Literature DB >> 18597916

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

Lawrence D Sherman1, Thomas D Rea, James D Waters, James J Menegazzi, Clifton W Callaway.   

Abstract

BACKGROUND: Measures of the ventricular fibrillation (VF) waveform may enable better allocation of cardiac arrest treatment by discriminating which patients should receive immediate defibrillation versus alternate therapies such as CPR. We derive a new measure based on the 'roughness' of the VF waveform, the Logarithm of the Absolute Correlations (LAC), and assess and contrast how well the LAC and the previously published scaling exponent (ScE) predict the duration of VF and the likelihood of return of spontaneous circulation (ROSC) under both optimal experimental and commercial-defibrillator sampling conditions. METHODS AND
RESULTS: We derived the LAC and ScE from two different populations--an animal study of 44 swine and a retrospective human sample of 158 out-of-hospital VF arrests treated with a commercial defibrillator. In the animal study, the LAC and ScE were calculated on 5s epochs of VF recorded at 1000 samples/s and then down sampled to 125 samples/s. In the human study, the LAC and ScE were calculated using 6s epochs recorded at 200 samples/s that occurred immediately prior to the initial shock. We compared the LAC and ScE measures using the Spearman correlation coefficients (CC) and areas under the receiver operating characteristic curve (AUC).
RESULTS: In the animal study, the LAC and ScE were highly correlated at 1000 sample/s (CC=0.93) but not at 125 samples/s (CC=-0.06). These correlations were reflected in how well the measures discriminated VF of < or =5 versus >5 min: AUC at 1000 samples/s was similar for LAC compared to ScE (0.71 versus 0.76). However AUC at 125 samples was greater for LAC compared to ScE (0.75 versus 0.62). In the human study, the LAC measure was a better predictor of ROSC following initial defibrillation as reflected by an AUC of 0.77 for LAC compared to 0.57 for ScE.
CONCLUSIONS: The LAC is an improvement over the ScE because the LAC retains its prognostic characteristics at lower ECG sampling rates typical of current clinical defibrillators. Hence, the LAC may have a role in better allocating treatment in resuscitation of VF cardiac arrest.

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Year:  2008        PMID: 18597916      PMCID: PMC2561072          DOI: 10.1016/j.resuscitation.2008.04.009

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  20 in total

1.  The predictive value of ventricular fibrillation electrocardiogram signal frequency and amplitude variables in patients with out-of-hospital cardiac arrest.

Authors:  H U Strohmenger; T Eftestol; K Sunde; V Wenzel; M Mair; H Ulmer; K H Lindner; P A Steen
Journal:  Anesth Analg       Date:  2001-12       Impact factor: 5.108

2.  Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest.

Authors:  T Eftestol; K Sunde; S Ole Aase; J H Husoy; P A Steen
Journal:  Circulation       Date:  2000-09-26       Impact factor: 29.690

3.  Scaling exponent predicts defibrillation success for out-of-hospital ventricular fibrillation cardiac arrest.

Authors:  C W Callaway; L D Sherman; V N Mosesso; T J Dietrich; E Holt; M C Clarkson
Journal:  Circulation       Date:  2001-03-27       Impact factor: 29.690

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

Authors:  C W Callaway; L D Sherman; M D Scheatzle; J J Menegazzi
Journal:  Pacing Clin Electrophysiol       Date:  2000-02       Impact factor: 1.976

Review 5.  Waveform analysis of ventricular fibrillation to predict defibrillation.

Authors:  Clifton W Callaway; James J Menegazzi
Journal:  Curr Opin Crit Care       Date:  2005-06       Impact factor: 3.687

6.  The three-phase model of cardiac arrest as applied to ventricular fibrillation in a large, urban emergency medical services system.

