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

Amplitude Spectrum Area of ventricular fibrillation to guide defibrillation: a small open-label, pseudo-randomized controlled multicenter trial

BACKGROUND

Ventricular fibrillation (VF) waveform analysis has been proposed as a potential non-invasive guide to optimize timing of defibrillation.

METHODS

The AMplitude Spectrum Area (AMSA) trial is an open-label, multicenter randomized controlled study reporting the first in-human use of AMSA analysis in out-of-hospital cardiac arrest (OHCA). The primary efficacy endpoint was the termination of VF for an AMSA ≥ 15.5 mV-Hz. Adult shockable OHCAs randomly received either an AMSA-guided cardiopulmonary resuscitation (CPR) or a standard-CPR. Randomization and allocation to trial group were carried out centrally. In the AMSA-guided CPR, an initial AMSA ≥ 15.5 mV-Hz prompted for immediate defibrillation, while lower values favored chest compression (CC). After completion of the first 2-min CPR cycle, an AMSA < 6.5 mV-Hz deferred defibrillation in favor of an additional 2-min CPR cycle. AMSA was measured and displayed in real-time during CC pauses for ventilation with a modified defibrillator.

FINDINGS

The trial was early discontinued for low recruitment due to the COVID-19 pandemics. A total of 31 patients were recruited in 3 Italian cities, 19 in AMSA-CPR and 12 in standard-CPR, and included in the data analysis. No difference in primary outcome was observed between the two groups. Termination of VF occurred in 74% of patients in the AMSA-CPR compared to 75% in the standard CPR (OR 0.93 [95% CI 0.18-4.90]). No adverse events were reported.

INTERPRETATION

AMSA was used prospectively in human patients during ongoing CPR. In this small trial, an AMSA-guided defibrillation provided no evidence of an improvement in termination of VF.

TRIAL REGISTRATION

NCT03237910.

FUNDING

European Commission - Horizon 2020; ZOLL Medical Corp., Chelmsford, USA (unrestricted grant); Italian Ministry of Health - Current research IRCCS.

[Adult advanced life support]

These European Resuscitation Council Advanced Life Support guidelines are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the prevention of and ALS treatments for both in-hospital cardiac arrest and out-of-hospital cardiac arrest.

European Resuscitation Council Guidelines 2021: Adult advanced life support

These European Resuscitation Council Advanced Life Support guidelines, are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the prevention of and ALS treatments for both in-hospital cardiac arrest and out-of-hospital cardiac arrest.

Fuzzy and Sample Entropies as Predictors of Patient Survival Using Short Ventricular Fibrillation Recordings during out of Hospital Cardiac Arrest

Optimal defibrillation timing guided by ventricular fibrillation (VF) waveform analysis would contribute to improved survival of out-of-hospital cardiac arrest (OHCA) patients by minimizing myocardial damage caused by futile defibrillation shocks and minimizing interruptions to cardiopulmonary resuscitation. Recently, fuzzy entropy (FuzzyEn) tailored to jointly measure VF amplitude and regularity has been shown to be an efficient defibrillation success predictor. In this study, 734 shocks from 296 OHCA patients (50 survivors) were analyzed, and the embedding dimension (m) and matching tolerance (r) for FuzzyEn and sample entropy (SampEn) were adjusted to predict defibrillation success and patient survival. Entropies were significantly larger in successful shocks and in survivors, and when compared to the available methods, FuzzyEn presented the best prediction results, marginally outperforming SampEn. The sensitivity and specificity of FuzzyEn were 83.3% and 76.7% when predicting defibrillation success, and 83.7% and 73.5% for patient survival. Sensitivities and specificities were two points above those of the best available methods, and the prediction accuracy was kept even for VF intervals as short as 2s. These results suggest that FuzzyEn and SampEn may be promising tools for optimizing the defibrillation time and predicting patient survival in OHCA patients presenting VF.

Association between ventricular fibrillation amplitude immediately prior to defibrillation and defibrillation success in out-of-hospital cardiac arrest

BACKGROUND

Several characteristics of the ventricular fibrillation (VF) waveform during cardiac arrest are associated with defibrillation success, including peak amplitude in the seconds prior to defibrillation. It is not known if immediate pre-defibrillation amplitude is associated with successful defibrillation, return of spontaneous circulation (ROSC) or survival to hospital discharge (SHD).

METHODS

We analyzed automated external defibrillation recordings of 80 patients with out-of-hospital VF cardiac arrest who received 284 defibrillations. We recorded the maximum amplitude during 3-second ECG tracings prior to each defibrillation attempt and the amplitude immediately prior to defibrillation.

RESULTS

Both the amplitude just prior to defibrillation and the highest amplitude within 3 seconds of the defibrillation were significantly higher in successful vs unsuccessful defibrillations (0.21 vs 0.11 mV, P = <.0001 and 0.51 vs 0.36 mV, P = <.0001). Amplitude immediately prior to defibrillation and maximal amplitude within 3 seconds of defibrillation were also higher in defibrillations with ROSC vs. defibrillations without ROSC (0.23 vs. 0.12 mV, P < .0001; and 0.52 vs. 0.38 mV, P < .0001). In defibrillations that resulted in SHD, immediate pre-defibrillation amplitude and maximum amplitude were also significantly larger (0.20 vs. 0.11 mV, P < .0001; and 0.52 vs. 0.35 mV, P < .0001). Binary logistic regression including both measures showed that only immediate pre-defibrillation amplitude remained significantly associated with ROSC while maximal amplitude did not (P = .006 and P = .135).

