.tb00473.x
Subject(s) - medicine , signal averaged electrocardiogram , qrs complex , cardiology , body surface area , body surface , coronary artery disease , ventricular tachycardia , electrocardiography , signal (programming language) , logistic regression , geometry , mathematics , computer science , programming language
Noninvasive techniques, such as the signal averaged ECG, have been used to assess risk of ventricular tachyarrhythmias (VT). However, these methods produce false positive and negative results. The purpose of this study was to develop body surface map algorithms which would enhance prediction of susceptibility to VT. Fifty‐three patients referred for programmed electrical stimulation were enrolled in this study. All patients underwent signal averaged ECG, body surface map, programmed electrical stimulation. Group I patients had no sustained inducible VT and group II patients had either inducible sustained VT at electrophysiology study or previously documented spontaneous, sustained VT. For body surface map analysis, the difference between extrema on isoarea maps was calculated and defined as the gradient range. An abnormal body surface map was defined as a QRST gradient range ≤ 109 mv.ms. The mean QRST gradient range in group II was significantly < that in group I (P < 0.05). By logistic regression analysis, the presence of coronary artery disease, a QRST gradient range ≤ 109 mv.ms, an EF < 40% and a singal averaged ECG QRS duration > 114 ms predicted VT. The sensitivity, specificity, positive and negative predictive values for predicting VT susceptibility of an algorithm which combines the signal averaged ECG QRS duration and the QRST gradients were 0.93, 0.76, 0.79, and 0.91, respectively, while those for the signal averaged ECG alone were 0.52, 0.69, 0.63, and 0.59 for VT susceptibility. A combined body surface map‐signal averaged ECG algorithm was more sensitive in detecting susceptibility to VT than the signal averaged ECG alone.