Prediction of Defibrillation Outcome by Ventricular Fibrillation Waveform Analysis: A Clinical Review

Abstract

The most frequent initial rhythm in out-of-hospital witnessed cardiac arrest is ventricular fibrillation (VF) and electrical defibrillation is still the only effective therapy for the termination of this life-threatening cardiac arrhythmia. Even though earlier defibrillation is greatly emphasized during cardiopulmonary resuscitation (CPR), unnecessary or repetitive high energy defibrillations are associated with decreased post-resuscitation myocardial function. Optimizing the timing of defibrillation is of great importance in order to discriminate patients should receive immediate defibrillation versus alternate therapies such as CPR. Since characteristics of VF waveform changes over time and with CPR, which exhibit predictable ability of defibrillation success, quantitative analysis of VF waveform has the potential to guide defibrillation. This article reviewed methods developed for VF waveform analysis (including time domain, frequency domain, time-frequency domain, nonlinear analysis, and combination analysis techniques) and their performances for the prediction of defibrillation outcomes in clinical settings. The retrospective meta-analysis confirmed that VF waveform could predict the return of organized electrical activity, restoration of spontaneous circulation, and survival reliably. Additionally, predictors based on time-frequency and nonlinear methods were superior to other methods on the whole. However, no prospective studies have been performed to identify the optimal time of defibrillation utilizing VF waveform analysis until now. Therefore, the value of VF waveform analysis to guide clinical countershock management still needs further investigation.

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

“…VF-waveform analysis is the tool-of-choice for the non-invasive prediction of defibrillation success [6,8,9,16]. The AUCs obtained in this study for AMSA and FuzzyEn are in line with previous findings, which are in the 0.60-0.85 range [9,12,16,30,44,45].…”

“…VF waveform analysis has been extensively studied as a non-invasive tool to predict shock success, and thus optimize CPR/defibrillation therapy [5]. Many VF waveform features have been proposed for this purpose [6][7][8][9], ranging from classical amplitude, slope or spectral analyses of VF [6,10], to quantitative measures of its non-linear nature such as Poincare plot [11] and detrended fluctuation analyses [12], fractal dimension [13] or Hurst and Scaling exponents [13,14]. The best known VF-waveform feature is Amplitude Spectrum Area (AMSA), a measure of amplitude and frequency distribution of VF [15,16].…”

Rhythm Analysis during Cardiopulmonary Resuscitation: Past, Present, and Future

“…Research on the suppression of the CPR artifact started in the mid 1990s within the field of VF waveform analysis. VF waveform analysis for shock outcome prediction is beyond the scope of this paper; excellent reviews of this topic are available in the literature [ 34 , 35 ]. In the first study by Strohmenger et al [ 36 ] and in subsequent ones [ 37 , 38 ], VF was induced in pigs and chest compressions were administered using a pneumatic piston at a constant chest compression rate of 80 cpm (1.33 Hz).…”

Analysis of electrocardiogram pre-shock waveforms during ventricular fibrillation

“…A comprehensive review of some of the works in predicting defibrillation shock success are discussed in the literature [6,7]. Briefly, the amplitude and energy of the ECG were proposed by [8,9] from the viewpoint that the amplitude of the ECG during VF decreases with time, indicating deterioration of cardiac function.…”