CONCLUSIONS

Amplitude of the VF waveform at the moment of defibrillation has a strong association with successful defibrillation, ROSC, and SHD.

Combining multiple ECG features does not improve prediction of defibrillation outcome compared to single features in a large population of out-of-hospital cardiac arrests

Introduction

Quantitative electrocardiographic (ECG) waveform analysis provides a noninvasive reflection of the metabolic milieu of the myocardium during resuscitation and is a potentially useful tool to optimize the defibrillation strategy. However, whether combining multiple ECG features can improve the capability of defibrillation outcome prediction in comparison to single feature analysis is still uncertain.

Methods

A total of 3828 defibrillations from 1617 patients who experienced out-of-hospital cardiac arrest were analyzed. A 2.048-s ECG trace prior to each defibrillation without chest compressions was used for the analysis. Sixteen predictive features were optimized through the training dataset that included 2447 shocks from 1050 patients. Logistic regression, neural network and support vector machine were used to combine multiple features for the prediction of defibrillation outcome. Performance between single and combined predictive features were compared by area under receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and prediction accuracy (PA) on a validation dataset that consisted of 1381 shocks from 567 patients.

Results

Among the single features, mean slope (MS) outperformed other methods with an AUC of 0.876. Combination of complementary features using neural network resulted in the highest AUC of 0.874 among the multifeature-based methods. Compared to MS, no statistical difference was observed in AUC, sensitivity, specificity, PPV, NPV and PA when multiple features were considered.

Conclusions

In this large dataset, the amplitude-related features achieved better defibrillation outcome prediction capability than other features. Combinations of multiple electrical features did not further improve prediction performance.

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

Early cardiopulmonary resuscitation together with early defibrillation is a key point in the chain of survival for cardiac arrest. Optimizing the timing of defibrillation by predicting the possibility of successful electric shock can guide treatments between defibrillation and cardiopulmonary resuscitation and improve the rate of restoration of spontaneous circulation. Numerous methods have been proposed for predicting defibrillation success based on quantification of the ventricular fibrillation waveform during past decades. To date, however, no analytical technique has been widely accepted for clinical application. In the present study, we investigate whether median stepping increment that is calculated from the Euclidean distance of consecutive points in Poincare plot could be used to predict the likelihood of successful defibrillation. Electrocardiographic recordings of out-of-hospital cardiac arrest patients were obtained from the external defibrillators. The performance of the proposed method was evaluated by receiver operating characteristic curve and compared with the results of other established features. The results indicated that median stepping increment has comparable performance to the established methods in predicting the likelihood of successful defibrillation.

Cardiac Arrest Resuscitation

Cardiac arrest is a dynamic disease that tests the multitasking and leadership abilities of emergency physicians. Providers must simultaneously manage the logistics of resuscitation while searching for the cause of cardiac arrest. The astute clinician will also realize that he or she is orchestrating only one portion of a larger series of events, each of which directly affects patient outcomes. Resuscitation science is rapidly evolving, and emergency providers must be familiar with the latest evidence and controversies surrounding resuscitative techniques. This article reviews evidence, discusses controversies, and offers strategies to provide quality cardiac arrest resuscitation.

Beyond ventricular fibrillation analysis: comprehensive waveform analysis for all cardiac rhythms occurring during resuscitation

AIM

To propose a method which analyses the electrocardiogram (ECG) waveform of any cardiac rhythm occurring during resuscitation and computes the probability of that rhythm converting into another with better prognosis (Pdes).

METHODS

Rhythm transitions occurring spontaneously or due to defibrillation were analyzed. For each possible rhythm, ventricular fibrillation/ventricular tachycardia (VF/VT), pulseless electrical activity (PEA), pulse-generating rhythm (PR) and asystole (AS), the desired and undesired transitions were defined. ECG segments corresponding to the last 3s of rhythms prior to transition were used to extract waveform features. For each rhythm type, waveform features were combined into a logistic regression model to develop a rhythm specific classifier of desired transitions. This model was the monitoring function for the Pdes. The capacity of each rhythm specific classifier to discriminate between desired and undesired transitions was evaluated in terms of area under the curve (AUC). Pdes was integrated into a state sequence representation, which structures the information of cardiac arrest episodes, to analyze the effect of therapy on patient. As a case study, the effect of optimal/suboptimal cardiopulmonary resuscitation (CPR) on Pdes was analyzed. The mean Pdes was computed for the pre- and post-CPR intervals which presented the same underlying rhythm. The relationship between the optimal/suboptimal CPR and increase/decrease of Pdes was analyzed.

RESULTS

The AUC was 0.80, 0.79, 0.73 and 0.61 for VF/VT, PEA, PR and AS respectively. The Pdes quantified the probability of every rhythm of the episode developing to a better state, and the evolution of Pdes was coherent with the provided therapy. The case study indicated, for most rhythms, that positive trends in the dynamic behaviour could be associated with optimal CPR, whereas the opposite seemed true for negative trends.

CONCLUSION

A method for continuous ECG waveform analysis covering all cardiac rhythms during resuscitation has been proposed. This methodology can be further developed to be used in retrospective studies of CPR techniques, and, in the future, for potentially monitoring in real time the probability of survival of patients being resuscitated.

