Literature DB >> 19523740

Association of intramyocardial high energy phosphate concentrations with quantitative measures of the ventricular fibrillation electrocardiogram waveform.

David D Salcido1, James J Menegazzi, Brian P Suffoletto, Eric S Logue, Lawrence D Sherman.   

Abstract

BACKGROUND: Quantitative measures of the ventricular fibrillation (VF) electrocardiogram (ECG) have been correlated with the success of rescue shocks, making them ideal measures for guiding resuscitative interventions. Correlation of intramyocardial energy stores with the change in quantitative VF ECG measures would provide mechanistic insight into their utility. We sought to investigate the relationship between intramyocardial energy stores and four quantitative ECG measures.
METHODS: Eighteen mixed-breed, domestic swine were sedated, anaesthetized and paralyzed. Swine were block randomized into three groups receiving 5, 10, or 15 min of untreated VF. Thoracotomy was performed and the heart was delivered. VF was induced by a 100 mA transthoracic shock while ECG was recorded. Biopsies of myocardial tissue were taken from the left and right ventricles after the prescribed duration of VF. Adenosine triphosphate (ATP) and adenosine diphosphate (ADP) concentrations in the tissue samples were measured. ECG data immediately prior to each biopsy were analyzed by each of four quantitative ECG methods: Scaling Exponent (ScE), Median Slope (MS), Amplitude Spectrum Area (AMSA), and logarithm of the Absolute Correlation (LAC). ATP and ADP concentrations of VF duration groups were compared. ATP and ADP concentrations were regressed against each quantitative ECG measure.
RESULTS: ATP concentrations differed between VF duration groups, but ADP concentrations differed only between 5 and 10 min groups. A significant association existed between ATP and three quantitative measures--ScE, MS, and AMSA--but no significant relationship was found for ADP.
CONCLUSION: Intramyocardial ATP levels correlate with quantitative measures of the ECG during ventricular fibrillation.

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Year:  2009        PMID: 19523740     DOI: 10.1016/j.resuscitation.2009.05.002

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


  18 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.  Predictive value of amplitude spectrum area of ventricular fibrillation waveform in patients with acute or previous myocardial infarction in out-of-hospital cardiac arrest.

Authors:  Michiel Hulleman; David D Salcido; James J Menegazzi; Patrick C Souverein; Hanno L Tan; Marieke T Blom; Rudolph W Koster
Journal:  Resuscitation       Date:  2017-08-24       Impact factor: 5.262

3.  Effects of intra-resuscitation antiarrhythmic administration on rearrest occurrence and intra-resuscitation ECG characteristics in the ROC ALPS trial.

Authors:  David D Salcido; Robert H Schmicker; Noah Kime; Jason E Buick; Sheldon Cheskes; Brian Grunau; Stephanie Zellner; Dana Zive; Tom P Aufderheide; Allison C Koller; Heather Herren; Jack Nuttall; Matthew L Sundermann; James J Menegazzi
Journal:  Resuscitation       Date:  2018-05-24       Impact factor: 5.262

4.  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

5.  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

Review 6.  Towards individualised treatment of out-of-hospital cardiac arrest patients: an update on technical innovations in the prehospital chain of survival.

Authors:  J Thannhauser; J Nas; R A Waalewijn; N van Royen; J L Bonnes; M A Brouwer; M J de Boer
Journal:  Neth Heart J       Date:  2021-08-09       Impact factor: 2.854

7.  Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients.

Authors:  Mi He; Yubao Lu; Lei Zhang; Hehua Zhang; Yushun Gong; Yongqin Li
Journal:  PLoS One       Date:  2016-02-10       Impact factor: 3.240

8.  Validation of spectral energy for the quantitative analysis of ventricular fibrillation waveform to guide defibrillation in a porcine model of cardiac arrest and resuscitation.

Authors:  Qiyu Yang; Ming Li; Zhaolan Huang; Zhuoyan Xie; Yue Wang; Qin Ling; Xuefen Liu; Wanchun Tang; Longyuan Jiang; Zhengfei Yang
Journal:  J Thorac Dis       Date:  2019-09       Impact factor: 2.895

9.  Electrocardiographic recording direction impacts ventricular fibrillation waveform measurements: A potential pitfall for VF-waveform guided defibrillation protocols.

Authors:  Jos Thannhauser; Joris Nas; Priya Vart; Joep L R M Smeets; Menko-Jan de Boer; Niels van Royen; Judith L Bonnes; Marc A Brouwer
Journal:  Resusc Plus       Date:  2021-04-02

10.  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

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