Literature DB >> 2817561

Estimating the duration of ventricular fibrillation.

C G Brown1, R Dzwonczyk, H A Werman, R L Hamlin.   

Abstract

As the duration of time between the onset of ventricular fibrillation and the application of defibrillation (downtime) increases, the rate of successful resuscitation decreases. Results of recent animal studies suggest that the rate of successful resuscitation may be increased after a prolonged cardiorespiratory arrest when pharmacologic therapy is instituted before defibrillation. An accurate estimation of downtime could be critical in selecting the most appropriate therapeutic intervention. The purpose of our study was to determine whether changes in the frequency or amplitude of the ventricular fibrillation ECG signal during cardiac arrest could be used to estimate downtime. We characterized the dynamics of both total power and frequency distribution of the power in the ECG during ventricular fibrillation in 11 swine to determine whether enough information existed in either parameter to estimate downtime. The median frequency of the power spectrum was used to track power distribution. Both parameters followed a dynamic, repeatable pattern. However, median frequency showed less intersubject variability than did total power. A mathematical model of median frequency was developed and used with data obtained from ten additional swine to estimate downtime. The model estimated downtime to within 1.3 minutes of actual downtime between one and ten minutes of ventricular fibrillation. Our study has identified a new, potentially useful parameter for studying various management strategies in ventricular fibrillation as a function of downtime.

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Year:  1989        PMID: 2817561     DOI: 10.1016/s0196-0644(89)80056-3

Source DB:  PubMed          Journal:  Ann Emerg Med        ISSN: 0196-0644            Impact factor:   5.721


  8 in total

1.  Effects of blockade of fast and slow inward current channels on ventricular fibrillation in the pig heart.

Authors:  A J Stewart; J D Allen; A B Devine; A A Adgey
Journal:  Heart       Date:  1996-12       Impact factor: 5.994

2.  Spectral analysis-based risk score enables early prediction of mortality and cerebral performance in patients undergoing therapeutic hypothermia for ventricular fibrillation and comatose status.

Authors:  David Filgueiras-Rama; Conrado J Calvo; Óscar Salvador-Montañés; Rosalía Cádenas; Jose Ruiz-Cantador; Eduardo Armada; Juan Ramón Rey; J L Merino; Rafael Peinado; Nicasio Pérez-Castellano; Julián Pérez-Villacastín; Jorge G Quintanilla; Santiago Jiménez; Francisco Castells; Francisco J Chorro; J L López-Sendón; Omer Berenfeld; José Jalife; Esteban López de Sá; José Millet
Journal:  Int J Cardiol       Date:  2015-03-14       Impact factor: 4.164

3.  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

4.  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

5.  Amplitude Changes during Ventricular Fibrillation: A Mechanistic Insight.

Authors:  Jane C Caldwell; Francis L Burton; Stuart M Cobbe; Godfrey L Smith
Journal:  Front Physiol       Date:  2012-05-23       Impact factor: 4.566

6.  Slowing of Electrical Activity in Ventricular Fibrillation is Not Associated with Increased Defibrillation Energies in the Isolated Rabbit Heart.

Authors:  Jane C Caldwell; Francis L Burton; Stuart M Cobbe; Godfrey L Smith
Journal:  Front Physiol       Date:  2011-04-06       Impact factor: 4.566

7.  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

8.  Computerized Analysis of the Ventricular Fibrillation Waveform Allows Identification of Myocardial Infarction: A Proof-of-Concept Study for Smart Defibrillator Applications in Cardiac Arrest.

Authors:  Jos Thannhauser; Joris Nas; Dennis J Rebergen; Sjoerd W Westra; Joep L R M Smeets; Niels Van Royen; Judith L Bonnes; Marc A Brouwer
Journal:  J Am Heart Assoc       Date:  2020-10-02       Impact factor: 5.501

  8 in total

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