Signal integral for optimizing the timing of defibrillation

OBJECTIVE

The possibility of successful defibrillation decreases with an increased duration of ventricular fibrillation (VF). Futile electrical shocks are inversely correlated with myocardial contractile function and long-term survival. Previous studies have demonstrated that various ECG waveform analyses predict the success of defibrillation. This study investigated whether the absolute amplitude of pre-shock VF waveform is likely to predict the success of defibrillation.

METHODS

ECG recordings of 350 out-of-hospital cardiac arrest (OOHCA) patients were obtained from the automated external defibrillator (AED) and analyzed by the method of signal integral. Successful defibrillation was defined as organized rhythm with heart rate ≥40beat/min commencing within one min of post-shock period and persisting for a minimum of 30s.

RESULTS

Signal integral was significantly greater in successful defibrillation than unsuccessful defibrillation (81.76±32.3mV vs. 34.9±15.33mV, p<0.001). The intersection of the sensitivity and specificity curve provided a threshold value of 51mV. The corresponding values of sensitivity, specificity, positive predictive and negative predictive values for successful defibrillation were 90%, 86%, 80% and 93%, respectively. The receiver operator curve further revealed that signal integral predicted the likelihood of successful defibrillation (area under the curve=0.949).

CONCLUSIONS

Signal integral predicted successful electrical shocks on patients with ventricular fibrillation and have potential to optimize the timing of defibrillation and reduce the number of electrical shocks.

Tissue oximetry by near-infrared spectroscopy in a porcine model of out-of-hospital cardiac arrest and resuscitation

INTRODUCTION

Monitoring during resuscitation remains relatively crude. Near-infrared spectroscopy (NIRS) measures aggregate oxygen saturation in a volume of tissue. We assessed the utility of continuous StO2 measurement in a porcine model of cardiac arrest, and explored the effects of differential vasoconstriction on StO2. We hypothesized that (1) StO2 trends correspond with the onset of loss of pulses, resuscitation, and return of spontaneous circulation (ROSC); (2) epinephrine has a dose-dependent effect on StO2.

METHODS

We anesthetized and instrumented 7 female swine, placing a NIRS probe on the left forelimb to recorded StO2. After 8 min of untreated VF and 2 min of CPR, we randomized animals to 0.015 mgkg(-1) (SDE) or 0.1mgkg(-1) (HDE) epinephrine. After 3 min of CPR, animals were defibrillated. Animals with ROSC were given SDE, then HDE for subsequent hemodynamic deteriorations. Data were analyzed with descriptive statistics and generalized linear model (alpha=0.05) to determine overall slope of pooled StO2 across animals for resuscitation segments.

RESULTS

Four animals received HDE and three SDE. All achieved ROSC. Significant coefficients (ΔStO2 min(-1)) were noted for resuscitation segments. StO2 decreased after loss of pulses (-29.1; 95%CI -33.4, -24.7; p<0.01) but plateaued during CPR (-0.2; 95%CI -1.2, 0.8; p=0.71). There was a graded decline in StO2 between SDE (-1.3; 95%CI -1.5, -1.2; p<0.01) and HDE (-3.1; 95%CI -5.8, -0.4; p=0.03). The slowest change occurred with ROSC (0.4; 95%CI 0.3, 0.5; p<0.01).

CONCLUSIONS

In a porcine model of OHCA, peripheral StO2 rapidly decreased after loss of pulses, but did not improve with CPR or epinephrine. It increased extremely slowly after ROSC.

Optimizing the duration of CPR prior to defibrillation improves the outcome of CPR in a rat model of prolonged cardiac arrest

AIMS

This study was to investigate whether optimal duration of CPR prior to defibrillation could be guided by Amplitude Spectrum Analysis (AMSA) in the setting of prolonged VF on outcome of CPR.

METHODS

VF was induced in thirty Sprague-Dawley rats and untreated for 8 minutes. Animals were then randomized into 3 groups prior to CPR: The duration of CPR prior to defibrillation was guided by AMSA (CC+AMSA); guidelines-based with delayed defibrillation that simulated the AED algorithm (GL+AED); and guidelines-based with immediate shock (GL+shock ready).

RESULTS

Regardless of groups, the majority of the animals (85%) required over 5 min of CPR to achieve restoration of spontaneous circulation (ROSC). Significantly greater rate of ROSC after first defibrillation (70% vs 0%, p < 0.01), lesser CPR interruptions and the number of defibrillations were observed in the CC+AMSA group when compared to both guidelines-based groups (p < 0.001). This was associated with a significantly better post-resuscitation myocardial and neurological function and longer durations of survival.

CONCLUSIONS

After prolonged VF, optimal duration of CPR prior to defibrillation guided by AMSA improves the outcome of CPR.

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

INTRODUCTION

The ventricular fibrillation (VF) waveform is dynamic and predicts defibrillation success. Quantitative waveform measures (QWMs) quantify these changes. Coronary perfusion pressure (CPP), a surrogate for myocardial perfusion, also predicts defibrillation success. The relationship between QWM and CPP has been preliminarily explored. We sought to further delineate this relationship in our porcine model and to determine if it is different between animals with/without ROSC (return of spontaneous circulation).

HYPOTHESIS

A relationship exists between QWM and CPP that is different between animals with/without ROSC.

METHODS

Utilizing a prior experiment in our porcine model of prolonged out-of-hospital VF cardiac arrest, we calculated mean CPP, cumulative dose CPP, and percent recovery of three QWM during resuscitation before the first defibrillation: amplitude spectrum area (AMSA), median slope (MS), and logarithm of the absolute correlations (LAC). A random effects linear regression model with an interaction term CPP ROSC investigated the association between CPP and percent recovery QWM and how this relationship changes with/without ROSC.

