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Improved differentiation of patients with and without ventricular tachycardia by frequency analysis of multiple electrocardiographic leads. - PubMed - NCBI
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Am J Cardiol. 1988 Sep 15;62(9):556-61.

Improved differentiation of patients with and without ventricular tachycardia by frequency analysis of multiple electrocardiographic leads.

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1
Cardiovascular Division, Washington University School of Medicine, St. Louis, Missouri 63110.

Abstract

Previously, these investigators have analyzed fast Fourier transforms of signal-averaged electrocardiograms (ECGs) to distinguish patients with from those without sustained ventricular tachycardia (VT). In these studies, analysis was performed on X, Y and Z ECG signals and patient to patient comparisons were based on an average of the X, Y and Z results. The purpose of this study was to determine the extent to which fast Fourier transform analysis of individual ECG leads and of the vector magnitude contribute to the differentiation of patient groups. Studies were performed in 28 normal subjects (group I), 38 patients with prior myocardial infarction but without VT (group II), 38 patients with anterior infarction and sustained VT (group III) and 29 patients with inferior infarction and sustained VT (group IV). Results in group I were used to define normal values for the area and peak magnitude ratios for the individual X, Y and Z leads and for the vector magnitude and to define normal values for the mean XYZ area and peak magnitude ratios. Spectra of the X, Y and Z leads, the vector magnitude and the mean XYZ results were significantly different in patients with VT compared with normal subjects and patients without VT (p less than 0.001). Results were abnormal in multiple leads from 71% of patients with VT and from only 5% of normal subjects (p less than 0.0001). In many patients with VT, abnormalities were identified in 2 of the 3 leads indicating a selective spatial distribution of altered ECG signals that elicit abnormal frequency components.(ABSTRACT TRUNCATED AT 250 WORDS)

PMID:
3414547
[Indexed for MEDLINE]
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