Literature DB >> 10709226

Scaling structure of electrocardiographic waveform during prolonged ventricular fibrillation in swine.

C W Callaway1, L D Sherman, M D Scheatzle, J J Menegazzi.   

Abstract

Ventricular fibrillation (VF) is the most common arrhythmia causing sudden cardiac death. However, the likelihood of successful defibrillation declines with increasing duration of VF. Because the morphology of the electrocardiogram (ECG) waveform during VF also changes with time, this study examined a new measure that describes the VF waveform and distinguishes between early and late VF. Surface ECG recordings were digitized at 200 samples/s from nine swine with induced VF. A new measure called the scaling exponent was calculated by examining the power-law relationship between the summation of amplitudes of a 1,024-point (5.12 second) waveform segment and the time scale of measurement. The scaling exponent is a local estimate of the fractal dimension of the ECG waveform. A consistent power-law relationship was observed for measurement time scales of 0.005-0.040 seconds. Calculation of the scaling exponent produced similar results between subjects, and distinguished early VF (< 4-minute duration) from late VF (> or = 4-minute duration). The scaling exponent was dependent on the order of the data, supporting the hypothesis that the surface ECG during VF is a deterministic rather than a random signal. The waveform of VF results from the interaction of multiple fronts of depolarization within the heart, and may be described using the tools of nonlinear dynamics. As a quantitative descriptor of waveform structure, the scaling exponent characterizes the time dependent organization of VF.

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Year:  2000        PMID: 10709226     DOI: 10.1111/j.1540-8159.2000.tb00799.x

Source DB:  PubMed          Journal:  Pacing Clin Electrophysiol        ISSN: 0147-8389            Impact factor:   1.976


  7 in total

1.  Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest.

Authors:  Beatriz Chicote; Elisabete Aramendi; Unai Irusta; Pamela Owens; Mohamud Daya; Ahamed Idris
Journal:  Resuscitation       Date:  2019-03-02       Impact factor: 5.262

2.  Frequency Variation of Ventricular Fibrillation May Help Predict Successful Defibrillation in a Rat Model of Cardiac Arrest.

Authors:  Wei-Ting Chen; Min-Shan Tsai; Shang-Ho Tsai; Yu-Chen Fang Jiang; Teck-Jin Yang; Chien-Hua Huang; Wei-Tien Chang; Wen-Jone Chen
Journal:  J Acute Med       Date:  2019-06-01

3.  Effects of pre-arrest and intra-arrest hypothermia on ventricular fibrillation and resuscitation.

Authors:  James J Menegazzi; Jon C Rittenberger; Brian P Suffoletto; Eric S Logue; David D Salcido; Joshua C Reynolds; Lawrence D Sherman
Journal:  Resuscitation       Date:  2008-10-25       Impact factor: 5.262

4.  The circadian pacemaker generates similar circadian rhythms in the fractal structure of heart rate in humans and rats.

Authors:  Kun Hu; Frank A J L Scheer; Ruud M Buijs; Steven A Shea
Journal:  Cardiovasc Res       Date:  2008-06-06       Impact factor: 10.787

5.  Logarithm of the absolute correlations of the ECG waveform estimates duration of ventricular fibrillation and predicts successful defibrillation.

Authors:  Lawrence D Sherman; Thomas D Rea; James D Waters; James J Menegazzi; Clifton W Callaway
Journal:  Resuscitation       Date:  2008-07-01       Impact factor: 5.262

6.  Influence of the skeletal muscle activity on time and frequency domain properties of the body surface ECG during evolving ventricular fibrillation in the pig.

Authors:  Alexander G Shvedko; Mark D Warren; Shibaji Shome; Jeroen Stinstra; Alexey V Zaitsev
Journal:  Resuscitation       Date:  2008-05-27       Impact factor: 5.262

7.  The effect of ischemia on ventricular fibrillation as measured by fractal dimension and frequency measures.

Authors:  Lawrence D Sherman; James T Niemann; John P Rosborough; James J Menegazzi
Journal:  Resuscitation       Date:  2007-07-13       Impact factor: 5.262

  7 in total

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