RESULTS

For 12 animals, CPP and QWM measures (except LAC) improved during resuscitation. A linear relationship existed between CPP and percent recovery AMSA (coefficient 0.27; 95%CI 0.23, 0.31; p<0.001) and percent recovery MS (coefficient 0.80; 95%CI 0.70, 0.90; p<0.001). A linear relationship existed between cumulative dose CPP and percent recovery AMSA (coefficient 2.29; 95%CI 2.0, 2.56; p<0.001) and percent recovery MS (coefficient 6.68; 95%CI 6.09, 7.26; p<0.001). Animals with ROSC had a significantly "steeper" dose-response relationship.

CONCLUSIONS

There is a linear relationship between QWM and CPP during chest compressions in our porcine cardiac arrest model that is different between animals with/without ROSC.

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

BACKGROUND

There are few if any real-time physiologic measures that currently provide feedback during resuscitation from cardiac arrest. Such measures could be used to guide therapy not simply based on process guidelines but on the physiologic response of the patient from moment to moment. To this end, we applied an existing technology - quantitative waveform measures (QWMs) of the ventricular fibrillation (VF) electrocardiogram (ECG) - as a continuous measure of myocardial response to reperfusion with cardiopulmonary bypass (CPB) after prolonged cardiac arrest.

METHODS

Sixteen domestic, mixed-breed swine were sedated, anesthetized and paralyzed. Mechanical ventilation with room air was provided. Large diameter bypass catheters were placed in the right external jugular vein and right femoral artery for cardiopulmonary bypass (CPB). VF was induced with a 3-s 100mA transthoracic shock and left untreated for 15, 20, 25, or 30min, followed by 10min of centrifugal pump CPB (Bard CPS). Continuous Lead II ECG was recorded with an electronic data acquisition system (Power Lab, ADInstruments). Four QWMs representing 4 signal characteristics of the VF ECG were calculated in 5-s windows throughout the course of untreated VF and resuscitation with CPB.

RESULTS

Four animals were assigned to each VF duration group. QWM recovery was inversely correlated with untreated VF duration, and was drastically reduced above 20min of untreated VF. Return of spontaneous circulation (ROSC) was highly unlikely after 20min of untreated VF.

CONCLUSION

QWMs of the VF ECG provided a real-time metric of myocardial electrophysiologic response to reperfusion with CPB. Resuscitation from greater than 20min of untreated cardiac arrest was unlikely. QWMs may be useful for titrating CPB duration before defibrillation and assessing CPR quality independently of process guidelines.

Wavelet-based markers of ventricular fibrillation in optimizing human cardiac resuscitation

During cardiac resuscitation from ventricular fibrillation (VF) it would be helpful if we could monitor and predict the optimal state of the heart to be shocked into a perfusing rhythm. Real-time feedback of this state to the emergency medical staff (EMS) could improve the survival rate after resuscitation. In this paper, using real world out-of-the-hospital human VF data obtained during resuscitation by EMS personnel, we present the results of applying wavelet markers in predicting the shock outcomes. We also performed comparative analysis of 5 existing techniques (spectral and correlation based approaches) against the proposed wavelet markers. A database of 29 human VF tracings was extracted from the defibrillator recordings collected by the EMS personnel and was used to validate the waveform markers. The results obtained by the comparison of the wavelet based features with other spectral, and correlation-based features indicates that the proposed wavelet features perform well with an overall accuracy of 79.3% in predicting the shock outcomes and hence demonstrate potential to provide near real-time feedback to EMS personnel in optimizing resuscitation outcomes.

Real-time electrogram analysis for monitoring coronary blood flow during human ventricular fibrillation: implications for CPR

BACKGROUND

Effective chest compressions during prolonged ventricular fibrillation (VF) have been shown to increase the chances of successful defibrillation to a rhythm associated with a sustainable cardiac output. There is currently no effective method of recording the degree of antegrade coronary artery flow during chest compression in VF.

OBJECTIVE

This study sought to quantify the relationship between the antegrade coronary flow and the characteristics of human VF using near real-time wavelet-based electrocardiographic markers.

METHODS

VF experiments were conducted in 8 isolated human hearts. The Langendorff perfusion enabled different flow rates (perfusion) during VF, which allowed for the simulation of chest compression with different efficacies. After the initiation of VF, the hearts were maintained in ischemia (no flow) for 3 minutes, followed by a 2-minute reperfusion and defibrillation. The experiments were repeated at flows of 0%, 30%, and 100% of baseline perfusion, and volume-conducted surface electrograms were recorded and analyzed using continuous wavelet transform in 5-second frames.

RESULTS

Near real-time wavelet features were derived that demonstrated significant differences in the multicomponent nature of VF signals and predicted perfusion rate characteristics for different flow rates (i.e., 0%, 30%, and 100%; P < .0006). A pattern classifier was trained using the feature values from 5 hearts, and the flow rates for 3 additional hearts were predicted with an accuracy of 90%.

CONCLUSION

VF electrogram characteristics as measured by wavelet analysis relate to antegrade coronary flow rate during VF. These findings suggest that chest compression efficacy of physiological importance could be monitored using near real-time wavelet analysis.

