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Effectiveness of high resolution ECG spectral analysis in discrimination of patients prone to ventricular tachycardia and fibrillation

Tomasz Mroczka, Piotr Lewandowski, Roman Maniewski, Adam Liebert, Mariola Spioch, Konrad Steinbach

Med Sci Monit 2000; 6(5): MT1018-1026 :: ID: 508066


Introduction: To improve the diagnostic power of high resolution electrocardiography for discriminating patients at risk of ventricular arrhythmias, new methods based on spectral analysis have been used in recent years. The purpose of this study was to evaluate the effectiveness of these methods for predicting the risk of ventricular tachycardia and ventricular fibrillation in patients after myocardial infarction.
Material and methods: High resolution ECG were recorded in 129 post-infarction patients and 23 healthy volunteers. Of the post-infarction patients: 62 presented with ventricular tachycardia, 23 with ventricular fibrillation, while 44 had no clinically relevant arrhythmias. The ECG signals were recorded in three orthogonal X, Y, Z leads and averaged using cross-correlation method. Spectral analysis was performed by fast Fourier transform and the parametric modeling method with autoregressive model. Spectral analysis data were evaluated quantitatively by computing normality factor for FFT and spectral factor for AR.
Results: Both methods were found to be useful for evaluating the risk of arrhythmias. The sensitivity of ventricular tachycardia risk evaluation was higher (81% - FFT, 73% - AR) than that of evaluating the risk of ventricular fibrillation (30% - FFT, 48% - AR). The specificity in post-infarction patients without arrhythmias (93% - FFT, 84% - AR) was as high as that in healthy subjects (96% Ð FFT, 87% - AR).
Conclusions: Spectral analysis of HRECG is an effective method for evaluating the risk of VT and VF in patients after myocardial infarction.

Keywords: ventricular tachycardia and fibrillation, frequency analysis, late potentials, high resolution ECG

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750