Literature DB >> 10924083

Frequency modulation within electrocardiograms during ventricular fibrillation.

A Patwardhan1, S Moghe, K Wang, F Leonelli.   

Abstract

Periods of reentrant activation and effective refractory periods are correlated with dominant frequency or reciprocal of cycle periods during ventricular fibrillation (VF). In the present study, we used an analysis technique based on Wigner transforms to quantify time-varying dominant frequencies in electrocardiograms (ECGs) during VF. We estimated dominant frequencies within orthogonal ECGs recorded in 10 dogs during trials of 10 s of VF and in 9 dogs during trials of 30 s of VF. In four additional dogs, we compared dominant frequencies during 10 s of VF before and after administration of amiodarone. Our results showed the following. 1) There was substantial frequency variation or modulation within the ECGs during 10 and 30 s of VF, the average variation being +/-15% from the mean frequency. Amiodarone decreased mean frequencies (P < 0.05) as expected; however, amiodarone also decreased the variation in frequencies (P < 0.05). 2) During 30 s of VF, the dominant frequencies increased continuously from 7.3 to 8.1 Hz (P < 0.05). The increase in frequency was almost linear with a rate of 0.022 Hz/s (r(2) = 0.93, P < 0.0005). 3) Modulation of frequencies during the first and the last one-half of 30 s of VF was not different. Average (in time) mean frequencies and modulation of frequencies were similar in all three ECGs. 4) Although the averages were similar, during any VF episode, dominant frequencies in ECGs recorded from different locations on the body surface were similar to each other at some times and markedly different from each other at other times. We conclude that during VF, 1) frequencies in ECGs vary considerably and continuously, and amiodarone decreases this variation; 2) mean frequencies increase linearly during first 30 s; 3) the variability in frequency does not change during 30 s; and 4) at any given time, the frequencies within spatially different body surface ECGs can be either similar or markedly different.

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Year:  2000        PMID: 10924083     DOI: 10.1152/ajpheart.2000.279.2.H825

Source DB:  PubMed          Journal:  Am J Physiol Heart Circ Physiol        ISSN: 0363-6135            Impact factor:   4.733


  3 in total

1.  Insights Into the Spatiotemporal Patterns of Complexity of Ventricular Fibrillation by Multilead Analysis of Body Surface Potential Maps.

Authors:  Marianna Meo; Arnaud Denis; Frédéric Sacher; Josselin Duchâteau; Ghassen Cheniti; Stéphane Puyo; Laura Bear; Pierre Jaïs; Mélèze Hocini; Michel Haïssaguerre; Olivier Bernus; Rémi Dubois
Journal:  Front Physiol       Date:  2020-09-23       Impact factor: 4.566

2.  Capture of activation during ventricular arrhythmia using distributed stimulation.

Authors:  Jason M Meunier; Sanjiv Ramalingam; Shien-Fong Lin; Abhijit R Patwardhan
Journal:  J Interv Card Electrophysiol       Date:  2007-05-23       Impact factor: 1.900

3.  Electrocardiogram frequency change by extracorporeal blood perfusion in a swine ventricular fibrillation model.

Authors:  Jung Chan Lee; Gil Joon Suh; Hee Chan Kim
Journal:  Biomed Eng Online       Date:  2013-11-25       Impact factor: 2.819

  3 in total

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