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

PURPOSE

Ventricular fibrillation (VF) is a common cardiac arrest rhythm that can be terminated by electrical defibrillation. During cardiopulmonary resuscitation, there is a strong need for a prompt and reliable predictor of successful defibrillation because myocardial damage can result from repeated futile defibrillation attempts. Continuous wavelet transform (CWT) provides excellent time and frequency resolution of signals. The purpose of this study was to evaluate whether features based on CWT could predict successful defibrillation.

METHODS

VF electrocardiogram (ECG) waveforms stored in ambulance-located defibrillators were collected. Predefibrillation waveforms were divided into 1.0- or 5.12-s VF waveforms. Indices in frequency domain or nonlinear analysis were calculated on the 5.12-s waveform. Simultaneously, CWT was performed on the 1.0-s waveform, and total low-band (1-3 Hz), mid-band (3-10 Hz), and high-band (10-32 Hz) energy were calculated.

RESULTS

In 152 patients with out-of-hospital cardiac arrest, a total of 233 ECG predefibrillation recordings, consisting of 164 unsuccessful and 69 successful episodes, were analyzed. Indices of frequency domain analysis (peak frequency, centroid frequency, and amplitude spectral area), nonlinear analysis (approximate entropy and Hurst exponent, detrended fluctuation analysis), and CWT analysis (mid-band and high-band energy) were significantly different between unsuccessful and successful episodes (P < 0.01 for all). However, logistic regression analysis showed that centroid frequency and total mid-band energy were effective predictors (P < 0.01 for both).

CONCLUSIONS

Energy spectrum analysis based on CWT as short as a 1.0-s VF ECG waveform enables prompt and reliable prediction of successful defibrillation.

Detrended fluctuation analysis predicts successful defibrillation for out-of-hospital ventricular fibrillation cardiac arrest

AIMS

Repeated failed shocks for ventricular fibrillation (VF) in out-of-hospital cardiac arrest (OOHCA) can worsen the outcome. It is very important to rapidly distinguish between early and late VF. We hypothesised that VF waveform analysis based on detrended fluctuation analysis (DFA) can help predict successful defibrillation.

METHODS

Electrocardiogram (ECG) recordings of VF signals from automated external defibrillators (AEDs) were obtained for subjects with OOHCA in Taipei city. To examine the time effect on DFA, we also analysed VF signals in subjects who experienced sudden cardiac death during Holter study from PhysioNet, a publicly accessible database. Waveform parameters including root-mean-squared (RMS) amplitude, mean amplitude, amplitude spectrum analysis (AMSA), frequency analysis as well as fractal measurements including scaling exponent (SE) and DFA were calculated. A defibrillation was regarded as successful when VF was converted to an organised rhythm within 5s after each defibrillation.

RESULTS

A total of 155 OOHCA subjects (37 successful and 118 unsuccessful defibrillations) with VF were included for analysis. Among the VF waveform parameters, only AMSA (7.61+/-3.30 vs. 6.30+/-3.13, P=0.028) and DFAalpha2 (0.38+/-0.24 vs. 0.49+/-0.24, P=0.013) showed significant difference between subjects with successful and unsuccessful defibrillation. The area under the curves (AUCs) for AMSA and DFAalpha2 was 0.63 (95% confidence interval (CI)=0.52-0.73) and 0.65 (95% CI=0.54-0.75), respectively. Among the waveform parameters, only DFAalpha2, SE and dominant frequency showed significant time effect.

CONCLUSIONS

The VF waveform analysis based on DFA could help predict first-shock defibrillation success in patients with OOHCA. The clinical utility of the approach deserves further investigation.

Effect of global ischemia and reperfusion during ventricular fibrillation in myopathic human hearts

The effect of lack of global coronary perfusion on myocardial activation rate, wavebreak, and its temporal progression during human ventricular fibrillation (VF) is not known. We tested the hypothesis that global myocardial ischemia decreases activation rate and spatiotemporal organization during VF in myopathic human hearts, while increasing wavebreak, and that a short duration of reperfusion can restore these spatiotemporal changes to baseline levels. The electrograms were acquired during VF in a human Langendorff model using global mapping consisting of two 112-electrode arrays placed on the epicardium and endocardium simultaneously. We found that global myocardial ischemia results in slowing of the global activation rate (combined endo and epi), from 4.89+/-0.04 Hz. to 3.60+/-0.04 Hz. during the 200 s of global ischemia (no coronary flow) (P<0.01) in eight myopathic hearts. Two minutes of reperfusion contributed to reversal of the slowing with activation rate value increasing close to VF onset (4.72+/-0.04 Hz). In addition, during the period of ischemia, an activation rate gradient between the endocardium (3.76+/-0.06 Hz) and epicardium (3.45+/-0.06 Hz) was observed (P<0.01). There was a concomitant difference in wavebreak index (that provides a normalized parameterization of phase singularities) between the epicardium (11.29+/-2.7) and endocardium (3.25+/-2.7) during the 200 s of ischemia (P=0.02). The activation rate, gradient, and wavebreak changes were reversed by short duration (2 min) of reperfusion. Global myocardial ischemia of 3 min leads to complex spatiotemporal changes during VF in myopathic human hearts; these changes can be reversed by a short duration of reperfusion.

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

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.

The effect of adenosine A1 receptor antagonism on return of spontaneous circulation and short-term survival in prolonged ventricular fibrillation

BACKGROUND

Endogenous adenosine (ADO) is cardioprotective during ischemia and its myocardial concentration increases during untreated ventricular fibrillation (VF). We have previously shown that ADO A1 receptor (ADOA1R) antagonism hastens the time-dependent decay in VF waveform morphology during the circulatory phase of cardiac arrest.