Authors:  Gary M Vilke; Theodore C Chan; James V Dunford; Marcelyn Metz; Ginger Ochs; Alan Smith; Roger Fisher; Jennifer C Poste; Lana McCallum-Brown; Daniel P Davis
Journal:  Resuscitation       Date:  2005-03       Impact factor: 5.262

7.  Ventricular fibrillation exhibits dynamical properties and self-similarity.

Authors:  L D Sherman; C W Callaway; J J Menegazzi
Journal:  Resuscitation       Date:  2000-10       Impact factor: 5.262

8.  Predicting the success of defibrillation by electrocardiographic analysis.

Authors:  Heitor P Povoas; Max Harry Weil; Wanchun Tang; Joe Bisera; Kada Klouche; Ann Barbatsis
Journal:  Resuscitation       Date:  2002-04       Impact factor: 5.262

9.  A novel wavelet transform based analysis reveals hidden structure in ventricular fibrillation.

Authors:  J N Watson; P S Addison; G R Clegg; M Holzer; F Sterz; C E Robertson
Journal:  Resuscitation       Date:  2000-01       Impact factor: 5.262

10.  Shock outcome is related to prior rhythm and duration of ventricular fibrillation.

Authors:  Joar Eilevstjønn; Jo Kramer-Johansen; Kjetil Sunde
Journal:  Resuscitation       Date:  2007-04-27       Impact factor: 5.262

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  14 in total

1.  Ventricular Fibrillation Waveform Analysis During Chest Compressions to Predict Survival From Cardiac Arrest.

Authors:  Jason Coult; Jennifer Blackwood; Lawrence Sherman; Thomas D Rea; Peter J Kudenchuk; Heemun Kwok
Journal:  Circ Arrhythm Electrophysiol       Date:  2019-01

2.  Quantitative waveform measures of the electrocardiogram as continuous physiologic feedback during resuscitation with cardiopulmonary bypass.

Authors:  David D Salcido; Young-Min Kim; Lawrence D Sherman; Greggory Housler; Xiaoyi Teng; Eric S Logue; James J Menegazzi
Journal:  Resuscitation       Date:  2011-10-01       Impact factor: 5.262

3.  Prompt prediction of successful defibrillation from 1-s ventricular fibrillation waveform in patients with out-of-hospital sudden cardiac arrest.

Authors:  Hiroshi Endoh; Seiji Hida; Satomi Oohashi; Yusuke Hayashi; Hidenori Kinoshita; Tadayuki Honda
Journal:  J Anesth       Date:  2010-11-27       Impact factor: 2.078

4.  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

5.  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

6.  Survival increases with CPR by Emergency Medical Services before defibrillation of out-of-hospital ventricular fibrillation or ventricular tachycardia: observations from the Resuscitation Outcomes Consortium.

Authors:  Steven M Bradley; Erin E Gabriel; Tom P Aufderheide; Roxy Barnes; Jim Christenson; Daniel P Davis; Ian G Stiell; Graham Nichol
Journal:  Resuscitation       Date:  2009-12-06       Impact factor: 5.262

7.  Extracorporeal life support during cardiac arrest resuscitation in a porcine model of ventricular fibrillation.

Authors:  Joshua C Reynolds; David D Salcido; Matthew L Sundermann; Allison C Koller; James J Menegazzi
Journal:  J Extra Corpor Technol       Date:  2013-03

8.  Correlation between coronary perfusion pressure and quantitative ECG waveform measures during resuscitation of prolonged ventricular fibrillation.

Authors:  Joshua C Reynolds; David D Salcido; James J Menegazzi
Journal:  Resuscitation       Date:  2012-05-03       Impact factor: 5.262

9.  Predict Defibrillation Outcome Using Stepping Increment of Poincare Plot for Out-of-Hospital Ventricular Fibrillation Cardiac Arrest.

Authors:  Yushun Gong; Yubao Lu; Lei Zhang; Hehua Zhang; Yongqin Li
Journal:  Biomed Res Int       Date:  2015-09-02       Impact factor: 3.411

Review 10.  Rhythm analysis during cardiopulmonary resuscitation: past, present, and future.

Authors:  Sofia Ruiz de Gauna; Unai Irusta; Jesus Ruiz; Unai Ayala; Elisabete Aramendi; Trygve Eftestøl
Journal:  Biomed Res Int       Date:  2014-01-09       Impact factor: 3.411

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