OBJECTIVE

To determine the effect of ADOA1R antagonism on ROSC and short-term survival in prolonged VF.

METHODS

Thirty-six swine were assigned by block randomization to one of three groups: a group that received only vehicle (CONTROL), an ADOA1R antagonist pretreatment group (PRE), and a group that was given ADOA1R antagonist during resuscitation (DURING). The animals were instrumented under anesthesia, and ADOA1R antagonist or vehicle, per group assignment, was infused 5 minutes prior to VF induction. At minute 8 of untreated VF, chest compression with ventilation was initiated and a standard drug cocktail, with ADOA1R antagonist or vehicle, was given. The first rescue shock (150 J biphasic) was delivered after 11 minutes of VF. Proportions with 95% confidence intervals (CIs) were calculated for the two outcome measures.

RESULTS

The baseline characteristics and chemistry values for the three groups were mathematically the same. The DURING group had a greater proportion of female animals (seven of 12) in comparison with the CONTROL group (two of 12) (p=0.03). ADOA1R antagonism hastened the decay of VF as previously demonstrated, but the rate of ROSC was the same for all groups: CONTROL=seven of 12, PRE=six of 12, and DURING=seven of 12. There were also no differences in short-term survival: CONTROL=four of 12, PRE=five of 12, and DURING=seven of 12.

CONCLUSIONS

In this study, ADOA1R antagonism had no effect on outcome whether given before induction of VF or upon resuscitation after 8 minutes of untreated VF. The role of endogenous ADO in prolonged VF remains unclear.

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

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.

Predicting defibrillation success

PURPOSE OF REVIEW

Ventricular fibrillation is the primary rhythm in many cardiac arrest patients. Since the late 1980s, the surface electrocardiogram of ventricular fibrillation has been subjected to analysis to obtain reliable information about the likelihood of successful countershock and to estimate the duration of cardiac arrest. Considerable efforts were made in the past 2 years to further improve the predictive power of rescue shock measures.

RECENT FINDINGS

In a retrospective clinical study, ventricular fibrillation single feature analysis was not able to reliably estimate duration between cardiac arrest onset and initial electrocardiogram. Combining ventricular fibrillation features in the time and frequency domain by employing neural networks did not further improve the best single feature prediction power taken from higher ventricular fibrillation frequency bands. Cardioversion outcome prediction based on the wavelet technique increased the specificity up to 66% at the 95% sensitivity level.

SUMMARY

Recent results question the ventricular fibrillation feature analysis as a reliable tool to estimate the duration of human cardiac arrest. Animal and clinical studies confirmed that ventricular fibrillation waveform analysis contains information to reliably predict the countershock success rate and further improved countershock outcome prediction. Prospective clinical studies are highly warranted to demonstrate that ventricular fibrillation waveform analysis definitely improves survival after cardiac arrest.

Resuscitation Outcomes Consortium (ROC) PRIMED cardiac arrest trial methods part 2: rationale and methodology for "Analyze Later vs. Analyze Early" protocol

OBJECTIVE

The primary objective of the trial is to compare survival to hospital discharge with modified Rankin score (MRS) < or =3 between a strategy that prioritizes a specified period of CPR before rhythm analysis (Analyze Later) versus a strategy of minimal CPR followed by early rhythm analysis (Analyze Early) in patients with out-of-hospital cardiac arrest.

METHODS

Design-Cluster randomized trial with cluster units defined by geographic region, or monitor/defibrillator machine. Population-Adults treated by emergency medical service (EMS) providers for non-traumatic out-of-hospital cardiac arrest not witnessed by EMS. Setting-EMS systems participating in the Resuscitation Outcomes Consortium and agreeing to cluster randomization to the Analyze Later versus Analyze Early intervention in a crossover fashion. Sample size-Based on a two-sided significance level of 0.05, a maximum of 13,239 evaluable patients will allow statistical power of 0.996 to detect a hypothesized improvement in the probability of survival to discharge with MRS < or =3 rate from 5.41% after Analyze Early to 7.45% after Analyze Later (2.04% absolute increase in primary outcome).

CONCLUSION

If this trial demonstrates a significant improvement in survival with a strategy of Analyze Later, it is estimated that 4000 premature deaths from cardiac arrest would be averted annually in North America alone.

Identifying approaches to improve the accuracy of shock outcome prediction for out-of-hospital cardiac arrest

BACKGROUND

Analysis of the electrocardiogram (ECG) can predict if a cardiac arrest patient in ventricular fibrillation is likely to have a return of spontaneous circulation if defibrillated. The accuracy of such methods determines how useful it is clinically and for retrospective analysis.

METHODS AND RESULTS

We wanted to identify if there is a potential of improving prediction accuracy by adding peri-arrest factors to an ECG-based prediction system, or constructing a prediction system that adapts to each patient. Therefore, we analysed shock outcome prediction data with a mixed effects logistic regression model to identify if there are random effects (unexplained variation between patients) influencing the prediction accuracy. We also added information about the patients' age, sex and presenting rhythm, ambulance response time and presence of bystander CPR to the model to try to improve it by reducing the random effects. For all the six predictive features analysed random effects where present, with p-values below 10(-3). The random effect size was 73-189% of the feature effect size. Adding the peri-arrest factors to the best ECG-based model gave no significant improvement.

CONCLUSIONS

The presence of random effects shows that the shock outcome prediction accuracy can be improved by explaining more of the variation between patients, for example using the approaches outlined above, and that there is within-patient correlation between samples that should be accounted for when evaluating prediction accuracy. The specific peri-arrest factors tested here did not significantly improve prediction accuracy, but other factors should be explored.

The effect of ischemia on ventricular fibrillation as measured by fractal dimension and frequency measures

INTRODUCTION

Most animal studies of ventricular fibrillation (VF) waveform characteristics involve healthy animals with VF initiated by electric shock. However, clinical VF is usually the result of ischemia. The waveform characteristics in these two types of VF may differ. The angular velocity (AV), frequency ratio (FR) and median frequency (MF) are three frequency-based measures of VF. The scaling exponent (ScE), the logarithm of the absolute correlations (LAC) and the Hurst exponent (HE) are three measures of the fractal dimension of VF.

HYPOTHESIS

We hypothesized that these quantitative measures would differ between ischemic and electrically initiated VF.

METHODS

VF was induced in 14 swine by electric shock and in 12 swine by ischemia. For ischemia induced VF animals, an angioplasty catheter was positioned in the mid-LAD and the balloon inflated. A mean of 891+/-608 (S.D.)s later, VF occurred. For electrically induced animals, an AC current was passed through a catheter in the RV. Following initiation by either method, VF was recorded for 7min. Sequential 5s epochs were analyzed for AV, FR, MF and fractal dimension measures.

RESULTS

Ischemic VF demonstrated a significantly higher fractal dimension as estimated by the ScE for the first 0-90s (p=0.021) and for 90-180s (p=0.016). The Hurst exponent was significantly higher for ischemic VF for both 0-90s (p<0.0001) and 90-180s (p<0.0001). The fractal dimension as estimated by the LAC method was not significantly different for 0-90s (p=0.056) but was highly significant for 90-180s (p=0.001). During the initial 90s the groups did differ in all measures of frequency as follows: AV (p<0.001), FR (p<0.001), MF (p<0.001). These differences did not persist beyond 90s except for a mild elevation of the FR after 270s (p<0.02).

CONCLUSION

Fractal based measures indicate an increase in the fractal dimension of ischemia induced VF for the first 180s when compared to electrically induced VF. Frequency-based measures uniformly demonstrate a pattern of higher frequencies for electrically induced VF for the first 90s. The increased fractal dimension and decreased frequencies associated with ischemia induced VF may reflect changes in the underlying myocardial physiology that can be used to guide therapies.

Three distinct phases of VF during global ischemia in the isolated blood-perfused pig heart

Changes in ventricular fibrillation (VF) organization occurring after the onset of global ischemia are relevant to defibrillation and survival but remain poorly understood. We hypothesized that ischemia-specific dynamic instability of the action potential (AP) causes a loss of spatiotemporal periodicity of propagation and broadening of the electrocardiogram (ECG) frequency spectrum during VF in the ischemic myocardium. We recorded voltage-sensitive fluorescence of di-4-ANEPPS (anterior left ventricle, 35 x 35 mm, 64 x 64 pixels) and the volume-conducted ECG in six blood-perfused hearts during 10 min of VF and global ischemia. We used coefficient of variation (CV) to estimate variability of AP amplitude, AP duration, and diastolic interval (CV-APA, CV-APD, and CV-DI, respectively). We computed excitation median frequency (Median_F), spectral width of the AP and ECG (SpW-AP and SpW-ECG, respectively), wavebreak incidence (WBI), and recurrence of propagation direction (RPD). We found three distinct phases of local VF dynamics: "relatively periodic" (<or=1 min, high Median_F, moderate AP variability, high WBI, low RPD), "highly periodic" (1-2 min, reduced Median_F, low AP variability, low WBI, high RPD), and "aperiodic" (3-10 min, low Median_F, high AP variability, high WBI, low RPD). In one experiment, spontaneous conversion from the aperiodic to the highly periodic phase occurred after 5 min of ischemia. The SpW-ECG was correlated with SpW-AP, CV-APD, and CV-APA. We conclude that 1) at least three distinct phases of VF dynamics are present in our model, and 2) the newly described aperiodic phase is related to ischemia-specific dynamic instability of the AP shape, which underlies broadening of the ECG spectrum during VF evolution.

Prediction of countershock success using single features from multiple ventricular fibrillation frequency bands and feature combinations using neural networks

Targeted defibrillation therapy is needed to optimise survival chances of ventricular fibrillation (VF) patients, but at present VF analysis strategies to optimise defibrillation timing have insufficient predictive power. From 197 patients with in-hospital and out-of-hospital cardiac arrest, 770 electrocardiogram (ECG) recordings of countershock attempts were analysed. Preshock VF ECG features in the time and frequency domain were tested retrospectively for outcome prediction. Using band pass filters, the ECG spectrum was split into various frequency bands of 2-26 Hz bandwidth in the range of 0-26 Hz. Neural networks were used for single feature combinations to optimise prediction of countershock success. Areas under curves (AUC) of receiver operating characteristics (ROC) were used to estimate prediction power of single and combined features. The highest ROC AUC of 0.863 was reached by the median slope in the interval 10-22 Hz resulting in a sensitivity of 95% and a specificity of 50%. The best specificity of 55% at the 95% sensitivity level was reached by power spectrum analysis (PSA) in the 6-26 Hz interval. Neural networks combining single predictive features were unable to increase outcome prediction. Using frequency band segmentation of human VF ECG, several single predictive features with high ROC AUC>0.840 were identified. Combining these single predictive features using neural networks did not further improve outcome prediction in human VF data. This may indicate that various simple VF features, such as median slope already reach the maximum prediction power extractable from VF ECG.

Assessment of a three-phase model of out-of-hospital cardiac arrest in patients with ventricular fibrillation

AIM

Cardiac arrest with ventricular fibrillation (VF) has been divided into three phases in which phase-specific therapy may improve outcome. The aim of this study was to assess the relationship between call-to-shock time, bystander CPR (BCPR), and cardiac arrest outcomes.

METHODS

In a retrospective analysis of prospectively-acquired data from witnessed VF out-of-hospital cardiac arrests (OHCA), patients were classified as phases 1, 2, or 3 based on call-to-shock time (<5, 5-8, and >8 min) and further stratified based on performance of BCPR. Groups were compared with regard to survival, neurological outcome, and restoration of spontaneous circulation (ROSC) with defibrillation only (no ALS interventions to achieve sustained ROSC).

RESULTS

Survival, neurologically intact survival, and ROSC with defibrillation were different between phases 1 and 2 (p=0.014 and p=0.005, p<0.01) but not between phases 2 and 3. Patients were further classified as having received BCPR (N=111) or no BCPR (N=107). Neurologically intact survival with and without BCPR, respectively, was 61% versus 72% (phase 1), 44% versus 41% (phase 2), and 42% versus 29% (phase 3). ROSC with defibrillation only with and without BCPR, respectively, was 64% versus 56% (phase 1), 37.0% versus 29% (phase 2), and 33% versus 8% (phase 3). ROSC with defibrillation alone was statistically higher in univariate analysis in phase 3 with BCPR (p=0.033) but not in multivariate analysis (p=0.068).

CONCLUSIONS

BCPR did not significantly improve survival in any phase of OHCA, though there was a trend toward increased neurologically intact survival and increased ROSC with defibrillation alone in phase 3.

Adenosine A1 receptor antagonism hastens the decay in ventricular fibrillation waveform morphology during porcine cardiac arrest

BACKGROUND

Endogenous adenosine (ADO) is known to be cardioprotective during acute myocardial ischemia. Coronary sinus ADO concentration has recently been shown to increase nearly 13-fold over baseline levels after 5 min of untreated ventricular fibrillation (VF). The role of ADO in VF has never been previously examined. The objective of this study was to determine the effect of ADO receptor antagonism, as measured by the scaling exponent (ScE), on the degeneration of VF over time during the circulatory phase of cardiac arrest.

METHODS AND RESULTS

A well-established swine model of prolonged VF arrest was used for this experiment. Eighteen domestic mixed-breed swine were assigned by block randomization to receive either DTI-0017 (5mg/kg), a potent ADO A(1) receptor antagonist or placebo in a double-blind fashion. The animals were instrumented under general anesthesia and acclimatized. The assigned solution was infused over 5 min. One minute after the infusion was completed, VF was induced with a 3s, 60 Hz, 100 mA transthoracic shock and left untreated. Lead II ECG was monitored continuously and recorded at 1000 samples/s. It was determined a priori that evaluation of the plots would be limited to a previously observed plateau phase historically occurring between 5 and 8 min corresponding to the circulatory phase of cardiac arrest. The scaling exponent values over this period were calculated for each of the 18 recordings using custom MATLAB routines. Using the Wald statistic to produce the Chi square distributions the null hypothesis, that there was no difference between the two groups, was tested. The Wald statistic calculation based on eight epochs from 300 to 475 s in placebo and DTI groups was significant to reject the null hypothesis of no difference in the groupxtime interaction at the 0.015 level (Chi square distribution for Wald=17.49, d.f.=7).

CONCLUSIONS

In this swine model, adenosine A(1) receptor antagonism accelerated the natural decay in the ECG VF waveform during the circulatory phase of cardiac arrest. Our findings would suggest that endogenous adenosine has cardioprotective effects during sudden cardiac arrest by slowing the time-dependent degeneration of VF.

The frequency ratio: An improved method to estimate ventricular fibrillation duration based on Fourier analysis of the waveform

BACKGROUND

CPR prior to defibrillation improves survival from prolonged ventricular fibrillation (VF) by over 10%, based on recent studies. Waveform analysis could identify those patients with VF of over 5 to 7-min duration who should receive CPR first. A method based on the changes in the Fourier-derived frequency spectrum over time could improve the ability to identify prolonged VF.

METHODS AND RESULTS

The Fourier frequency spectra were calculated on 5-s epochs of VF from 45 swine for 12.5 min. The average power at each frequency shows a marked loss of frequencies above 8 Hz occurring at 5 min accompanied by an increase in the power in frequency spectra from 3 to 5 Hz. A measure termed the frequency ratio is defined as the ratio of the power in the high frequency band from 8 to 24 Hz compared to the power in the low frequency band from 3 to 5 Hz. The frequency ratio is shown to detect 90% of epochs with VF less than 5 min while allowing selection of 74% of those epochs over 5 min. When the frequency ratio is set to detect 90% of episodes of VF under 7 min, it is able to select 88% of those traces with VF over 7 min. The receiver operating curve (ROC) for the frequency ratio has an area under the curve of 0.91 at 5 min and 0.95 at 7 min of VF duration.

CONCLUSIONS

The frequency ratio is an improved frequency-based measure of VF duration. Waveform analysis techniques could determine which patients should receive shock first and which should receive a period of CPR prior to shock, thereby increasing probability of survival.